1
Review Front Oncol
. 2020 May 29;10:738. doi: 10.3389/fonc.2020.00738. eCollection 2020.
CUX1, A Controversial Player in Tumor Development
Ning Liu 1, Qiliang Sun 2, Long Wan 1, Xuan Wang 3, Yu Feng 4, Judong Luo 5, Hailong Wu 6 7 8
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PMID: 32547943 PMCID: PMC7272708 DOI: 10.3389/fonc.2020.00738
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Abstract
CUX1 belongs to the homeodomain transcription factor family and is evolutionarily and functionally conserved from Drosophila to humans. In addition to the involvement in various physiological events including tissue development, cell proliferation, differentiation and migration, and DNA damage response, CUX1 has been implicated in tumorigenesis. Interestingly, CUX1 has been recently recognized as a haploinsufficient tumor suppressor, which is paradoxically overexpressed in tumor cells. While loss of heterozygosity and/or mutations of CUX1 have been frequently detected in many types of cancers, genomic amplification, and overexpression of CUX1 have also been reported in cancer tissues and are correlated with higher tumor grade and poor prognosis. Therefore, deciphering the roles of different CUX1 isoforms and in different tumor stages is required to establish a CUX1-based therapeutic strategy for cancer treatment.
Keywords: CUX1; DNA damage; KRAS mutation; haploinsufficient tumor suppressor; tumor progression.
Copyright © 2020 Liu, Sun, Wan, Wang, Feng, Luo and Wu.
102 references2 figures
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Review Front Oncol
. 2020 May 29;10:810. doi: 10.3389/fonc.2020.00810. eCollection 2020.
Non-Coding RNAs Operate in the Crosstalk Between Cancer Metabolic Reprogramming and Metastasis
Ziyi Li 1, Xueying Sun 1 2
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PMID: 32547948 PMCID: PMC7273922 DOI: 10.3389/fonc.2020.00810
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Abstract
Metastasis, the spread of cancer cells from a primary tumor to a secondary site, represents one of the hallmarks of malignancies and the leading cause of cancer-related death. The process of metastasis is a result of the interaction of genetic heterogeneity, abnormal metabolism, and tumor microenvironments. On the other hand, metabolic reprogramming, another malignancy hallmark, refers to the ability of cancer cells to alter metabolic and nutrient acquisition modes in order to support the energy demands for accomplishing the rapid growth, dissemination, and colonization. Cancer cells remodel metabolic patterns to supplement nutrients for their metastasis and also undergo metabolic adjustments at different stages of metastasis. Genes and signaling pathways involved in tumor metabolic reprogramming crosstalk with those participating in metastasis. Non-coding RNAs are a group of RNA molecules that do not code proteins but have pivotal biological functions. Some of microRNAs and lncRNAs, which are the two most extensively studied non-coding RNAs, have been identified to participate in regulating metabolic remodeling of glucose, lipid, glutamine, oxidative phosphorylation, and mitochondrial respiration, as well as the process of metastasis involving cell motility, transit in the circulation and growth at a new site. This article reviews recent progress on non-coding RNAs operating in the crosstalk between tumor metabolic reprogramming and metastasis, particularly those influencing metastasis through regulating metabolism, and the underlying mechanisms of how they exert their regulatory functions.
Keywords: cancer metastasis; long non-coding RNA; metabolic reprogramming; microRNA; non-coding RNA.
Copyright © 2020 Li and Sun.
135 references4 figures
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Review Front Oncol
. 2020 May 27;10:817. doi: 10.3389/fonc.2020.00817. eCollection 2020.
Nimotuzumab for Patients With Inoperable Cancer of the Head and Neck
Tania Crombet Ramos 1, Braulio Mestre Fernández 2, Zaima Mazorra Herrera 1, Normando E Iznaga Escobar 3
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PMID: 32537431 PMCID: PMC7266975 DOI: 10.3389/fonc.2020.00817
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Abstract
EGFR activation induces cell proliferation, neoformation of blood vessels, survival, and metastasis of the cancer cells. Nimotuzumab is an engineered, intermediate affinity anti-EGFR antibody, that apart from other drugs in its class, is very safe and does not cause hypomagnesemia or grade 3-4 cutaneous rash. The antibody inhibits cell proliferation and angiogenesis, activates natural killer cells, stimulates dendritic cell maturation, and induces cytotoxic T cells. Nimotuzumab restores MHC-I expression on tumor cells, hindering one of the EGFR immune-escape ways. The antibody has been extensively studied in 7 clinical trials, concurrently with irradiation or irradiation plus chemotherapy in subjects with inoperable head and neck tumors. Nimotuzumab was safe and efficacious in unfit patients receiving irradiation alone and in subjects treated with cisplatin and radiotherapy. In patients with locally advanced squamous cell carcinomas of the head and neck, nimotuzumab in combination with low dose cisplatin and radiotherapy was superior to cisplatin and radiotherapy in progression free survival, disease free survival, and locoregional tumor control.
Keywords: EGFR; head and neck; monoclonal antibody; nimotuzumab; radiotherapy.
Copyright © 2020 Crombet Ramos, Mestre Fernández, Mazorra Herrera and Iznaga Escobar.
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4
Front Oncol
. 2020 May 28;10:847. doi: 10.3389/fonc.2020.00847. eCollection 2020.
Big Data-Based Identification of Multi-Gene Prognostic Signatures in Liver Cancer
Meiliang Liu 1, Xia Liu 2, Shun Liu 1, Feifei Xiao 3, Erna Guo 1 4, Xiaoling Qin 1, Liuyu Wu 1, Qiuli Liang 1, Zerui Liang 1, Kehua Li 1, Di Zhang 1, Yu Yang 1, Xingxi Luo 1, Lei Lei 1, Jennifer Hui Juan Tan 5, Fuqiang Yin 6 7, Xiaoyun Zeng 1 7
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PMID: 32547951 PMCID: PMC7270198 DOI: 10.3389/fonc.2020.00847
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Abstract
Simultaneous identification of multiple single genes and multi-gene prognostic signatures with higher efficacy in liver cancer has rarely been reported. Here, 1,173 genes potentially related to the liver cancer prognosis were mined with Coremine, and the gene expression and survival data in 370 samples for overall survival (OS) and 319 samples for disease-free survival (DFS) were retrieved from The Cancer Genome Atlas. Numerous survival analyses results revealed that 39 genes and 28 genes significantly associated with DFS and OS in liver cancer, including 18 and 12 novel genes that have not been systematically reported in relation to the liver cancer prognosis, respectively. Next, totally 9,139 three-gene combinations (including 816 constructed by 18 novel genes) for predicting DFS and 3,276 three-gene combinations (including 220 constructed by 12 novel genes) for predicting OS were constructed based on the above genes, and the top 15 of these four parts three-gene combinations were selected and shown. Moreover, a huge difference between high and low expression group of these three-gene combination was detected, with median survival difference of DFS up to 65.01 months, and of OS up to 83.57 months. The high or low expression group of these three-gene combinations can predict the longest prognosis of DFS and OS is 71.91 months and 102.66 months, and the shortest is 6.24 months and 13.96 months. Quantitative real-time polymerase chain reaction and immunohistochemistry reconfirmed that three genes F2, GOT2, and TRPV1 contained in one of the above combinations, are significantly dysregulated in liver cancer tissues, low expression of F2, GOT2, and TRPV1 is associated with poor prognosis in liver cancer. Overall, we discovered a few novel single genes and multi-gene combinations biomarkers that are closely related to the long-term prognosis of liver cancer, and they can be potential therapeutic targets for liver cancer.
Keywords: data mining; disease-free survival (DFS); gene combinations; liver cancer; overall survival (OS).
Copyright © 2020 Liu, Liu, Liu, Xiao, Guo, Qin, Wu, Liang, Liang, Li, Zhang, Yang, Luo, Lei, Tan, Yin and Zeng.
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5
Review Front Oncol
. 2020 May 29;10:709. doi: 10.3389/fonc.2020.00709. eCollection 2020.
Isolated Pancreatic Metastases of Renal Cell Carcinoma-A Paradigm of a Seed and Soil Mechanism: A Literature Analysis of 1,034 Observations
Franz Sellner 1
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PMID: 32547940 PMCID: PMC7273884 DOI: 10.3389/fonc.2020.00709
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Abstract
Previously documented arguments, in favor of the suspected impact of a seed and soil mechanism, in the development and progression of isolated pancreatic metastasis of renal cell carcinomas (isPM) are: (1) uniform and independent from the side of the primary tumor distribution of isPM within the pancreas and, (2) the similar survival rates for singular and multiple isPM. In addition, the present study adds new arguments that further confirm the importance of an seed and soil mechanism in isPM: (1) Within the singular isPM, the size of the metastasis does not affect the overall survival; (2) Within the group of multiple isPMs, the overall survival does not depend on the number of metastases; (3) For synchronous and metachronous isPM, survival rates are also not different, and (4) Within the group of metachronous isPM there is also no correlation between the overall survival and interval until metastases occurs. This unusual ineffectiveness of otherwise known risk factors of solid cancers can be explained plausibly by the hypothesis of a very selective seed and soil mechanism in isPM. It only allows embolized renal carcinoma cells in the pancreas to complete all steps required to grow into clinically manifest metastases. In all other organs, on the other hand, the body is able to eliminate the embolized tumor cells or at least put them into a dormant state for many years. This minimizes the risk of occult micrometastases in distant organs, which could later-after isPM treatment-grow into clinically manifest metastases, so that the prognosis of the isPM is only determined by an adequate therapy of the pancreatic foci, and prognostic factors, such as total tumor burden or interval until the occurrence of the isPM remain ineffective.
Keywords: isolated pancreatic metastases; renal cell carcinoma; renal cell carcinoma metastasis; seed and soil mechanism; treatment results.
Copyright © 2020 Sellner.
307 references6 figures
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6
Review Front Oncol
. 2020 May 12;10:619. doi: 10.3389/fonc.2020.00619. eCollection 2020.
Functional Landscape of Dysregulated MicroRNAs in Oral Squamous Cell Carcinoma: Clinical Implications
Ruma Dey Ghosh 1, Arun Pattatheyil 2, Susanta Roychoudhury 3
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PMID: 32547936 PMCID: PMC7274490 DOI: 10.3389/fonc.2020.00619
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Abstract
MicroRNA (miRNA) dysregulation is associated with the pathogenesis of oral squamous cell carcinoma (OSCC), and its elucidation could potentially provide information on patient outcome. A growing body of translational research on miRNA biology is focusing on precision oncology, aiming to decode the miRNA regulatory network in the development and progression of cancer. Tissue-specific expression and stable presence in all body fluids are unique features of miRNAs, which could be potentially exploited in the clinical setting. Recent understanding of miRNA properties has led them to be useful, attractive, and potential tools either as biomarkers (distinct miRNA expression signature) for diagnosis and prognostic outcomes or as targets for novel therapeutic entities, enabling personalized treatment for OSCC. In this review, we discuss recent research on different aspects of alterations in miRNA profiles along with their clinical significance and strive to identify probable potential miRNA biomarkers for diagnosis and prognosis of OSCC. We also discuss the current understanding and scope of development of miRNA-based therapeutics against OSCC.
Keywords: dysregulated miRNA; miRNA biomarker; miRNA-based therapy; non-invasive biomarker; oral squamous cell carcinoma.
Copyright © 2020 Ghosh, Pattatheyil and Roychoudhury.
123 references
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7
Front Oncol
. 2020 May 25;10:634. doi: 10.3389/fonc.2020.00634. eCollection 2020.
Anterior Clinoidal Meningiomas: Meningeal Anatomical Considerations and Surgical Implications
Tao Xu 1, Yong Yan 1, Alexander I Evins 2, Zhenyu Gong 1, Lei Jiang 1, Huaiyu Sun 3, Li Cai 4, Hongxiang Wang 1, Weiqing Li 5, Yicheng Lu 1, Ming Zhang 6, Juxiang Chen 1
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PMID: 32547937 PMCID: PMC7278713 DOI: 10.3389/fonc.2020.00634
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Abstract
Objective: Surgical removal of anterior clinoidal meningiomas (ACMs) remains a challenge because of its complicated relationship with surrounding meninges, major arteries and cranial nerves. This study aims to define the meningeal structures around the anterior clinoid process (ACP) and its surgical implications. Methods: Five dry skulls and 19 cadavers were used in the anatomical study. Cadavers were prepared as transverse, coronal, and sagittal plastinated sections, and the meningeal architecture around the ACP was studied with dissecting and confocal microscopies. The database of meningiomas in one single center was retrospectively reviewed, and the patients with ACMs were collected for clinical analysis. Results: The superior, lateral, medial surfaces, and the tip of ACP were covered by different layers and types of meninges. The ACMs were classified into four main types based on the sites of origin, possible extending pathways following meningeal dura. In the retrospective cohort of 131 ACMs, the percentage of types I, IIa, IIb, III, and IV were 42.0% (55/131), 19.8% (26/131), 9.2% (12/131), 16.8% (22/131), and 12.2% (16/131), respectively. We found that types IIa and I had higher chances for achieving Simpson grade 1-2 resection (92.3 and 85.4%, respectively), followed by type III (54.5%) and type IV (31.3%), while type IIb showed little chance of Simpson grade 1-2 resection. Univariate and multivariate analyses revealed ACM classification and tumor size (<3 cm) to be independent risk factors for achieving more extensive resection. Conclusion: The meningeal architecture around the ACP may guide and determine the origin and extension of ACMs. The classification based on the meningeal architecture helps to understand surgical anatomy as well as predicting surgical outcomes.
Keywords: anterior clinoid process; anterior clinoidal meningioma; carotid artery; cavernous sinus; classification; meninges; surgical anatomy.
Copyright © 2020 Xu, Yan, Evins, Gong, Jiang, Sun, Cai, Wang, Li, Lu, Zhang and Chen.
44 references4 figures
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8
Review Front Oncol
. 2020 May 27;10:860. doi: 10.3389/fonc.2020.00860. eCollection 2020.
Minimal Residual Disease in Multiple Myeloma: Current Landscape and Future Applications With Immunotherapeutic Approaches
Ioannis V Kostopoulos 1, Ioannis Ntanasis-Stathopoulos 2, Maria Gavriatopoulou 2, Ourania E Tsitsilonis 1, Evangelos Terpos 2
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PMID: 32537439 PMCID: PMC7267070 DOI: 10.3389/fonc.2020.00860
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Abstract
The basic principle that deeper therapeutic responses lead to better clinical outcomes in cancer has emerged technologies capable of detecting rare residual tumor cells. The need for ultra-sensitive approaches for minimal residual disease (MRD) detection is particularly evident in Multiple Myeloma (MM), where patients will ultimately relapse despite the achievement of complete remission, which is commonplace due to remarkable therapeutic advances. Consequently, current response criteria on MM have been amended based on MRD status and MRD negativity is now considered the most dominant prognostic factor and the most valuable indicator for a subsequent relapse. However, there are particular limitations and several aspects for MRD assessment that remain open. This review summarizes current data on MRD in the clinical management of MM, highlights open issues and discusses the challenges and the endless opportunities arising for both patients and clinicians. Furthermore, it focuses on the current status of MRD in clinical trials, its dynamics in addressing debatable aspects in the clinical handling and its potential role as the prevailing factor for future MRD-driven tailored therapies.
Keywords: minimal residual disease; multiple myeloma; primary endpoint; prognostic factor; therapeutic intervention.
Copyright © 2020 Kostopoulos, Ntanasis-Stathopoulos, Gavriatopoulou, Tsitsilonis and Terpos.
114 references
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9
Front Oncol
. 2020 Jun 1;10:809. doi: 10.3389/fonc.2020.00809. eCollection 2020.
Identification of Potential Key Genes for Pathogenesis and Prognosis in Prostate Cancer by Integrated Analysis of Gene Expression Profiles and the Cancer Genome Atlas
Shuang Liu 1, Wenxin Wang 2, Yan Zhao 3, Kaige Liang 1, Yaojiang Huang 1 4
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PMID: 32547947 PMCID: PMC7277826 DOI: 10.3389/fonc.2020.00809
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Abstract
Background: Prostate cancer (PCa)is a malignancy of the urinary system with a high incidence, which is the second most common male cancer in the world. There are still huge challenges in the treatment of prostate cancer. It is urgent to screen out potential key biomarkers for the pathogenesis and prognosis of PCa. Methods: Multiple gene differential expression profile datasets of PCa tissues and normal prostate tissues were integrated analysis by R software. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis of the overlapping Differentially Expressed Genes (DEG) were performed. The STRING online database was used in conjunction with Cytospace software for protein-protein interaction (PPI) network analysis to define hub genes. The relative mRNA expression of hub genes was detected in Gene Expression Profiling Interactive Analysis (GEPIA) database. A prognostic gene signature was identified by Univariate and multivariate Cox regression analysis. Results: Three hundred twelve up-regulated genes and 85 down-regulated genes were identified from three gene expression profiles (GSE69223, GSE3325, GSE55945) and The Cancer Genome Atlas Prostate Adenocarcinoma (TCGA-PRAD) dataset. Seven hub genes (FGF2, FLNA, FLNC, VCL, CAV1, ACTC1, and MYLK) further were detected, which related to the pathogenesis of PCa. Seven prognostic genes (BCO1, BAIAP2L2, C7, AP000844.2, ASB9, MKI67P1, and TMEM272) were screened to construct a prognostic gene signature, which shows good predictive power for survival by the ROC curve analysis. Conclusions: We identified a robust set of new potential key genes in PCa, which would provide reliable biomarkers for early diagnosis and prognosis and would promote molecular targeting therapy for PCa.
Keywords: GEO; TCGA; bioinformatics; biomarker; prostate cancer; survival.
Copyright © 2020 Liu, Wang, Zhao, Liang and Huang.
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Review Front Oncol
. 2020 May 27;10:831. doi: 10.3389/fonc.2020.00831. eCollection 2020.
Biomarkers for Pancreatic Neuroendocrine Neoplasms (PanNENs) Management-An Updated Review
Martine Bocchini 1, Fabio Nicolini 1, Stefano Severi 2, Alberto Bongiovanni 3, Toni Ibrahim 3, Giorgia Simonetti 1, Ilaria Grassi 2, Massimiliano Mazza 1
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PMID: 32537434 PMCID: PMC7267066 DOI: 10.3389/fonc.2020.00831
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Pancreatic neuroendocrine tumors (PanNENs) are rare sporadic cancers or develop as part of hereditary syndromes. PanNENs can be both functioning and non-functioning based on whether they produce bioactive peptides. Some PanNENs are well differentiated while others-poorly. Symptoms, thus, depend on both oncological and hormonal causes. PanNEN diagnosis and treatment benefit from and in some instances are guided by biomarker monitoring. However, plasmatic monoanalytes are only suggestive of PanNEN pathological status and their positivity is typically followed by deepen diagnostic analyses through imaging techniques. There is a strong need for new biomarkers and follow-up modalities aimed to improve the outcome of PanNEN patients. Liquid biopsy follow-up, i.e., sequential analysis on tumor biomarkers in body fluids offers a great potential, that need to be substantiated by additional studies focusing on the specific markers and the timing of the analyses. This review provides the most updated panorama on PanNEN biomarkers.
Keywords: FDG (18F-fluorodeoxyglucose)-PET/CT; biomarker; neuroendocrine syndrome; pancreatic neuroendocrine tumor; pancreatic tumor.
Copyright © 2020 Bocchini, Nicolini, Severi, Bongiovanni, Ibrahim, Simonetti, Grassi and Mazza.
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11
Front Oncol
. 2020 May 29;10:823. doi: 10.3389/fonc.2020.00823. eCollection 2020.
RNA Sequencing Revealed Signals of Evolution From Gallbladder Stone to Gallbladder Carcinoma
Jinghan Wang 1, Chang Xu 1, Qingbao Cheng 1, Jiangman Zhao 2 3, Shouxin Wu 2 3, Wushuang Li 2 3, Wencong Ma 1, Chen Liu 1, Xiaoqing Jiang 1
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PMID: 32547950 PMCID: PMC7272658 DOI: 10.3389/fonc.2020.00823
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Abstract
Gallbladder stone is a major risk factor for gallbladder carcinoma (GBC), while there is still a controversy whether period of follow-up since newly diagnoses of asymptomatic gallstones increases the risk of GBC. In this study, 10 GBC patients and 30 patients with gallstones were admitted to our hospital. Patients with gallstones were divided into 3 groups according to the follow-up time, involving 10 patients with follow-up period of 1-3 years (GS3 group), 10 patients with follow-up period of 5-10 years (GS5 group), and 10 patients with follow-up period of more than 10 years (GS10 group). Tumor and para-tumor tissues of GBC patients, and gallbladder tissues of gallstone patients were collected. RNA sequencing was performed on the 50 samples. Besides, 1,704 differentially expressed genes (DEGs) were identified in tumors compared with para-tumor tissues of 10 GBC patients, which were enriched into some well-known cancer-related pathways, such as PI3K-Akt, mitogen-activated protein kinase (MAPK), Ras, and Wnt signaling pathways, and the most significant pathway was neuroactive ligand-receptor interaction. Patients with gallstones with periods of follow-up equal to 1-3 and > 10 years showed to have higher cancer risk than those with 5-10 years. ALPP and GPR87 are potential biomarkers for predicting cancer risk in patients with gallstones. The in vitro results revealed that GPR-87 can promote the proliferation, migration, and invasion of GBC cells. Herein, we explored the relationship between GBC patients and patients with gallstones with different periods of follow-up in transcriptome level.
Keywords: ALPP; GPR87; RNA sequencing; follow-up time; gallbladder carcinoma; gallbladder stone.
Copyright © 2020 Wang, Xu, Cheng, Zhao, Wu, Li, Ma, Liu and Jiang.
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Front Oncol
. 2020 May 27;10:835. doi: 10.3389/fonc.2020.00835. eCollection 2020.
Development and Validation of a 12-Gene Immune Relevant Prognostic Signature for Lung Adenocarcinoma Through Machine Learning Strategies
Liang Xue 1, Guoshu Bi 1, Cheng Zhan 1, Yi Zhang 1, Yunfeng Yuan 1, Hong Fan 1
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PMID: 32537435 PMCID: PMC7267039 DOI: 10.3389/fonc.2020.00835
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Background: Although immunotherapy with checkpoint inhibitors is changing the face of lung adenocarcinoma (LUAD) treatments, only limited patients could benefit from it. Therefore, we aimed to develop an immune-relevant-gene-based signature to predict LUAD patients' prognosis and to characterize their tumor microenvironment thus guiding therapeutic strategy. Methods and Materials: Gene expression data of LUAD patients from Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) were systematically analyzed. We performed Cox regression and random survival forest algorithm to identify immune-relevant genes with potential prognostic value. A risk score formula was then established by integrating these selected genes and patients were classified into high- and low-risk score group. Differentially expressed genes, infiltration level of immune cells, and several immune-associated molecules were further compared across the two groups. Results: Nine hundred and fifty-four LUAD patients were enrolled in this study. After implementing the 2-steps machine learning screening methods, 12 immune-relevant genes were finally selected into the risk-score formula and the patients in high-risk group had significantly worse overall survival (HR = 10.6, 95%CI = 3.21-34.95, P < 0.001). We also found the distinct immune infiltration patterns in the two groups that several immune cells like cytotoxic cells and immune checkpoint molecules were significantly enriched and upregulated in patients from the high-risk group. These findings were further validated in two independent LUAD cohorts. Conclusion: Our risk score formula could serve as a powerful and accurate tool for predicting survival of LUAD patients and may facilitate clinicians to choose the optimal therapeutic regimen more precisely.
Keywords: immune infiltration; lung adenocarcinoma; machine learning; risk score formula; survival.
Copyright © 2020 Xue, Bi, Zhan, Zhang, Yuan and Fan.
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Front Oncol
. 2020 May 29;10:814. doi: 10.3389/fonc.2020.00814. eCollection 2020.
Whole Pelvic Radiotherapy With Stereotactic Body Radiotherapy Boost vs. Conventionally Fractionated Radiotherapy for Patients With High or Very High-Risk Prostate Cancer
Shih-Chang Wang 1, Wei-Chen Ting 2, Yun-Ching Chang 3, Ching-Chieh Yang 1 4, Li-Ching Lin 1, Hsiu-Wen Ho 1, Shou-Sheng Chu 1, Yu-Wei Lin 1 4 5
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PMID: 32547949 PMCID: PMC7273130 DOI: 10.3389/fonc.2020.00814
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Background: Whole pelvic radiotherapy (WPRT) with stereotactic body radiotherapy (SBRT) boost has been shown to be effective in patients with high-risk prostate cancer (PC). However, no study has directly compared the efficacy of WPRT with SBRT boost with that of conventionally fractionated radiotherapy (CFRT). We compared the clinical outcomes between CFRT and WPRT with SBRT boost in patients with high or very high-risk PC (National Comprehensive Cancer Network definition). Methods: In total, 132 patients treated with CFRT and 121 patients treated with WPRT followed by SBRT boost were retrospectively analyzed. For the CFRT group, the prescribed dose range was 74-79.2 Gray (Gy) administered at 1.8-2 Gy per fraction. For WPRT with SBRT boost, the prescribed doses were 45 Gy administered in 25 fractions to the whole pelvis followed by 21 Gy boost (3 fractions of 7 Gy each) to prostate and seminal vesicles. The overall survival (OS) and biochemical failure (Phoenix definition) free survival (bFFS) were assessed by using the Kaplan-Meier method or the Cox proportional hazards regression model. The gastrointestinal (GI) and genitourinary (GU) tract toxicity were assessed using the National Cancer Institute Common Terminology Criteria for Adverse Events (CTCAE) v3.0. Results: The estimated 4-years overall survival in the CFRT and WPRT with SBRT boost groups was 91.6 and 97.7%, respectively (P = 0.18). The estimated 4-years biochemical failure-free survival in the CFRT and WPRT with SBRT boost groups was 89.1 and 93.9%, respectively (P = 0.41). No acute grade 3 or higher GI and GU toxicity was observed in both groups. Late grade 3 GI and GU toxicity occurred in 2.3 and 2.3% in the CFRT group, and in 1.7 and 0.8% in the WPRT with SBRT boost group, respectively. There was no significant between-group difference with respect to acute or late toxicity. Conclusions: In patients with high or very high-risk localized PC, compared with CFRT, WPRT with SBRT boost resulted in similar biochemical-free and overall survival rate with minimal toxicity. WPRT with SBRT boost is a feasible option for patients with high or very high-risk PC.
Keywords: SBRT; conventionally fractionated; high risk; prostate cancer; radiotherapy.
Copyright © 2020 Wang, Ting, Chang, Yang, Lin, Ho, Chu and Lin.
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Front Oncol
. 2020 May 29;10:873. doi: 10.3389/fonc.2020.00873. eCollection 2020.
Identification of an Autophagy-Related Prognostic Signature for Clear Cell Renal Cell Carcinoma
Mei Chen 1, Shufang Zhang 1, Zhenyu Nie 1, Xiaohong Wen 1, Yuanhui Gao 1
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PMID: 32547955 PMCID: PMC7274034 DOI: 10.3389/fonc.2020.00873
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Abnormal autophagy is closely related to the development of cancer. Many studies have demonstrated that autophagy plays an important role in biological function in clear cell renal cell carcinoma (ccRCC). This study aimed to construct a prognostic signature for ccRCC based on autophagy-related genes (ARGs) to predict the prognosis of ccRCC. Differentially expressed ARGs were obtained from ccRCC RNA-seq data in The Cancer Genome Atlas (TCGA) database. ARGs were enriched by gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). The prognostic ARGs used to construct the risk score models for overall survival (OS) and disease-free survival (DFS) were identified by Cox regression analyses. According to the median value of the risk score, patients were divided into a high-risk group and a low-risk group. The OS and DFS were analyzed by the Kaplan-Meier method. The predictive accuracy was determined by a receiver operating characteristic (ROC) curve analysis. Additionally, we performed stratification analyses based on different clinical variables and evaluated the correlation between the risk score and the clinical variables. The differentially expressed ARGs were mainly enriched in the platinum drug resistance pathway. The prognostic signatures based on 11 ARGs for OS and 5 ARGs for DFS were constructed and showed that the survive time was significantly shorter in the high-risk group than in the low-risk group (P < 0.001). The ROC curve for OS exhibited good predictive accuracy, with an area under the curve value of 0.738. In the stratification analyses, the OS time of the high-risk group was shorter than that of the low-risk group stratified by different clinical variables. In conclusion, an autophagy-related signature for OS we constructed can independently predict the prognosis of ccRCC patient, and provide a deep understanding of the potential biological mechanisms of autophagy in ccRCC.
Keywords: autophagy; clear cell renal cell carcinoma; platinum drug resistance; prognosis; the cancer genome atlas.
Copyright © 2020 Chen, Zhang, Nie, Wen and Gao.
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Front Oncol
. 2020 May 27;10:821. doi: 10.3389/fonc.2020.00821. eCollection 2020.
PD-L1 Inhibitor Regulates the miR-33a-5p/PTEN Signaling Pathway and Can Be Targeted to Sensitize Glioblastomas to Radiation
Wenzheng Xia 1, Jin Zhu 1, Yinda Tang 1, Xueyi Wang 1, Xiangyu Wei 1, Xuan Zheng 1, Meng Hou 2, Shiting Li 1
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PMID: 32537433 PMCID: PMC7266984 DOI: 10.3389/fonc.2020.00821
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Abstract
Glioblastoma (GBM) is the most common and lethal brain tumor in adults. Ionizing radiation (IR) is a standard treatment for GBM patients and results in DNA damage. However, the clinical efficacy of IR is limited due to therapeutic resistance. The programmed death ligand 1 (PD-L1) blockade has a shown the potential to increase the efficacy of radiotherapy by inhibiting DNA damage and repair responses. The miR-33a-5p is an essential microRNA that promotes GBM growth and self-renewal. In this study, we investigated whether a PD-L1 inhibitor (a small molecule inhibitor) exerted radio-sensitive effects to impart an anti-tumor function in GBM cells by modulating miR-33a-5p. U87 MG cells and U251 cells were pretreated with PD-L1 inhibitor. The PD-L1 inhibitor-induced radio-sensitivity in these cells was assessed by assaying cellular apoptosis, clonogenic survival assays, and migration. TargetScan and luciferase assay showed that miR-33a-5p targeted the phosphatase and tensin homolog (PTEN) 3' untranslated region. The expression level of PTEN was measured by western blotting, and was also silenced using small interfering RNAs. The levels of DNA damage following radiation was measured by the presence of γ-H2AX foci, cell cycle, and the mRNA of the DNA damage-related genes, BRCA1, NBS1, RAD50, and MRE11. Our results demonstrated that the PD-L1 inhibitor significantly decreased the expression of the target gene, miR-33a-5p. In addition, pretreatment of U87 MG and U251 cells with the PD-L1 inhibitor increased radio-sensitivity, as indicated by increased apoptosis, while decreased survival and migration of GBM cells. Mir-33a-5p overexpression or silencing PTEN in U87 MG and U251 cells significantly attenuated PD-L1 radiosensitive effect. Additionally, PD-L1 inhibitor treatment suppressed the expression of the DNA damage response-related genes, BRCA1, NBS1, RAD50, and MRE11. Our results demonstrated a novel role for the PD-L1 inhibitor in inducing radio- sensitivity in GBM cells, where inhibiting miR-33a-5p, leading to PTEN activated, and inducing DNA damage was crucial for antitumor immunotherapies to treat GBM.
Keywords: DNA damage response; glioblastoma; miR-33a-5p/PTEN signaling pathway; programmed death ligand 1 (PD-L1) blockade; radio-sensitization.
Copyright © 2020 Xia, Zhu, Tang, Wang, Wei, Zheng, Hou and Li.
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Front Oncol
. 2020 May 29;10:592. doi: 10.3389/fonc.2020.00592. eCollection 2020.
A Computed Tomography-Based Radiomics Nomogram to Preoperatively Predict Tumor Necrosis in Patients With Clear Cell Renal Cell Carcinoma
Yi Jiang 1 2, Wuchao Li 3 4, Chencui Huang 5, Chong Tian 3 4, Qi Chen 2, Xianchun Zeng 3 4, Yin Cao 6, Yi Chen 6, Yintong Yang 6, Heng Liu 7, Yonghua Bo 8, Chenggong Luo 9, Yiming Li 5, Tijiang Zhang 7, Rongping Wang 1 3 4
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PMID: 32547934 PMCID: PMC7272670 DOI: 10.3389/fonc.2020.00592
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Abstract
Objective: To develop and validate a radiomics nomogram for preoperative prediction of tumor necrosis in patients with clear cell renal cell carcinoma (ccRCC). Methods: In total, 132 patients with pathologically confirmed ccRCC in one hospital were enrolled as a training cohort, while 123 ccRCC patients from second hospital served as the independent validation cohort. Radiomic features were extracted from corticomedullary and nephrographic phase contrast-enhanced computed tomography (CT) images. A radiomics signature based on optimal features selected by consistency analysis and the least absolute shrinkage and selection operator was developed. An image features model was constructed based on independent image features according to visual assessment. By integrating the radiomics signature and independent image features, a radiomics nomograph was constructed. The predictive performance of the above models was evaluated using receiver operating characteristic (ROC) curve analysis. Furthermore, the nomogram was assessed using calibration curve and decision curve analysis. Results: Thirty-seven features were used to establish a radiomics signature, which demonstrated better predictive performance than did the image features model constructed using tumor size and intratumoral vessels in the training and validation cohorts (p <0.05). The radiomics nomogram demonstrated satisfactory discrimination in the training (area under the ROC curve [AUC] 0.93 [95% CI 0.87-0.96]) and validation (AUC 0.87 [95% CI 0.79-0.93]) cohorts and good calibration (Hosmer-Lemeshow p>0.05). Decision curve analysis verified that the radiomics nomogram had the best clinical utility compared with the other models. Conclusion: The radiomics nomogram developed in the present study is a promising tool to predict tumor necrosis and facilitate preoperative clinical decision-making for patients with ccRCC.
Keywords: clear cell renal cell carcinoma; computed tomography; prediction model; radiomics; tumor necrosis.
Copyright © 2020 Jiang, Li, Huang, Tian, Chen, Zeng, Cao, Chen, Yang, Liu, Bo, Luo, Li, Zhang and Wang.
29 references4 figures
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Front Oncol
. 2020 Jun 1;10:895. doi: 10.3389/fonc.2020.00895. eCollection 2020.
A Nomogram Combined Radiomic and Semantic Features as Imaging Biomarker for Classification of Ovarian Cystadenomas
Shushu Pan 1, Zhongxiang Ding 1, Lexing Zhang 1, Mei Ruan 1, Yanna Shan 1, Meixiang Deng 2, Peipei Pang 3, Qijun Shen 1
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PMID: 32547958 PMCID: PMC7277787 DOI: 10.3389/fonc.2020.00895
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Abstract
Objective: To construct and validate a combined Nomogram model based on radiomic and semantic features to preoperatively classify serous and mucinous pathological types in patients with ovarian cystadenoma. Methods: A total of 103 patients with pathology-confirmed ovarian cystadenoma who underwent CT examination were collected from two institutions. All cases divided into training cohort (N = 73) and external validation cohort (N = 30). The CT semantic features were identified by two abdominal radiologists. The preprocessed initial CT images were used for CT radiomic features extraction. The LASSO regression were applied to identify optimal radiomic features and construct the Radscore. A Nomogram model was constructed combining the Radscore and the optimal semantic feature. The model performance was evaluated by ROC analysis, calibration curve and decision curve analysis (DCA). Result: Five optimal features were ultimately selected and contributed to the Radscore construction. Unilocular/multilocular identification was significant difference from semantic features. The Nomogram model showed a better performance in both training cohort (AUC = 0.94, 95%CI 0.86-0.98) and external validation cohort (AUC = 0.92, 95%CI 0.76-0.98). The calibration curve and DCA analysis indicated a better accuracy of the Nomogram model for classification than either Radscore or the loculus alone. Conclusion: The Nomogram model combined radiomic and semantic features could be used as imaging biomarker for classification of serous and mucinous types of ovarian cystadenomas.
Keywords: algorithm; classification; cystadenoma; ovarian neoplasms; tomography; x-ray computed.
Copyright © 2020 Pan, Ding, Zhang, Ruan, Shan, Deng, Pang and Shen.
31 references6 figures
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Front Oncol
. 2020 May 27;10:838. doi: 10.3389/fonc.2020.00838. eCollection 2020.
CT-Imaging Based Analysis of Invasive Lung Adenocarcinoma Presenting as Ground Glass Nodules Using Peri- And Intra-nodular Radiomic Features
Linyu Wu 1 2, Chen Gao 1 2, Ping Xiang 1 2, Sisi Zheng 1 2, Peipei Pang 3, Maosheng Xu 1 2
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PMID: 32537436 PMCID: PMC7267037 DOI: 10.3389/fonc.2020.00838
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Abstract
Objective: To evaluate whether radiomic features extracted from intra and peri-nodular lesions can enhance the ability to differentiate between invasive adenocarcinoma (IA), minimally invasive adenocarcinoma (MIA), and adenocarcinoma in situ (AIS) manifesting as ground-glass nodule (GGN). Materials and Methods: This retrospective study enrolled 120 patients with a total of 121 pathologically confirmed lung adenocarcinomas (85 IA and 36 AIS/MIA) from January 2015 to May 2019. The recruited patients were randomly divided into training (84 nodules) and validation sets (37 nodules), with a ratio of 7:3. The minority group in the training set was balanced by the synthetic minority over-sampling (SMOTE) method. The intra-, peri-nodular, and gross region of interests (ROI) were delineated with manual annotation. Image features were quantitatively extracted from each ROI on CT images. The minimum redundancy maximum relevance (mRMR) feature ranking method and the least absolute shrinkage and selection operator (LASSO) classifier were used to eliminate unnecessary features. The intra- and peri-nodular radiomic features were combined to produce the gross radiomic signature. A combined clinical-radiomic model was constructed by multivariable logistic regression analysis. The predicted performances of different models were evaluated using receiver operating curve (ROC) and calibration curve. Results: The gross radiomic signature (AUC: training set = 0.896; validation set = 0.876) showed a good ability to discriminate the invasiveness of adenocarcinoma, comparing to intra-nodular (AUC: training set = 0.862; validation set = 0.852) or peri-nodular radiomic signature (AUC: training set = 0.825; validation set = 0.820). The AUC of the combined clinical-radiomic model was 0.917 for the training and 0.876 for the validation cohort, respectively. Conclusions: The gross radiomic signature of intra- and peri-nodular regions improved the prediction ability and aided predicting the invasiveness of lung adenocarcinoma appearing as GGN.
Keywords: X-ray computed; computational biology; ground-glass nodule; lung adenocarcinoma; radiomics; tomography.
Copyright © 2020 Wu, Gao, Xiang, Zheng, Pang and Xu.
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Case Reports Front Oncol
. 2020 May 29;10:876. doi: 10.3389/fonc.2020.00876. eCollection 2020.
Follicular Dendritic Cell Sarcoma With Co-Expression of CD4 and CD30 Mimics Anaplastic Large Cell Lymphoma
Hui Liu 1 2, Chenxi Xiang 2, Mei Wu 1, Shimin Hu 3
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PMID: 32547956 PMCID: PMC7273153 DOI: 10.3389/fonc.2020.00876
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Abstract
Follicular dendritic cell sarcoma (FDCS) is a low-grade malignant neoplasm that tends to be under-recognized owing to its rarity and wide pathologic spectrum. Knowledge of the atypical morphology and immunophenotype of FDCS is critical to avoid misdiagnosis. Here we presented a case of extranodal FDCS with an unusual morphology and a previously unreported immunophenotype leading to misdiagnosis. A 32-years-old man presented with a tonsilar mass that showed epithelioid cells in nested and alveolar patterns. Immunohistochemistry study revealed that the tumor cells were positive for CD4 and CD30, and were negative for cytokeratin, CD3, CD20, CD68, CD163, lysozyme, ALK, S-100, and desmin. Multiple outside expert consultations rendered a consensus diagnosis of ALK-negative anaplastic large cell lymphoma (ALCL). The patient received multiple lines of chemotherapy and radiotherapy. However, the residual tumor progressively enlarged eight months later and a more complex morphology was presented in the re-excised tumor: including spindle cells with vesicular nuclei and nuclear pseudoinclusions in fascicles or a whorled pattern, and plump ovoid cells arranged in meningioma-like whorls as well as epithelioid tumor cells similar to the initial biopsy. All these three components were positive for CD4, CD21, CD23, and CD35. The diagnosis was revised to FDCS after a positive immunostaining for CD21, CD23, and CD35 on the initial specimen was confirmed retrospectively. A literature review identified 57 cases of FDCS published from 2009 through 2019, and 13 (22.8%) of them were misdiagnosed at initial presentation. Among these misdiagnosed cases, all except one case were extranodal, and the incorrect initial diagnosis was mostly location-related. These cases expand the pathologic spectrum of FDCS, and further emphasize the necessity for pathologists to stay alert for this rare entity, bringing FDCS into the differentials for any spindle cell tumors, undifferentiated epithelioid cell tumors, and ALCL to avoid misdiagnosis.
Keywords: CD30; CD4; Follicular dendritic cell sarcoma; anaplastic large cell lymphoma; pathologic spectrum.
Copyright © 2020 Liu, Xiang, Wu and Hu.
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Front Oncol
. 2020 May 28;10:680. doi: 10.3389/fonc.2020.00680. eCollection 2020.
Deep Learning for Accurate Diagnosis of Liver Tumor Based on Magnetic Resonance Imaging and Clinical Data
Shi-Hui Zhen 1 2, Ming Cheng 2, Yu-Bo Tao 2, Yi-Fan Wang 1, Sarun Juengpanich 1, Zhi-Yu Jiang 1, Yan-Kai Jiang 1 2, Yu-Yu Yan 2, Wei Lu 3 4, Jie-Min Lue 1, Jia-Hong Qian 2, Zhong-Yu Wu 5, Ji-Hong Sun 3, Hai Lin 2, Xiu-Jun Cai 1
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PMID: 32547939 PMCID: PMC7271965 DOI: 10.3389/fonc.2020.00680
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Abstract
Background: Early-stage diagnosis and treatment can improve survival rates of liver cancer patients. Dynamic contrast-enhanced MRI provides the most comprehensive information for differential diagnosis of liver tumors. However, MRI diagnosis is affected by subjective experience, so deep learning may supply a new diagnostic strategy. We used convolutional neural networks (CNNs) to develop a deep learning system (DLS) to classify liver tumors based on enhanced MR images, unenhanced MR images, and clinical data including text and laboratory test results. Methods: Using data from 1,210 patients with liver tumors (N = 31,608 images), we trained CNNs to get seven-way classifiers, binary classifiers, and three-way malignancy-classifiers (Model A-Model G). Models were validated in an external independent extended cohort of 201 patients (N = 6,816 images). The area under receiver operating characteristic (ROC) curve (AUC) were compared across different models. We also compared the sensitivity and specificity of models with the performance of three experienced radiologists. Results: Deep learning achieves a performance on par with three experienced radiologists on classifying liver tumors in seven categories. Using only unenhanced images, CNN performs well in distinguishing malignant from benign liver tumors (AUC, 0.946; 95% CI 0.914-0.979 vs. 0.951; 0.919-0.982, P = 0.664). New CNN combining unenhanced images with clinical data greatly improved the performance of classifying malignancies as hepatocellular carcinoma (AUC, 0.985; 95% CI 0.960-1.000), metastatic tumors (0.998; 0.989-1.000), and other primary malignancies (0.963; 0.896-1.000), and the agreement with pathology was 91.9%.These models mined diagnostic information in unenhanced images and clinical data by deep-neural-network, which were different to previous methods that utilized enhanced images. The sensitivity and specificity of almost every category in these models reached the same high level compared to three experienced radiologists. Conclusion: Trained with data in various acquisition conditions, DLS that integrated these models could be used as an accurate and time-saving assisted-diagnostic strategy for liver tumors in clinical settings, even in the absence of contrast agents. DLS therefore has the potential to avoid contrast-related side effects and reduce economic costs associated with current standard MRI inspection practices for liver tumor patients.
Keywords: MRI; artificial intelligence; deep learning; diagnosis; liver cancer; liver mass.
Copyright © 2020 Zhen, Cheng, Tao, Wang, Juengpanich, Jiang, Jiang, Yan, Lu, Lue, Qian, Wu, Sun, Lin and Cai.
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Review Front Oncol
. 2020 May 29;10:738. doi: 10.3389/fonc.2020.00738. eCollection 2020.
CUX1, A Controversial Player in Tumor Development
Ning Liu 1, Qiliang Sun 2, Long Wan 1, Xuan Wang 3, Yu Feng 4, Judong Luo 5, Hailong Wu 6 7 8
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PMID: 32547943 PMCID: PMC7272708 DOI: 10.3389/fonc.2020.00738
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Abstract
CUX1 belongs to the homeodomain transcription factor family and is evolutionarily and functionally conserved from Drosophila to humans. In addition to the involvement in various physiological events including tissue development, cell proliferation, differentiation and migration, and DNA damage response, CUX1 has been implicated in tumorigenesis. Interestingly, CUX1 has been recently recognized as a haploinsufficient tumor suppressor, which is paradoxically overexpressed in tumor cells. While loss of heterozygosity and/or mutations of CUX1 have been frequently detected in many types of cancers, genomic amplification, and overexpression of CUX1 have also been reported in cancer tissues and are correlated with higher tumor grade and poor prognosis. Therefore, deciphering the roles of different CUX1 isoforms and in different tumor stages is required to establish a CUX1-based therapeutic strategy for cancer treatment.
Keywords: CUX1; DNA damage; KRAS mutation; haploinsufficient tumor suppressor; tumor progression.
Copyright © 2020 Liu, Sun, Wan, Wang, Feng, Luo and Wu.
102 references2 figures
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Review Front Oncol
. 2020 May 29;10:810. doi: 10.3389/fonc.2020.00810. eCollection 2020.
Non-Coding RNAs Operate in the Crosstalk Between Cancer Metabolic Reprogramming and Metastasis
Ziyi Li 1, Xueying Sun 1 2
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PMID: 32547948 PMCID: PMC7273922 DOI: 10.3389/fonc.2020.00810
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Abstract
Metastasis, the spread of cancer cells from a primary tumor to a secondary site, represents one of the hallmarks of malignancies and the leading cause of cancer-related death. The process of metastasis is a result of the interaction of genetic heterogeneity, abnormal metabolism, and tumor microenvironments. On the other hand, metabolic reprogramming, another malignancy hallmark, refers to the ability of cancer cells to alter metabolic and nutrient acquisition modes in order to support the energy demands for accomplishing the rapid growth, dissemination, and colonization. Cancer cells remodel metabolic patterns to supplement nutrients for their metastasis and also undergo metabolic adjustments at different stages of metastasis. Genes and signaling pathways involved in tumor metabolic reprogramming crosstalk with those participating in metastasis. Non-coding RNAs are a group of RNA molecules that do not code proteins but have pivotal biological functions. Some of microRNAs and lncRNAs, which are the two most extensively studied non-coding RNAs, have been identified to participate in regulating metabolic remodeling of glucose, lipid, glutamine, oxidative phosphorylation, and mitochondrial respiration, as well as the process of metastasis involving cell motility, transit in the circulation and growth at a new site. This article reviews recent progress on non-coding RNAs operating in the crosstalk between tumor metabolic reprogramming and metastasis, particularly those influencing metastasis through regulating metabolism, and the underlying mechanisms of how they exert their regulatory functions.
Keywords: cancer metastasis; long non-coding RNA; metabolic reprogramming; microRNA; non-coding RNA.
Copyright © 2020 Li and Sun.
135 references4 figures
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Review Front Oncol
. 2020 May 27;10:817. doi: 10.3389/fonc.2020.00817. eCollection 2020.
Nimotuzumab for Patients With Inoperable Cancer of the Head and Neck
Tania Crombet Ramos 1, Braulio Mestre Fernández 2, Zaima Mazorra Herrera 1, Normando E Iznaga Escobar 3
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PMID: 32537431 PMCID: PMC7266975 DOI: 10.3389/fonc.2020.00817
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EGFR activation induces cell proliferation, neoformation of blood vessels, survival, and metastasis of the cancer cells. Nimotuzumab is an engineered, intermediate affinity anti-EGFR antibody, that apart from other drugs in its class, is very safe and does not cause hypomagnesemia or grade 3-4 cutaneous rash. The antibody inhibits cell proliferation and angiogenesis, activates natural killer cells, stimulates dendritic cell maturation, and induces cytotoxic T cells. Nimotuzumab restores MHC-I expression on tumor cells, hindering one of the EGFR immune-escape ways. The antibody has been extensively studied in 7 clinical trials, concurrently with irradiation or irradiation plus chemotherapy in subjects with inoperable head and neck tumors. Nimotuzumab was safe and efficacious in unfit patients receiving irradiation alone and in subjects treated with cisplatin and radiotherapy. In patients with locally advanced squamous cell carcinomas of the head and neck, nimotuzumab in combination with low dose cisplatin and radiotherapy was superior to cisplatin and radiotherapy in progression free survival, disease free survival, and locoregional tumor control.
Keywords: EGFR; head and neck; monoclonal antibody; nimotuzumab; radiotherapy.
Copyright © 2020 Crombet Ramos, Mestre Fernández, Mazorra Herrera and Iznaga Escobar.
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Front Oncol
. 2020 May 28;10:847. doi: 10.3389/fonc.2020.00847. eCollection 2020.
Big Data-Based Identification of Multi-Gene Prognostic Signatures in Liver Cancer
Meiliang Liu 1, Xia Liu 2, Shun Liu 1, Feifei Xiao 3, Erna Guo 1 4, Xiaoling Qin 1, Liuyu Wu 1, Qiuli Liang 1, Zerui Liang 1, Kehua Li 1, Di Zhang 1, Yu Yang 1, Xingxi Luo 1, Lei Lei 1, Jennifer Hui Juan Tan 5, Fuqiang Yin 6 7, Xiaoyun Zeng 1 7
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PMID: 32547951 PMCID: PMC7270198 DOI: 10.3389/fonc.2020.00847
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Abstract
Simultaneous identification of multiple single genes and multi-gene prognostic signatures with higher efficacy in liver cancer has rarely been reported. Here, 1,173 genes potentially related to the liver cancer prognosis were mined with Coremine, and the gene expression and survival data in 370 samples for overall survival (OS) and 319 samples for disease-free survival (DFS) were retrieved from The Cancer Genome Atlas. Numerous survival analyses results revealed that 39 genes and 28 genes significantly associated with DFS and OS in liver cancer, including 18 and 12 novel genes that have not been systematically reported in relation to the liver cancer prognosis, respectively. Next, totally 9,139 three-gene combinations (including 816 constructed by 18 novel genes) for predicting DFS and 3,276 three-gene combinations (including 220 constructed by 12 novel genes) for predicting OS were constructed based on the above genes, and the top 15 of these four parts three-gene combinations were selected and shown. Moreover, a huge difference between high and low expression group of these three-gene combination was detected, with median survival difference of DFS up to 65.01 months, and of OS up to 83.57 months. The high or low expression group of these three-gene combinations can predict the longest prognosis of DFS and OS is 71.91 months and 102.66 months, and the shortest is 6.24 months and 13.96 months. Quantitative real-time polymerase chain reaction and immunohistochemistry reconfirmed that three genes F2, GOT2, and TRPV1 contained in one of the above combinations, are significantly dysregulated in liver cancer tissues, low expression of F2, GOT2, and TRPV1 is associated with poor prognosis in liver cancer. Overall, we discovered a few novel single genes and multi-gene combinations biomarkers that are closely related to the long-term prognosis of liver cancer, and they can be potential therapeutic targets for liver cancer.
Keywords: data mining; disease-free survival (DFS); gene combinations; liver cancer; overall survival (OS).
Copyright © 2020 Liu, Liu, Liu, Xiao, Guo, Qin, Wu, Liang, Liang, Li, Zhang, Yang, Luo, Lei, Tan, Yin and Zeng.
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Review Front Oncol
. 2020 May 29;10:709. doi: 10.3389/fonc.2020.00709. eCollection 2020.
Isolated Pancreatic Metastases of Renal Cell Carcinoma-A Paradigm of a Seed and Soil Mechanism: A Literature Analysis of 1,034 Observations
Franz Sellner 1
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PMID: 32547940 PMCID: PMC7273884 DOI: 10.3389/fonc.2020.00709
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Abstract
Previously documented arguments, in favor of the suspected impact of a seed and soil mechanism, in the development and progression of isolated pancreatic metastasis of renal cell carcinomas (isPM) are: (1) uniform and independent from the side of the primary tumor distribution of isPM within the pancreas and, (2) the similar survival rates for singular and multiple isPM. In addition, the present study adds new arguments that further confirm the importance of an seed and soil mechanism in isPM: (1) Within the singular isPM, the size of the metastasis does not affect the overall survival; (2) Within the group of multiple isPMs, the overall survival does not depend on the number of metastases; (3) For synchronous and metachronous isPM, survival rates are also not different, and (4) Within the group of metachronous isPM there is also no correlation between the overall survival and interval until metastases occurs. This unusual ineffectiveness of otherwise known risk factors of solid cancers can be explained plausibly by the hypothesis of a very selective seed and soil mechanism in isPM. It only allows embolized renal carcinoma cells in the pancreas to complete all steps required to grow into clinically manifest metastases. In all other organs, on the other hand, the body is able to eliminate the embolized tumor cells or at least put them into a dormant state for many years. This minimizes the risk of occult micrometastases in distant organs, which could later-after isPM treatment-grow into clinically manifest metastases, so that the prognosis of the isPM is only determined by an adequate therapy of the pancreatic foci, and prognostic factors, such as total tumor burden or interval until the occurrence of the isPM remain ineffective.
Keywords: isolated pancreatic metastases; renal cell carcinoma; renal cell carcinoma metastasis; seed and soil mechanism; treatment results.
Copyright © 2020 Sellner.
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Review Front Oncol
. 2020 May 12;10:619. doi: 10.3389/fonc.2020.00619. eCollection 2020.
Functional Landscape of Dysregulated MicroRNAs in Oral Squamous Cell Carcinoma: Clinical Implications
Ruma Dey Ghosh 1, Arun Pattatheyil 2, Susanta Roychoudhury 3
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PMID: 32547936 PMCID: PMC7274490 DOI: 10.3389/fonc.2020.00619
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Abstract
MicroRNA (miRNA) dysregulation is associated with the pathogenesis of oral squamous cell carcinoma (OSCC), and its elucidation could potentially provide information on patient outcome. A growing body of translational research on miRNA biology is focusing on precision oncology, aiming to decode the miRNA regulatory network in the development and progression of cancer. Tissue-specific expression and stable presence in all body fluids are unique features of miRNAs, which could be potentially exploited in the clinical setting. Recent understanding of miRNA properties has led them to be useful, attractive, and potential tools either as biomarkers (distinct miRNA expression signature) for diagnosis and prognostic outcomes or as targets for novel therapeutic entities, enabling personalized treatment for OSCC. In this review, we discuss recent research on different aspects of alterations in miRNA profiles along with their clinical significance and strive to identify probable potential miRNA biomarkers for diagnosis and prognosis of OSCC. We also discuss the current understanding and scope of development of miRNA-based therapeutics against OSCC.
Keywords: dysregulated miRNA; miRNA biomarker; miRNA-based therapy; non-invasive biomarker; oral squamous cell carcinoma.
Copyright © 2020 Ghosh, Pattatheyil and Roychoudhury.
123 references
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Front Oncol
. 2020 May 25;10:634. doi: 10.3389/fonc.2020.00634. eCollection 2020.
Anterior Clinoidal Meningiomas: Meningeal Anatomical Considerations and Surgical Implications
Tao Xu 1, Yong Yan 1, Alexander I Evins 2, Zhenyu Gong 1, Lei Jiang 1, Huaiyu Sun 3, Li Cai 4, Hongxiang Wang 1, Weiqing Li 5, Yicheng Lu 1, Ming Zhang 6, Juxiang Chen 1
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PMID: 32547937 PMCID: PMC7278713 DOI: 10.3389/fonc.2020.00634
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Abstract
Objective: Surgical removal of anterior clinoidal meningiomas (ACMs) remains a challenge because of its complicated relationship with surrounding meninges, major arteries and cranial nerves. This study aims to define the meningeal structures around the anterior clinoid process (ACP) and its surgical implications. Methods: Five dry skulls and 19 cadavers were used in the anatomical study. Cadavers were prepared as transverse, coronal, and sagittal plastinated sections, and the meningeal architecture around the ACP was studied with dissecting and confocal microscopies. The database of meningiomas in one single center was retrospectively reviewed, and the patients with ACMs were collected for clinical analysis. Results: The superior, lateral, medial surfaces, and the tip of ACP were covered by different layers and types of meninges. The ACMs were classified into four main types based on the sites of origin, possible extending pathways following meningeal dura. In the retrospective cohort of 131 ACMs, the percentage of types I, IIa, IIb, III, and IV were 42.0% (55/131), 19.8% (26/131), 9.2% (12/131), 16.8% (22/131), and 12.2% (16/131), respectively. We found that types IIa and I had higher chances for achieving Simpson grade 1-2 resection (92.3 and 85.4%, respectively), followed by type III (54.5%) and type IV (31.3%), while type IIb showed little chance of Simpson grade 1-2 resection. Univariate and multivariate analyses revealed ACM classification and tumor size (<3 cm) to be independent risk factors for achieving more extensive resection. Conclusion: The meningeal architecture around the ACP may guide and determine the origin and extension of ACMs. The classification based on the meningeal architecture helps to understand surgical anatomy as well as predicting surgical outcomes.
Keywords: anterior clinoid process; anterior clinoidal meningioma; carotid artery; cavernous sinus; classification; meninges; surgical anatomy.
Copyright © 2020 Xu, Yan, Evins, Gong, Jiang, Sun, Cai, Wang, Li, Lu, Zhang and Chen.
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Review Front Oncol
. 2020 May 27;10:860. doi: 10.3389/fonc.2020.00860. eCollection 2020.
Minimal Residual Disease in Multiple Myeloma: Current Landscape and Future Applications With Immunotherapeutic Approaches
Ioannis V Kostopoulos 1, Ioannis Ntanasis-Stathopoulos 2, Maria Gavriatopoulou 2, Ourania E Tsitsilonis 1, Evangelos Terpos 2
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PMID: 32537439 PMCID: PMC7267070 DOI: 10.3389/fonc.2020.00860
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Abstract
The basic principle that deeper therapeutic responses lead to better clinical outcomes in cancer has emerged technologies capable of detecting rare residual tumor cells. The need for ultra-sensitive approaches for minimal residual disease (MRD) detection is particularly evident in Multiple Myeloma (MM), where patients will ultimately relapse despite the achievement of complete remission, which is commonplace due to remarkable therapeutic advances. Consequently, current response criteria on MM have been amended based on MRD status and MRD negativity is now considered the most dominant prognostic factor and the most valuable indicator for a subsequent relapse. However, there are particular limitations and several aspects for MRD assessment that remain open. This review summarizes current data on MRD in the clinical management of MM, highlights open issues and discusses the challenges and the endless opportunities arising for both patients and clinicians. Furthermore, it focuses on the current status of MRD in clinical trials, its dynamics in addressing debatable aspects in the clinical handling and its potential role as the prevailing factor for future MRD-driven tailored therapies.
Keywords: minimal residual disease; multiple myeloma; primary endpoint; prognostic factor; therapeutic intervention.
Copyright © 2020 Kostopoulos, Ntanasis-Stathopoulos, Gavriatopoulou, Tsitsilonis and Terpos.
114 references
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Front Oncol
. 2020 Jun 1;10:809. doi: 10.3389/fonc.2020.00809. eCollection 2020.
Identification of Potential Key Genes for Pathogenesis and Prognosis in Prostate Cancer by Integrated Analysis of Gene Expression Profiles and the Cancer Genome Atlas
Shuang Liu 1, Wenxin Wang 2, Yan Zhao 3, Kaige Liang 1, Yaojiang Huang 1 4
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PMID: 32547947 PMCID: PMC7277826 DOI: 10.3389/fonc.2020.00809
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Abstract
Background: Prostate cancer (PCa)is a malignancy of the urinary system with a high incidence, which is the second most common male cancer in the world. There are still huge challenges in the treatment of prostate cancer. It is urgent to screen out potential key biomarkers for the pathogenesis and prognosis of PCa. Methods: Multiple gene differential expression profile datasets of PCa tissues and normal prostate tissues were integrated analysis by R software. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis of the overlapping Differentially Expressed Genes (DEG) were performed. The STRING online database was used in conjunction with Cytospace software for protein-protein interaction (PPI) network analysis to define hub genes. The relative mRNA expression of hub genes was detected in Gene Expression Profiling Interactive Analysis (GEPIA) database. A prognostic gene signature was identified by Univariate and multivariate Cox regression analysis. Results: Three hundred twelve up-regulated genes and 85 down-regulated genes were identified from three gene expression profiles (GSE69223, GSE3325, GSE55945) and The Cancer Genome Atlas Prostate Adenocarcinoma (TCGA-PRAD) dataset. Seven hub genes (FGF2, FLNA, FLNC, VCL, CAV1, ACTC1, and MYLK) further were detected, which related to the pathogenesis of PCa. Seven prognostic genes (BCO1, BAIAP2L2, C7, AP000844.2, ASB9, MKI67P1, and TMEM272) were screened to construct a prognostic gene signature, which shows good predictive power for survival by the ROC curve analysis. Conclusions: We identified a robust set of new potential key genes in PCa, which would provide reliable biomarkers for early diagnosis and prognosis and would promote molecular targeting therapy for PCa.
Keywords: GEO; TCGA; bioinformatics; biomarker; prostate cancer; survival.
Copyright © 2020 Liu, Wang, Zhao, Liang and Huang.
40 references8 figures
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Review Front Oncol
. 2020 May 27;10:831. doi: 10.3389/fonc.2020.00831. eCollection 2020.
Biomarkers for Pancreatic Neuroendocrine Neoplasms (PanNENs) Management-An Updated Review
Martine Bocchini 1, Fabio Nicolini 1, Stefano Severi 2, Alberto Bongiovanni 3, Toni Ibrahim 3, Giorgia Simonetti 1, Ilaria Grassi 2, Massimiliano Mazza 1
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PMID: 32537434 PMCID: PMC7267066 DOI: 10.3389/fonc.2020.00831
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Pancreatic neuroendocrine tumors (PanNENs) are rare sporadic cancers or develop as part of hereditary syndromes. PanNENs can be both functioning and non-functioning based on whether they produce bioactive peptides. Some PanNENs are well differentiated while others-poorly. Symptoms, thus, depend on both oncological and hormonal causes. PanNEN diagnosis and treatment benefit from and in some instances are guided by biomarker monitoring. However, plasmatic monoanalytes are only suggestive of PanNEN pathological status and their positivity is typically followed by deepen diagnostic analyses through imaging techniques. There is a strong need for new biomarkers and follow-up modalities aimed to improve the outcome of PanNEN patients. Liquid biopsy follow-up, i.e., sequential analysis on tumor biomarkers in body fluids offers a great potential, that need to be substantiated by additional studies focusing on the specific markers and the timing of the analyses. This review provides the most updated panorama on PanNEN biomarkers.
Keywords: FDG (18F-fluorodeoxyglucose)-PET/CT; biomarker; neuroendocrine syndrome; pancreatic neuroendocrine tumor; pancreatic tumor.
Copyright © 2020 Bocchini, Nicolini, Severi, Bongiovanni, Ibrahim, Simonetti, Grassi and Mazza.
237 references1 figure
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Front Oncol
. 2020 May 29;10:823. doi: 10.3389/fonc.2020.00823. eCollection 2020.
RNA Sequencing Revealed Signals of Evolution From Gallbladder Stone to Gallbladder Carcinoma
Jinghan Wang 1, Chang Xu 1, Qingbao Cheng 1, Jiangman Zhao 2 3, Shouxin Wu 2 3, Wushuang Li 2 3, Wencong Ma 1, Chen Liu 1, Xiaoqing Jiang 1
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PMID: 32547950 PMCID: PMC7272658 DOI: 10.3389/fonc.2020.00823
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Gallbladder stone is a major risk factor for gallbladder carcinoma (GBC), while there is still a controversy whether period of follow-up since newly diagnoses of asymptomatic gallstones increases the risk of GBC. In this study, 10 GBC patients and 30 patients with gallstones were admitted to our hospital. Patients with gallstones were divided into 3 groups according to the follow-up time, involving 10 patients with follow-up period of 1-3 years (GS3 group), 10 patients with follow-up period of 5-10 years (GS5 group), and 10 patients with follow-up period of more than 10 years (GS10 group). Tumor and para-tumor tissues of GBC patients, and gallbladder tissues of gallstone patients were collected. RNA sequencing was performed on the 50 samples. Besides, 1,704 differentially expressed genes (DEGs) were identified in tumors compared with para-tumor tissues of 10 GBC patients, which were enriched into some well-known cancer-related pathways, such as PI3K-Akt, mitogen-activated protein kinase (MAPK), Ras, and Wnt signaling pathways, and the most significant pathway was neuroactive ligand-receptor interaction. Patients with gallstones with periods of follow-up equal to 1-3 and > 10 years showed to have higher cancer risk than those with 5-10 years. ALPP and GPR87 are potential biomarkers for predicting cancer risk in patients with gallstones. The in vitro results revealed that GPR-87 can promote the proliferation, migration, and invasion of GBC cells. Herein, we explored the relationship between GBC patients and patients with gallstones with different periods of follow-up in transcriptome level.
Keywords: ALPP; GPR87; RNA sequencing; follow-up time; gallbladder carcinoma; gallbladder stone.
Copyright © 2020 Wang, Xu, Cheng, Zhao, Wu, Li, Ma, Liu and Jiang.
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Front Oncol
. 2020 May 27;10:835. doi: 10.3389/fonc.2020.00835. eCollection 2020.
Development and Validation of a 12-Gene Immune Relevant Prognostic Signature for Lung Adenocarcinoma Through Machine Learning Strategies
Liang Xue 1, Guoshu Bi 1, Cheng Zhan 1, Yi Zhang 1, Yunfeng Yuan 1, Hong Fan 1
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PMID: 32537435 PMCID: PMC7267039 DOI: 10.3389/fonc.2020.00835
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Background: Although immunotherapy with checkpoint inhibitors is changing the face of lung adenocarcinoma (LUAD) treatments, only limited patients could benefit from it. Therefore, we aimed to develop an immune-relevant-gene-based signature to predict LUAD patients' prognosis and to characterize their tumor microenvironment thus guiding therapeutic strategy. Methods and Materials: Gene expression data of LUAD patients from Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) were systematically analyzed. We performed Cox regression and random survival forest algorithm to identify immune-relevant genes with potential prognostic value. A risk score formula was then established by integrating these selected genes and patients were classified into high- and low-risk score group. Differentially expressed genes, infiltration level of immune cells, and several immune-associated molecules were further compared across the two groups. Results: Nine hundred and fifty-four LUAD patients were enrolled in this study. After implementing the 2-steps machine learning screening methods, 12 immune-relevant genes were finally selected into the risk-score formula and the patients in high-risk group had significantly worse overall survival (HR = 10.6, 95%CI = 3.21-34.95, P < 0.001). We also found the distinct immune infiltration patterns in the two groups that several immune cells like cytotoxic cells and immune checkpoint molecules were significantly enriched and upregulated in patients from the high-risk group. These findings were further validated in two independent LUAD cohorts. Conclusion: Our risk score formula could serve as a powerful and accurate tool for predicting survival of LUAD patients and may facilitate clinicians to choose the optimal therapeutic regimen more precisely.
Keywords: immune infiltration; lung adenocarcinoma; machine learning; risk score formula; survival.
Copyright © 2020 Xue, Bi, Zhan, Zhang, Yuan and Fan.
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Front Oncol
. 2020 May 29;10:814. doi: 10.3389/fonc.2020.00814. eCollection 2020.
Whole Pelvic Radiotherapy With Stereotactic Body Radiotherapy Boost vs. Conventionally Fractionated Radiotherapy for Patients With High or Very High-Risk Prostate Cancer
Shih-Chang Wang 1, Wei-Chen Ting 2, Yun-Ching Chang 3, Ching-Chieh Yang 1 4, Li-Ching Lin 1, Hsiu-Wen Ho 1, Shou-Sheng Chu 1, Yu-Wei Lin 1 4 5
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PMID: 32547949 PMCID: PMC7273130 DOI: 10.3389/fonc.2020.00814
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Background: Whole pelvic radiotherapy (WPRT) with stereotactic body radiotherapy (SBRT) boost has been shown to be effective in patients with high-risk prostate cancer (PC). However, no study has directly compared the efficacy of WPRT with SBRT boost with that of conventionally fractionated radiotherapy (CFRT). We compared the clinical outcomes between CFRT and WPRT with SBRT boost in patients with high or very high-risk PC (National Comprehensive Cancer Network definition). Methods: In total, 132 patients treated with CFRT and 121 patients treated with WPRT followed by SBRT boost were retrospectively analyzed. For the CFRT group, the prescribed dose range was 74-79.2 Gray (Gy) administered at 1.8-2 Gy per fraction. For WPRT with SBRT boost, the prescribed doses were 45 Gy administered in 25 fractions to the whole pelvis followed by 21 Gy boost (3 fractions of 7 Gy each) to prostate and seminal vesicles. The overall survival (OS) and biochemical failure (Phoenix definition) free survival (bFFS) were assessed by using the Kaplan-Meier method or the Cox proportional hazards regression model. The gastrointestinal (GI) and genitourinary (GU) tract toxicity were assessed using the National Cancer Institute Common Terminology Criteria for Adverse Events (CTCAE) v3.0. Results: The estimated 4-years overall survival in the CFRT and WPRT with SBRT boost groups was 91.6 and 97.7%, respectively (P = 0.18). The estimated 4-years biochemical failure-free survival in the CFRT and WPRT with SBRT boost groups was 89.1 and 93.9%, respectively (P = 0.41). No acute grade 3 or higher GI and GU toxicity was observed in both groups. Late grade 3 GI and GU toxicity occurred in 2.3 and 2.3% in the CFRT group, and in 1.7 and 0.8% in the WPRT with SBRT boost group, respectively. There was no significant between-group difference with respect to acute or late toxicity. Conclusions: In patients with high or very high-risk localized PC, compared with CFRT, WPRT with SBRT boost resulted in similar biochemical-free and overall survival rate with minimal toxicity. WPRT with SBRT boost is a feasible option for patients with high or very high-risk PC.
Keywords: SBRT; conventionally fractionated; high risk; prostate cancer; radiotherapy.
Copyright © 2020 Wang, Ting, Chang, Yang, Lin, Ho, Chu and Lin.
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Front Oncol
. 2020 May 29;10:873. doi: 10.3389/fonc.2020.00873. eCollection 2020.
Identification of an Autophagy-Related Prognostic Signature for Clear Cell Renal Cell Carcinoma
Mei Chen 1, Shufang Zhang 1, Zhenyu Nie 1, Xiaohong Wen 1, Yuanhui Gao 1
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PMID: 32547955 PMCID: PMC7274034 DOI: 10.3389/fonc.2020.00873
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Abstract
Abnormal autophagy is closely related to the development of cancer. Many studies have demonstrated that autophagy plays an important role in biological function in clear cell renal cell carcinoma (ccRCC). This study aimed to construct a prognostic signature for ccRCC based on autophagy-related genes (ARGs) to predict the prognosis of ccRCC. Differentially expressed ARGs were obtained from ccRCC RNA-seq data in The Cancer Genome Atlas (TCGA) database. ARGs were enriched by gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). The prognostic ARGs used to construct the risk score models for overall survival (OS) and disease-free survival (DFS) were identified by Cox regression analyses. According to the median value of the risk score, patients were divided into a high-risk group and a low-risk group. The OS and DFS were analyzed by the Kaplan-Meier method. The predictive accuracy was determined by a receiver operating characteristic (ROC) curve analysis. Additionally, we performed stratification analyses based on different clinical variables and evaluated the correlation between the risk score and the clinical variables. The differentially expressed ARGs were mainly enriched in the platinum drug resistance pathway. The prognostic signatures based on 11 ARGs for OS and 5 ARGs for DFS were constructed and showed that the survive time was significantly shorter in the high-risk group than in the low-risk group (P < 0.001). The ROC curve for OS exhibited good predictive accuracy, with an area under the curve value of 0.738. In the stratification analyses, the OS time of the high-risk group was shorter than that of the low-risk group stratified by different clinical variables. In conclusion, an autophagy-related signature for OS we constructed can independently predict the prognosis of ccRCC patient, and provide a deep understanding of the potential biological mechanisms of autophagy in ccRCC.
Keywords: autophagy; clear cell renal cell carcinoma; platinum drug resistance; prognosis; the cancer genome atlas.
Copyright © 2020 Chen, Zhang, Nie, Wen and Gao.
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Front Oncol
. 2020 May 27;10:821. doi: 10.3389/fonc.2020.00821. eCollection 2020.
PD-L1 Inhibitor Regulates the miR-33a-5p/PTEN Signaling Pathway and Can Be Targeted to Sensitize Glioblastomas to Radiation
Wenzheng Xia 1, Jin Zhu 1, Yinda Tang 1, Xueyi Wang 1, Xiangyu Wei 1, Xuan Zheng 1, Meng Hou 2, Shiting Li 1
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PMID: 32537433 PMCID: PMC7266984 DOI: 10.3389/fonc.2020.00821
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Glioblastoma (GBM) is the most common and lethal brain tumor in adults. Ionizing radiation (IR) is a standard treatment for GBM patients and results in DNA damage. However, the clinical efficacy of IR is limited due to therapeutic resistance. The programmed death ligand 1 (PD-L1) blockade has a shown the potential to increase the efficacy of radiotherapy by inhibiting DNA damage and repair responses. The miR-33a-5p is an essential microRNA that promotes GBM growth and self-renewal. In this study, we investigated whether a PD-L1 inhibitor (a small molecule inhibitor) exerted radio-sensitive effects to impart an anti-tumor function in GBM cells by modulating miR-33a-5p. U87 MG cells and U251 cells were pretreated with PD-L1 inhibitor. The PD-L1 inhibitor-induced radio-sensitivity in these cells was assessed by assaying cellular apoptosis, clonogenic survival assays, and migration. TargetScan and luciferase assay showed that miR-33a-5p targeted the phosphatase and tensin homolog (PTEN) 3' untranslated region. The expression level of PTEN was measured by western blotting, and was also silenced using small interfering RNAs. The levels of DNA damage following radiation was measured by the presence of γ-H2AX foci, cell cycle, and the mRNA of the DNA damage-related genes, BRCA1, NBS1, RAD50, and MRE11. Our results demonstrated that the PD-L1 inhibitor significantly decreased the expression of the target gene, miR-33a-5p. In addition, pretreatment of U87 MG and U251 cells with the PD-L1 inhibitor increased radio-sensitivity, as indicated by increased apoptosis, while decreased survival and migration of GBM cells. Mir-33a-5p overexpression or silencing PTEN in U87 MG and U251 cells significantly attenuated PD-L1 radiosensitive effect. Additionally, PD-L1 inhibitor treatment suppressed the expression of the DNA damage response-related genes, BRCA1, NBS1, RAD50, and MRE11. Our results demonstrated a novel role for the PD-L1 inhibitor in inducing radio- sensitivity in GBM cells, where inhibiting miR-33a-5p, leading to PTEN activated, and inducing DNA damage was crucial for antitumor immunotherapies to treat GBM.
Keywords: DNA damage response; glioblastoma; miR-33a-5p/PTEN signaling pathway; programmed death ligand 1 (PD-L1) blockade; radio-sensitization.
Copyright © 2020 Xia, Zhu, Tang, Wang, Wei, Zheng, Hou and Li.
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Front Oncol
. 2020 May 29;10:592. doi: 10.3389/fonc.2020.00592. eCollection 2020.
A Computed Tomography-Based Radiomics Nomogram to Preoperatively Predict Tumor Necrosis in Patients With Clear Cell Renal Cell Carcinoma
Yi Jiang 1 2, Wuchao Li 3 4, Chencui Huang 5, Chong Tian 3 4, Qi Chen 2, Xianchun Zeng 3 4, Yin Cao 6, Yi Chen 6, Yintong Yang 6, Heng Liu 7, Yonghua Bo 8, Chenggong Luo 9, Yiming Li 5, Tijiang Zhang 7, Rongping Wang 1 3 4
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PMID: 32547934 PMCID: PMC7272670 DOI: 10.3389/fonc.2020.00592
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Abstract
Objective: To develop and validate a radiomics nomogram for preoperative prediction of tumor necrosis in patients with clear cell renal cell carcinoma (ccRCC). Methods: In total, 132 patients with pathologically confirmed ccRCC in one hospital were enrolled as a training cohort, while 123 ccRCC patients from second hospital served as the independent validation cohort. Radiomic features were extracted from corticomedullary and nephrographic phase contrast-enhanced computed tomography (CT) images. A radiomics signature based on optimal features selected by consistency analysis and the least absolute shrinkage and selection operator was developed. An image features model was constructed based on independent image features according to visual assessment. By integrating the radiomics signature and independent image features, a radiomics nomograph was constructed. The predictive performance of the above models was evaluated using receiver operating characteristic (ROC) curve analysis. Furthermore, the nomogram was assessed using calibration curve and decision curve analysis. Results: Thirty-seven features were used to establish a radiomics signature, which demonstrated better predictive performance than did the image features model constructed using tumor size and intratumoral vessels in the training and validation cohorts (p <0.05). The radiomics nomogram demonstrated satisfactory discrimination in the training (area under the ROC curve [AUC] 0.93 [95% CI 0.87-0.96]) and validation (AUC 0.87 [95% CI 0.79-0.93]) cohorts and good calibration (Hosmer-Lemeshow p>0.05). Decision curve analysis verified that the radiomics nomogram had the best clinical utility compared with the other models. Conclusion: The radiomics nomogram developed in the present study is a promising tool to predict tumor necrosis and facilitate preoperative clinical decision-making for patients with ccRCC.
Keywords: clear cell renal cell carcinoma; computed tomography; prediction model; radiomics; tumor necrosis.
Copyright © 2020 Jiang, Li, Huang, Tian, Chen, Zeng, Cao, Chen, Yang, Liu, Bo, Luo, Li, Zhang and Wang.
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Front Oncol
. 2020 Jun 1;10:895. doi: 10.3389/fonc.2020.00895. eCollection 2020.
A Nomogram Combined Radiomic and Semantic Features as Imaging Biomarker for Classification of Ovarian Cystadenomas
Shushu Pan 1, Zhongxiang Ding 1, Lexing Zhang 1, Mei Ruan 1, Yanna Shan 1, Meixiang Deng 2, Peipei Pang 3, Qijun Shen 1
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PMID: 32547958 PMCID: PMC7277787 DOI: 10.3389/fonc.2020.00895
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Objective: To construct and validate a combined Nomogram model based on radiomic and semantic features to preoperatively classify serous and mucinous pathological types in patients with ovarian cystadenoma. Methods: A total of 103 patients with pathology-confirmed ovarian cystadenoma who underwent CT examination were collected from two institutions. All cases divided into training cohort (N = 73) and external validation cohort (N = 30). The CT semantic features were identified by two abdominal radiologists. The preprocessed initial CT images were used for CT radiomic features extraction. The LASSO regression were applied to identify optimal radiomic features and construct the Radscore. A Nomogram model was constructed combining the Radscore and the optimal semantic feature. The model performance was evaluated by ROC analysis, calibration curve and decision curve analysis (DCA). Result: Five optimal features were ultimately selected and contributed to the Radscore construction. Unilocular/multilocular identification was significant difference from semantic features. The Nomogram model showed a better performance in both training cohort (AUC = 0.94, 95%CI 0.86-0.98) and external validation cohort (AUC = 0.92, 95%CI 0.76-0.98). The calibration curve and DCA analysis indicated a better accuracy of the Nomogram model for classification than either Radscore or the loculus alone. Conclusion: The Nomogram model combined radiomic and semantic features could be used as imaging biomarker for classification of serous and mucinous types of ovarian cystadenomas.
Keywords: algorithm; classification; cystadenoma; ovarian neoplasms; tomography; x-ray computed.
Copyright © 2020 Pan, Ding, Zhang, Ruan, Shan, Deng, Pang and Shen.
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Front Oncol
. 2020 May 27;10:838. doi: 10.3389/fonc.2020.00838. eCollection 2020.
CT-Imaging Based Analysis of Invasive Lung Adenocarcinoma Presenting as Ground Glass Nodules Using Peri- And Intra-nodular Radiomic Features
Linyu Wu 1 2, Chen Gao 1 2, Ping Xiang 1 2, Sisi Zheng 1 2, Peipei Pang 3, Maosheng Xu 1 2
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PMID: 32537436 PMCID: PMC7267037 DOI: 10.3389/fonc.2020.00838
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Objective: To evaluate whether radiomic features extracted from intra and peri-nodular lesions can enhance the ability to differentiate between invasive adenocarcinoma (IA), minimally invasive adenocarcinoma (MIA), and adenocarcinoma in situ (AIS) manifesting as ground-glass nodule (GGN). Materials and Methods: This retrospective study enrolled 120 patients with a total of 121 pathologically confirmed lung adenocarcinomas (85 IA and 36 AIS/MIA) from January 2015 to May 2019. The recruited patients were randomly divided into training (84 nodules) and validation sets (37 nodules), with a ratio of 7:3. The minority group in the training set was balanced by the synthetic minority over-sampling (SMOTE) method. The intra-, peri-nodular, and gross region of interests (ROI) were delineated with manual annotation. Image features were quantitatively extracted from each ROI on CT images. The minimum redundancy maximum relevance (mRMR) feature ranking method and the least absolute shrinkage and selection operator (LASSO) classifier were used to eliminate unnecessary features. The intra- and peri-nodular radiomic features were combined to produce the gross radiomic signature. A combined clinical-radiomic model was constructed by multivariable logistic regression analysis. The predicted performances of different models were evaluated using receiver operating curve (ROC) and calibration curve. Results: The gross radiomic signature (AUC: training set = 0.896; validation set = 0.876) showed a good ability to discriminate the invasiveness of adenocarcinoma, comparing to intra-nodular (AUC: training set = 0.862; validation set = 0.852) or peri-nodular radiomic signature (AUC: training set = 0.825; validation set = 0.820). The AUC of the combined clinical-radiomic model was 0.917 for the training and 0.876 for the validation cohort, respectively. Conclusions: The gross radiomic signature of intra- and peri-nodular regions improved the prediction ability and aided predicting the invasiveness of lung adenocarcinoma appearing as GGN.
Keywords: X-ray computed; computational biology; ground-glass nodule; lung adenocarcinoma; radiomics; tomography.
Copyright © 2020 Wu, Gao, Xiang, Zheng, Pang and Xu.
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Case Reports Front Oncol
. 2020 May 29;10:876. doi: 10.3389/fonc.2020.00876. eCollection 2020.
Follicular Dendritic Cell Sarcoma With Co-Expression of CD4 and CD30 Mimics Anaplastic Large Cell Lymphoma
Hui Liu 1 2, Chenxi Xiang 2, Mei Wu 1, Shimin Hu 3
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PMID: 32547956 PMCID: PMC7273153 DOI: 10.3389/fonc.2020.00876
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Follicular dendritic cell sarcoma (FDCS) is a low-grade malignant neoplasm that tends to be under-recognized owing to its rarity and wide pathologic spectrum. Knowledge of the atypical morphology and immunophenotype of FDCS is critical to avoid misdiagnosis. Here we presented a case of extranodal FDCS with an unusual morphology and a previously unreported immunophenotype leading to misdiagnosis. A 32-years-old man presented with a tonsilar mass that showed epithelioid cells in nested and alveolar patterns. Immunohistochemistry study revealed that the tumor cells were positive for CD4 and CD30, and were negative for cytokeratin, CD3, CD20, CD68, CD163, lysozyme, ALK, S-100, and desmin. Multiple outside expert consultations rendered a consensus diagnosis of ALK-negative anaplastic large cell lymphoma (ALCL). The patient received multiple lines of chemotherapy and radiotherapy. However, the residual tumor progressively enlarged eight months later and a more complex morphology was presented in the re-excised tumor: including spindle cells with vesicular nuclei and nuclear pseudoinclusions in fascicles or a whorled pattern, and plump ovoid cells arranged in meningioma-like whorls as well as epithelioid tumor cells similar to the initial biopsy. All these three components were positive for CD4, CD21, CD23, and CD35. The diagnosis was revised to FDCS after a positive immunostaining for CD21, CD23, and CD35 on the initial specimen was confirmed retrospectively. A literature review identified 57 cases of FDCS published from 2009 through 2019, and 13 (22.8%) of them were misdiagnosed at initial presentation. Among these misdiagnosed cases, all except one case were extranodal, and the incorrect initial diagnosis was mostly location-related. These cases expand the pathologic spectrum of FDCS, and further emphasize the necessity for pathologists to stay alert for this rare entity, bringing FDCS into the differentials for any spindle cell tumors, undifferentiated epithelioid cell tumors, and ALCL to avoid misdiagnosis.
Keywords: CD30; CD4; Follicular dendritic cell sarcoma; anaplastic large cell lymphoma; pathologic spectrum.
Copyright © 2020 Liu, Xiang, Wu and Hu.
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Front Oncol
. 2020 May 28;10:680. doi: 10.3389/fonc.2020.00680. eCollection 2020.
Deep Learning for Accurate Diagnosis of Liver Tumor Based on Magnetic Resonance Imaging and Clinical Data
Shi-Hui Zhen 1 2, Ming Cheng 2, Yu-Bo Tao 2, Yi-Fan Wang 1, Sarun Juengpanich 1, Zhi-Yu Jiang 1, Yan-Kai Jiang 1 2, Yu-Yu Yan 2, Wei Lu 3 4, Jie-Min Lue 1, Jia-Hong Qian 2, Zhong-Yu Wu 5, Ji-Hong Sun 3, Hai Lin 2, Xiu-Jun Cai 1
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PMID: 32547939 PMCID: PMC7271965 DOI: 10.3389/fonc.2020.00680
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Background: Early-stage diagnosis and treatment can improve survival rates of liver cancer patients. Dynamic contrast-enhanced MRI provides the most comprehensive information for differential diagnosis of liver tumors. However, MRI diagnosis is affected by subjective experience, so deep learning may supply a new diagnostic strategy. We used convolutional neural networks (CNNs) to develop a deep learning system (DLS) to classify liver tumors based on enhanced MR images, unenhanced MR images, and clinical data including text and laboratory test results. Methods: Using data from 1,210 patients with liver tumors (N = 31,608 images), we trained CNNs to get seven-way classifiers, binary classifiers, and three-way malignancy-classifiers (Model A-Model G). Models were validated in an external independent extended cohort of 201 patients (N = 6,816 images). The area under receiver operating characteristic (ROC) curve (AUC) were compared across different models. We also compared the sensitivity and specificity of models with the performance of three experienced radiologists. Results: Deep learning achieves a performance on par with three experienced radiologists on classifying liver tumors in seven categories. Using only unenhanced images, CNN performs well in distinguishing malignant from benign liver tumors (AUC, 0.946; 95% CI 0.914-0.979 vs. 0.951; 0.919-0.982, P = 0.664). New CNN combining unenhanced images with clinical data greatly improved the performance of classifying malignancies as hepatocellular carcinoma (AUC, 0.985; 95% CI 0.960-1.000), metastatic tumors (0.998; 0.989-1.000), and other primary malignancies (0.963; 0.896-1.000), and the agreement with pathology was 91.9%.These models mined diagnostic information in unenhanced images and clinical data by deep-neural-network, which were different to previous methods that utilized enhanced images. The sensitivity and specificity of almost every category in these models reached the same high level compared to three experienced radiologists. Conclusion: Trained with data in various acquisition conditions, DLS that integrated these models could be used as an accurate and time-saving assisted-diagnostic strategy for liver tumors in clinical settings, even in the absence of contrast agents. DLS therefore has the potential to avoid contrast-related side effects and reduce economic costs associated with current standard MRI inspection practices for liver tumor patients.
Keywords: MRI; artificial intelligence; deep learning; diagnosis; liver cancer; liver mass.
Copyright © 2020 Zhen, Cheng, Tao, Wang, Juengpanich, Jiang, Jiang, Yan, Lu, Lue, Qian, Wu, Sun, Lin and Cai.
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Publication date: September 2020Source: International Immunopharmacology, Volume 86Author(s): Mi-Young Park, Young-Kug Choo, Seong Ho Jeon, Won-Gu Jang, Ju-Hee Lee, Joo-Hee Park, Chang-Hyun Kim
Thu Jun 18, 2020 15:04
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Thu Jun 18, 2020 15:01
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Thu Jun 18, 2020 15:01
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Thu Jun 18, 2020 15:01
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Thu Jun 18, 2020 15:01
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Thu Jun 18, 2020 15:01
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Thu Jun 18, 2020 15:01
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Thu Jun 18, 2020 15:01
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