scholarly journals Impact of accumulated alterations in driver and passenger genes on response to radiation therapy

2020 ◽  
Vol 93 (1109) ◽  
pp. 20190625
Author(s):  
Yuji Seo ◽  
Keisuke Tamari ◽  
Yutaka Takahashi ◽  
Kazumasa Minami ◽  
Fumiaki Isohashi ◽  
...  
Keyword(s):  
Radiation Therapy ◽  
Cell Lines ◽  
Gene Mutations ◽  
The Cancer Genome Atlas ◽  
Driver Gene ◽  
Data Sets ◽  
Atlas Data ◽  
Cancer Genome Atlas ◽  
Genome Atlas ◽  
Gene Alterations

Objective: Although various single genetic factors have been shown to affect radiosensitivity, high-throughput DNA sequencing analyses have revealed complex genomic landscapes in many cancer types. The aim of this study is to elucidate the association between accumulated alterations in driver and passenger genes and radiation therapy response. Methods: We used 59 human solid cancer cell lines derived from 11 organ sites. Radiation-induced cell death was measured using a standard colony-forming assay delivered as a single dose ranging from 0 to 12 Gy. Comprehensive genomic data for the cell lines were acquired from the Catalogue Of Somatic Mutations In Cancer v. 80. Random forest classifiers were constructed to predict radioresistant phenotypes using genomic features. The Cancer Genome Atlas data sets were used to evaluate the clinical impact of the genomic feature following radiotherapy. Results: The 59 cancer cell lines harbored either nucleotide variations or copy number variations in a median of 157 genes per cell. Radiosensitivity of the cancer cells was correlated with neither the number of driver gene mutations nor the number of passenger gene mutations. However, the proportion of driver gene alterations to total gene alterations in gene sets selected from the Kyoto Encyclopedia Genes and Genomes predicted radioresistant cells with sensitivity of 85% and specificity of 73%. High probability of radioresistance predicted by the model was associated with worse overall survival following definitive radiotherapy in patients of The Cancer Genome Atlas data sets. Conclusion: Cellular radiosensitivity was associated with the proportion of driver to total gene alterations in the selected oncogenic pathways, which may be a biomarker candidate for response to radiation therapy. Advances in knowledge: These findings suggest that accumulated alterations in not only driver genes but also passenger genes affect radiosensitivity.

Prediction of transcription factors binding events based on epigenetic modifications in different human cells

Epigenomics ◽  
2020 ◽  
Vol 12 (16) ◽  
pp. 1443-1456
Author(s):  
Yan Huang ◽  
Dianshuang Zhou ◽  
Yihan Wang ◽  
Xingda Zhang ◽  
Mu Su ◽  
...  
Keyword(s):  
Cell Lines ◽  
Predictive Models ◽  
High Performance ◽  
Epigenetic Modifications ◽  
The Cancer Genome Atlas ◽  
Encode Project ◽  
Atlas Data ◽  
Random Forest Method ◽  
Cancer Genome Atlas ◽  
Genome Atlas

Aim: We aim to predict transcription factor (TF) binding events from knowledge of gene expression and epigenetic modifications. Materials & methods: TF-binding events based on the Encode project and The Cancer Genome Atlas data were analyzed by the random forest method. Results: We showed the high performance of TF-binding predictive models in GM12878, HeLa, HepG2 and K562 cell lines and applied them to other cell lines and tissues. The genes bound by the top TFs ( MAX and MAZ) were significantly associated with cancer-related processes such as cell proliferation and DNA repair. Conclusion: We successfully constructed TF-binding predictive models in cell lines and applied them in tissues.

scholarly journals PR/SET Domain Family and Cancer: Novel Insights from the Cancer Genome Atlas

2018 ◽  
Vol 19 (10) ◽  
pp. 3250 ◽  
Author(s):  
Anna Sorrentino ◽  
Antonio Federico ◽  
Monica Rienzo ◽  
Patrizia Gazzerro ◽  
Maurizio Bifulco ◽  
...  
Keyword(s):  
Family Members ◽  
Cancer Genome ◽  
The Cancer Genome Atlas ◽  
Driver Gene ◽  
Rna Seq ◽  
Set Domain ◽  
Primary Tumors ◽  
Cancer Genome Atlas ◽  
Pan Cancer ◽  
Genome Atlas

The PR/SET domain gene family (PRDM) encodes 19 different transcription factors that share a subtype of the SET domain [Su(var)3-9, enhancer-of-zeste and trithorax] known as the PRDF1-RIZ (PR) homology domain. This domain, with its potential methyltransferase activity, is followed by a variable number of zinc-finger motifs, which likely mediate protein–protein, protein–RNA, or protein–DNA interactions. Intriguingly, almost all PRDM family members express different isoforms, which likely play opposite roles in oncogenesis. Remarkably, several studies have described alterations in most of the family members in malignancies. Here, to obtain a pan-cancer overview of the genomic and transcriptomic alterations of PRDM genes, we reanalyzed the Exome- and RNA-Seq public datasets available at The Cancer Genome Atlas portal. Overall, PRDM2, PRDM3/MECOM, PRDM9, PRDM16 and ZFPM2/FOG2 were the most mutated genes with pan-cancer frequencies of protein-affecting mutations higher than 1%. Moreover, we observed heterogeneity in the mutation frequencies of these genes across tumors, with cancer types also reaching a value of about 20% of mutated samples for a specific PRDM gene. Of note, ZFPM1/FOG1 mutations occurred in 50% of adrenocortical carcinoma patients and were localized in a hotspot region. These findings, together with OncodriveCLUST results, suggest it could be putatively considered a cancer driver gene in this malignancy. Finally, transcriptome analysis from RNA-Seq data of paired samples revealed that transcription of PRDMs was significantly altered in several tumors. Specifically, PRDM12 and PRDM13 were largely overexpressed in many cancers whereas PRDM16 and ZFPM2/FOG2 were often downregulated. Some of these findings were also confirmed by real-time-PCR on primary tumors.

scholarly journals The PD-L1 Metabolic Interactome Intersects with Choline Metabolism and Inflammation

2020 ◽  
Author(s):  
Jesús Pacheco-Torres ◽  
Marie-France Penet ◽  
Yelena Mironchik ◽  
Balaji Krishnamachary ◽  
Zaver M Bhujwalla
Keyword(s):  
Breast Cancer ◽  
Cell Lines ◽  
Cancer Cell ◽  
Immune Checkpoint ◽  
Cancer Metabolism ◽  
The Cancer Genome Atlas ◽  
Immune Checkpoints ◽  
Cancer Genome Atlas ◽  
Cox 2 ◽  
Genome Atlas

Abstract Background: Harnessing the power of the immune system by using immune checkpoint inhibitors has resulted in some of the most exciting advances in cancer treatment. The full potential of this approach has, however, not been fully realized for treating many cancers such as pancreatic and breast cancer. Cancer metabolism influences many aspects of cancer progression including immune surveillance. An expanded understanding of how cancer metabolism can directly impact immune checkpoints may allow further optimization of immunotherapy. We therefore investigated, for the first time, the relationship between the overexpression of choline kinase-α (Chk-α), an enzyme observed in most cancers, and expression of the immune checkpoint PD-L1. Methods: We used small interfering RNA to downregulate Chk-a, PD-L1 or both in two triple negative human breast cancer cell lines (MDA-MB-231 and SUM-149) and two human pancreatic ductal adenocarcinoma cell lines (Pa09C and Pa20C). The effects of the downregulation were studied at the genomic, proteomic and metabolomic levels. The findings were compared with results obtained by analysis of public data from The Cancer Genome Atlas Program.Results: We identified an inverse dependence between Chk-α and PD-L1 at the genomic, proteomic and metabolomic levels. We also found that prostaglandin-endoperoxide synthase 2 (COX-2) and transforming growth factor beta (TGF-β) play an important role in this relationship. We independently confirmed this relationship in human cancers by analyzing data from The Cancer Genome Atlas Program. Conclusions: Our data identified previously unknown roles of PD-L1 in cancer cell metabolic reprogramming, and revealed the immunosuppressive increased PD-L1 effect of Chk-α downregulation. These data suggest that PD-L1 regulation of metabolism may be mediated through Chk-α, COX-2 and TGF-β. The observations provide new insights that can be applied to the rational design of combinatorial therapies targeting immune checkpoints and cancer metabolism.

scholarly journals The PD-L1 metabolic interactome intersects with choline metabolism and inflammation

2021 ◽  
Author(s):  
Jesús Pacheco-Torres ◽  
Marie-France Penet ◽  
Yelena Mironchik ◽  
Balaji Krishnamachary ◽  
Zaver M Bhujwalla
Keyword(s):  
Breast Cancer ◽  
Cell Lines ◽  
Cancer Cell ◽  
Immune Checkpoint ◽  
Cancer Metabolism ◽  
The Cancer Genome Atlas ◽  
Immune Checkpoints ◽  
Cancer Genome Atlas ◽  
Cox 2 ◽  
Genome Atlas

Abstract Background: Harnessing the power of the immune system by using immune checkpoint inhibitors has resulted in some of the most exciting advances in cancer treatment. The full potential of this approach has, however, not been fully realized for treating many cancers such as pancreatic and breast cancer. Cancer metabolism influences many aspects of cancer progression including immune surveillance. An expanded understanding of how cancer metabolism can directly impact immune checkpoints may allow further optimization of immunotherapy. We therefore investigated, for the first time, the relationship between the overexpression of choline kinase-α (Chk-α), an enzyme observed in most cancers, and expression of the immune checkpoint PD-L1. Methods: We used small interfering RNA to downregulate Chk-a, PD-L1 or both in two triple negative human breast cancer cell lines (MDA-MB-231 and SUM-149) and two human pancreatic ductal adenocarcinoma cell lines (Pa09C and Pa20C). The effects of the downregulation were studied at the genomic, proteomic and metabolomic levels. The findings were compared with results obtained by analysis of public data from The Cancer Genome Atlas Program.Results: We identified an inverse dependence between Chk-α and PD-L1 at the genomic, proteomic and metabolomic levels. We also found that prostaglandin-endoperoxide synthase 2 (COX-2) and transforming growth factor beta (TGF-β) play an important role in this relationship. We independently confirmed this relationship in human cancers by analyzing data from The Cancer Genome Atlas Program. Conclusions: Our data identified previously unknown roles of PD-L1 in cancer cell metabolic reprogramming, and revealed the immunosuppressive increased PD-L1 effect of Chk-α downregulation. These data suggest that PD-L1 regulation of metabolism may be mediated through Chk-α, COX-2 and TGF-β. The observations provide new insights that can be applied to the rational design of combinatorial therapies targeting immune checkpoints and cancer metabolism.

scholarly journals Targeting the coding sequence: opposing roles in regulating classical and non-classical MHC class I molecules by miR-16 and miR-744

2020 ◽  
Vol 8 (1) ◽  
pp. e000396
Author(s):  
Michael Friedrich ◽  
Christoforos K Vaxevanis ◽  
Katharina Biehl ◽  
Anja Mueller ◽  
Barbara Seliger
Keyword(s):  
Mhc Class I ◽  
Binding Sites ◽  
Hla Class I ◽  
The Cancer Genome Atlas ◽  
Class I ◽  
Atlas Data ◽  
Candidate Mirnas ◽  
Cancer Genome Atlas ◽  
Mhc Class I Molecules ◽  
Genome Atlas

BackgroundTo control gene expression, microRNAs (miRNAs) are of key importance and their deregulation is associated with the development and progression of various cancer types. In this context, a discordant messenger RNA/protein expression pointing to extensive post-transcriptional regulation of major histocompatibility complex (MHC) class I molecules was already shown. However, only a very limited number of miRNAs targeting these molecules have yet been identified. Despite an increasing evidence of coding sequence (CDS)-located miRNA binding sites, there exists so far, no detailed study of the interaction of miRNAs with the CDS of MHC class I molecules.MethodsUsing an MS2-tethering approach in combination with small RNA sequencing, a number of putative miRNAs binding to the CDS of human leukocyte antigen (HLA)-G were identified. These candidate miRNAs were extensively screened for their effects in the HLA-G-positive JEG3 cell line. Due to the high sequence similarity between HLA-G and classical MHC class I molecules, the impact of HLA-G candidate miRNAs on HLA class I surface expression was also analyzed. The Cancer Genome Atlas data were used to correlate candidate miRNAs and HLA class I gene expression.ResultsTransfection of candidate miRNAs revealed that miR-744 significantly downregulates HLA-G protein levels. In contrast, overexpression of the candidate miRNAs miR-15, miR-16, and miR-424 sharing the same seed sequence resulted in an unexpected upregulation of HLA-G. Comparable results were obtained for classical MHC class I members after transfection of miRNA mimics into HEK293T cells. Analyses of The Cancer Genome Atlas data sets for miRNA and MHC class I expression further validated the results.ConclusionsOur data expand the knowledge about MHC class I regulation and showed for the first time an miRNA-dependent control of MHC class I antigens mediated by the CDS. CDS-located miRNA binding sites could improve the general use of miRNA-based therapeutic approaches as these sites are highly independent of structural variations (e.g. mutations) in the gene body. Surprisingly, miR-16 family members promoted MHC class I expression potentially in a gene activation-like mechanism.

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