Pan-cancer driver copy number alterations identified by joint expression/CNA data analysis

Abstract Analysis of large gene expression datasets from biopsies of cancer patients can identify co-expression signatures representing particular biomolecular events in cancer. Some of these signatures involve genomically co-localized genes resulting from the presence of copy number alterations (CNAs), for which analysis of the expression of the underlying genes provides valuable information about their combined role as oncogenes or tumor suppressor genes. Here we focus on the discovery and interpretation of such signatures that are present in multiple cancer types due to driver amplifications and deletions in particular regions of the genome after doing a comprehensive analysis combining both gene expression and CNA data from The Cancer Genome Atlas.

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Somatic Copy Number Alterations in Human Cancers: An Analysis of Publicly Available Data From The Cancer Genome Atlas

Frontiers in Oncology ◽

10.3389/fonc.2021.700568 ◽

2021 ◽

Vol 11 ◽

Author(s):

Luuk Harbers ◽

Federico Agostini ◽

Marcin Nicos ◽

Dimitri Poddighe ◽

Magda Bienko ◽

...

Keyword(s):

Copy Number ◽

Cancer Genome ◽

The Cancer Genome Atlas ◽

Copy Number Alterations ◽

Multiple Cancer ◽

Human Cancers ◽

Cancer Genome Atlas ◽

Cancer Types ◽

Somatic Copy Number Alterations ◽

Genome Atlas

Somatic copy number alterations (SCNAs) are a pervasive trait of human cancers that contributes to tumorigenesis by affecting the dosage of multiple genes at the same time. In the past decade, The Cancer Genome Atlas (TCGA) and the International Cancer Genome Consortium (ICGC) initiatives have generated and made publicly available SCNA genomic profiles from thousands of tumor samples across multiple cancer types. Here, we present a comprehensive analysis of 853,218 SCNAs across 10,729 tumor samples belonging to 32 cancer types using TCGA data. We then discuss current models for how SCNAs likely arise during carcinogenesis and how genomic SCNA profiles can inform clinical practice. Lastly, we highlight open questions in the field of cancer-associated SCNAs.

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Identification and Characterization of MicroRNAs Associated with Somatic Copy Number Alterations in Cancer

Cancers ◽

10.3390/cancers10120475 ◽

2018 ◽

Vol 10 (12) ◽

pp. 475 ◽

Cited By ~ 1

Author(s):

Jihee Soh ◽

Hyejin Cho ◽

Chan-Hun Choi ◽

Hyunju Lee

Keyword(s):

Copy Number ◽

The Cancer Genome Atlas ◽

Cancer Development ◽

Cancer Type ◽

Biological Processes ◽

Copy Number Alterations ◽

Coding Regions ◽

Cancer Genome Atlas ◽

Cancer Types ◽

Somatic Copy Number Alterations

MicroRNAs (miRNAs) are key molecules that regulate biological processes such as cell proliferation, differentiation, and apoptosis in cancer. Somatic copy number alterations (SCNAs) are common genetic mutations that play essential roles in cancer development. Here, we investigated the association between miRNAs and SCNAs in cancer. We collected 2538 tumor samples for seven cancer types from The Cancer Genome Atlas. We found that 32−84% of miRNAs are in SCNA regions, with the rate depending on the cancer type. In these regions, we identified 80 SCNA-miRNAs whose expression was mainly associated with SCNAs in at least one cancer type and showed that these SCNA-miRNAs are related to cancer by survival analysis and literature searching. We also identified 58 SCNA-miRNAs common in the seven cancer types (CC-SCNA-miRNAs) and showed that these CC-SCNA-miRNAs are more likely to be related with protein and gene expression than other miRNAs. Furthermore, we experimentally validated the oncogenic role of miR-589. In conclusion, our results suggest that SCNA-miRNAs significantly alter biological processes related to cancer development, confirming the importance of SCNAs in non-coding regions in cancer.

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Computing MicroRNA-Gene Interaction Networks in Pan-cancer Using MiRDriver

10.21203/rs.3.rs-1101651/v1 ◽

2021 ◽

Author(s):

Banabithi Bose ◽

Matthew Moravec ◽

Serdar Bozdag

Keyword(s):

Copy Number ◽

Target Genes ◽

The Cancer Genome Atlas ◽

Gene Interactions ◽

Microrna Target ◽

Multiple Cancer ◽

Driver Genes ◽

Microrna Gene ◽

Cancer Types ◽

Pan Cancer

Abstract DNA copy number aberrated regions in cancer are known to harbor cancer driver genes and the short non-coding RNA molecules, i.e., microRNAs. In this study, we integrated the multi-omics datasets such as copy number aberration, DNA methylation, gene and microRNA expression to identify the signature microRNA-gene associations from frequently aberrated DNA regions across pan-cancer utilizing a LASSO-based regression approach. We studied 7,294 patient samples associated with eighteen different cancer types from The Cancer Genome Atlas (TCGA) database and identified several cancer-specific microRNA-gene interactions enriched in experimentally validated microRNA-target databases. We highlighted several oncogenic and tumor suppressor microRNAs and genes that were common in several cancer types. Our method substantially outperformed the five state-of-art methods in selecting significantly known microRNA-gene interactions in multiple cancer types. Several microRNAs and genes were found to be associated with tumor survival and progression. Selected target genes were found to be significantly enriched in cancer-related pathways, cancer Hallmark and Gene Ontology (GO) terms. Furthermore, subtype-specific potential gene signatures were discovered in multiple cancer types.

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Integrated Dissection of lncRNA-Perturbated Triplets Reveals Novel Prognostic Signatures Across Cancer Types

International Journal of Molecular Sciences ◽

10.3390/ijms21176087 ◽

2020 ◽

Vol 21 (17) ◽

pp. 6087

Author(s):

Yunzhen Wei ◽

Limeng Zhou ◽

Yingzhang Huang ◽

Dianjing Guo

Keyword(s):

Cancer Biology ◽

Noncoding Rna ◽

The Cancer Genome Atlas ◽

Dynamic Changes ◽

Computational Framework ◽

Potential Biomarker ◽

Cancer Genome Atlas ◽

Cancer Types ◽

Tcga Dataset ◽

Pan Cancer

Long noncoding RNA (lncRNA)/microRNA(miRNA)/mRNA triplets contribute to cancer biology. However, identifying significative triplets remains a major challenge for cancer research. The dynamic changes among factors of the triplets have been less understood. Here, by integrating target information and expression datasets, we proposed a novel computational framework to identify the triplets termed as “lncRNA-perturbated triplets”. We applied the framework to five cancer datasets in The Cancer Genome Atlas (TCGA) project and identified 109 triplets. We showed that the paired miRNAs and mRNAs were widely perturbated by lncRNAs in different cancer types. LncRNA perturbators and lncRNA-perturbated mRNAs showed significantly higher evolutionary conservation than other lncRNAs and mRNAs. Importantly, the lncRNA-perturbated triplets exhibited high cancer specificity. The pan-cancer perturbator OIP5-AS1 had higher expression level than that of the cancer-specific perturbators. These lncRNA perturbators were significantly enriched in known cancer-related pathways. Furthermore, among the 25 lncRNA in the 109 triplets, lncRNA SNHG7 was identified as a stable potential biomarker in lung adenocarcinoma (LUAD) by combining the TCGA dataset and two independent GEO datasets. Results from cell transfection also indicated that overexpression of lncRNA SNHG7 and TUG1 enhanced the expression of the corresponding mRNA PNMA2 and CDC7 in LUAD. Our study provides a systematic dissection of lncRNA-perturbated triplets and facilitates our understanding of the molecular roles of lncRNAs in cancers.

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Pan-Cancer Analysis of the Genomic Alterations and Mutations of the Matrisome

Cancers ◽

10.3390/cancers12082046 ◽

2020 ◽

Vol 12 (8) ◽

pp. 2046 ◽

Cited By ~ 2

Author(s):

Valerio Izzi ◽

Martin N. Davis ◽

Alexandra Naba

Keyword(s):

Cancer Progression ◽

Protein Function ◽

The Cancer Genome Atlas ◽

Copy Number Alterations ◽

Cellular Functions ◽

Genomic Alterations ◽

Genes Encoding ◽

Cancer Genome Atlas ◽

Biomechanical Changes ◽

Pan Cancer

The extracellular matrix (ECM) is a master regulator of all cellular functions and a major component of the tumor microenvironment. We previously defined the “matrisome” as the ensemble of genes encoding ECM proteins and proteins modulating ECM structure or function. While compositional and biomechanical changes in the ECM regulate cancer progression, no study has investigated the genomic alterations of matrisome genes in cancers and their consequences. Here, mining The Cancer Genome Atlas (TCGA) data, we found that copy number alterations and mutations are frequent in matrisome genes, even more so than in the rest of the genome. We also found that these alterations are predicted to significantly impact gene expression and protein function. Moreover, we identified matrisome genes whose mutational burden is an independent predictor of survival. We propose that studying genomic alterations of matrisome genes will further our understanding of the roles of this compartment in cancer progression and will lead to the development of innovative therapeutic strategies targeting the ECM.

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Integrative Analysis Reveals Comprehensive Altered Metabolic Genes Linking with Tumor Epigenetics Modification in Pan-Cancer

BioMed Research International ◽

10.1155/2019/6706354 ◽

2019 ◽

Vol 2019 ◽

pp. 1-17 ◽

Cited By ~ 1

Author(s):

Yahui Shi ◽

Jinfen Wei ◽

Zixi Chen ◽

Yuchen Yuan ◽

Xingsong Li ◽

...

Keyword(s):

Gene Expression ◽

Dna Methylation ◽

Histone Acetylation ◽

Epigenetic Modification ◽

Metabolic Reprogramming ◽

The Cancer Genome Atlas ◽

Altered Expression ◽

Metabolic Genes ◽

Cancer Types ◽

Pan Cancer

Background. Cancer cells undergo various rewiring of metabolism and dysfunction of epigenetic modification to support their biosynthetic needs. Although the major features of metabolic reprogramming have been elucidated, the global metabolic genes linking epigenetics were overlooked in pan-cancer. Objectives. Identifying the critical metabolic signatures with differential expressions which contributes to the epigenetic alternations across cancer types is an urgent issue for providing the potential targets for cancer therapy. Method. The differential gene expression and DNA methylation were analyzed by using the 5726 samples data from the Cancer Genome Atlas (TCGA). Results. Firstly, we analyzed the differential expression of metabolic genes and found that cancer underwent overall metabolism reprogramming, which exhibited a similar expression trend with the data from the Gene Expression Omnibus (GEO) database. Secondly, the regulatory network of histone acetylation and DNA methylation according to altered expression of metabolism genes was summarized in our results. Then, the survival analysis showed that high expression of DNMT3B had a poorer overall survival in 5 cancer types. Integrative altered methylation and expression revealed specific genes influenced by DNMT3B through DNA methylation across cancers. These genes do not overlap across various cancer types and are involved in different function annotations depending on the tissues, which indicated DNMT3B might influence DNA methylation in tissue specificity. Conclusions. Our research clarifies some key metabolic genes, ACLY, SLC2A1, KAT2A, and DNMT3B, which are most disordered and indirectly contribute to the dysfunction of histone acetylation and DNA methylation in cancer. We also found some potential genes in different cancer types influenced by DNMT3B. Our study highlights possible epigenetic disorders resulting from the deregulation of metabolic genes in pan-cancer and provides potential therapy in the clinical treatment of human cancer.

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Higher prevalence of homologous recombination-deficiency in lung squamous carcinoma from African Americans

10.1101/651794 ◽

2019 ◽

Author(s):

Sanju Sinha ◽

Khadijah A. Mitchell ◽

Adriana Zingone ◽

Elise Bowman ◽

Neelam Sinha ◽

...

Keyword(s):

Homologous Recombination ◽

Copy Number ◽

Squamous Carcinoma ◽

The Cancer Genome Atlas ◽

Multiple Cancer ◽

Homologous Recombination Deficiency ◽

Molecular Features ◽

Incidence And Mortality ◽

Cancer Types ◽

Lung Squamous Carcinoma

AbstractTo improve our understanding of the longstanding disparities in incidence and mortality across multiple cancer types among minority populations, we performed a systematic comparative analysis of molecular features in tumors from African American (AA) and European American (EA) ancestry. Our pan-cancer analysis on the cancer genome atlas (TCGA) and a more focused analysis of genome-wide somatic copy number profiles integrated with tumor-normal RNA sequencing in a racially balanced cohort of 222 non-small cell lung cancers (NSCLC) reveals more aggressive genomic characteristics of AA tumors. In general, we find AA tumors exhibit higher genomic instability (GI), homologous recombination-deficiency (HRD) levels, and more aggressive molecular features such as chromothripsis across many cancer types, including lung squamous carcinoma (LUSC). GI and HRD levels are strongly correlated across AA tumors, indicating that HRD plays an important role in GI in these patients. The prevalence of germline HRD is higher in AA tumors, suggesting that the somatic differences observed have genetic ancestry origins. Finally, we identify AA-specific copy number-based arm, focal and gene level recurrent features in lung cancer, including a higher frequency of PTEN deletion and KRAS amplification and a lower frequency of CDKN2A deletion. These results highlight the importance of including minority and under-represented populations in genomics research and may have therapeutic implications.

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Pan-cancer analysis reveals complex tumor-specific alternative polyadenylation

10.1101/160960 ◽

2017 ◽

Author(s):

Zhuyi Xue ◽

René L Warren ◽

Ewan A Gibb ◽

Daniel MacMillan ◽

Johnathan Wong ◽

...

Keyword(s):

Alternative Polyadenylation ◽

Length Change ◽

The Cancer Genome Atlas ◽

Cancer Type ◽

Rna Seq ◽

Multiple Cancer ◽

Tissue Samples ◽

Cancer Genome Atlas ◽

Specific Alternative ◽

Cancer Types

AbstractAlternative polyadenylation (APA) of 3’ untranslated regions (3’ UTRs) has been implicated in cancer development. Earlier reports on APA in cancer primarily focused on 3’ UTR length modifications, and the conventional wisdom is that tumor cells preferentially express transcripts with shorter 3’ UTRs. Here, we analyzed the APA patterns of 114 genes, a select list of oncogenes and tumor suppressors, in 9,939 tumor and 729 normal tissue samples across 33 cancer types using RNA-Seq data from The Cancer Genome Atlas, and we found that the APA regulation machinery is much more complicated than what was previously thought. We report 77 cases (gene-cancer type pairs) of differential 3’ UTR cleavage patterns between normal and tumor tissues, involving 33 genes in 13 cancer types. For 15 genes, the tumor-specific cleavage patterns are recurrent across multiple cancer types. While the cleavage patterns in certain genes indicate apparent trends of 3’ UTR shortening in tumor samples, over half of the 77 cases imply 3’ UTR length change trends in cancer that are more complex than simple shortening or lengthening. This work extends the current understanding of APA regulation in cancer, and demonstrates how large volumes of RNA-seq data generated for characterizing cancer cohorts can be mined to investigate this process.

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Inferring Homologous Recombination Deficiency of Ovarian Cancer From the Landscape of Copy Number Variation at Subchromosomal and Genetic Resolutions

Frontiers in Oncology ◽

10.3389/fonc.2021.772604 ◽

2021 ◽

Vol 11 ◽

Author(s):

Meng Zhang ◽

Si-Cong Ma ◽

Jia-Le Tan ◽

Jian Wang ◽

Xue Bai ◽

...

Keyword(s):

Ovarian Cancer ◽

Homologous Recombination ◽

Copy Number Variation ◽

Copy Number ◽

The Cancer Genome Atlas ◽

Homologous Recombination Deficiency ◽

Number Variation ◽

Cancer Genome Atlas ◽

Tumor Types ◽

Pan Cancer

BackgroundHomologous recombination deficiency (HRD) is characterized by overall genomic instability and has emerged as an indispensable therapeutic target across various tumor types, particularly in ovarian cancer (OV). Unfortunately, current detection assays are far from perfect for identifying every HRD patient. The purpose of this study was to infer HRD from the landscape of copy number variation (CNV).MethodsGenome-wide CNV landscape was measured in OV patients from the Australian Ovarian Cancer Study (AOCS) clinical cohort and >10,000 patients across 33 tumor types from The Cancer Genome Atlas (TCGA). HRD-predictive CNVs at subchromosomal resolution were identified through exploratory analysis depicting the CNV landscape of HRD versus non-HRD OV patients and independently validated using TCGA and AOCS cohorts. Gene-level CNVs were further analyzed to explore their potential predictive significance for HRD across tumor types at genetic resolution.ResultsAt subchromosomal resolution, 8q24.2 amplification and 5q13.2 deletion were predominantly witnessed in HRD patients (both p < 0.0001), whereas 19q12 amplification occurred mainly in non-HRD patients (p < 0.0001), compared with their corresponding counterparts within TCGA-OV. The predictive significance of 8q24.2 amplification (p < 0.0001), 5q13.2 deletion (p = 0.0056), and 19q12 amplification (p = 0.0034) was externally validated within AOCS. Remarkably, pan-cancer analysis confirmed a cross-tumor predictive role of 8q24.2 amplification for HRD (p < 0.0001). Further analysis of CNV in 8q24.2 at genetic resolution revealed that amplifications of the oncogenes, MYC (p = 0.0001) and NDRG1 (p = 0.0004), located on this fragment were also associated with HRD in a pan-cancer manner.ConclusionsThe CNV landscape serves as a generalized predictor of HRD in cancer patients not limited to OV. The detection of CNV at subchromosomal or genetic resolution could aid in the personalized treatment of HRD patients.

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A pan-cancer atlas of transcriptional dependence on DNA methylation and copy number aberrations

10.1101/2020.05.04.076901 ◽

2020 ◽

Author(s):

Christian Fougner ◽

Elen K. Höglander ◽

Tonje G. Lien ◽

Therese Sørlie ◽

Silje Nord ◽

...

Keyword(s):

Gene Expression ◽

Dna Methylation ◽

Copy Number ◽

Normal Cell ◽

Tumor Heterogeneity ◽

Copy Number Alterations ◽

Cell Of Origin ◽

Online Tool ◽

Copy Number Aberrations ◽

Pan Cancer

AbstractCancer transcriptomes are shaped by genetic and epigenetic features, such as DNA methylation and copy number aberrations. Knowledge of the relationships between gene expression and such features is fundamental to understanding the basis of tumor phenotypes. Here, we present a pan-cancer atlas of transcriptional dependence on DNA methylation and copy number aberrations (PANORAMA). Our analyses suggest that copy number alterations are a central driver of inter-tumor heterogeneity, while the majority of expression-methylation associations found in cancer are a reflection of cell-of-origin and normal cell admixture. The atlas is made available through an online tool at https://pancancer.app.

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