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

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

Scientific Reports ◽

10.1038/s41598-020-74276-6 ◽

2020 ◽

Vol 10 (1) ◽

Author(s):

Gaojianyong Wang ◽

Dimitris Anastassiou

Keyword(s):

Gene Expression ◽

Copy Number ◽

The Cancer Genome Atlas ◽

Copy Number Alterations ◽

Multiple Cancer ◽

Cancer Driver ◽

Large Gene ◽

Cancer Genome Atlas ◽

Cancer Types ◽

Pan Cancer

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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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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Identifying cancer type specific oncogenes and tumor suppressors using limited size data

Journal of Bioinformatics and Computational Biology ◽

10.1142/s0219720016500311 ◽

2016 ◽

Vol 14 (06) ◽

pp. 1650031 ◽

Cited By ~ 4

Author(s):

Ana B. Pavel ◽

Cristian I. Vasile

Keyword(s):

Tumor Suppressors ◽

Molecular Mechanisms ◽

Lung Squamous Cell Carcinoma ◽

The Cancer Genome Atlas ◽

Driver Mutations ◽

Cancer Type ◽

Multiple Cancer ◽

Driver Genes ◽

Cancer Subtypes ◽

Cancer Types

Cancer is a complex and heterogeneous genetic disease. Different mutations and dysregulated molecular mechanisms alter the pathways that lead to cell proliferation. In this paper, we explore a method which classifies genes into oncogenes (ONGs) and tumor suppressors. We optimize this method to identify specific (ONGs) and tumor suppressors for breast cancer, lung adenocarcinoma (LUAD), lung squamous cell carcinoma (LUSC) and colon adenocarcinoma (COAD), using data from the cancer genome atlas (TCGA). A set of genes were previously classified as ONGs and tumor suppressors across multiple cancer types (Science 2013). Each gene was assigned an ONG score and a tumor suppressor score based on the frequency of its driver mutations across all variants from the catalogue of somatic mutations in cancer (COSMIC). We evaluate and optimize this approach within different cancer types from TCGA. We are able to determine known driver genes for each of the four cancer types. After establishing the baseline parameters for each cancer type, we identify new driver genes for each cancer type, and the molecular pathways that are highly affected by them. Our methodology is general and can be applied to different cancer subtypes to identify specific driver genes and improve personalized therapy.

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Reconstructing and characterizing focal amplifications in cancer using AmpliconArchitect

10.1101/457333 ◽

2018 ◽

Cited By ~ 1

Author(s):

Viraj Deshpande ◽

Jens Luebeck ◽

Mehrdad Bakhtiari ◽

Nam-Phuong D Nguyen ◽

Kristen M Turner ◽

...

Keyword(s):

Cervical Cancer ◽

Fine Structure ◽

Tumor Growth ◽

Genome Sequencing ◽

Copy Number ◽

Whole Genome ◽

Multiple Cancer ◽

Cancer Data ◽

Cancer Types ◽

Pan Cancer

AbstractFocal oncogene amplification and rearrangements drive tumor growth and evolution in multiple cancer types. We developed a tool, AmpliconArchitect (AA), which can robustly reconstruct the fine structure of focally amplified regions using whole genome sequencing. AA-reconstructed amplicons in pan-cancer data and in virus-driven cervical cancer samples revealed many novel insights about focal amplifications. Specifically, the findings lend support to extrachromosomally mediated mechanisms for copy number expansion, and oncoviral pathogenesis.

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Integrated Genomic Analysis of Hypoxia Genes across Cancer Types Identifies Significant Associations with Cancer Hallmarks

10.1101/403717 ◽

2018 ◽

Author(s):

Lingjian Yang ◽

Laura Forker ◽

Christina S. Fjeldbo ◽

Robert G. Bristow ◽

Heidi Lyng ◽

...

Keyword(s):

Environmental Factor ◽

Epithelial Mesenchymal Transition ◽

Tumour Progression ◽

The Cancer Genome Atlas ◽

Silent Mutation ◽

Multiple Cancer ◽

Mesenchymal Transition ◽

Cancer Types ◽

Pan Cancer

ABSTRACTHypoxia is a generic micro-environmental factor in most solid tumours. While most published literature focused on in vitro or single tumour type investigations, we carried out the first multi-omics pan cancer analysis of hypoxia with the aim of gaining a comprehensive understanding of its implication in tumour biology. A core set of 52 mRNAs were curated based on experimentally validated hypoxia gene sets from multiple cancer types. The 52 mRNAs collectively stratified high- and low-hypoxia tumours from The Cancer Genome Atlas (TCGA) database (9698 primary tumours) in each of the 32 cancer types available. High- hypoxia tumours had high expression of not only mRNA but also protein and microRNA markers of hypoxia. In a pan cancer transcriptomic analysis, ≥70% of the known cancer hallmark pathways were enriched in high-hypoxia tumours, most notably epithelial mesenchymal transition potential, proliferation (G2M checkpoint, E2F targets, MYC targets) and immunology response. In a multi-omics analysis, gene expression-determined high- hypoxia tumours had a higher non-silent mutation rate, DNA damage repair deficiency and leukocyte infiltration. The associations largely remained significant after correcting for confounding factors, showing a profound impact of hypoxia in tumour evolution across cancer types. High-hypoxia tumours determined using the core gene set had a poor prognosis in 16/32 cancer types, with statistical significances remaining in five after adjusting for tumour stage and omics biomarkers. In summary, this first comprehensive in vivo map of hypoxia in cancers highlights the importance of this micro-environmental factor in driving tumour progression.

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Separated Siamese Twins: Intronic Small Nucleolar RNAs and Matched Host Genes May be Altered in Conjunction or Separately in Multiple Cancer Types

Cells ◽

10.3390/cells9020387 ◽

2020 ◽

Vol 9 (2) ◽

pp. 387 ◽

Cited By ~ 1

Author(s):

Marianna Penzo ◽

Rosanna Clima ◽

Davide Trerè ◽

Lorenzo Montanaro

Keyword(s):

Copy Number ◽

Host Gene ◽

The Cancer Genome Atlas ◽

Cancer Development ◽

Rna Modification ◽

Small Nucleolar Rnas ◽

Multiple Cancer ◽

Cancer Types ◽

Nucleolar Rnas ◽

Host Genes

Small nucleolar RNAs (snoRNAs) are non-coding RNAs involved in RNA modification and processing. Approximately half of the so far identified snoRNA genes map within the intronic regions of host genes, and their expression, as well as the expression of their host genes, is dependent on transcript splicing and maturation. Growing evidence indicates that mutations and/or deregulations that affect snoRNAs, as well as host genes, play a significant role in oncogenesis. Among the possible factors underlying snoRNA/host gene expression deregulation is copy number alteration (CNA). We analyzed the data available in The Cancer Genome Atlas database, relative to CNA and expression of 295 snoRNA/host gene couples in 10 cancer types, to understand whether the genetic or expression alteration of snoRNAs and their matched host genes would have overlapping trends. Our results show that, counterintuitively, copy number and expression alterations of snoRNAs and matched host genes are not necessarily coupled. In addition, some snoRNA/host genes are mutated and overexpressed recurrently in multiple cancer types. Our findings suggest that the differential contribution to cancer development of both snoRNAs and host genes should always be considered, and that snoRNAs and their host genes may contribute to cancer development in conjunction or independently.

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Genomic profiling of microRNA target genes in colorectal cancer

Tumor Biology ◽

10.1177/1010428320933512 ◽

2020 ◽

Vol 42 (6) ◽

pp. 101042832093351

Author(s):

Adewale Oluwaseun Fadaka ◽

Olalekan Olanrewaju Bakare ◽

Ashley Pretorius ◽

Ashwil Klein

Keyword(s):

Colorectal Cancer ◽

Protein Interaction ◽

Tyrosine Kinases ◽

Target Genes ◽

Genetic Mutation ◽

Tumor Formation ◽

The Cancer Genome Atlas ◽

Microrna Target ◽

Driver Genes ◽

Protein Protein Interaction

Colorectal cancer is the second and third most common cancer in men and women, respectively, worldwide. Alterations such as genetic and epigenetic are common in colorectal cancer and are the basis of tumor formation. The exploration of the molecular basis of colorectal cancer can drive a better understanding of the disease as well as guide the prognosis, therapeutics, and disease management. This study is aimed at investigating the genetic mutation profile of five candidate microRNAs (hsa-miR-513b-3p, hsa-miR-500b-3p, hsa-miR-500a-3p, hsa-miR-450b-3p, hsa-miR-193a-5p) targeted by seven genes (APC, KRAS, TCF7L2, EGFR, IGF1R, CASP8, and GNAS)) using in silico approaches. Two datasets (dataset 1 from our previous study and dataset two (The Cancer Genome Atlas, Nature 2012) were considered for this study. Protein–protein interaction, expression analysis, and genetic profiling were carried out using STRING, FireBrowse, and cBioPortal, respectively. Protein–protein interaction network showed that epidermal growth factor receptor has the highest connection among the target genes and this can be considered as the hub gene. Relative to other solid tumors, in colorectal cancer, six of the target genes were downregulated and only CASP8 was upregulated. Genes with protein tyrosine kinases domain were frequently altered in colorectal cancer and the most common alteration in these genes/domain are missense mutation. These results could serve as a lead in the identification of driver genes responsible for colorectal cancer initiation and progression. However, the intense mechanism of these results remains unclear and further experimental validation and molecular approaches are the focal points in the nearest future.

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MEXCOWalk: Mutual Exclusion and Coverage Based Random Walk to Identify Cancer Modules

10.1101/547653 ◽

2019 ◽

Author(s):

Rafsan Ahmed ◽

Ilyes Baali ◽

Cesim Erten ◽

Evis Hoxha ◽

Hilal Kazan

Keyword(s):

Random Walk ◽

Mutual Exclusion ◽

Risk Scores ◽

Cancer Genes ◽

Multiple Cancer ◽

Driver Genes ◽

Cancer Driver ◽

Cancer Data ◽

Cancer Types ◽

Pan Cancer

AbstractMotivationGenomic analyses from large cancer cohorts have revealed the mutational heterogeneity problem which hinders the identification of driver genes based only on mutation profiles. One way to tackle this problem is to incorporate the fact that genes act together in functional modules. The connectivity knowledge present in existing protein-protein interaction networks together with mutation frequencies of genes and the mutual exclusivity of cancer mutations can be utilized to increase the accuracy of identifying cancer driver modules.ResultsWe present a novel edge-weighted random walk-based approach that incorporates connectivity information in the form of protein-protein interactions, mutual exclusion, and coverage to identify cancer driver modules. MEXCOWalk outperforms several state-of-the-art computational methods on TCGA pan-cancer data in terms of recovering known cancer genes, providing modules that are capable of classifying normal and tumor samples, and that are enriched for mutations in specific cancer types. Furthermore, the risk scores determined with output modules can stratify patients into low-risk and high-risk groups in multiple cancer types. MEXCOwalk identifies modules containing both well-known cancer genes and putative cancer genes that are rarely mutated in the pan-cancer data. The data, the source code, and useful scripts are available at:https://github.com/abu-compbio/[email protected]

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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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Prognostic and Immunological Characterization of NSD3 Evaluated through an Integrative Pan-Cancer Analysis

10.21203/rs.3.rs-591803/v1 ◽

2021 ◽

Author(s):

Sha Li ◽

Yaqiong Liu ◽

Chaoling Yao ◽

Anji Xu ◽

Xiaoling Zeng ◽

...

Keyword(s):

Immune Cell ◽

Human Cancer ◽

The Cancer Genome Atlas ◽

Functional Enrichment ◽

Cell Infiltration ◽

Immune Cell Infiltration ◽

Multiple Cancer ◽

Cancer Dataset ◽

Cancer Types ◽

Pan Cancer

Abstract Background: Nuclear receptor binding SET domain protein-3 (NSD3) has been reported to be a crucial regulator of carcinogenesis as a histone lysine methyltransferase in multiple cancer types. However, the underlying mechanisms have not been clearly delineated. Therefore, we aimed to investigate the expression pattern, prognostic value, and potential function of NSD3 in 33 types of human cancer. Methods: The potential roles of NSD3 were explored using datasets from The Cancer Genome Atlas (TCGA) pan-cancer dataset and an array of bioinformatics methods, including analyses of the relationship between NSD3 expression and prognosis, tumor mutational burden (TMB), microsatellite instability (MSI), DNA amplification, and immune cell inﬁltration across 33 cancer types. Results: Many types of cancers are characterized according to the dysregulation of NSD3, which is associated with the pathological stage of cancer. Patients in our study with higher NDS3 levels, which were attributed to NSD3 copy number amplification, always experienced shorter survival periods. Additionally, NSD3 expression was associated with TMB and MSI in 10 different cancer types. The top five cancers whose NSD3 expression correlated with immune scores were further analyzed. The levels of immune-cell infiltration differed significantly between high and low NSD3-expressing samples in each of the five cancer types. Functional enrichment of the NSD3 co-expressed genes indicated a role for NSD3 in the regulation of immune responses and tumorigenesis. Conclusions: Our study revealed that NSD3 can function as a prognostic marker in various cancers due to its role in tumorigenesis and tumor immunity.

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