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

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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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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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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Multi-omics characterization and validation of invasiveness-related molecular features across multiple cancer types

Journal of Translational Medicine ◽

10.1186/s12967-021-02773-x ◽

2021 ◽

Vol 19 (1) ◽

Author(s):

Guoshu Bi ◽

Jiaqi Liang ◽

Yuansheng Zheng ◽

Runmei Li ◽

Mengnan Zhao ◽

...

Keyword(s):

Gene Expression ◽

Predictive Biomarker ◽

Gene Expression Omnibus ◽

The Cancer Genome Atlas ◽

Functional Enrichment ◽

Integrated Analysis ◽

Multiple Cancer ◽

Tumor Invasiveness ◽

Molecular Features ◽

Cancer Types

Abstract Background Tumor invasiveness reflects many biological changes associated with tumorigenesis, progression, metastasis, and drug resistance. Therefore, we performed a systematic assessment of invasiveness-related molecular features across multiple human cancers. Materials and methods Multi-omics data, including gene expression, miRNA, DNA methylation, and somatic mutation, in approximately 10,000 patients across 30 cancer types from The Cancer Genome Atlas, Gene Expression Omnibus, PRECOG, and our institution were enrolled in this study. Results Based on a robust gene signature, we established an invasiveness score and found that the score was significantly associated with worse prognosis in almost all cancers. Then, we identified common invasiveness-associated dysregulated molecular features between high- and low-invasiveness score group across multiple cancers, as well as investigated their mutual interfering relationships thus determining whether the dysregulation of invasiveness-related genes was caused by abnormal promoter methylation or miRNA expression. We also analyzed the correlations between the drug sensitivity data from cancer cell lines and the expression level of 685 invasiveness-related genes differentially expressed in at least ten cancer types. An integrated analysis of the correlations among invasiveness-related genetic features and drug response were conducted in esophageal carcinoma patients to outline the complicated regulatory mechanism of tumor invasiveness status in multiple dimensions. Moreover, functional enrichment suggests the invasiveness score might serve as a predictive biomarker for cancer patients receiving immunotherapy. Conclusion Our pan-cancer study provides a comprehensive atlas of tumor invasiveness and may guide more precise therapeutic strategies for tumor patients.

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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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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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Genomic Determinants of Homologous Recombination Deficiency across Human Cancers

Cancers ◽

10.3390/cancers13184572 ◽

2021 ◽

Vol 13 (18) ◽

pp. 4572

Author(s):

Tao Qing ◽

Xinfeng Wang ◽

Tomi Jun ◽

Li Ding ◽

Lajos Pusztai ◽

...

Keyword(s):

Homologous Recombination ◽

Copy Number ◽

Somatic Mutations ◽

Synthetic Lethality ◽

Driver Mutations ◽

Multiple Cancer ◽

Clinical Biomarkers ◽

Somatic Alterations ◽

Cancer Types ◽

Prostate Cancers

Germline BRCA1/2 mutations associated with HRD are clinical biomarkers for sensitivity to poly-ADP ribose polymerase inhibitors (PARPi) treatment in breast, ovarian, pancreatic, and prostate cancers. However, it remains unclear whether other mutations may also lead to HRD and PARPi sensitivity across a broader range of cancer types. Our goal was to determine the germline or somatic alterations associated with the HRD phenotype that might therefore confer PARPi sensitivity. Using germline and somatic genomic data from over 9000 tumors representing 32 cancer types, we examined associations between HRD scores and pathogenic germline variants, somatic driver mutations, and copy number deletions in 30 candidate genes involved in homologous recombination. We identified several germline and somatic mutations (e.g., BRCA1/2, PALB2, ATM, and ATR mutations) associated with HRD phenotype in ovarian, breast, pancreatic, stomach, bladder, and lung cancer. The co-occurrence of germline BRCA1 variants and somatic TP53 mutations was significantly associated with increasing HRD in breast cancer. Notably, we also identified multiple somatic copy number deletions associated with HRD. Our study suggests that multiple cancer types include tumor subsets that show HRD phenotype and should be considered in the future clinical studies of PARPi and synthetic lethality strategies exploiting HRD, which can be caused by a large number of genomic alterations.

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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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RNA Exosome Component EXOSC4 Amplified in Multiple Cancer Types Is Required for the Cancer Cell Survival

International Journal of Molecular Sciences ◽

10.3390/ijms23010496 ◽

2022 ◽

Vol 23 (1) ◽

pp. 496

Author(s):

Kenzui Taniue ◽

Tanzina Tanu ◽

Yuki Shimoura ◽

Shuhei Mitsutomi ◽

Han Han ◽

...

Keyword(s):

Pancreatic Cancer ◽

Cell Viability ◽

The Cancer Genome Atlas ◽

Multiple Cancer ◽

Pancreatic Cancer Cells ◽

Cancer Cell Survival ◽

Cellular Machinery ◽

Cancer Types ◽

Rna Exosome ◽

Tumor Types

The RNA exosome is a multi-subunit ribonuclease complex that is evolutionally conserved and the major cellular machinery for the surveillance, processing, degradation, and turnover of diverse RNAs essential for cell viability. Here we performed integrated genomic and clinicopathological analyses of 27 RNA exosome components across 32 tumor types using The Cancer Genome Atlas PanCancer Atlas Studies’ datasets. We discovered that the EXOSC4 gene, which encodes a barrel component of the RNA exosome, was amplified across multiple cancer types. We further found that EXOSC4 alteration is associated with a poor prognosis of pancreatic cancer patients. Moreover, we demonstrated that EXOSC4 is required for the survival of pancreatic cancer cells. EXOSC4 also repressed BIK expression and destabilized SESN2 mRNA by promoting its degradation. Furthermore, knockdown of BIK and SESN2 could partially rescue pancreatic cells from the reduction in cell viability caused by EXOSC4 knockdown. Our study provides evidence for EXOSC4-mediated regulation of BIK and SESN2 mRNA in the survival of pancreatic tumor cells.

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Landscape of Microsatellite Instability Across 39 Cancer Types

JCO Precision Oncology ◽

10.1200/po.17.00073 ◽

2017 ◽

pp. 1-15 ◽

Cited By ~ 93

Author(s):

Russell Bonneville ◽

Melanie A. Krook ◽

Esko A. Kautto ◽

Jharna Miya ◽

Michele R. Wing ◽

...

Keyword(s):

Microsatellite Instability ◽

Mismatch Repair ◽

Human Cancer ◽

The Cancer Genome Atlas ◽

Repair System ◽

Multiple Cancer ◽

External Data ◽

Mismatch Repair System ◽

Cancer Types ◽

Genomic Microsatellites

Purpose Microsatellite instability (MSI) is a pattern of hypermutation that occurs at genomic microsatellites and is caused by defects in the mismatch repair system. Mismatch repair deficiency that leads to MSI has been well described in several types of human cancer, most frequently in colorectal, endometrial, and gastric adenocarcinomas. MSI is known to be both predictive and prognostic, especially in colorectal cancer; however, current clinical guidelines only recommend MSI testing for colorectal and endometrial cancers. Therefore, less is known about the prevalence and extent of MSI among other types of cancer. Methods Using our recently published MSI-calling software, MANTIS, we analyzed whole-exome data from 11,139 tumor-normal pairs from The Cancer Genome Atlas and Therapeutically Applicable Research to Generate Effective Treatments projects and external data sources across 39 cancer types. Within a subset of these cancer types, we assessed mutation burden, mutational signatures, and somatic variants associated with MSI. Results We identified MSI in 3.8% of all cancers assessed—present in 27 of tumor types—most notably adrenocortical carcinoma (ACC), cervical cancer (CESC), and mesothelioma, in which MSI has not yet been well described. In addition, MSI-high ACC and CESC tumors were observed to have a higher average mutational burden than microsatellite-stable ACC and CESC tumors. Conclusion We provide evidence of as-yet-unappreciated MSI in several types of cancer. These findings support an expanded role for clinical MSI testing across multiple cancer types as patients with MSI-positive tumors are predicted to benefit from novel immunotherapies in clinical trials.

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