scholarly journals Pan cancer patterns of allelic imbalance from chromosomal alterations in 33 tumor types

Genetics ◽  
2021 ◽  
Vol 217 (1) ◽  
Author(s):  
Smruthy Sivakumar ◽  
F Anthony San Lucas ◽  
Yasminka A Jakubek ◽  
Zuhal Ozcan ◽  
Jerry Fowler ◽  
...  
Keyword(s):  
Copy Number ◽  
Recurrent Events ◽  
Allelic Imbalance ◽  
Neutral Loss ◽  
Allele Frequencies ◽  
The Cancer Genome Atlas ◽  
Chromosomal Alterations ◽  
R Ratio ◽  
Binary Segmentation ◽  
Pan Cancer

Abstract Somatic copy number alterations (SCNAs) serve as hallmarks of tumorigenesis and often result in deviations from one-to-one allelic ratios at heterozygous loci, leading to allelic imbalance (AI). The Cancer Genome Atlas (TCGA) reports SCNAs identified using a circular binary segmentation algorithm, providing segment mean copy number estimates from single-nucleotide polymorphism DNA microarray total intensities (log R ratio), but not allele-specific intensities (“B allele” frequencies) that inform of AI. Our approach provides more sensitive identification of SCNAs by modeling the “B allele” frequencies jointly, thereby bolstering the catalog of chromosomal alterations in this widely utilized resource. Here we present AI summaries for all 33 tumor sites in TCGA, including those induced by SCNAs and copy-neutral loss-of-heterozygosity (cnLOH). We identified AI in 94% of the tumors, higher than in previous reports. Recurrent events included deletions of 17p, 9q, 3p, amplifications of 8q, 1q, 7p, as well as mixed event types on 8p and 13q. We also observed both site-specific and pan-cancer (spanning 17p) cnLOH, patterns which have not been comprehensively characterized. The identification of such cnLOH events elucidates tumor suppressors and multi-hit pathways to carcinogenesis. We also contrast the landscapes inferred from AI- and total intensity-derived SCNAs and propose an automated procedure to improve and adjust SCNAs in TCGA for cases where high levels of aneuploidy obscured baseline intensity identification. Our findings support the exploration of additional methods for robust automated inference procedures and to aid empirical discoveries across TCGA.

scholarly journals Pan cancer patterns of allelic imbalance from chromosomal aberrations in 33 tumor types

2019 ◽  
Author(s):  
Smruthy Sivakumar ◽  
F Anthony San Lucas ◽  
Yasminka A Jakubek ◽  
Jerry Fowler ◽  
Paul Scheet
Keyword(s):  
Copy Number ◽  
Recurrent Events ◽  
Allelic Imbalance ◽  
Neutral Loss ◽  
The Cancer Genome Atlas ◽  
Multiple Tumor ◽  
Adjustment Procedure ◽  
R Ratio ◽  
Binary Segmentation ◽  
Allele Specific

ABSTRACTSomatic copy number alterations (SCNAs), including deletions and duplications, serve as hallmarks of tumorigenesis. SCNAs may span entire chromosomes and typically result in deviations from an expected one-to-one ratio of alleles at heterozygous loci, leading to allelic imbalance (AI). The Cancer Genome Atlas (TCGA) reports SCNAs identified using a circular binary segmentation (CBS) algorithm, providing segment mean copy number estimates from Affymetrix single-nucleotide polymorphism DNA microarray total (log R ratio) intensities, but not allele-specific (“B allele”) intensities that inform of AI. Here we seek to provide a TCGA-wide description of AI in tumor genomes, including AI induced by SCNAs and copy-neutral loss-of-heterozygosity (cnLOH), using a powerful haplotype-based method applied to allele-specific intensities. We present AI summaries for all 33 tumor sites and propose an automated adjustment procedure to improve calibration of existing SCNA calls in TCGA for tumors with high levels of aneuploidy where baseline intensities were difficult to establish without annotation of AI. Overall, 94% of tumor samples exhibited AI. Recurrent events included deletions of 17p, 9q, 3p, amplifications of 8q, 1q, 7p as well as mixed event types on 8p and 13q. The AI-based approach identified frequent cnLOH on 17p across multiple tumor sites, with additional site-specific cnLOH patterns. Our findings support the exploration of additional methods for robust automated inference procedures and to aid empirical discoveries across TCGA.

scholarly journals CLONAL HEMATOPOIESIS IN A CENTENARIAN COHORT

2019 ◽  
Vol 3 (Supplement_1) ◽  
pp. S105-S106
Author(s):  
Aparna Bhutkar ◽  
Anastasia Gurinovich ◽  
Thomas T Perls ◽  
Paola Sebastiani ◽  
Stefano Monti
Keyword(s):  
New England ◽  
Loss Of Heterozygosity ◽  
Copy Number ◽  
Neutral Loss ◽  
Single Individual ◽  
Copy Number State ◽  
Chromosomal Alterations ◽  
R Ratio ◽  
Chromosomal Alteration ◽  
Extreme Longevity

Abstract Mosaicism, the presence of two or more genotypically or karyotypically distinct populations of cells in a single individual, plays an important role in human disease. Mosaicism can result in mutations and/or chromosomal alterations such as loss, gain, or copy-number neutral loss of heterozygosity. Clonal mosaicism and its relationship to aging and cancer, has been previously studied, and earlier work suggests that clonal mosaicism tends to increase with age. The aim of our research is to use genotype data of centenarians to explore the relationship between extreme longevity and mosaic chromosomal alterations (mCAs). To this end, we analyzed genome-wide genotypes from blood-derived DNA of 338 individuals from the New England Centenarian Study. The participants in this dataset ranged from 45 to 112 years of age. For the detection of mCA events, we used MoChA (https://github.com/freeseek/mocha), a bcftools extension, that predicts mCAs based on B-allele frequency (BAF) and log2 intensity(R) ratio (LRR), and uses long-range phase information to increase sensitivity. Chromosomal alteration events, including whole chromosome events, were detected in 180 out of the 338 individuals. A total of 165 duplications, 97 deletions, and 9 copy-number neutral loss of heterozygosity were detected. Additionally, there were 42 events whose copy number state could not be determined with high confidence. 236 events out of the 313 were detected in individuals aged 100 and older. Our analysis of chromosomal alteration frequency by age indicates that, within centenarians, the proportion of individuals with mCAs significantly decreases with increased age (p < 0.05, correlation -0.73).

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

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.

scholarly journals Hematopoietic mosaic chromosomal alterations in the New England Centenarian Study

2021 ◽  
Vol 5 (Supplement_1) ◽  
pp. 679-680
Author(s):  
Anastasia Leshchyk ◽  
Giulio Genovese ◽  
Stefano Monti ◽  
Thomas Perls ◽  
Paola Sebastiani
Keyword(s):  
New England ◽  
Neutral Loss ◽  
Large Population ◽  
Population Based ◽  
Steady Increase ◽  
Base Pairs ◽  
Chromosomal Alterations ◽  
Dna Microarray Data ◽  
R Ratio ◽  
Genome Wide

Abstract Mosaic chromosomal alterations (mCAs) are structural alterations that include deletions, duplications, or copy-neutral loss of heterozygosity. mCAs are reported to be associated with survival, age, cancer, and cardiovascular disease. Previous studies of mCAs in large population-based cohorts (UK Biobank, MGBB, BioBank Japan, and FinnGen) have demonstrated a steady increase of mCAs as people age. The distribution of mCAs in centenarians and their offspring is not well characterized. We applied MOsaic CHromosomal Alteration (MoChA) caller on 2298 genome-wide genotype samples of 1582 centenarians, 443 centenarians’ offspring, and 273 unrelated controls from the New England Centenarian Study (NECS). Integrating Log R ratio and B-allele frequency (BAF) intensities with genotype phase information, MoChA employs a Hidden Markov Model to detect mCA-induced deviations in allelic balance at heterozygous sites consistent with genotype phase in the DNA microarray data. We analyzed mCAs spanning over 100 k base pairs, with an estimated cell fraction less than 50%, within samples with genome-wide BAF phase concordance across phased heterozygous sites less than 0.51, and with LOD score of more than 10 for the model based on BAF and genotype phase. Our analysis showed that somatic mCAs increase with older age up to approximately 102 years, but the prevalence of the subjects with mCAs tend to decrease after that age, thus suggesting that accumulation of mCAs is less prevalent in long-lived individuals. We also used Poisson regression to show that centenarians and their offspring tend to accumulate less mCA (RR = 0.63, p=0.045) compared to the controls.

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

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.

Correlation between JAK1/2 expression and immune-related genes and JAK2 gene variants: A pan-cancer analysis.

2020 ◽  
Vol 38 (15_suppl) ◽  
pp. e15057-e15057
Author(s):  
Lichao Xu ◽  
Ding Zhang ◽  
Guoqiang Wang ◽  
Chao Chen ◽  
Ying Wang ◽  
...  
Keyword(s):  
Mrna Expression ◽  
Copy Number ◽  
Checkpoint Inhibitors ◽  
The Cancer Genome Atlas ◽  
Gene Variants ◽  
Missense Mutations ◽  
Sequencing Data ◽  
Primary Resistance ◽  
Immune Related Genes ◽  
Pan Cancer

e15057 Background: Loss of function mutations for Janus kinases 1/2 (JAK1/2) have shown to be the underling mechanism of primary resistance to immune checkpoint inhibitors (ICIs). However, the correlation between JAK1/2 expression and immune-related genes have not been studied. Methods: Survival, mRNA expression and whole-exome sequencing data from 32 pan-cancer atlas studies were obtained from The Cancer Genome Atlas (TCGA). Correlations between JAK1/2 expression and immune-related genes were depicted in heatmaps. We also analyzed the association between JAK2 gene variants and JAK2 expression. Results: In total, 10071 samples with mRNA expression data were included for analysis. Expression of 46 immune-related genes were positively correlated with JAK2 expression in 25 tumors instead of JAK1 expression. Patients with higher expression of JAK2 had better prognosis than patients with lower expression of JAK2 in 13 tumors. Among 10071 patients, 363 (3.60%) patients harbored JAK2 variants, including 8 with frame shift mutations, 44 with nonsense mutations, 142 with missense mutations, 11 with splices, 8 with fusions, 90 with copy-number reduction and 116 with copy-number amplification. There was no difference in JAK2 expression between patients with JAK2 variants and those without JAK2 variants. However, JAK2 fusion (2.20%, 8/363) and amplification (31.96%, 116/363) were associated with higher JAK2 expression. Conclusions: Our pan-cancer analysis found that JAK2 expression was correlated with immune-related genes and the prognosis of cancer patients. JAK2 fusion and amplification increased the expression of JAK2. Altogether, patients with high JAK2 expression may benefit from ICIs.

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

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.

scholarly journals Comprehensive Analysis of DNA Methylation Regulator DNA Methyltransferase (DNMT) Family and Ten-Eleven-Translocation (TET) Enzymes Family in Pan-Cancer

2021 ◽  
Author(s):  
Cheng Ouyang ◽  
Hao Li ◽  
Liping Sun
Keyword(s):  
Dna Methylation ◽  
Copy Number ◽  
Dna Methyltransferase ◽  
Copy Number Variations ◽  
Cholesterol Homeostasis ◽  
The Cancer Genome Atlas ◽  
Cancer Types ◽  
Tet Genes ◽  
Pan Cancer ◽  
Dnmt Family

Abstract Background: DNA methyltransferase (DNMT) family and ten-eleven-translocation (TET) family enzymes play pivotal roles in regulating DNA methylation, and are closely related to diverse cancers. This study was designed to clarify the specific roles of DNMT and TET genes in pan-cancers.Methods: The expression, mutation, copy number variations (CNVs), cancer-related pathways, immune cell infiltration correlation, and prognostic potential of DNMT/TET genes were systematically investigated in 33 cancer types using next-generation sequence data from the Cancer Genome Atlas database. Results: DNMT3B was more highly expressed in the majority of tumors analyzed than in normal tissues. Most DNMT/TET genes were frequently mutated in uterine carcinosarcoma, and TET1 and TET2 showed higher mutation frequencies in various cancer types. DNMT3B exhibited inclusive copy number amplification in almost all cancers, such as stomach adenocarcinoma(STAD) and colon adenocarcinoma(COAD)l, while most DNMT/TET genes displayed highly copy number deletion in kidney chromophobe（KICH）. DNMT/TET genes were mainly involved in the following cancer-related pathways: UV response DN, mitotic spindle, cholesterol homeostasis, TGF beat signaling, xenobiotic metabolism, G2/M checkpoint, and E2F targets. DNMT/TET genes were significantly correlated with NK cells, CD4 positive T cells, and Tfh cells. Additionally, Most DNMT/TET genes were significantly associated with lower survival rates of adrenocortical carcinoma (ACC), mesothelioma, and liver hepatocellular carcinoma (LIHC), but played a protective role in thymoma (THYM). Furthermore, overexpression of most DNMT genes, except for DMAP1, was associated worse prognoses in pan-cancer. Conclusion: These results suggest that DNMT/TET genes can serve as potential predictors for prognosis and treatment in pan-cancer, providing new insight for future study.

scholarly journals Distribution-based measures of tumor heterogeneity are sensitive to mutation calling and lack strong clinical predictive power

2018 ◽  
Author(s):  
Javad Noorbakhsh ◽  
Hyunsoo Kim ◽  
Sandeep Namburi ◽  
Jeffrey Chuang
Keyword(s):  
Allele Frequency ◽  
Copy Number ◽  
Mutant Allele ◽  
Tumor Heterogeneity ◽  
Predictive Power ◽  
Allele Frequencies ◽  
The Cancer Genome Atlas ◽  
Tumor Evolution ◽  
Frequency Distributions ◽  
Math Score

Mutant allele frequency distributions in cancer samples have been used to estimate intratumoral heterogeneity and its implications for patient survival. However, mutation calls are sensitive to the calling algorithm. It remains unknown whether the relationship of heterogeneity and clinical outcome is robust to these variations. To resolve this question, we studied the robustness of allele frequency distributions to the mutation callers MuTect, SomaticSniper, and VarScan in 4722 cancer samples from The Cancer Genome Atlas. We observed discrepancies among the results, particularly a pronounced difference between allele frequency distributions called by VarScan and SomaticSniper. Survival analysis showed little robust predictive power for heterogeneity as measured by Mutant-Allele Tumor Heterogeneity (MATH) score, with the exception of uterine corpus endometrial carcinoma. However, we found that variations in mutant allele frequencies were mediated by variations in copy number. Our results indicate that the clinical predictions associated with MATH score are primarily caused by copy number aberrations that alter mutant allele frequencies. Finally, we present a mathematical model of linear tumor evolution demonstrating why MATH score is insufficient for distinguishing different scenarios of tumor growth. Our findings elucidate the importance of allele frequency distributions as a measure for tumor heterogeneity and their prognostic role.

scholarly journals Chromosomal copy number heterogeneity predicts survival rates across cancers

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Erik van Dijk ◽  
Tom van den Bosch ◽  
Kristiaan J. Lenos ◽  
Khalid El Makrini ◽  
Lisanne E. Nijman ◽  
...  
Keyword(s):  
Copy Number ◽  
Cancer Survival ◽  
Survival Rates ◽  
Cancer Prognosis ◽  
Disease Outcomes ◽  
Distinct Disease ◽  
Cancer Types ◽  
Chromosomal Copy Number ◽  
Chromosomal Copy ◽  
Pan Cancer

AbstractSurvival rates of cancer patients vary widely within and between malignancies. While genetic aberrations are at the root of all cancers, individual genomic features cannot explain these distinct disease outcomes. In contrast, intra-tumour heterogeneity (ITH) has the potential to elucidate pan-cancer survival rates and the biology that drives cancer prognosis. Unfortunately, a comprehensive and effective framework to measure ITH across cancers is missing. Here, we introduce a scalable measure of chromosomal copy number heterogeneity (CNH) that predicts patient survival across cancers. We show that the level of ITH can be derived from a single-sample copy number profile. Using gene-expression data and live cell imaging we demonstrate that ongoing chromosomal instability underlies the observed heterogeneity. Analysing 11,534 primary cancer samples from 37 different malignancies, we find that copy number heterogeneity can be accurately deduced and predicts cancer survival across tissues of origin and stages of disease. Our results provide a unifying molecular explanation for the different survival rates observed between cancer types.

Sign in / Sign up

Export Citation Format

Share Document