scholarly journals Significant associations between driver gene mutations and DNA methylation alterations across many cancer types

2017 ◽  
Vol 13 (11) ◽  
pp. e1005840 ◽  
Author(s):  
Yun-Ching Chen ◽  
Valer Gotea ◽  
Gennady Margolin ◽  
Laura Elnitski
Keyword(s):  
Dna Methylation ◽  
Gene Mutations ◽  
Driver Gene ◽  
Cancer Types

scholarly journals Significant associations between driver gene mutations and DNA methylation alterations across many cancer types

2017 ◽  
Author(s):  
Yun-Ching Chen ◽  
Valer Gotea ◽  
Gennady Margolin ◽  
Laura Elnitski
Keyword(s):  
Gene Expression ◽  
Dna Methylation ◽  
Thyroid Cancer ◽  
Gene Mutations ◽  
Driver Gene ◽  
Driver Genes ◽  
Cancer Subtypes ◽  
Genome Wide ◽  
Cancer Types ◽  
Methylation Patterns

AbstractRecent evidence shows that mutations in several driver genes can cause aberrant methylation patterns, a hallmark of cancer. In light of these findings, we hypothesized that the landscapes of tumor genomes and epigenomes are tightly interconnected. We measured this relationship using principal component analyses and methylation-mutation associations applied at the nucleotide level and with respect to genome-wide trends. We found a few mutated driver genes were associated with genome-wide patterns of aberrant hypomethylation or CpG island hypermethylation in specific cancer types. We identified associations between 737 mutated driver genes and site-specific methylation changes. Moreover, using these mutation-methylation associations, we were able to distinguish between two uterine and two thyroid cancer subtypes. The driver gene mutation-associated methylation differences between the thyroid cancer subtypes were linked to differential gene expression in JAK-STAT signaling, NADPH oxidation, and other cancer-related pathways. These results establish that driver-gene mutations are associated with methylation alterations capable of shaping regulatory network functions. In addition, the methodology presented here can be used to subdivide tumors into more homogeneous subsets corresponding to their underlying molecular characteristics, which could improve treatment efficacy.Author summaryMutations that alter the function of driver genes by changing DNA nucleotides have been recognized as a key player in cancer progression. Recent evidence showed that DNA methylation, a molecular signature that is used for controlling gene expression and that consists of cytosine residues with attached methyl groups in the context of CG dinucleotides, is also highly dysregulated in cancer and contributes to carcinogenesis. However, whether those methylation alterations correspond to mutated driver genes in cancer remains unclear. In this study, we analyzed 4,302 tumors from 18 cancer types and demonstrated that driver gene mutations are inherently connected with the aberrant DNA methylation landscape in cancer. We showed that those driver gene-associated methylation patterns can classify heterogeneous tumors in a cancer type into homogeneous subtypes and have the potential to influence the genes that contribute to tumor growth. This finding could help us to better understand the fundamental connection between driver gene mutations and DNA methylation alterations in cancer and to further improve the cancer treatment.

scholarly journals Cancer-specific associations of driver genes with immunotherapy outcome

2020 ◽  
Author(s):  
Tomi Jun ◽  
Tao Qing ◽  
Guanlan Dong ◽  
Maxim Signaevski ◽  
Julia F Hopkins ◽  
...  
Keyword(s):  
Immune Checkpoint Inhibitor ◽  
Gene Mutations ◽  
Driver Gene ◽  
Oncogenic Signaling ◽  
Multiple Cancer ◽  
Driver Genes ◽  
Tumor Mutation Burden ◽  
Mutation Burden ◽  
Cancer Types ◽  
Oncogenic Signaling Pathways

AbstractGenomic features such as microsatellite instability (MSI) and tumor mutation burden (TMB) are predictive of immune checkpoint inhibitor (ICI) response. However, they do not account for the functional effects of specific driver gene mutations, which may alter the immune microenvironment and influence immunotherapy outcomes. By analyzing a multi-cancer cohort of 1,525 ICI-treated patients, we identified 12 driver genes in 6 cancer types associated with treatment outcomes, including genes involved in oncogenic signaling pathways (NOTCH, WNT, FGFR) and chromatin remodeling. Mutations of PIK3CA, PBRM1, SMARCA4, and KMT2D were associated with worse outcomes across multiple cancer types. In comparison, genes showing cancer-specific associations—such as KEAP1, BRAF, and RNF43—harbored distinct variant types and variants, some of which were individually associated with outcomes. In colorectal cancer, a common RNF43 indel was a putative neoantigen associated with higher immune infiltration and favorable ICI outcomes. Finally, we showed that selected mutations were associated with PD-L1 status and could further stratify patient outcomes beyond MSI or TMB, highlighting their potential as biomarkers for immunotherapy.

scholarly journals Pan-cancer computational histopathology reveals mutations, tumor composition and prognosis

2019 ◽  
Author(s):  
Yu Fu ◽  
Alexander W Jung ◽  
Ramon Viñas Torne ◽  
Santiago Gonzalez ◽  
Harald Vöhringer ◽  
...  
Keyword(s):  
Computer Vision ◽  
Survival Data ◽  
Gene Mutations ◽  
Driver Gene ◽  
Spatially Resolved ◽  
Molecular Tests ◽  
Modern Computer ◽  
Genome Duplications ◽  
Cancer Types ◽  
Pan Cancer

The diagnosis of cancer is typically based on histopathological assessment of tissue sections, and supplemented by genetic and other molecular tests1–6. Modern computer vision algorithms have high diagnostic accuracy and potential to augment histopathology workflows7–9. Here we use deep transfer learning to quantify histopathological patterns across 17,396 hematoxylin and eosin (H&E) stained histopathology slide images from 28 cancer types and correlate these with matched genomic, transcriptomic and survival data. This approach accurately classifies cancer types and provides spatially resolved tumor and normal distinction. Automatically learned computational histopathological features correlate with a large range of recurrent genetic aberrations pan-cancer. This includes whole genome duplications, which display universal features across cancer types, individual chromosomal aneuploidies, focal amplifications and deletions as well as driver gene mutations. There are wide-spread associations between bulk gene expression levels and histopathology, which reflect tumour composition and enables localising transcriptomically defined tumour infiltrating lymphocytes. Computational histopathology augments prognosis based on histopathological subtyping and grading and highlights prognostically relevant areas such as necrosis or lymphocytic aggregates. These findings demonstrate the large potential of computer vision to characterise the molecular basis of tumour histopathology and lay out a rationale for integrating molecular and histopathological data to augment diagnostic and prognostic workflows.

Novel Recurrent Altered Genes in Chinese Patients With Anaplastic Thyroid Cancer

2021 ◽  
Author(s):  
Lingyun Zhang ◽  
Zhixiang Ren ◽  
Zhengzheng Su ◽  
Yang Liu ◽  
Tian Yang ◽  
...  
Keyword(s):  
Thyroid Cancer ◽  
Copy Number ◽  
Treatment Strategies ◽  
Gene Mutations ◽  
Anaplastic Thyroid Cancer ◽  
Chinese Patients ◽  
Driver Gene ◽  
Phosphatidylinositol 3 Kinase ◽  
Entire Cohort ◽  
Whole Exome

Abstract Background Anaplastic thyroid cancer (ATC) is a rare but lethal malignancy, and few systematic investigations on genomic profiles of ATC have been performed in Chinese patients. Methods Fifty-four ATC patients in West China Hospital between 2010 to 2020 were retrospectively analyzed, while 29 patients with available samples were sequenced by whole-exome sequencing (WES). The associations between genomic alterations and clinical characteristics were statistically evaluated. Results The median overall survival was 3.0 months in the entire cohort, which was impacted by multiple clinical features, including age, tumor size, and different treatment strategies. In the WES cohort, totally 797 nonsilent mutations were detected; the most frequently altered genes were TP53 (48%), BRAF (24%), PIK3CA (24%), and TERT promoter (21%). Although these mutations have been well-reported in previous studies, ethnic specificity was exhibited in terms of mutation frequency. Moreover, several novel significantly mutated genes were identified including RBM15 (17%), NOTCH2NL (14%), CTNNA3 (10%), and KATNAL2 (10%). WES-based copy number alteration analysis also revealed a high frequent gain of NOTCH2NL (41%), which induced its increased expression. Gene mutations and copy number alterations were enriched in phosphatidylinositol 3-kinase/AKT/mechanistic target of rapamycin (mTOR), NOTCH, and WNT pathways. Conclusions This study reveals shared and ethnicity-specific genomic profiles of ATC in Chinese patients and suggests NOTCH2NL may act as a novel candidate driver gene for ATC tumorigenesis.

scholarly journals High throughput estimation of functional cell activities reveals disease mechanisms and predicts relevant clinical outcomes

2016 ◽  
Author(s):  
Marta R. Hidalgo ◽  
Cankut Cubuk ◽  
Alicia Amadoz ◽  
Francisco Salavert ◽  
José Carbonell-Caballero ◽  
...  
Keyword(s):  
High Throughput ◽  
Gene Mutations ◽  
Diagnostic Value ◽  
Therapeutic Interventions ◽  
Biological Knowledge ◽  
Individual Gene ◽  
Main Challenge ◽  
Activity Measurements ◽  
Cancer Types ◽  
Or Gene

AbstractUnderstanding the aspects of the cell functionality that account for disease or drug action mechanisms is a main challenge for precision medicine. Here we propose a new method that models cell signaling using biological knowledge on signal transduction. The method recodes individual gene expression values (and/or gene mutations) into accurate measurements of changes in the activity of signaling circuits, which ultimately constitute high-throughput estimations of cell functionalities caused by gene activity within the pathway. Moreover, such estimations can be obtained either at cohort-level, in case/control comparisons, or personalized for individual patients. The accuracy of the method is demonstrated in an extensive analysis involving 5640 patients from 12 different cancer types. Circuit activity measurements not only have a high diagnostic value but also can be related to relevant disease outcomes such as survival, and can be used to assess therapeutic interventions.

scholarly journals Systematic identification of non-coding somatic single nucleotide variants associated with altered transcription and DNA methylation in adult and pediatric cancers

NAR Cancer ◽  
2021 ◽  
Vol 3 (1) ◽  
Author(s):  
Fengju Chen ◽  
Yiqun Zhang ◽  
Chad J Creighton
Keyword(s):  
Dna Methylation ◽  
Brain Tumor ◽  
Low Grade ◽  
Single Nucleotide Variants ◽  
Multiple Cancer ◽  
Single Nucleotide ◽  
Altered Expression ◽  
Wide Range ◽  
Mutational Hotspots ◽  
Cancer Types

Abstract Whole-genome sequencing combined with transcriptomics can reveal impactful non-coding single nucleotide variants (SNVs) in cancer. Here, we developed an integrative analytical approach that, as a first step, identifies genes altered in expression or DNA methylation in association with nearby somatic SNVs, in contrast to alternative approaches that first identify mutational hotspots. Using genomic datasets from the Pan-Cancer Analysis of Whole Genomes (PCAWG) consortium and the Children's Brain Tumor Tissue Consortium (CBTTC), we identified hundreds of genes and associated CpG islands for which the nearby presence of a non-coding somatic SNV recurrently associated with altered expression or DNA methylation, respectively. Genomic regions upstream or downstream of genes, gene introns and gene untranslated regions were all involved. The PCAWG adult cancer cohort yielded different significant SNV-expression associations from the CBTTC pediatric brain tumor cohort. The SNV-expression associations involved a wide range of cancer types and histologies, as well as potential gain or loss of transcription factor binding sites. Notable genes with SNV-associated increased expression include TERT, COPS3, POLE2 and HDAC2—involving multiple cancer types—MYC, BCL2, PIM1 and IGLL5—involving lymphomas—and CYHR1—involving pediatric low-grade gliomas. Non-coding somatic SNVs show a major role in shaping the cancer transcriptome, not limited to mutational hotspots.

scholarly journals Germline HLA-B evolutionary divergence influences the efficacy of immune checkpoint blockade therapy in gastrointestinal cancer

2021 ◽  
Vol 13 (1) ◽  
Author(s):  
Zhihao Lu ◽  
Huan Chen ◽  
Xi Jiao ◽  
Yujiao Wang ◽  
Lijia Wu ◽  
...  
Keyword(s):  
Immune Checkpoint ◽  
Gene Mutations ◽  
Human Leukocyte ◽  
Immune Checkpoint Blockade ◽  
Checkpoint Blockade ◽  
Cancer Center ◽  
Driver Gene ◽  
Evolutionary Divergence ◽  
Rna Profiling ◽  
Gi Cancer

Abstract Background The human leukocyte antigen class I (HLA-I) genotype has been linked with differential immune responses to infectious disease and cancer. However, the clinical relevance of germline HLA-mediated immunity in gastrointestinal (GI) cancer remains elusive. Methods This study retrospectively analyzed the genomic profiling data from 84 metastatic GI cancer patients treated with immune checkpoint blockade (ICB) recruited from Peking University Cancer Hospital (PUCH). A publicly available dataset from the Memorial Sloan Kettering (MSK) Cancer Center (MSK GI cohort) was employed as the validation cohort. For the PUCH cohort, we performed HLA genotyping by whole exome sequencing (WES) analysis on the peripheral blood samples from all patients. Tumor tissues from 76 patients were subjected to WES analysis and immune oncology-related RNA profiling. We studied the associations of two parameters of germline HLA as heterozygosity and evolutionary divergence (HED, a quantifiable measure of HLA-I evolution) with the clinical outcomes of patients in both cohorts. Results Our data showed that neither HLA heterozygosity nor HED at the HLA-A/HLA-C locus correlated with the overall survival (OS) in the PUCH cohort. Interestingly, in both the PUCH and MSK GI cohorts, patients with high HLA-B HED showed a better OS compared with low HLA-B HED subgroup. Of note, a combinatorial biomarker of HLA-B HED and tumor mutational burden (TMB) may better stratify potential responders. Furthermore, patients with high HLA-B HED were characterized with a decreased prevalence of multiple driver gene mutations and an immune-inflamed phenotype. Conclusions Our results unveil how HLA-B evolutionary divergence influences the ICB response in patients with GI cancers, supporting its potential utility as a combinatorial biomarker together with TMB for patient stratification in the future.

scholarly journals Non-invasive detection of bladder cancer through the analysis of driver gene mutations and aneuploidy

2017 ◽  
Author(s):  
Simeon Springer ◽  
Maria Del Carmen Rodriguez Pena ◽  
Lu Li ◽  
Christopher Douville ◽  
Yuxuan Wang ◽  
...  
Keyword(s):  
At Risk ◽  
Bladder Cancer ◽  
Gene Mutations ◽  
Urine Samples ◽  
Driver Gene ◽  
Low Grade ◽  
Invasive Approach ◽  
Non Invasive ◽  
Patients At Risk ◽  
Copy Number Changes

AbstractCurrent non-invasive approaches for bladder cancer (BC) detection are suboptimal. We report the development of non-invasive molecular test for BC using DNA recovered from cells shed into urine. This “UroSEEK” test incorporates assays for mutations in 11 genes and copy number changes on 39 chromosome arms. We first evaluated 570 urine samples from patients at risk for BC (microscopic hematuria or dysuria). UroSEEK was positive in 83% of patients that developed BC, but in only 7% of patients who did not develop BC. Combined with cytology, 95% of patients that developed BC were positive. We then evaluated 322 urine samples from patients soon after their BCs had been surgically resected. UroSEEK detected abnormalities in 66% of the urine samples from these patients, sometimes up to 4 years prior to clinical evidence of residual neoplasia, while cytology was positive in only 25% of such urine samples. The advantages of UroSEEK over cytology were particularly evident in low-grade tumors, wherein cytology detected none while UroSEEK detected 67% of 49 cases. These results establish the foundation for a new, non-invasive approach to the detection of BC in patients at risk for initial or recurrent disease.

scholarly journals Non-invasive detection of urothelial cancer through the analysis of driver gene mutations and aneuploidy

eLife ◽  
2018 ◽  
Vol 7 ◽  
Author(s):  
Simeon U Springer ◽  
Chung-Hsin Chen ◽  
Maria Del Carmen Rodriguez Pena ◽  
Lu Li ◽  
Christopher Douville ◽  
...  
Keyword(s):  
Urothelial Cancer ◽  
Gene Mutations ◽  
Driver Gene ◽  
Low Grade ◽  
Invasive Approach ◽  
Non Invasive ◽  
Genetic Abnormalities ◽  
Patients At Risk ◽  
Upper Tract Urothelial Cancer ◽  
Copy Number Changes

Current non-invasive approaches for detection of urothelial cancers are suboptimal. We developed a test to detect urothelial neoplasms using DNA recovered from cells shed into urine. UroSEEK incorporates massive parallel sequencing assays for mutations in 11 genes and copy number changes on 39 chromosome arms. In 570 patients at risk for bladder cancer (BC), UroSEEK was positive in 83% of those who developed BC. Combined with cytology, UroSEEK detected 95% of patients who developed BC. Of 56 patients with upper tract urothelial cancer, 75% tested positive by UroSEEK, including 79% of those with non-invasive tumors. UroSEEK detected genetic abnormalities in 68% of urines obtained from BC patients under surveillance who demonstrated clinical evidence of recurrence. The advantages of UroSEEK over cytology were evident in low-grade BCs; UroSEEK detected 67% of cases whereas cytology detected none. These results establish the foundation for a new non-invasive approach for detection of urothelial cancer.

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