scholarly journals MutEx: a multifaceted gateway for exploring integrative pan-cancer genomic data

2019 ◽  
Vol 21 (4) ◽  
pp. 1479-1486 ◽  
Author(s):  
Jie Ping ◽  
Olufunmilola Oyebamiji ◽  
Hui Yu ◽  
Scott Ness ◽  
Jeremy Chien ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
Somatic Mutation ◽  
Survival Data ◽  
Somatic Mutations ◽  
Genomic Data ◽  
Mismatch Repair Gene ◽  
Survival Difference ◽  
Cancer Types ◽  
Pan Cancer

Abstract Somatic mutation and gene expression dysregulation are considered two major tumorigenesis factors. While independent investigations of either factor pervade, studies of associations between somatic mutations and gene expression changes have been sporadic and nonsystematic. Utilizing genomic data collected from 11 315 subjects of 33 distinct cancer types, we constructed MutEx, a pan-cancer integrative genomic database. This database records the relationships among gene expression, somatic mutation and survival data for cancer patients. MutEx can be used to swiftly explore the relationship between these genomic/clinic features within and across cancer types and, more importantly, search for corroborating evidence for hypothesis inception. Our database also incorporated Gene Ontology and several pathway databases to enhance functional annotation, and elastic net and a gene expression composite score to aid in survival analysis. To demonstrate the usability of MutEx, we provide several application examples, including top somatic mutations associated with the most extensive expression dysregulation in breast cancer, differential mutational burden downstream of DNA mismatch repair gene mutations and composite gene expression score-based survival difference in breast cancer. MutEx can be accessed at http://www.innovebioinfo.com/Databases/Mutationdb_About.php.

scholarly journals Unraveling the Genomic-Epigenomic Interaction Landscape in Triple Negative and Non-Triple Negative Breast Cancer

Cancers ◽  
2020 ◽  
Vol 12 (6) ◽  
pp. 1559
Author(s):  
Jiande Wu ◽  
Tarun Karthik Kumar Mamidi ◽  
Lu Zhang ◽  
Chindo Hicks
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
Signaling Pathways ◽  
Somatic Mutation ◽  
Gene Expression Data ◽  
Triple Negative Breast Cancer ◽  
Somatic Mutations ◽  
Triple Negative ◽  
Expression Data ◽  
Gene Expression Signatures

Background: The recent surge of next generation sequencing of breast cancer genomes has enabled development of comprehensive catalogues of somatic mutations and expanded the molecular classification of subtypes of breast cancer. However, somatic mutations and gene expression data have not been leveraged and integrated with epigenomic data to unravel the genomic-epigenomic interaction landscape of triple negative breast cancer (TNBC) and non-triple negative breast cancer (non-TNBC). Methods: We performed integrative data analysis combining somatic mutation, epigenomic and gene expression data from The Cancer Genome Atlas (TCGA) to unravel the possible oncogenic interactions between genomic and epigenomic variation in TNBC and non-TNBC. We hypothesized that within breast cancers, there are differences in somatic mutation, DNA methylation and gene expression signatures between TNBC and non-TNBC. We further hypothesized that genomic and epigenomic alterations affect gene regulatory networks and signaling pathways driving the two types of breast cancer. Results: The investigation revealed somatic mutated, epigenomic and gene expression signatures unique to TNBC and non-TNBC and signatures distinguishing the two types of breast cancer. In addition, the investigation revealed molecular networks and signaling pathways enriched for somatic mutations and epigenomic changes unique to each type of breast cancer. The most significant pathways for TNBC were: retinal biosynthesis, BAG2, LXR/RXR, EIF2 and P2Y purigenic receptor signaling pathways. The most significant pathways for non-TNBC were: UVB-induced MAPK, PCP, Apelin endothelial, Endoplasmatic reticulum stress and mechanisms of viral exit from host signaling Pathways. Conclusion: The investigation revealed integrated genomic, epigenomic and gene expression signatures and signing pathways unique to TNBC and non-TNBC, and a gene signature distinguishing the two types of breast cancer. The study demonstrates that integrative analysis of multi-omics data is a powerful approach for unravelling the genomic-epigenomic interaction landscape in TNBC and non-TNBC.

scholarly journals Pan-Cancer Transcriptional Models Predicting Chemosensitivity in Human Tumors

2021 ◽  
Vol 20 ◽  
pp. 117693512110024
Author(s):  
Jason D Wells ◽  
Jacqueline R Griffin ◽  
Todd W Miller
Keyword(s):  
Gene Expression ◽  
Expression Profiles ◽  
Human Tumors ◽  
Molecular Characteristics ◽  
Survival Times ◽  
Chemotherapy Drugs ◽  
Testing Dataset ◽  
Cancer Models ◽  
Cancer Types ◽  
Pan Cancer

Motivation: Despite increasing understanding of the molecular characteristics of cancer, chemotherapy success rates remain low for many cancer types. Studies have attempted to identify patient and tumor characteristics that predict sensitivity or resistance to different types of conventional chemotherapies, yet a concise model that predicts chemosensitivity based on gene expression profiles across cancer types remains to be formulated. We attempted to generate pan-cancer models predictive of chemosensitivity and chemoresistance. Such models may increase the likelihood of identifying the type of chemotherapy most likely to be effective for a given patient based on the overall gene expression of their tumor. Results: Gene expression and drug sensitivity data from solid tumor cell lines were used to build predictive models for 11 individual chemotherapy drugs. Models were validated using datasets from solid tumors from patients. For all drug models, accuracy ranged from 0.81 to 0.93 when applied to all relevant cancer types in the testing dataset. When considering how well the models predicted chemosensitivity or chemoresistance within individual cancer types in the testing dataset, accuracy was as high as 0.98. Cell line–derived pan-cancer models were able to statistically significantly predict sensitivity in human tumors in some instances; for example, a pan-cancer model predicting sensitivity in patients with bladder cancer treated with cisplatin was able to significantly segregate sensitive and resistant patients based on recurrence-free survival times ( P = .048) and in patients with pancreatic cancer treated with gemcitabine ( P = .038). These models can predict chemosensitivity and chemoresistance across cancer types with clinically useful levels of accuracy.

scholarly journals Integrating Genetic and Transcriptomic Data to Reveal Pathogenesis and Prognostic Markers of Pancreatic Adenocarcinoma

2021 ◽  
Vol 12 ◽  
Author(s):  
Kaisong Bai ◽  
Tong Zhao ◽  
Yilong Li ◽  
Xinjian Li ◽  
Zhantian Zhang ◽  
...  
Keyword(s):  
Gene Expression ◽  
Pancreatic Adenocarcinoma ◽  
Somatic Mutation ◽  
Somatic Mutations ◽  
Prognostic Markers ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Genomic Variation ◽  
The Cancer Genome Atlas ◽  
Driver Genes

Pancreatic adenocarcinoma (PAAD) is one of the deadliest malignancies and mortality for PAAD have remained increasing under the conditions of substantial improvements in mortality for other major cancers. Although multiple of studies exists on PAAD, few studies have dissected the oncogenic mechanisms of PAAD based on genomic variation. In this study, we integrated somatic mutation data and gene expression profiles obtained by high-throughput sequencing to characterize the pathogenesis of PAAD. The mutation profile containing 182 samples with 25,470 somatic mutations was obtained from The Cancer Genome Atlas (TCGA). The mutation landscape was generated and somatic mutations in PAAD were found to have preference for mutation location. The combination of mutation matrix and gene expression profiles identified 31 driver genes that were closely associated with tumor cell invasion and apoptosis. Co-expression networks were constructed based on 461 genes significantly associated with driver genes and the hub gene FAM133A in the network was identified to be associated with tumor metastasis. Further, the cascade relationship of somatic mutation-Long non-coding RNA (lncRNA)-microRNA (miRNA) was constructed to reveal a new mechanism for the involvement of mutations in post-transcriptional regulation. We have also identified prognostic markers that are significantly associated with overall survival (OS) of PAAD patients and constructed a risk score model to identify patients’ survival risk. In summary, our study revealed the pathogenic mechanisms and prognostic markers of PAAD providing theoretical support for the development of precision medicine.

scholarly journals Somatic mutations in breast and serous ovarian cancer young patients: a systematic review and meta-analysis

2015 ◽  
Vol 61 (5) ◽  
pp. 474-483 ◽  
Author(s):  
Giselly Encinas ◽  
Simone Maistro ◽  
Fátima Solange Pasini ◽  
Maria Lucia Hirata Katayama ◽  
Maria Mitzi Brentani ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Systematic Review ◽  
Ovarian Cancer ◽  
Somatic Mutation ◽  
Early Onset ◽  
Older Patients ◽  
Somatic Mutations ◽  
Age Groups ◽  
Older Age ◽  
Serous Ovarian Cancer

Summary Objective: our aim was to evaluate whether somatic mutations in five genes were associated with an early age at presentation of breast cancer (BC) or serous ovarian cancer (SOC). Methods: COSMIC database was searched for the five most frequent somatic mutations in BC and SOC. A systematic review of PubMed was performed. Young age for BC and SOC patients was set at ≤35 and ≤40 years, respectively. Age groups were also classified in <30years and every 10 years thereafter. Results: twenty six (1,980 patients, 111 younger) and 16 studies (598, 41 younger), were analyzed for BC and SOC, respectively. In BC, PIK3CA wild type tumor was associated with early onset, not confirmed in binary regression with estrogen receptor (ER) status. In HER2-negative tumors, there was increased frequency of PIK3CA somatic mutation in older age groups; in ER-positive tumors, there was a trend towards an increased frequency of PIK3CA somatic mutation in older age groups. TP53 somatic mutation was described in 20% of tumors from both younger and older patients; PTEN, CDH1 and GATA3 somatic mutation was investigated only in 16 patients and PTEN mutation was detected in one of them. In SOC, TP53 somatic mutation was rather common, detected in more than 50% of tumors, however, more frequently in older patients. Conclusion: frequency of somatic mutations in specific genes was not associated with early-onset breast cancer. Although very common in patients with serous ovarian cancer diagnosed at all ages, TP53 mutation was more frequently detected in older women.

scholarly journals HIF1α is not a target of 14q deletion in clear cell renal cancer

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Niraj Shenoy
Keyword(s):  
Gene Expression ◽  
Tumor Suppressor ◽  
Protein Expression ◽  
Survival Data ◽  
Clear Cell ◽  
Genetic Manipulation ◽  
The Cancer Genome Atlas ◽  
Cell Renal Cell Carcinoma ◽  
Survival Difference

Abstract HIF1α has been termed a tumor-suppressor in clear cell renal cell carcinoma (ccRCC), primarily based on functional proliferation studies in cell lines (in vitro and in vivo) with genetic manipulation, and the adverse prognosis of 14q-deleted ccRCC patients. In other malignancies, however, HIF1α has an established tumor-promoting role. Therefore, this study sought to further examine the role of HIF1α in ccRCC using bioinformatic analyses of 530 ccRCC patients from The Cancer Genome Atlas (TCGA) and The Cancer Proteome Atlas (TCPA) registries. Although lower copy numbers of HIF1A (encoding HIF1α, located at 14q23.2) was associated with worse survival, there was no survival difference based on either HIF1A mRNA or HIF1α protein expression. Interestingly, L2HGDH (L-2-Hydroxyglutarate Dehydrogenase), a recently characterized epigenetic modulating ccRCC tumor-suppressor with a marked impact on survival, was found to be located only ~ 11.5Mbp from HIF1A on 14q (at 14q21.3). L2HGDH was therefore co-deleted in ~ 95% of 14q deletions involving HIF1A locus. Remarkably, HIF1A CNV had a markedly stronger correlation with L2HGDH expression (Rho = 0.55) than its own gene expression (Rho = 0.27), indicating high preserved-allele compensation of HIF1A. Genetic loss of HIF1A was therefore associated with a much greater reduction of L2HGDH gene expression than its own gene expression, providing a possible explanation for survival differences based on HIF1A CNV and mRNA expression. Furthermore, in 14q-deleted ccRCC patients with complete (uncensored) survival data, in the relatively rare cases where genetic loss of HIF1A occurred without genetic loss of L2HGDH (n = 5), the survival was significantly greater than where there was simultaneous genetic loss of both (n = 87) (mean survival 1670.8 ± 183.5 days vs 885.1 ± 78.4 days; p = 0.007). In addition, there was no correlation between HIF1A mRNA and HIF1α protein expression in ccRCC (R = 0.02), reflecting the primarily post-translational regulation of HIF1α. Lastly, even between L2HGDH and HIF1A loci, 14q was found to have several other yet-to-be-characterized potential ccRCC tumor-suppressors. Taken together, the data indicate that HIF1α is not a target of 14q deletion in ccRCC and that it is not a tumor-suppressor in this malignancy.

Prognostic value of Ki67 analysed by cytology or histology in primary breast cancer

2018 ◽  
Vol 71 (9) ◽  
pp. 787-794 ◽  
Author(s):  
Stephanie Robertson ◽  
Gustav Stålhammar ◽  
Eva Darai-Ramqvist ◽  
Mattias Rantalainen ◽  
Nicholas P Tobin ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
Overall Survival ◽  
Survival Data ◽  
Prognostic Value ◽  
Molecular Subtype ◽  
Axillary Lymph Node Metastasis ◽  
Axillary Lymph ◽  
Poor Overall Survival ◽  
Breast Tumours

AimsThe accuracy of biomarker assessment in breast pathology is vital for therapy decisions. The therapy predictive and prognostic biomarkers oestrogen receptor (ER), progesterone receptor, HER2 and Ki67 may act as surrogates to gene expression profiling of breast cancer. The aims of this study were to investigate the concordance of consecutive biomarker assessment by immunocytochemistry on preoperative fine-needle aspiration cytology versus immunohistochemistry (IHC) on the corresponding resected breast tumours. Further, to investigate the concordance with molecular subtype and correlation to stage and outcome.MethodsTwo retrospective cohorts comprising 385 breast tumours with clinicopathological data including gene expression-based subtype and up to 10-year overall survival data were evaluated.ResultsIn both cohorts, we identified a substantial variation in Ki67 index between cytology and histology and a switch between low and high proliferation within the same tumour in 121/360 cases. ER evaluations were discordant in only 1.5% of the tumours. From cohort 2, gene expression data with PAM50 subtype were used to correlate surrogate subtypes. IHC-based surrogate classification could identify the correct molecular subtype in 60% and 64% of patients by cytology (n=63) and surgical resections (n=73), respectively. Furthermore, high Ki67 in surgical resections but not in cytology was associated with poor overall survival and higher probability for axillary lymph node metastasis.ConclusionsThis study shows considerable differences in the prognostic value of Ki67 but not ER in breast cancer depending on the diagnostic method. Furthermore, our findings show that both methods are insufficient in predicting true molecular subtypes.

scholarly journals Data Fusion Techniques for the Integration of Multi-Domain Genomic Data from Uveal Melanoma

Cancers ◽  
2019 ◽  
Vol 11 (10) ◽  
pp. 1434 ◽  
Author(s):  
Max Pfeffer ◽  
André Uschmajew ◽  
Adriana Amaro ◽  
Ulrich Pfeffer
Keyword(s):  
Gene Expression ◽  
Data Fusion ◽  
Uveal Melanoma ◽  
Copy Number ◽  
Somatic Mutations ◽  
Genomic Data ◽  
The Cancer Genome Atlas ◽  
Driver Genes ◽  
Discrimination Power ◽  
Value Decomposition

Uveal melanoma (UM) is a rare cancer that is well characterized at the molecular level. Two to four classes have been identified by the analyses of gene expression (mRNA, ncRNA), DNA copy number, DNA-methylation and somatic mutations yet no factual integration of these data has been reported. We therefore applied novel algorithms for data fusion, joint Singular Value Decomposition (jSVD) and joint Constrained Matrix Factorization (jCMF), as well as similarity network fusion (SNF), for the integration of gene expression, methylation and copy number data that we applied to the Cancer Genome Atlas (TCGA) UM dataset. Variant features that most strongly impact on definition of classes were extracted for biological interpretation of the classes. Data fusion allows for the identification of the two to four classes previously described. Not all of these classes are evident at all levels indicating that integrative analyses add to genomic discrimination power. The classes are also characterized by different frequencies of somatic mutations in putative driver genes (GNAQ, GNA11, SF3B1, BAP1). Innovative data fusion techniques confirm, as expected, the existence of two main types of uveal melanoma mainly characterized by copy number alterations. Subtypes were also confirmed but are somewhat less defined. Data fusion allows for real integration of multi-domain genomic data.

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

2019 ◽  
Vol 2019 ◽  
pp. 1-17 ◽  
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.

scholarly journals Integrating Germline and Somatic Mutation Information for the Discovery of Biomarkers in Triple-Negative Breast Cancer

2019 ◽  
Vol 16 (6) ◽  
pp. 1055 ◽  
Author(s):  
Jiande Wu ◽  
Tarun Mamidi ◽  
Lu Zhang ◽  
Chindo Hicks
Keyword(s):  
Breast Cancer ◽  
Somatic Mutation ◽  
Triple Negative Breast Cancer ◽  
Somatic Mutations ◽  
Triple Negative ◽  
Germline Mutations ◽  
Biological Pathways ◽  
Molecular Networks ◽  
Increased Risk ◽  
Mutation Information

Recent advances in high-throughput genotyping and the recent surge of next generation sequencing of the cancer genomes have enabled discovery of germline mutations associated with an increased risk of developing breast cancer and acquired somatic mutations driving the disease. Emerging evidence indicates that germline mutations may interact with somatic mutations to drive carcinogenesis. However, the possible oncogenic interactions and cooperation between germline and somatic alterations in triple-negative breast cancer (TNBC) have not been characterized. The objective of this study was to investigate the possible oncogenic interactions and cooperation between genes containing germline and somatic mutations in TNBC. Our working hypothesis was that genes containing germline mutations associated with an increased risk developing breast cancer also harbor somatic mutations acquired during tumorigenesis, and that these genes are functionally related. We further hypothesized that TNBC originates from a complex interplay among and between genes containing germline and somatic mutations, and that these complex array of interacting genetic factors affect entire molecular networks and biological pathways which in turn drive the disease. We tested this hypothesis by integrating germline mutation information from genome-wide association studies (GWAS) with somatic mutation information on TNBC from The Cancer Genome Atlas (TCGA) using gene expression data from 110 patients with TNBC and 113 controls. We discovered a signature of 237 functionally related genes containing both germline and somatic mutations. We discovered molecular networks and biological pathways enriched for germline and somatic mutations. The top pathways included the hereditary breast cancer and role of BRCA1 in DNA damage response signaling pathways. In conclusion, this is the first large-scale and comprehensive analysis delineating possible oncogenic interactions and cooperation among and between genes containing germline and somatic mutations in TNBC. Genetic and somatic mutations, along with the genes discovered in this study, will require experimental functional validation in different ethnic populations. Functionally validated genetic and somatic variants will have important implications for the development of novel precision prevention strategies and discovery of prognostic markers in TNBC.

The prevalence of CDK12 alterations in Chinese cancer patients and the association with tumor mutation burden(TMB) and survival.

2020 ◽  
Vol 38 (15_suppl) ◽  
pp. e13663-e13663
Author(s):  
Ke Li ◽  
Xi Guo ◽  
Yunhua Mao ◽  
Mengmei Yang ◽  
Mengli Huang ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Cancer Patients ◽  
Molecular Subtype ◽  
Prostate Adenocarcinoma ◽  
Chinese Patients ◽  
Cyclin Dependent Kinase ◽  
Poor Prognostic Factor ◽  
Cancer Types ◽  
Chinese Cancer Patients ◽  
Pan Cancer

e13663 Background: Cyclin-dependent kinase 12 (CDK12) is a cyclin-dependent kinase that regulates transcription and RNA splicing, thereby modulating multiple cellular processes. It has been suggested that CDK12 loss-of-function mutations lead to a higher neoantigen burden and favorable responses to PD-1 inhibitors in advanced prostate cancer. Given this potentially actionable molecular subtype, we sought to determine the prevalence of CDK12 alterations in Chinese cancer patients and the association with TMB and overall survival(OS). Methods: The prevalence of CDK12 alterations were queried in 3D Medicines database with 15,745 Chinese cancer patients involved. Whole-exome sequencing data of 464 patients with prostate adenocarcinoma(PRAD) from the Cancer Genome Altas (TCGA) were downloaded to explore the association between CDK12 gene alteration and OS. And the association with TMB were analyzed in a cohort of 731 patients with various cancer types published by Memorial Sloan Kettering (MSKCC) (Samstein et al., Nature Genetics, 2019). Results: Any CDK12 and known or likely deleterious CDK12 mutations were identified in 598(3.8%) and 98(0.62%) patients, respectively. Across all cancer types, prostate adenocarcinoma(PRAD) was found to have the highest frequency of deleterious mutations(8.75%, 23/263), followed by breast cancer (4.97%, 25/503). Mutations were also detected in multiple cancer types including bladder cancer, ovarian cancer, lung cancer, colorectal cancer and so on with a frequency of less than 1%. CDK12 mutations were associated with shorter OS (HR = 15.25; 95% CI, 2.88-80.73; p < 0.001) in TCGA PRAD and cholangiocarcinoma datasets, which was not seen in other cancer types. Patients harboring CDK12 mutation had a significant higher TMB(p < 0.001) in the pan-cancer study of publicly-available cohort from MSKCC. Conclusions: CDK12 alterations existed across tumor types in Chinese patients with relatively high frequencies detected in PRAD and breast cancer and represent extremely rare events in multiple cancers. CDK12 mutation was a poor prognostic factor in PRAD and cholangiocarcinoma. In a pan cancer analysis patients with CDK12 mutation tended to have a significant higher TMB and may benefit from PD-1/L1 blockade immunotherapy.

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