scholarly journals A multiomics comparison between endometrial cancer and serous ovarian cancer

PeerJ ◽  
2019 ◽  
Vol 8 ◽  
pp. e8347 ◽  
Author(s):  
Hui Zhong ◽  
Huiyu Chen ◽  
Huahong Qiu ◽  
Chen Huang ◽  
Zhihui Wu
Keyword(s):  
Gene Expression ◽  
Copy Number ◽  
Large Scale ◽  
Copy Number Alteration ◽  
Immune Cell ◽  
Gene Signature ◽  
The Cancer Genome Atlas ◽  
Cancer Type ◽  
Tumor Microenvironments ◽  
Molecular Phenotypes

Background Endometrial carcinoma (EC) and serous ovarian carcinoma (OvCa) are both among the common cancer types in women. EC can be divided into two subtypes, endometroid EC and serous-like EC, with distinct histological characterizations and molecular phenotypes. There is an increasing awareness that serous-like EC resembles serous OvCa in genetic landscape, but a clear relationship between them is still lacking. Methods Here, we took advantage of the large-scale molecular profiling of The Cancer Genome Atlas(TCGA) to compare the two EC subtypes and serous OvCa. We used bioinformatics data analytic methods to systematically examine the somatic mutation (SM) and copy number alteration (SCNA), gene expression, pathway activities, survival gene signatures and immune infiltration. Based on these quantifiable molecular characterizations, we asked whether serous-like EC should be grouped more closely to serous OvCa, based on the context of being serous-like; or if should be grouped more closely to endometroid EC, based on the same organ origin. Results We found that although serous-like EC and serous OvCa share some common genotypes, including mutation and copy number alteration, they differ in molecular phenotypes such as gene expression and signaling pathway activity. Moreover, no shared prognostic gene signature was found, indicating that they use unique genes governing tumor progression. Finally, although the endometrioid EC and serous OvCa are both highly immune infiltrated, the immune cell composition in serous OvCa is mostly immune suppressive, whereas endometrioid EC has a higher level of cytotoxic immune cells. Overall, our genetic aberration and molecular phenotype characterizations indicated that serous-like EC and serous OvCa cannot be simply treated as a simple “serous” cancer type. In particular, additional attention should be paid to their unique gene activities and tumor microenvironments for novel targeted therapy development.

scholarly journals iEDGE: integration of Epi-DNA and Gene Expression and applications to the discovery of somatic copy number-associated drivers in cancer

2019 ◽  
Author(s):  
Amy Li ◽  
Bjoern Chapuy ◽  
Xaralabos Varelas ◽  
Paola Sebastiani ◽  
Stefano Monti
Keyword(s):  
Gene Expression ◽  
Copy Number ◽  
Regulatory Networks ◽  
Large Scale ◽  
Method Development ◽  
The Cancer Genome Atlas ◽  
Pathway Enrichment Analysis ◽  
Cancer Genes ◽  
Driver Genes ◽  
Cis And Trans

AbstractThe emergence of large-scale multi-omics data warrants method development for data integration. Genomic studies from cancer patients have identified epigenetic and genetic regulators – such as methylation marks, somatic mutations, and somatic copy number alterations (SCNAs), among others – as predictive features of cancer outcome. However, identification of “driver genes” associated with a given alteration remains a challenge. To this end, we developed a computational tool, iEDGE, to model cis and trans effects of (epi-)DNA alterations and identify potential cis driver genes, where cis and trans genes denote those genes falling within and outside the genomic boundaries of a given (epi-)genetic alteration, respectively.First, iEDGE identifies the cis and trans genes associated with the presence/absence of a particular epi-DNA alteration across samples. Tests of statistical mediation are then performed to determine the cis genes predictive of the trans gene expression. Finally, cis and trans effects are annotated by pathway enrichment analysis to gain insights into the underlying regulatory networks.We used iEDGE to perform integrative analysis of SCNAs and gene expression data from breast cancer and 18 additional cancer types included in The Cancer Genome Atlas (TCGA). Notably, cis gene drivers identified by iEDGE were found to be significantly enriched for known driver genes from multiple compendia of validated oncogenes and tumor suppressors, suggesting that the remainder are of equal importance. Furthermore, predicted drivers were enriched for functionally relevant cancer genes with amplification-driven dependencies, which are of potential prognostic and therapeutic value. All the analyses results are accessible athttps://montilab.bu.edu/iEDGE.

scholarly journals CNAPE: A Machine Learning Method for Copy Number Alteration Prediction from Gene Expression

2019 ◽  
Author(s):  
Quanhua Mu ◽  
Jiguang Wang
Keyword(s):  
Gene Expression ◽  
Machine Learning ◽  
Copy Number ◽  
Copy Number Alteration ◽  
The Cancer Genome Atlas ◽  
Detection Methods ◽  
Dna Arrays ◽  
Machine Learning Model ◽  
Cancer Genome Atlas ◽  
Genomic Regions

AbstractCopy number alteration (CNA), the abnormal number of copies of genomic regions, plays a key role in cancer initiation and progression. Current high-throughput CNA detection methods, including DNA arrays and genomic sequencing, are relatively expensive and require DNA samples at a microgram level, which are not achievable in certain occasions such as clinical biopsies or single-cell genomes. Here we proposed an alternative method—CNAPE to computationally infer CNA using gene expression data. A prior knowledge-aided machine learning model was proposed, trained and tested on the transcriptomic profiles with matched CNA data of 9,740 cancers from The Cancer Genome Atlas. Using brain tumors as a proof-of-concept study, CNAPE achieved over 90% accuracy in the prediction of arm-level CNAs. Prediction performance for 12 gene-level CNAs (commonly altered genes in glioma) was also evaluated, and CNAPE achieved reasonable accuracy. CNAPE is developed as an easy-to-use tool at http://wang-lab.ust.hk/software/Software.html.

scholarly journals Novel Epigenetic Eight-Gene Signature Predictive of Poor Prognosis and MSI-Like Phenotype in Human Metastatic Colorectal Carcinomas

Cancers ◽  
2021 ◽  
Vol 13 (1) ◽  
pp. 158
Author(s):  
Valentina Condelli ◽  
Giovanni Calice ◽  
Alessandra Cassano ◽  
Michele Basso ◽  
Maria Grazia Rodriquenz ◽  
...  
Keyword(s):  
Gene Expression ◽  
Poor Prognosis ◽  
Cpg Island ◽  
Colon Adenocarcinoma ◽  
Gene Signature ◽  
Gene Expression Omnibus ◽  
The Cancer Genome Atlas ◽  
Cpg Island Methylator Phenotype ◽  
Prognostic Information ◽  
Global Methylation

Epigenetics is involved in tumor progression and drug resistance in human colorectal carcinoma (CRC). This study addressed the hypothesis that the DNA methylation profiling may predict the clinical behavior of metastatic CRCs (mCRCs). The global methylation profile of two human mCRC subgroups with significantly different outcome was analyzed and compared with gene expression and methylation data from The Cancer Genome Atlas COlon ADenocarcinoma (TCGA COAD) and the NCBI GENE expression Omnibus repository (GEO) GSE48684 mCRCs datasets to identify a prognostic signature of functionally methylated genes. A novel epigenetic signature of eight hypermethylated genes was characterized that was able to identify mCRCs with poor prognosis, which had a CpG-island methylator phenotype (CIMP)-high and microsatellite instability (MSI)-like phenotype. Interestingly, methylation events were enriched in genes located on the q-arm of chromosomes 13 and 20, two chromosomal regions with gain/loss alterations associated with adenoma-to-carcinoma progression. Finally, the expression of the eight-genes signature and MSI-enriching genes was confirmed in oxaliplatin- and irinotecan-resistant CRC cell lines. These data reveal that the hypermethylation of specific genes may provide prognostic information that is able to identify a subgroup of mCRCs with poor prognosis.

scholarly journals Analysis of blood-based gene expression in idiopathic Parkinson disease

Neurology ◽  
2017 ◽  
Vol 89 (16) ◽  
pp. 1676-1683 ◽  
Author(s):  
Ron Shamir ◽  
Christine Klein ◽  
David Amar ◽  
Eva-Juliane Vollstedt ◽  
Michael Bonin ◽  
...  
Keyword(s):  
Gene Expression ◽  
Parkinson Disease ◽  
Gene Networks ◽  
Large Scale ◽  
Expression Profiles ◽  
Area Under The Curve ◽  
Gene Expression Profiles ◽  
Gene Signature ◽  
Gene Profiles ◽  
Independent Test

Objective:To examine whether gene expression analysis of a large-scale Parkinson disease (PD) patient cohort produces a robust blood-based PD gene signature compared to previous studies that have used relatively small cohorts (≤220 samples).Methods:Whole-blood gene expression profiles were collected from a total of 523 individuals. After preprocessing, the data contained 486 gene profiles (n = 205 PD, n = 233 controls, n = 48 other neurodegenerative diseases) that were partitioned into training, validation, and independent test cohorts to identify and validate a gene signature. Batch-effect reduction and cross-validation were performed to ensure signature reliability. Finally, functional and pathway enrichment analyses were applied to the signature to identify PD-associated gene networks.Results:A gene signature of 100 probes that mapped to 87 genes, corresponding to 64 upregulated and 23 downregulated genes differentiating between patients with idiopathic PD and controls, was identified with the training cohort and successfully replicated in both an independent validation cohort (area under the curve [AUC] = 0.79, p = 7.13E–6) and a subsequent independent test cohort (AUC = 0.74, p = 4.2E–4). Network analysis of the signature revealed gene enrichment in pathways, including metabolism, oxidation, and ubiquitination/proteasomal activity, and misregulation of mitochondria-localized genes, including downregulation of COX4I1, ATP5A1, and VDAC3.Conclusions:We present a large-scale study of PD gene expression profiling. This work identifies a reliable blood-based PD signature and highlights the importance of large-scale patient cohorts in developing potential PD biomarkers.

scholarly journals Germline genetic polymorphisms influence tumor gene expression and immune cell infiltration

2018 ◽  
Vol 115 (50) ◽  
pp. E11701-E11710 ◽  
Author(s):  
Yoong Wearn Lim ◽  
Haiyin Chen-Harris ◽  
Oleg Mayba ◽  
Steve Lianoglou ◽  
Arthur Wuster ◽  
...  
Keyword(s):  
Gene Expression ◽  
Cancer Immunotherapy ◽  
Genetic Variants ◽  
Immune Cell ◽  
Response To Therapy ◽  
Cell Infiltration ◽  
Cancer Type ◽  
Immune Cell Infiltration ◽  
Durable Response ◽  
The Impact

Cancer immunotherapy has emerged as an effective therapy in a variety of cancers. However, a key challenge in the field is that only a subset of patients who receive immunotherapy exhibit durable response. It has been hypothesized that host genetics influences the inherent immune profiles of patients and may underlie their differential response to immunotherapy. Herein, we systematically determined the association of common germline genetic variants with gene expression and immune cell infiltration of the tumor. We identified 64,094 expression quantitative trait loci (eQTLs) that associated with 18,210 genes (eGenes) across 24 human cancers. Overall, eGenes were enriched for their being involved in immune processes, suggesting that expression of immune genes can be shaped by hereditary genetic variants. We identified the endoplasmic reticulum aminopeptidase 2 (ERAP2) gene as a pan-cancer type eGene whose expression levels stratified overall survival in a subset of patients with bladder cancer receiving anti–PD-L1 (atezolizumab) therapy. Finally, we identified 103 gene signature QTLs (gsQTLs) that were associated with predicted immune cell abundance within the tumor microenvironment. Our findings highlight the impact of germline SNPs on cancer-immune phenotypes and response to therapy; and these analyses provide a resource for integration of germline genetics as a component of personalized cancer immunotherapy.

scholarly journals Genome-Wide Scan for Copy Number Alteration Association with Relapse-Free Survival in Colorectal Cancer with Liver Metastasis Patients

2018 ◽  
Vol 7 (11) ◽  
pp. 446 ◽  
Author(s):  
Po-Sheng Yang ◽  
Hsi-Hsien Hsu ◽  
Tzu-Chi Hsu ◽  
Ming-Jen Chen ◽  
Cin-Di Wang ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Liver Metastasis ◽  
Liver Metastases ◽  
Copy Number ◽  
Copy Number Alteration ◽  
Gene Signature ◽  
Comparative Genomic ◽  
Relapse Free Survival ◽  
Cgh Array ◽  
Free Survival

Predicting a patient’s risk of recurrence after the resection of liver metastases from colorectal cancer is critical for evaluating and selecting therapeutic approaches. Clinical and pathologic parameters have shown limited accuracy thus far. Therefore, we combined the clinical status with a genomic approach to stratify relapse-free survival in colorectal cancer liver metastases patients. To identify new molecular and genetic signatures specific to colorectal cancer with liver metastasis (CRCLM) patients, we conducted DNA copy number profiling on a cohort of 21 Taiwanese CRCLM patients using a comparative genomic hybridization (CGH) array. We identified a three-gene signature based on differential copy number alteration between patients with different statuses of (1) recurrence and (2) synchronous metastasis. In relapse hotspot regions, only three genes (S100PBP, CSMD2, and TGFBI) were significantly associated with the synchronous liver metastasis factor. A final set of three genes—S100PBP, CSMD2, TGFBI—significantly predicted relapse-free survival in our cohort (p = 0.04) and another CRCLM cohort (p = 0.02). This three-gene signature is the first genomic signature validated for relapse-free survival in post-hepatectomy CRCLM patients. Our three-gene signature was developed using a whole-genome CGH array and has a good prognostic position for the relapse-free survival of CRCLM patients after hepatectomy.

scholarly journals Pervasive cis effects of variation in copy number of large tandem repeats on local epigenetics and gene expression

2020 ◽  
Author(s):  
Paras Garg ◽  
Alejandro Martin-Trujillo ◽  
Oscar L. Rodriguez ◽  
Scott J. Gies ◽  
Bharati Jadhav ◽  
...  
Keyword(s):  
Gene Expression ◽  
Dna Methylation ◽  
Copy Number ◽  
Large Scale ◽  
Tandem Repeats ◽  
Local Variation ◽  
Read Depth ◽  
Variable Number ◽  
Human Populations ◽  
Functional Variation

ABSTRACTVariable Number Tandem Repeats (VNTRs) are composed of large tandemly repeated motifs, many of which are highly polymorphic in copy number. However, due to their large size and repetitive nature, they remain poorly studied. To investigate the regulatory potential of VNTRs, we used read-depth data from Illumina whole genome sequencing to perform association analysis between copy number of ~70,000 VNTRs (motif size ≥10bp) with both gene expression (404 samples in 48 tissues) and DNA methylation (235 samples in peripheral blood), identifying thousands of VNTRs that are associated with local gene expression (eVNTRs) and DNA methylation levels (mVNTRs). Using large-scale replication analysis in an independent cohort we validated 73-80% of signals observed in the two discovery cohorts, providing robust evidence to support that these represent genuine associations. Further, conditional analysis indicated that many eVNTRs and mVNTRs act as QTLs independently of other local variation. We also observed strong enrichments of eVNTRs and mVNTRs for regulatory features such as enhancers and promoters. Using the Human Genome Diversity Panel, we defined sets of VNTRs that show highly divergent copy numbers among human populations, show that these are enriched for regulatory effects on gene expression and epigenetics, and preferentially associate with genes that have been linked with human phenotypes through GWAS. Our study provides strong evidence supporting functional variation at thousands of VNTRs, and defines candidate sets of VNTRs, copy number variation of which potentially plays a role in numerous human phenotypes.

scholarly journals ASF1B Promotes Oncogenesis in Lung Adenocarcinoma and Other Cancer Types

2021 ◽  
Vol 11 ◽  
Author(s):  
Wencheng Zhang ◽  
Zhouyong Gao ◽  
Mingxiu Guan ◽  
Ning Liu ◽  
Fanjie Meng ◽  
...  
Keyword(s):  
Lung Adenocarcinoma ◽  
Immune Cell ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Tumor Promoter ◽  
Regulatory Subunit ◽  
Cell Cycle Distribution ◽  
Cancer Type ◽  
Dependent Manner ◽  
Cancer Types

Anti-silencing function 1B histone chaperone (ASF1B) is known to be an important modulator of oncogenic processes, yet its role in lung adenocarcinoma (LUAD) remains to be defined. In this study, an integrated assessment of The Cancer Genome Atlas (TCGA) and genotype-tissue expression (GTEx) datasets revealed the overexpression of ASF1B in all analyzed cancer types other than LAML. Genetic, epigenetic, microsatellite instability (MSI), and tumor mutational burden (TMB) analysis showed that ASF1B was regulated by single or multiple factors. Kaplan-Meier survival curves suggested that elevated ASF1B expression was associated with better or worse survival in a cancer type-dependent manner. The CIBERSORT algorithm was used to evaluate immune microenvironment composition, and distinct correlations between ASF1B expression and immune cell infiltration were evident when comparing tumor and normal tissue samples. Gene set enrichment analysis (GSEA) indicated that ASF1B was associated with proliferation- and immunity-related pathways. Knocking down ASF1B impaired the proliferation, affected cell cycle distribution, and induced cell apoptosis in LUAD cell lines. In contrast, ASF1B overexpression had no impact on the malignant characteristics of LUAD cells. At the mechanistic level, ASF1B served as an indirect regulator of DNA Polymerase Epsilon 3, Accessory Subunit (POLE3), CDC28 protein kinase regulatory subunit 1(CKS1B), Dihydrofolate reductase (DHFR), as established through proteomic profiling and Immunoprecipitation-Mass Spectrometry (IP-MS) analyses. Overall, these data suggested that ASF1B serves as a tumor promoter and potential target for cancer therapy and provided us with clues to better understand the importance of ASF1B in many types of cancer.

MYC as a candidate upstream controller involved in TYMS gene expression and 5-FU/folate treatment efficacy in colorectal cancer.

2021 ◽  
Vol 39 (15_suppl) ◽  
pp. e15512-e15512
Author(s):  
David A. Drubin ◽  
Anne-Katrin Hess ◽  
Natalie L. Catlett ◽  
Alessandro Di Cara ◽  
Yvonne Wettergren ◽  
...  
Keyword(s):  
Gene Expression ◽  
Colorectal Cancer ◽  
Immune Cell ◽  
Stage Iv ◽  
Gene Signature ◽  
Immune Cell Population ◽  
Potential Biomarker ◽  
Cancer Genome Atlas ◽  
Classical Monocytes

e15512 Background: One of the target enzymes of 5-fluorouracil (5-FU)-based therapies is thymidylate synthase (TS) encoded by the TYMS gene. To enhance the effect of 5-FU, a folate analogue is often provided as part of the treatment. In this context, it has previously been shown in the ISO-CC-005 clinical study that TYMS gene expression can be predictive of response to 5-FU + folate analogue Arfolitixorin. Methods: To better understand the role of TYMS expression as a predictor of response to 5-FU + folate-based therapies and identify potential mechanisms and biomarkers of sensitivity/resistance, we leveraged data from the publicly available cancer genome atlas database (TCGA). We combined this information with a knowledgebase of causal biological relationships extracted from peer reviewed publications, to identify other relevant genes and candidate upstream controllers directly or indirectly related to TYMS expression and 5-FU + folate efficacy. Results: In TCGA subjects suffering from colorectal cancer (CRC) (stage IV tumors, treated with FOLFOX/FOLFIRI (n = 38)), lower TYMS expression was associated with a better overall survival (OS). This is consistent with what has been observed in the ISO-CC-005 study. Applying our causal biology knowledgebase to both genes identified as correlated to TYMS expression in TCGA CRC tumors and other published sets of genes associated with FOLFOX or FOLFIRI efficacy, we identified overlap with a MYCN signature. Notably MYC has been shown to directly activate TYMS expression. Thus, the MYC family is a compelling candidate upstream controller of these genes. We scored TCGA CRC tumors for inferred MYC activity, using this MYCN gene signature, and evaluated the inferred activity with respect to OS. In stage IV tumors, higher inferred MYC activity appears to be associated with worse OS. To further characterize this inferred MYC activity, we employed a transcriptomics-based cell deconvolution estimation of immune cell population proportions in the TCGA CRC cohort. We found inferred MYC activity inversely correlated with immune cell proportions overall, specifically strongest with those of pDCs and classical monocytes. Conclusions: MYC activation, a known transcriptional regulator of TYMS, has been identified as a potentially relevant common upstream controller of a group of genes involved in 5-FU + folate analogue efficacy. Here we have also observed a similar relationship to OS between TYMS and inferred MYC activity in Stage IV CRC. MYC family activity (and activated protein forms), genes of the MYCN signature, or the identified immune cell proportions are all potential biomarker candidates to explore as factors in 5-FU + folate analogue efficacy.

Large-scale analysis of longitudinal skin gene expression in systemic sclerosis reveals relationships of immune cell and fibroblast activity with skin thickness and a trend towards normalisation over time

2021 ◽  
pp. annrheumdis-2021-221352
Author(s):  
Brian Skaug ◽  
Marka A Lyons ◽  
William R Swindell ◽  
Gloria A Salazar ◽  
Minghua Wu ◽  
...  
Keyword(s):  
Gene Expression ◽  
Systemic Sclerosis ◽  
Immunohistochemical Staining ◽  
Large Scale ◽  
Immune Cell ◽  
Treatment Strategies ◽  
Principal Component ◽  
Skin Thickness ◽  
High Baseline ◽  
Over Time

ObjectivesDetermine relationships between skin gene expression and systemic sclerosis (SSc) clinical disease features, and changes in skin gene expression over time.MethodsA total of 339 forearm skin biopsies were obtained from 113 SSc patients and 44 matched healthy controls. 105 SSc patients had a second biopsy, and 76 had a third biopsy. Global gene expression profiling was performed, and differentially expressed genes and cell type-specific signatures in SSc were evaluated for relationships to modified Rodnan Skin Score (mRSS) and other clinical variables. Changes in skin gene expression over time were analysed by mixed effects models and principal component analysis. Immunohistochemical staining was performed to validate conclusions.ResultsGene expression dysregulation was greater in SSc patients with affected skin than in those with unaffected skin. Immune cell and fibroblast signatures positively correlated with mRSS. High baseline immune cell and fibroblast signatures predicted higher mRSS over time, but were not independently predictive of longitudinal mRSS after adjustment for baseline mRSS. In early diffuse cutaneous SSc, immune cell and fibroblast signatures declined over time, and overall skin gene expression trended towards normalisation. On immunohistochemical staining, most early diffuse cutaneous SSc patients with high baseline T cell and macrophage numbers had declines in these numbers at follow-up.ConclusionsSkin thickness in SSc is related to dysregulated immune cell and fibroblast gene expression. Skin gene expression changes over time in early diffuse SSc, with a tendency towards normalisation. These observations are relevant for understanding SSc pathogenesis and could inform treatment strategies and clinical trial design.

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