Cancer Type-Dependent Correlations betweenTP53Mutations and Antitumor Immunity

AbstractMany studies have shown thatTP53mutations play a negative role in antitumor immunity. However, a few studies reported thatTP53mutations could promote antitumor immunity. To explain these contradictory findings, we analyzed five cancer cohorts from The Cancer Genome Atlas (TCGA) project. We found thatTP53-mutated cancers had significantly higher levels of antitumor immune signatures thanTP53-wildtype cancers in breast invasive carcinoma (BRCA) and lung adenocarcinoma (LUAD). In contrast,TP53-mutated cancers had significantly lower antitumor immune signature levels thanTP53-wildtype cancers in stomach adenocarcinoma (STAD), colon adenocarcinoma (COAD), and head and neck squamous cell carcinoma (HNSC). Moreover,TP53-mutated cancers likely had higher tumor mutation burden (TMB) and tumor aneuploidy level (TAL) thanTP53-wildtype cancers. However, the TMB differences were more marked betweenTP53-mutated andTP53-wildtype cancers than the TAL differences in BRCA and LUAD, and the TAL differences were more significant in STAD and COAD. Furthermore, we showed that TMB and TAL had a positive and a negative correlation with antitumor immunity and that TMB affected antitumor immunity more greatly than TAL did in BRCA and LUAD while TAL affected antitumor immunity more strongly than TMB in STAD and HNSC. These findings indicate that the distinct correlations betweenTP53mutations and antitumor immunity in different cancer types are a consequence of the joint effect of the altered TMB and TAL caused byTP53mutations on tumor immunity. Our data suggest that theTP53mutation status could be a useful biomarker for cancer immunotherapy response depending on cancer types.

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Pan-cancer analysis reveals complex tumor-specific alternative polyadenylation

10.1101/160960 ◽

2017 ◽

Author(s):

Zhuyi Xue ◽

René L Warren ◽

Ewan A Gibb ◽

Daniel MacMillan ◽

Johnathan Wong ◽

...

Keyword(s):

Alternative Polyadenylation ◽

Length Change ◽

The Cancer Genome Atlas ◽

Cancer Type ◽

Rna Seq ◽

Multiple Cancer ◽

Tissue Samples ◽

Cancer Genome Atlas ◽

Specific Alternative ◽

Cancer Types

AbstractAlternative polyadenylation (APA) of 3’ untranslated regions (3’ UTRs) has been implicated in cancer development. Earlier reports on APA in cancer primarily focused on 3’ UTR length modifications, and the conventional wisdom is that tumor cells preferentially express transcripts with shorter 3’ UTRs. Here, we analyzed the APA patterns of 114 genes, a select list of oncogenes and tumor suppressors, in 9,939 tumor and 729 normal tissue samples across 33 cancer types using RNA-Seq data from The Cancer Genome Atlas, and we found that the APA regulation machinery is much more complicated than what was previously thought. We report 77 cases (gene-cancer type pairs) of differential 3’ UTR cleavage patterns between normal and tumor tissues, involving 33 genes in 13 cancer types. For 15 genes, the tumor-specific cleavage patterns are recurrent across multiple cancer types. While the cleavage patterns in certain genes indicate apparent trends of 3’ UTR shortening in tumor samples, over half of the 77 cases imply 3’ UTR length change trends in cancer that are more complex than simple shortening or lengthening. This work extends the current understanding of APA regulation in cancer, and demonstrates how large volumes of RNA-seq data generated for characterizing cancer cohorts can be mined to investigate this process.

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Integrative Analysis of Cancer Omics Data for Prognosis Modeling

Genes ◽

10.3390/genes10080604 ◽

2019 ◽

Vol 10 (8) ◽

pp. 604 ◽

Cited By ~ 2

Author(s):

Wang ◽

Wu ◽

Keyword(s):

Integrative Analysis ◽

The Cancer Genome Atlas ◽

Cancer Prognosis ◽

Sufficient Information ◽

Cancer Type ◽

Multiple Cancer ◽

Cancer Genome Atlas ◽

Cancer Types ◽

Information Borrowing ◽

Penalization Technique

Prognosis modeling plays an important role in cancer studies. With the development of omics profiling, extensive research has been conducted to search for prognostic markers for various cancer types. However, many of the existing studies share a common limitation by only focusing on a single cancer type and suffering from a lack of sufficient information. With potential molecular similarity across cancer types, one cancer type may contain information useful for the analysis of other types. The integration of multiple cancer types may facilitate information borrowing so as to more comprehensively and more accurately describe prognosis. In this study, we conduct marginal and joint integrative analysis of multiple cancer types, effectively introducing integration in the discovery process. For accommodating high dimensionality and identifying relevant markers, we adopt the advanced penalization technique which has a solid statistical ground. Gene expression data on nine cancer types from The Cancer Genome Atlas (TCGA) are analyzed, leading to biologically sensible findings that are different from the alternatives. Overall, this study provides a novel venue for cancer prognosis modeling by integrating multiple cancer types.

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Identification and Characterization of MicroRNAs Associated with Somatic Copy Number Alterations in Cancer

Cancers ◽

10.3390/cancers10120475 ◽

2018 ◽

Vol 10 (12) ◽

pp. 475 ◽

Cited By ~ 1

Author(s):

Jihee Soh ◽

Hyejin Cho ◽

Chan-Hun Choi ◽

Hyunju Lee

Keyword(s):

Copy Number ◽

The Cancer Genome Atlas ◽

Cancer Development ◽

Cancer Type ◽

Biological Processes ◽

Copy Number Alterations ◽

Coding Regions ◽

Cancer Genome Atlas ◽

Cancer Types ◽

Somatic Copy Number Alterations

MicroRNAs (miRNAs) are key molecules that regulate biological processes such as cell proliferation, differentiation, and apoptosis in cancer. Somatic copy number alterations (SCNAs) are common genetic mutations that play essential roles in cancer development. Here, we investigated the association between miRNAs and SCNAs in cancer. We collected 2538 tumor samples for seven cancer types from The Cancer Genome Atlas. We found that 32−84% of miRNAs are in SCNA regions, with the rate depending on the cancer type. In these regions, we identified 80 SCNA-miRNAs whose expression was mainly associated with SCNAs in at least one cancer type and showed that these SCNA-miRNAs are related to cancer by survival analysis and literature searching. We also identified 58 SCNA-miRNAs common in the seven cancer types (CC-SCNA-miRNAs) and showed that these CC-SCNA-miRNAs are more likely to be related with protein and gene expression than other miRNAs. Furthermore, we experimentally validated the oncogenic role of miR-589. In conclusion, our results suggest that SCNA-miRNAs significantly alter biological processes related to cancer development, confirming the importance of SCNAs in non-coding regions in cancer.

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Association of RYR2 Mutation with Tumor Mutation Burden, Prognosis and Antitumor Immunity in Patients with Esophageal Adenocarcinoma

10.21203/rs.3.rs-143762/v1 ◽

2021 ◽

Author(s):

Zaoqu Liu ◽

Long Liu ◽

Chunguang Guo ◽

Libo Wang ◽

Zhaonan Li ◽

...

Keyword(s):

Antitumor Immunity ◽

Immune Cell ◽

Cancer Genome ◽

The Cancer Genome Atlas ◽

Immune Checkpoints ◽

Tumor Mutation Burden ◽

Mutation Burden ◽

Potential Biomarker ◽

Cancer Genome Atlas ◽

Additional Reference

Abstract BackgroundEsophageal adenocarcinoma (EAC) remains a leading cause of cancer-related deaths worldwide, and demonstrates a predominant rising incidence in Western countries. Recently, immunotherapy has dramatically changed the landscape of treatment for many advanced cancers, the benefit in EAC thus far been limited to a small fraction of patients. MethodsUsing somatic mutations data of The Cancer Genome Atlas (TCGA) and the International Cancer Genome Consortium (ICGC), we delineated somatic mutation landscape of EAC patients from US and England. Bioinformatics algorithms were utilized to perform function annotation, immune cell infiltration analysis, and immunotherapy response assessment.ResultsWe found that RYR2 was a common frequently mutated gene (FMG) in both cohorts, and patients with RYR2 mutation suggested higher tumor mutation burden (TMB), better prognosis, and superior expression of immune checkpoints. Moreover, RYR2 mutation upregulated the signaling pathways implicated in immune response and enhanced antitumor immunity in EAC. Multiple bioinformatics algorithms for assessing immunotherapy response demonstrated that patients with RYR2 mutation might benefit more from immunotherapy. In order to provide additional reference for antitumor therapy of different RYR2 status, we identified nine latent antitumor drugs associated with RYR2 status in EAC. ConclusionsThis study reveals a novel gene whose mutation could be served as a potential biomarker for prognosis, TMB, and immunotherapy of EAC patients.

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Chromoanagenesis Landscape in 10,000 TCGA Patients

Cancers ◽

10.3390/cancers13164197 ◽

2021 ◽

Vol 13 (16) ◽

pp. 4197

Author(s):

Roni Rasnic ◽

Michal Linial

Keyword(s):

Whole Genome Sequencing ◽

Genome Sequencing ◽

Learning Algorithm ◽

The Cancer Genome Atlas ◽

Cancer Type ◽

Whole Genome ◽

Cancer Genome Atlas ◽

Cancer Types ◽

Tumor Biopsies ◽

Pan Cancer

During the past decade, whole-genome sequencing of tumor biopsies and individuals with congenital disorders highlighted the phenomenon of chromoanagenesis, a single chaotic event of chromosomal rearrangement. Chromoanagenesis was shown to be frequent in many types of cancers, to occur in early stages of cancer development, and significantly impact the tumor’s nature. However, an in-depth, cancer-type dependent analysis has been somewhat incomplete due to the shortage in whole genome sequencing of cancerous samples. In this study, we extracted data from The Pan-Cancer Analysis of Whole Genome (PCAWG) and The Cancer Genome Atlas (TCGA) to construct and test a machine learning algorithm that can detect chromoanagenesis with high accuracy (86%). The algorithm was applied to ~10,000 unlabeled TCGA cancer patients. We utilize the chromoanagenesis assignment results, to analyze cancer-type specific chromoanagenesis characteristics in 20 TCGA cancer types. Our results unveil prominent genes affected in either chromoanagenesis or non-chromoanagenesis tumorigenesis. The analysis reveals a mutual exclusivity relationship between the genes impaired in chromoanagenesis versus non-chromoanagenesis cases. We offer the discovered characteristics as possible targets for cancer diagnostic and therapeutic purposes.

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Transcriptome Based System Biology Exploration Reveals Homogeneous Tumorigenicity of Alimentary Tract Malignancy

Frontiers in Oncology ◽

10.3389/fonc.2020.580276 ◽

2021 ◽

Vol 10 ◽

Author(s):

Yu-Chen Lu ◽

Jing-Qi Shi ◽

Zi-Xin Zhang ◽

Jia-Yi Zhou ◽

Hai-Kun Zhou ◽

...

Keyword(s):

Digestive Tract ◽

Alimentary Tract ◽

Colon Adenocarcinoma ◽

The Cancer Genome Atlas ◽

Hub Genes ◽

Competitive Endogenous Rnas ◽

Cancer Genome Atlas ◽

Stomach Adenocarcinoma ◽

Gene Modules ◽

Single Tumor

Malignancies of alimentary tract include esophageal carcinoma (ESCA), stomach adenocarcinoma (STAD), colon adenocarcinoma (COAD), and rectum adenocarcinoma (READ). Despite of their similarities in cancer development and progression, there are numerous researches concentrating on single tumor but relatively little on their common mechanisms. Our study explored the transcriptomic data of digestive tract cancers from The Cancer Genome Atlas database, yielding their common differentially expressed genes including 1,700 mRNAs, 29 miRNAs, and 362 long non-coding RNAs (lncRNAs). There were 12 mRNAs, 5 miRNAs, and 16 lncRNAs in the core competitive endogenous RNAs network by RNA-RNA interactions, highlighting the prognostic nodes of SERPINE1, hsa-mir-145, and SNHG1. In addition, the weighted gene co-expression network analysis (WGCNA) illustrated 20 gene modules associated with clinical traits. By taking intersections of modules related to the same trait, we got 67 common genes shared by ESCA and READ and screened 5 hub genes, including ADCY6, CXCL3, NPBWR1, TAS2R38, and PTGDR2. In conclusion, the present study found that SERPINE1/has-mir-145/SNHG1 axis acted as promising targets and the hub genes reasoned the similarity between ESCA and READ, which revealed the homogeneous tumorigenicity of digestive tract cancers at the transcriptome level and led to further comprehension and therapeutics for digestive tract cancers.

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The presence or absence alone of miRNA isoforms (isomiRs) successfully discriminate amongst the 32 TCGA cancer types

10.1101/082685 ◽

2016 ◽

Cited By ~ 2

Author(s):

Aristeidis G. Telonis ◽

Rogan Magee ◽

Phillipe Loher ◽

Inna Chervoneva ◽

Eric Londin ◽

...

Keyword(s):

Expression Profiles ◽

The Cancer Genome Atlas ◽

Cancer Type ◽

Average Sensitivity ◽

Research Attention ◽

Disease Subtype ◽

False Discovery ◽

Cancer Genome Atlas ◽

Cancer Types ◽

Genome Atlas

Previously, we demonstrated that miRNA isoforms (isomiRs) are constitutive and their expression profiles depend on tissue, tissue state, and disease subtype. We have now extended our isomiR studies to The Cancer Genome Atlas (TCGA) repository. Specifically, we studied whether isomiR profiles can distinguish amongst the 32 cancers. We analyzed 10,271 datasets from 32 cancers and found 7,466 isomiRs from 807 miRNA hairpin-arms to be expressed above threshold. Using the top 20% most abundant isomiRs, we built a classifier that relied on “binary” isomiR profiles: isomiRs were simply represented as ‘present’ or ‘absent’ and, unlike previous methods, all knowledge about their expression levels was ignored. The classifier could label tumor samples with an average sensitivity of 93% and a False Discovery Rate of 3%. Notably, its ability to classify well persisted even when we reduced the set of used features (=isomiRs) by a factor of 10. A counterintuitive finding of our analysis is that the isomiRs and miRNA loci with the highest ability to classify tumors arenotthe ones that have been attracting the most research attention in the miRNA field. Our results provide a framework in which to study cancer-type-specific isomiRs and explore their potential uses as cancer biomarkers

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Chromoanagenesis landscape in 10,000 TCGA patients

10.1101/2021.04.29.441937 ◽

2021 ◽

Author(s):

Roni Rasnic ◽

Michal Linial

Keyword(s):

Whole Genome Sequencing ◽

Genome Sequencing ◽

Learning Algorithm ◽

The Cancer Genome Atlas ◽

Cancer Type ◽

Whole Genome ◽

Cancer Genome Atlas ◽

Cancer Types ◽

Tumor Biopsies ◽

Pan Cancer

During the past decade, whole-genome sequencing of tumor biopsies and individuals with congenital disorders highlighted the phenomenon of chromoanagenesis, a single chaotic event of chromosomal rearrangement. Chromoanagenesis was shown to be frequent in many types of cancers, to occur in early stages of cancer development, and significantly impact the tumors nature. However, an in-depth, cancer-type dependent analysis has been somewhat incomplete due to the shortage in whole genome sequencing of cancerous samples. In this study, we extracted data from The Pan-Cancer Analysis of Whole Genome (PCAWG) and The Cancer Genome Atlas (TCGA) to construct a machine learning algorithm that can detect chromoanagenesis with high accuracy (86%). The algorithm was applied to ~10,000 TCGA cancer patients. We utilize the chromoanagenesis assignment results, to analyze cancer-type specific chromoanagenesis characteristics in 20 TCGA cancer types. Our results unveil prominent genes affected in either chromoanagenesis or non-chromoanagenesis tumorigenesis. The analysis reveals a mutual exclusivity relationship between the genes impaired in chromoanagenesis versus non-chromoanagenesis cases. We offer the discovered characteristics as possible targets for cancer diagnostic and therapeutic purposes.

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Comprehensive assessment of PD-L1 and PD-L2 dysregulation in gastrointestinal cancers

Epigenomics ◽

10.2217/epi-2020-0093 ◽

2020 ◽

Author(s):

Qijie Zhao ◽

Jinan Guo ◽

Yueshui Zhao ◽

Jing Shen ◽

Parham Jabbarzadeh Kaboli ◽

...

Keyword(s):

Transcription Factor ◽

Signaling Pathways ◽

Underlying Mechanism ◽

Comprehensive Analysis ◽

The Cancer Genome Atlas ◽

Gastrointestinal Cancers ◽

Tumor Mutation Burden ◽

Mutation Burden ◽

Cancer Genome Atlas ◽

Genome Atlas

Background: PD-L1 and PD-L2 are ligands of PD-1. Their overexpression has been reported in different cancers. However, the underlying mechanism of PD-L1 and PD-L2 dysregulation and their related signaling pathways are still unclear in gastrointestinal cancers. Materials & methods: The expression of PD-L1 and PD-L2 were studied in The Cancer Genome Atlas and Genotype-Tissue Expression databases. The gene and protein alteration of PD-L1 and PD-L2 were analyzed in cBioportal. The direct transcription factor regulating PD-L1/ PD-L2 was determined with ChIP-seq data. The association of PD-L1/PD-L2 expression with clinicopathological parameters, survival, immune infiltration and tumor mutation burden were investigated with data from The Cancer Genome Atlas. Potential targets and pathways of PD-L1 and PD-L2 were determined by protein enrichment, WebGestalt and gene ontology. Results: Comprehensive analysis revealed that PD-L1 and PD-L2 were significantly upregulated in most types of gastrointestinal cancers and their expressions were positively correlated. SP1 was a key transcription factor regulating the expression of PD-L1. Conclusion: Higher PD-L1 or PD-L2 expression was significantly associated with poor overall survival, higher tumor mutation burden and more immune and stromal cell populations. Finally, HIF-1, ERBB and mTOR signaling pathways were most significantly affected by PD-L1 and PD-L2 dysregulation. Altogether, this study provided comprehensive analysis of the dysregulation of PD-L1 and PD-L2, its underlying mechanism and downstream pathways, which add to the knowledge of manipulating PD-L1/PD-L2 for cancer immunotherapy.

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Identification of novel autophagy-related lncRNAs associated with a poor prognosis of colon adenocarcinoma through bioinformatics analysis

Scientific Reports ◽

10.1038/s41598-021-87540-0 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Dejun Wu ◽

Zhenhua Yin ◽

Yisheng Ji ◽

Lin Li ◽

Yunxin Li ◽

...

Keyword(s):

High Risk ◽

Poor Prognosis ◽

Notch Pathway ◽

Colon Adenocarcinoma ◽

High Risk Group ◽

The Cancer Genome Atlas ◽

Future Research ◽

Risk Patients ◽

Cancer Genome Atlas ◽

Immune Score

AbstractLncRNAs play a pivotal role in tumorigenesis and development. However, the potential involvement of lncRNAs in colon adenocarcinoma (COAD) needs to be further explored. All the data used in this study were obtained from The Cancer Genome Atlas database, and all analyses were conducted using R software. Basing on the seven prognosis-related lncRNAs finally selected, we developed a prognosis-predicting model with powerful effectiveness (training cohort, 1 year: AUC = 0.70, 95% Cl = 0.57–0.78; 3 years: AUC = 0.71, 95% Cl = 0.6–0.8; 5 years: AUC = 0.76, 95% Cl = 0.66–0.87; validation cohort, 1 year: AUC = 0.70, 95% Cl = 0.58–0.8; 3 years: AUC = 0.73, 95% Cl = 0.63–0.82; 5 years: AUC = 0.68, 95% Cl = 0.5–0.85). The VEGF and Notch pathway were analyzed through GSEA analysis, and low immune and stromal scores were found in high-risk patients (immune score, cor = − 0.15, P < 0.001; stromal score, cor = − 0.18, P < 0.001) , which may partially explain the poor prognosis of patients in the high-risk group. We screened lncRNAs that are significantly associated with the survival of patients with COAD and possibly participate in autophagy regulation. This study may provide direction for future research.

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