scholarly journals AutoEncoder-Based Computational Framework for Tumor Microenvironment Decomposition and Biomarker Identification in Metastatic Melanoma

2021 ◽  
Vol 12 ◽  
Author(s):  
Yanding Zhao ◽  
Yadong Dong ◽  
Yongqi Sun ◽  
Chao Cheng
Keyword(s):  
Immune Cell ◽  
Tumor Vaccine ◽  
Predictive Biomarkers ◽  
The Cancer Genome Atlas ◽  
Computational Framework ◽  
Aggressive Cancer ◽  
Cancer Genome Atlas ◽  
Cancer Types ◽  
Patient Prognosis ◽  
Microarray Datasets

Melanoma is one of the most aggressive cancer types whose prognosis is determined by both the tumor cell-intrinsic and -extrinsic features as well as their interactions. In this study, we performed systematic and unbiased analysis using The Cancer Genome Atlas (TCGA) melanoma RNA-seq data and identified two gene signatures that captured the intrinsic and extrinsic features, respectively. Specifically, we selected genes that best reflected the expression signals from tumor cells and immune infiltrate cells. Then, we applied an AutoEncoder-based method to decompose the expression of these genes into a small number of representative nodes. Many of these nodes were found to be significantly associated with patient prognosis. From them, we selected two most prognostic nodes and defined a tumor-intrinsic (TI) signature and a tumor-extrinsic (TE) signature. Pathway analysis confirmed that the TE signature recapitulated cytotoxic immune cell related pathways while the TI signature reflected MYC pathway activity. We leveraged these two signatures to investigate six independent melanoma microarray datasets and found that they were able to predict the prognosis of patients under standard care. Furthermore, we showed that the TE signature was also positively associated with patients’ response to immunotherapies, including tumor vaccine therapy and checkpoint blockade immunotherapy. This study developed a novel computational framework to capture the tumor-intrinsic and -extrinsic features and identified robust prognostic and predictive biomarkers in melanoma.

scholarly journals Integrated Dissection of lncRNA-Perturbated Triplets Reveals Novel Prognostic Signatures Across Cancer Types

2020 ◽  
Vol 21 (17) ◽  
pp. 6087
Author(s):  
Yunzhen Wei ◽  
Limeng Zhou ◽  
Yingzhang Huang ◽  
Dianjing Guo
Keyword(s):  
Cancer Biology ◽  
Noncoding Rna ◽  
The Cancer Genome Atlas ◽  
Dynamic Changes ◽  
Computational Framework ◽  
Potential Biomarker ◽  
Cancer Genome Atlas ◽  
Cancer Types ◽  
Tcga Dataset ◽  
Pan Cancer

Long noncoding RNA (lncRNA)/microRNA(miRNA)/mRNA triplets contribute to cancer biology. However, identifying significative triplets remains a major challenge for cancer research. The dynamic changes among factors of the triplets have been less understood. Here, by integrating target information and expression datasets, we proposed a novel computational framework to identify the triplets termed as “lncRNA-perturbated triplets”. We applied the framework to five cancer datasets in The Cancer Genome Atlas (TCGA) project and identified 109 triplets. We showed that the paired miRNAs and mRNAs were widely perturbated by lncRNAs in different cancer types. LncRNA perturbators and lncRNA-perturbated mRNAs showed significantly higher evolutionary conservation than other lncRNAs and mRNAs. Importantly, the lncRNA-perturbated triplets exhibited high cancer specificity. The pan-cancer perturbator OIP5-AS1 had higher expression level than that of the cancer-specific perturbators. These lncRNA perturbators were significantly enriched in known cancer-related pathways. Furthermore, among the 25 lncRNA in the 109 triplets, lncRNA SNHG7 was identified as a stable potential biomarker in lung adenocarcinoma (LUAD) by combining the TCGA dataset and two independent GEO datasets. Results from cell transfection also indicated that overexpression of lncRNA SNHG7 and TUG1 enhanced the expression of the corresponding mRNA PNMA2 and CDC7 in LUAD. Our study provides a systematic dissection of lncRNA-perturbated triplets and facilitates our understanding of the molecular roles of lncRNAs in cancers.

scholarly journals Commentary on: Screening of immunosuppressive cells from colorectal adenocarcinoma and identification of prognostic markers

2021 ◽  
Author(s):  
Kexin Chen ◽  
Zhen Zeng ◽  
Chunxiang Ma ◽  
Yuan Dang ◽  
Hu Zhang
Keyword(s):  
Th17 Cells ◽  
Colorectal Adenocarcinoma ◽  
Immune Cell ◽  
Predictive Biomarkers ◽  
Gene Expression Omnibus ◽  
The Cancer Genome Atlas ◽  
Cancer Prognosis ◽  
Therapy Strategy ◽  
Cancer Genome Atlas ◽  
Immunosuppressive Cells

Colorectal adenocarcinoma (COAD) is one subtype of colorectal carcinoma (CRC), whose development is associated with genetics, inappropriate immune response, and environmental factors. Although significant advances have been made in the treatment of COAD, the mortality rate remains high. It is a pressing need to explore novel therapeutic targets of COAD. Available evidence indicated that immune cell infiltration was correlated with cancer prognosis. To reveal the roles of immune cells in the COAD prognosis, a study published in Bioscience Reports by Li et al. (Bioscience Reports (2021) 41, https://doi.org/10.1042/BSR20203496) analyzed data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) dataset. It demonstrated a beneficial effect of Th17 cells in COAD prognosis. In addition, six hub genes (KRT23, ULBP2, ASRGL1, SERPINA1, SCIN, and SLC28A2) were identified to correlate with Th17 cells and COAD prognosis, suggesting one new therapy strategy and some predictive biomarkers of COAD. These findings reported by Li et al. may pave one way to explore the molecular mechanism of COAD further.

scholarly journals TIMER2.0 for analysis of tumor-infiltrating immune cells

2020 ◽  
Vol 48 (W1) ◽  
pp. W509-W514 ◽  
Author(s):  
Taiwen Li ◽  
Jingxin Fu ◽  
Zexian Zeng ◽  
David Cohen ◽  
Jing Li ◽  
...  
Keyword(s):  
Immune Cells ◽  
Large Scale ◽  
Immune Cell ◽  
The Cancer Genome Atlas ◽  
Multiple Cancer ◽  
Public Data ◽  
Cancer Genome Atlas ◽  
Cancer Types ◽  
Transcriptomic Changes ◽  
Web Platform

Abstract Tumor progression and the efficacy of immunotherapy are strongly influenced by the composition and abundance of immune cells in the tumor microenvironment. Due to the limitations of direct measurement methods, computational algorithms are often used to infer immune cell composition from bulk tumor transcriptome profiles. These estimated tumor immune infiltrate populations have been associated with genomic and transcriptomic changes in the tumors, providing insight into tumor–immune interactions. However, such investigations on large-scale public data remain challenging. To lower the barriers for the analysis of complex tumor–immune interactions, we significantly improved our previous web platform TIMER. Instead of just using one algorithm, TIMER2.0 (http://timer.cistrome.org/) provides more robust estimation of immune infiltration levels for The Cancer Genome Atlas (TCGA) or user-provided tumor profiles using six state-of-the-art algorithms. TIMER2.0 provides four modules for investigating the associations between immune infiltrates and genetic or clinical features, and four modules for exploring cancer-related associations in the TCGA cohorts. Each module can generate a functional heatmap table, enabling the user to easily identify significant associations in multiple cancer types simultaneously. Overall, the TIMER2.0 web server provides comprehensive analysis and visualization functions of tumor infiltrating immune cells.

scholarly journals An Integrative Pan-Cancer Analysis of the Oncogenic Role of COPB2 in Human Tumors

2021 ◽  
Vol 2021 ◽  
pp. 1-18
Author(s):  
Biao Wu ◽  
Yumeng Wu ◽  
Xianlin Guo ◽  
Yanping Yue ◽  
Yuanyuan Li ◽  
...  
Keyword(s):  
Gene Expression Omnibus ◽  
The Cancer Genome Atlas ◽  
Comprehensive Understanding ◽  
Chemotherapy Sensitivity ◽  
Tumor Study ◽  
Cancer Genome Atlas ◽  
Cancer Types ◽  
Patient Prognosis ◽  
Pan Cancer

Several studies have suggested that coatomer protein complex subunit beta 2 (COPB2) may act as an oncogene in various cancer types. However, no systematic pan-cancer analysis has been performed to date. Therefore, the present study analyzed the potential oncogenic role of COPB2 using TCGA (The Cancer Genome Atlas) and GEO (Gene Expression Omnibus) datasets. The majority of the cancer types overexpressed the COPB2 protein, and its expression significantly correlated with tumor prognosis. In certain tumors, such as those found in breast and ovarian tissues, phosphorylated S859 exhibited high expression. It was found that mutations of the COPB2 protein in kidney and endometrial cancers exhibited a significant impact on patient prognosis. It is interesting to note that COPB2 expression correlated with the number of cancer-associated fibroblasts in certain tumors, such as cervical and endocervical cancers and colon adenocarcinomas. In addition, COPB2 was involved in the transport of substances and correlated with chemotherapy sensitivity. This is considered the first pan-tumor study, which provided a relatively comprehensive understanding of the mechanism by which COPB2 promotes cancer growth.

scholarly journals Pan-Cancer Analysis of PIMREG as a Biomarker for the Prognostic and Immunological Role

2021 ◽  
Vol 12 ◽  
Author(s):  
Hua Zhu ◽  
Xinyao Hu ◽  
Yingze Ye ◽  
Zhihong Jian ◽  
Yi Zhong ◽  
...  
Keyword(s):  
Signaling Pathway ◽  
Chemokine Receptors ◽  
Antigen Processing ◽  
Immune Cell ◽  
Nk Cell ◽  
Cell Lineage ◽  
Cell Receptor ◽  
The Cancer Genome Atlas ◽  
Cancer Types ◽  
Pan Cancer

Phosphatidylinositol binding clathrin assembly protein interacting mitotic regulator (PIMREG) localizes to the nucleus and can significantly elevate the nuclear localization of clathrin assembly lymphomedullary leukocythemia gene. Although there is some evidence to support an important action for PIMREG in the occurrence and development of certain cancers, currently no pan-cancer analysis of PIMREG is available. Therefore, we intended to estimate the prognostic predictive value of PIMREG and to explore its potential immune function in 33 cancer types. By using a series of bioinformatics approaches, we extracted and analyzed datasets from Oncomine, The Cancer Genome Atlas, Cancer Cell Lineage Encyclopedia (CCLE) and the Human Protein Atlas (HPA), to explore the underlying carcinogenesis of PIMREG, including relevance of PIMREG to prognosis, microsatellite instability (MSI), tumor mutation burden (TMB), tumor microenvironment (TME) and infiltration of immune cells in various types of cancer. Our findings indicate that PIMREG is highly expressed in at least 24 types of cancer, and is negatively correlated with prognosis in major cancer types. In addition, PIMREG expression was correlated with TMB in 24 cancers and with MSI in 10 cancers. We revealed that PIMREG is co-expressed with genes encoding major histocompatibility complex, immune activation, immune suppression, chemokine and chemokine receptors. We also found that the different roles of PIMREG in the infiltration of different immune cell types in different tumors. PIMREG can potentially influence the etiology or pathogenesis of cancer by acting on immune-related pathways, chemokine signaling pathway, regulation of autophagy, RIG-I like receptor signaling pathway, antigen processing and presentation, FC epsilon RI pathway, complement and coagulation cascades, T cell receptor pathway, NK cell mediated cytotoxicity and other immune-related pathways. Our study suggests that PIMREG can be applied as a prognostic marker in a variety of malignancies because of its role in tumorigenesis and immune infiltration.

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.

scholarly journals KDM1A Identified as a Potential Oncogenic Driver and Prognostic Biomarker via Multi-Omics Analysis

2021 ◽  
Vol 2021 ◽  
pp. 1-18
Author(s):  
Lingyue Li ◽  
Yiyu Wang ◽  
Yuan Mou ◽  
Hao Wu ◽  
Ye Qin
Keyword(s):  
Immune Cell ◽  
Prognostic Biomarker ◽  
The Cancer Genome Atlas ◽  
Cell Infiltration ◽  
Th2 Cells ◽  
Th1 Cell ◽  
Transport Pathways ◽  
Epigenetic Factor ◽  
Omics Analysis ◽  
Cancer Types

Background. Lysine-specific demethylase 1A (KDM1A) is a histone demethylation enzyme and a crucial epigenetic factor for multiple pathological pathways that mediate carcinogenesis and immunogenicity. Although increasing evidence supposes the association between KDM1A and cancers, no systematic multi-omics analysis of KDM1A is available. Methods. We systematically evaluated the KDM1A expression of various cancer and normal tissues and the unique relationship between KDM1A expression and prognosis of cancer cases based on The Cancer Genome Atlas (TCGA), Genotype Tissue Expression (GTEx), and Clinical Proteomic Tumor Analysis Consortium (CPTAC) database. The genetic variations, phosphorylation, and DNA methylation of KDM1A were analyzed via various tools. We further analyzed the correlation of KDM1A expression and fibroblasts and immune cell infiltration score of TCGA samples via TIMER2.0. Results. KDM1A was highly expressed in 17 types of total 33 cancers, while it expressed low levels in only 4 cancers. High KDM1A expression was associated with worse survival status in various cancers. KDM1A expression was positively correlated with the cancer-associated fibroblasts and myeloid-derived suppressor cells infiltration levels in most cancer types. Additionally, KDM1A in most cancer types was negatively correlated with Th1 cell infiltration and positively correlated with Th2 cells. Moreover, spliceosome, cell cycle, and RNA transport pathways were involved in the functional mechanisms of KDM1A via enrichment analysis. Conclusions. Our study describes the epigenetic factor KDM1A as an oncogene and prognostic biomarker. Our findings provide valuable guidance for further analysis of KDM1A function in pathogenesis and potential clinical treatment.

Identification of predictive biomarker for immunotherapy by associating with CD8+T cell Infiltration in lung adenocarcinoma.

2021 ◽  
Vol 39 (15_suppl) ◽  
pp. e21177-e21177
Author(s):  
Puyuan Xing ◽  
Teng Li ◽  
Han Wang ◽  
Lin Yang ◽  
Guoqiang Wang ◽  
...  
Keyword(s):  
Lung Adenocarcinoma ◽  
Predictive Biomarkers ◽  
Tumor Infiltrating Lymphocytes ◽  
Predictive Performance ◽  
Predictive Biomarker ◽  
Pooled Analysis ◽  
The Cancer Genome Atlas ◽  
T Cell Infiltration ◽  
Or Groups ◽  
Cancer Genome Atlas

e21177 Background: Tumor immune microenvironment (TIME) has been proved associated with response to immunotherapy(I/O). We hypothesized that screening potential mutation pattern which could significantly impact the tumor infiltrating lymphocytes(TILs) can help us to identify predictive biomarkers for I/O in Lung adenocarcinoma(LUAD). Methods: Multiple-dimensional data from The Cancer Genome Atlas LUAD cohort (n = 514) was used for building a mathematical model beween mutation signature and CD8+TIL score (based on MCP-counter). An independent public validation cohort (cohort 1: LUAD, n = 598) were used to assess the immunotherapeutic predictive performance of the potential mutation patterns. Results: Top 100 gene associated with CD8+TIL score were selected based on MC+ model which can provides the minimum non-convexity of the penalized loss given the level of bias. Seven TIME genes (SPTA1 coef 0.09; MET coef 0.02; HSD3B1 coef -0.00; STAT4 coef -0.01; EGFR coef -0.08; PIK3CB coef -0.08; KEAP1 coef -0.24) were generated by taking the intersection of the top 100 mutant genes and FoundationOne (F1) CDx NGS 315 genes panel and verified in cohort 1. Survival analysis showed that SPTA1mt was the only one that associated with both significantly longer PFS (median PFS 3.15 vs 2.89 months; HR 0.65; 95% CI 0.45 to 0.93; p = 0.02) and OS (median PFS 15.08 vs 7.36 months; HR 0.59; 95% CI 0.40 to 0.88; p = 0.01) for patients who received I/O compared with chemotherapy(CT) among seven TIME genes. In order to test our hypothesis fully, a pooled analysis of SPTA1mt (a core positive predictors of CD8+TILs) and KEAP1mt (a core negative predictors for CD8+TILs ) were conducted and yielded that co occurrence of SPTA1mt and KEAP1mt had a compound effects for TIME. The validation showed that co mutation with SPTA1mt was accompanied by an decrease HR for I/O vs. CT in both PFS (HR S+K vs. K only 0.59 vs 1.56) and OS (HR S+K vs. K only 0.39 vs 0.80) for KEAP1mt patients. Conclusions: Our data show that it is feasible to identify individuals or groups of individual with specific mutations to immunotherapy responses from TIME view. SPTA1mt was a core predictors for higher CD8+ TILs and can be identified as a predictive biomarker for benefit from I/O compared with CT. Prospective studies are warranted for further investigation.

Computational recognition of lncRNA signature of tumor-infiltrating B lymphocytes with potential implications in prognosis and immunotherapy of bladder cancer

2020 ◽  
Author(s):  
Meng Zhou ◽  
Zicheng Zhang ◽  
Siqi Bao ◽  
Ping Hou ◽  
Congcong Yan ◽  
...  
Keyword(s):  
B Lymphocytes ◽  
Noncoding Rna ◽  
Immune Cell ◽  
Functional Characterization ◽  
Predictive Biomarkers ◽  
Computational Framework ◽  
Gene Markers ◽  
Programmed Death ◽  
Clinical Covariates ◽  
Programmed Death 1

Abstract Long noncoding RNAs (lncRNAs) have been associated with cancer immunity regulation and the tumor microenvironment (TME). However, functions of lncRNAs of tumor-infiltrating B lymphocytes (TIL-Bs) and their clinical significance have not yet been fully elucidated. In the present study, a machine learning-based computational framework is presented for the identification of lncRNA signature of TIL-Bs (named ‘TILBlncSig’) through integrative analysis of immune, lncRNA and clinical profiles. The TILBlncSig comprising eight lncRNAs (TNRC6C-AS1, WASIR2, GUSBP11, OGFRP1, AC090515.2, PART1, MAFG-DT and LINC01184) was identified from the list of 141 B-cell-specific lncRNAs. The TILBlncSig was capable of distinguishing worse compared with improved survival outcomes across different independent patient datasets and was also independent of other clinical covariates. Functional characterization of TILBlncSig revealed it to be an indicator of infiltration of mononuclear immune cells (i.e. natural killer cells, B-cells and mast cells), and it was associated with hallmarks of cancer, as well as immunosuppressive phenotype. Furthermore, the TILBlncSig revealed predictive value for the survival outcome and immunotherapy response of patients with anti-programmed death-1 (PD-1) therapy and added significant predictive power to current immune checkpoint gene markers. The present study has highlighted the value of the TILBlncSig as an indicator of immune cell infiltration in the TME from a noncoding RNA perspective and strengthened the potential application of lncRNAs as predictive biomarkers of immunotherapy response, which warrants further investigation.

scholarly journals Epstein-Barr Virus-Positive Cancers Show Altered B-Cell Clonality

mSystems ◽  
2018 ◽  
Vol 3 (5) ◽  
Author(s):  
Sara R. Selitsky ◽  
David Marron ◽  
Lisle E. Mose ◽  
Joel S. Parker ◽  
Dirk P. Dittmer
Keyword(s):  
B Cells ◽  
B Cell ◽  
Epstein Barr Virus ◽  
The Cancer Genome Atlas ◽  
Barr Virus ◽  
Cancer Genome Atlas ◽  
Cancer Types ◽  
Epstein Barr ◽  
Tumor Types ◽  
Genome Atlas

ABSTRACTEpstein-Barr virus (EBV) is convincingly associated with gastric cancer, nasopharyngeal carcinoma, and certain lymphomas, but its role in other cancer types remains controversial. To test the hypothesis that there are additional cancer types with high prevalence of EBV, we determined EBV viral expression in all the Cancer Genome Atlas Project (TCGA) mRNA sequencing (mRNA-seq) samples (n= 10,396) from 32 different tumor types. We found that EBV was present in gastric adenocarcinoma and lymphoma, as expected, and was also present in >5% of samples in 10 additional tumor types. For most samples, EBV transcript levels were low, which suggests that EBV was likely present due to infected infiltrating B cells. In order to determine if there was a difference in the B-cell populations, we assembled B-cell receptors for each sample and found B-cell receptor abundance (P≤ 1.4 × 10−20) and diversity (P≤ 8.3 × 10−27) were significantly higher in EBV-positive samples. Moreover, diversity was independent of B-cell abundance, suggesting that the presence of EBV was associated with an increased and altered B-cell population.IMPORTANCEAround 20% of human cancers are associated with viruses. Epstein-Barr virus (EBV) contributes to gastric cancer, nasopharyngeal carcinoma, and certain lymphomas, but its role in other cancer types remains controversial. We assessed the prevalence of EBV in RNA-seq from 32 tumor types in the Cancer Genome Atlas Project (TCGA) and found EBV to be present in >5% of samples in 12 tumor types. EBV infects epithelial cells and B cells and in B cells causes proliferation. We hypothesized that the low expression of EBV in most of the tumor types was due to infiltration of B cells into the tumor. The increase in B-cell abundance and diversity in subjects where EBV was detected in the tumors strengthens this hypothesis. Overall, we found that EBV was associated with an increased and altered immune response. This result is not evidence of causality, but a potential novel biomarker for tumor immune status.

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