scholarly journals Comprehensive Analysis of Subtype-Specific Molecular Characteristics of Colon Cancer: Specific Genes, Driver Genes, Signaling Pathways, and Immunotherapy Responses

2021 ◽  
Vol 9 ◽  
Author(s):  
Fangjie Hu ◽  
Jianyi Wang ◽  
Minghui Zhang ◽  
Shuoshuo Wang ◽  
Lingyu Zhao ◽  
...  
Keyword(s):  
Colon Cancer ◽  
Signaling Pathways ◽  
Classification System ◽  
Immune Cell ◽  
Molecular Subtypes ◽  
Molecular Classification ◽  
The Cancer Genome Atlas ◽  
Molecular Characteristics ◽  
Driver Genes ◽  
Cancer Subtypes

Colon cancer is a complex, heterogeneous disease. The Colorectal Cancer Subtyping Consortium reported a novel classification system for colon cancer in 2015 to better understand its heterogeneity. This molecular classification system divided colon cancer into four distinct consensus molecular subtypes (CMS 1, 2, 3, and 4). However, the characteristics of different colon cancer molecular subtypes have not been fully elucidated. This study comprehensively analyzed the molecular characteristics of varying colon cancer subtypes using multiple databases and algorithms, including The Cancer Genome Atlas (TCGA) database, DriverDBv3 database, CIBERSORT, and MCP-counter algorithms. We analyzed the alterations in the subtype-specific genes of different colon cancer subtypes, such as the RNA levels and DNA alterations, and showed that specific subtype-specific genes significantly affected prognosis. We also explored the changes in colon cancer driver genes and representative genes of 10 signaling pathways in different subtypes. We identified genes that were altered in specific subtypes. We further detected the infiltration of 22 immune cell types in four colon cancer subtypes and the infiltration level of primary immune cells among these subtypes. Additionally, we explored changes in immune checkpoint genes (ICGs) and immunotherapy responses among different colon cancer subtypes. This study may provide clues for the molecular mechanism of tumorigenesis and progression in colon cancer. It also offers potential biomarkers and targets for the clinical diagnosis and treatment of different colon cancer subtypes.

scholarly journals Uncovering the Subtype-Specific Molecular Characteristics of Breast Cancer by Multiomics Analysis of Prognosis-Associated Genes, Driver Genes, Signaling Pathways, and Immune Activity

2021 ◽  
Vol 9 ◽  
Author(s):  
Xinhui Li ◽  
Jian Zhou ◽  
Mingming Xiao ◽  
Lingyu Zhao ◽  
Yan Zhao ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Signaling Pathways ◽  
Immune Cell ◽  
Copy Number Variations ◽  
The Cancer Genome Atlas ◽  
Breast Cancer Subtypes ◽  
Molecular Characteristics ◽  
Driver Genes ◽  
Cancer Subtypes ◽  
Molecular Events

Breast cancer is a heterogeneous malignant disease with different prognoses and has been divided into four molecular subtypes. It is believed that molecular events occurring in breast stem/progenitor cells contribute to the carcinogenesis and development of different breast cancer subtypes. However, these subtype-specific molecular characteristics are largely unknown. In this study, we employed 1217 breast cancer samples from The Cancer Genome Atlas (TCGA) database for a multiomics analysis of the molecular characteristics of different breast cancer subtypes based on PAM50 algorithms. We detected the expression changes of subtype-specific genes and revealed that the expression of particular subtype-specific genes significantly affected prognosis. We also investigated the mutations and copy number variations (CNVs) of breast cancer driver genes and the representative genes of ten signaling pathways in different subtypes and revealed several subtype-specifically altered genes. Moreover, we detected the infiltration of various immune cells in different subtypes of breast cancer and showed that the infiltration levels of major immune cell types are different among these subtypes. Additionally, we investigated the factors affecting the immune infiltration level and the immune cytolytic activity in different breast cancer subtypes, namely, the mutation burden, genome instability and cancer-associated fibroblast (CAF) infiltration. This study may shed light on the molecular events contributing to carcinogenesis and development and provide potential markers and targets for the clinical diagnosis and treatment of different breast cancer subtypes.

scholarly journals Identification of Molecular Subtypes and a Prognostic Signature Based on Inflammation-Related Genes in Colon Adenocarcinoma

2021 ◽  
Vol 12 ◽  
Author(s):  
Chenjie Qiu ◽  
Wenxiang Shi ◽  
Huili Wu ◽  
Shenshan Zou ◽  
Jianchao Li ◽  
...  
Keyword(s):  
Colon Cancer ◽  
Cancer Patients ◽  
Immune Cell ◽  
Molecular Subtypes ◽  
Differential Expression Analysis ◽  
Human Leukocyte ◽  
The Cancer Genome Atlas ◽  
Risk Scores ◽  
Immune Checkpoints ◽  
Prognostic Signature

Both tumour-infiltrating immune cells and inflammation-related genes that can mediate immune infiltration contribute to the initiation and prognosis of patients with colon cancer. In this study, we developed a method to predict the survival outcomes among colon cancer patients and direct immunotherapy and chemotherapy. We obtained patient data from The Cancer Genome Atlas (TCGA) and captured inflammation-related genes from the GeneCards database. The package “ConsensusClusterPlus” was used to generate molecular subtypes based on inflammation-related genes obtained by differential expression analysis and univariate Cox analysis. A prognostic signature including four genes (PLCG2, TIMP1, BDNF and IL13) was also constructed and was an independent prognostic factor. Cluster 2 and higher risk scores meant worse overall survival and higher expression of human leukocyte antigen and immune checkpoints. Immune cell infiltration calculated by the estimate, CIBERSORT, TIMER, ssGSEA algorithms, tumour immune dysfunction and exclusion (TIDE), and tumour stemness indices (TSIs) were also compared on the basis of inflammation-related molecular subtypes and the risk signature. In addition, analyses of stratification, somatic mutation, nomogram construction, chemotherapeutic response prediction and small-molecule drug prediction were performed based on the risk signature. We finally used qRT–PCR to detect the expression levels of four genes in colon cancer cell lines and obtained results consistent with the prediction. Our findings demonstrated a four-gene prognostic signature that could be useful for prognostication in colon cancer patients and designing personalized treatments, which could provide new versions of personalized management for these patients.

scholarly journals Identification of three molecular subtypes based on immune infiltration in ovarian cancer and its prognostic value

2020 ◽  
Vol 40 (10) ◽  
Author(s):  
Juan Liu ◽  
Zongjian Tan ◽  
Jun He ◽  
Tingting Jin ◽  
Yuanyuan Han ◽  
...  
Keyword(s):  
Ovarian Cancer ◽  
Drug Targets ◽  
Immune Cell ◽  
Cox Regression ◽  
Molecular Subtypes ◽  
Molecular Classification ◽  
R Package ◽  
The Cancer Genome Atlas ◽  
Functional Enrichment ◽  
Immune Infiltration

Abstract Background: Increasing studies suggest that tumor immune infiltration is a relative factor of prognosis in ovarian cancer (OvCa). The present study explored the composition of tumor-infiltrating immune cells (TIICs) in OvCa using CIBERSORT algorithm and further assessed their values for prognosis and therapeutic strategies by molecular subtypes. Methods: Publicly available databases including The Cancer Genome Atlas (TCGA) and GTEx were searched. Ovarian tumor samples were available from TCGA, and normal ovarian samples were obtained from the GTEx dataset. The relative proportions of immune cell profiling in OvCa and normal samples were evaluated by CIBERSORT algorithm. Association between each immune cell subtype and survival was inferred by the fractions of 22 immune cell types. “CancerSubtypes” R-package was employed to identify the three types of molecular classification and analyze the functional enrichment in each subclass. Response to immunotherapy and anticancer drug targets was predicted via TIDE algorithm and GDSC dataset. Results: Substantial variation reflecting individual difference was identified between cancer and normal tissues in the immune infiltration profiles. T cells CD4 memory activated, macrophages M1 were associated with improved overall survival (OS) as evaluated by univariate Cox regression and multivariate Cox. Three subtypes were identified by ´CancerSubtypes’ R-package and every sub-cluster possessed specific immune cell characterization. Meanwhile, Cluster II exhibited poor prognosis and sensitive response to immunotherapy. Conclusions: The cellular component of immune infiltration shows remarkable variation in OvCa. Profiling of immune infiltration is useful in prediction of prognosis of OvCa. The results from profiling might be considered in therapeutic modulation.

scholarly journals DNA Methylation Based Molecular Subtypes Predict Prognosis in Breast Cancer Patients

2021 ◽  
Vol 28 ◽  
pp. 107327482098851
Author(s):  
Zeng-Hong Wu ◽  
Yun Tang ◽  
Yan Zhou
Keyword(s):  
Breast Cancer ◽  
Dna Methylation ◽  
Molecular Subtypes ◽  
Methylation Status ◽  
The Cancer Genome Atlas ◽  
Training Dataset ◽  
Consensus Clustering ◽  
Breast Cancer Patients ◽  
Cancer Subtypes ◽  
Novel Biomarkers

Background: Epigenetic changes are tightly linked to tumorigenesis development and malignant transformation’ However, DNA methylation occurs earlier and is constant during tumorigenesis. It plays an important role in controlling gene expression in cancer cells. Methods: In this study, we determining the prognostic value of molecular subtypes based on DNA methylation status in breast cancer samples obtained from The Cancer Genome Atlas database (TCGA). Results: Seven clusters and 204 corresponding promoter genes were identified based on consensus clustering using 166 CpG sites that significantly influenced survival outcomes. The overall survival (OS) analysis showed a significant prognostic difference among the 7 groups (p<0.05). Finally, a prognostic model was used to estimate the results of patients on the testing set based on the classification findings of a training dataset DNA methylation subgroups. Conclusions: The model was found to be important in the identification of novel biomarkers and could be of help to patients with different breast cancer subtypes when predicting prognosis, clinical diagnosis and management.

scholarly journals 3p Arm Loss and Survival in Head and Neck Cancer: An Analysis of TCGA Dataset

Cancers ◽  
2021 ◽  
Vol 13 (21) ◽  
pp. 5313
Author(s):  
Hugh Andrew Jinwook Kim ◽  
Mushfiq Hassan Shaikh ◽  
Mark Lee ◽  
Peter Y. F. Zeng ◽  
Alana Sorgini ◽  
...  
Keyword(s):  
Head And Neck Cancer ◽  
Head And Neck ◽  
Neck Cancer ◽  
Survival Data ◽  
Statistical Power ◽  
Immune Cell ◽  
The Cancer Genome Atlas ◽  
Cytokine Signaling ◽  
Molecular Characteristics ◽  
Chromosome 3P

Loss of the 3p chromosome arm has previously been reported to be a biomarker of poorer outcome in both human papillomavirus (HPV)-positive and HPV-negative head and neck cancer. However, the precise operational measurement of 3p arm loss is unclear and the mutational profile associated with the event has not been thoroughly characterized. We downloaded the clinical, single nucleotide variation (SNV), copy number aberration (CNA), RNA sequencing, and reverse phase protein assay (RPPA) data from The Cancer Genome Atlas (TCGA) and The Cancer Proteome Atlas HNSCC cohorts. Survival data and hypoxia scores were downloaded from published studies. In addition, we report the inclusion of an independent Memorial Sloan Kettering cohort. We assessed the frequency of loci deletions across the 3p arm separately in HPV-positive and -negative disease. We found that deletions on chromosome 3p were almost exclusively an all or none event in the HPV-negative cohort; patients either had <1% or >97% of the arm deleted. 3p arm loss, defined as >97% deletion in HPV-positive patients and >50% in HPV-negative patients, had no impact on survival (p > 0.05). However, HPV-negative tumors with 3p arm loss presented at a higher N-category and overall stage and developed more distant metastases (p < 0.05). They were enriched for SNVs in TP53, and depleted for point mutations in CASP8, HRAS, HLA-A, HUWE1, HLA-B, and COL22A1 (false discovery rate, FDR < 0.05). 3p arm loss was associated with CNAs across the whole genome (FDR < 0.1), and pathway analysis revealed low lymphoid–non-lymphoid cell interactions and cytokine signaling (FDR < 0.1). In the tumor microenvironment, 3p arm lost tumors had low immune cell infiltration (FDR < 0.1) and elevated hypoxia (FDR < 0.1). 3p arm lost tumors had lower abundance of proteins phospho-HER3 and ANXA1, and higher abundance of miRNAs hsa-miR-548k and hsa-miR-421, which were all associated with survival. There were no molecular differences by 3p arm status in HPV-positive patients, at least at our statistical power level. 3p arm loss is largely an all or none phenomenon in HPV-negative disease and does not predict poorer survival from the time of diagnosis in TCGA cohort. However, it produces tumors with distinct molecular characteristics and may represent a clinically useful biomarker to guide treatment decisions for HPV-negative patients.

scholarly journals SERPINE1 associated with remodeling of the tumor microenvironment in colon cancer progression: a novel therapeutic target

BMC Cancer ◽  
2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Shaokun Wang ◽  
Li Pang ◽  
Zuolong Liu ◽  
Xiangwei Meng
Keyword(s):  
Colorectal Cancer ◽  
Colon Cancer ◽  
Immune Cells ◽  
Immune Cell ◽  
Cox Regression ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Cell Infiltration ◽  
Immune Cell Infiltration ◽  
The Relationship

Abstract Background The change of immune cell infiltration essentially influences the process of colorectal cancer development. The infiltration of immune cells can be regulated by a variety of genes. Thus, modeling the immune microenvironment of colorectal cancer by analyzing the genes involved can be more conducive to the in-depth understanding of carcinogenesis and the progression thereof. Methods In this study, the number of stromal and immune cells in malignant tumor tissues were first estimated by using expression data (ESTIMATE) and cell-type identification with relative subsets of known RNA transcripts (CIBERSORT) to calculate the proportion of infiltrating immune cell and stromal components of colon cancer samples from the Cancer Genome Atlas database. Then the relationship between the TMN Classification and prognosis of malignant tumors was evaluated. Results By investigating differentially expressed genes using COX regression and protein-protein interaction network (PPI), the candidate hub gene serine protease inhibitor family E member 1 (SERPINE1) was found to be associated with immune cell infiltration. Gene Set Enrichment Analysis (GSEA) further projected the potential pathways with elevated SERPINE1 expression to carcinogenesis and immunity. CIBERSORT was subsequently utilized to investigate the relationship between the expression differences of SERPINE1 and immune cell infiltration and to identify eight immune cells associated with SERPINE1 expression. Conclusion We found that SERPINE1 plays a role in the remodeling of the colon cancer microenvironment and the infiltration of immune cells.

scholarly journals Comprehensive Characterization of Alternative mRNA Splicing Events in Glioblastoma: Implications for Prognosis, Molecular Subtypes, and Immune Microenvironment Remodeling

2021 ◽  
Vol 10 ◽  
Author(s):  
Liang Zhao ◽  
Jiayue Zhang ◽  
Zhiyuan Liu ◽  
Yu Wang ◽  
Shurui Xuan ◽  
...  
Keyword(s):  
Risk Score ◽  
Immune Cell ◽  
Cox Regression ◽  
Malignant Tumors ◽  
Cox Model ◽  
Molecular Classification ◽  
The Cancer Genome Atlas ◽  
Consensus Clustering ◽  
Cox Regression Analysis ◽  
Alternative Mrna Splicing

Alternative splicing (AS) of pre-mRNA has been widely reported to be associated with the progression of malignant tumors. However, a systematic investigation into the prognostic value of AS events in glioblastoma (GBM) is urgently required. The gene expression profile and matched AS events data of GBM patients were obtained from The Cancer Genome Atlas Project (TCGA) and TCGA SpliceSeq database, respectively. 775 AS events were identified as prognostic factors using univariate Cox regression analysis. The least absolute shrinkage and selection operator (LASSO) cox model was performed to narrow down candidate AS events, and a risk score model based on several AS events were developed subsequently. The risk score-based signature was proved as an efficient predictor of overall survival and was closely related to the tumor purity and immunosuppression in GBM. Combined similarity network fusion and consensus clustering (SNF-CC) analysis revealed two distinct GBM subtypes based on the prognostic AS events, and the associations between this novel molecular classification and clinicopathological factors, immune cell infiltration, as well as immunogenic features were further explored. We also constructed a regulatory network to depict the potential mechanisms that how prognostic splicing factors (SFs) regulate splicing patterns in GBM. Finally, a nomogram incorporating AS events signature and other clinical-relevant covariates was built for clinical application. This comprehensive analysis highlights the potential implications for predicting prognosis and clinical management in GBM.

scholarly journals The emerging role of molecular pathology in directing the systemic treatment of endometrial cancer

2021 ◽  
Vol 13 ◽  
pp. 175883592110359
Author(s):  
Amy Jamieson ◽  
Tjalling Bosse ◽  
Jessica N. McAlpine
Keyword(s):  
Endometrial Cancer ◽  
Molecular Subtypes ◽  
Treatment Decision ◽  
Molecular Classification ◽  
The Cancer Genome Atlas ◽  
Molecular Profile ◽  
Therapeutic Implications ◽  
Treatment Decision Making ◽  
Exciting Time ◽  
Classification Tool

Following the discovery of the four molecular subtypes of endometrial cancer (EC) by The Cancer Genome Atlas (TCGA) in 2013, subsequent studies used surrogate markers to develop and validate a clinically relevant EC classification tool to recapitulate TCGA subtypes. Molecular classification combines focused sequencing ( POLE) and immunohistochemistry (mismatch repair and p53 proteins) to assign patients with EC to one of four molecular subtypes: POLEmut, MMRd, p53abn and NSMP (no specific molecular profile). Unlike histopathological evaluation, the molecular subtyping of EC offers an objective and reproducible classification system that has been shown to have prognostic value and therapeutic implications. It is an exciting time in EC care where we have moved beyond treatment based on histomorphology alone, and molecular classification will now finally allow assessment of treatment efficacy within biologically similar tumours. It is now recommended that molecular classification should be considered for all ECs, and should be performed routinely in all high grade tumours. It is also recommended to incorporate molecular classification into standard pathology reporting and treatment decision-making algorithms. In this review, we will discuss how the molecular classification of EC can be used to guide both conventional and targeted therapy in this new molecular era.

scholarly journals Identification of two molecular subtypes of dysregulated immune lncRNAs in ovarian cancer

2020 ◽  
pp. 153537022097202
Author(s):  
Xiaojun Liu ◽  
Jinghai Gao ◽  
Jing Wang ◽  
Jing Chu ◽  
Jiahao You ◽  
...  
Keyword(s):  
Ovarian Cancer ◽  
Differentially Expressed Genes ◽  
Immune Cell ◽  
Molecular Subtypes ◽  
Good Prognosis ◽  
The Cancer Genome Atlas ◽  
Functional Enrichment ◽  
Differentially Expressed ◽  
Receptor Interaction ◽  
Cancer Multiple

Long non-coding RNA (lncRNA) has increasingly been identified as a key regulator in pathologies such as cancer. Multiple platforms were used for comprehensive analysis of ovarian cancer to identify molecular subgroups. However, lncRNA and its role in mapping the ovarian cancer subpopulation are still largely unknown. RNA-sequencing and clinical characteristics of ovarian cancer were acquired from The Cancer Genome Atlas database (TCGA). A total of 52 lncRNAs were identified as aberrant immune lncRNAs specific to ovarian cancer. We redefined two different molecular subtypes, C1(188) and C2(184 samples), in “iClusterPlus” R package, among which C2 grouped ovarian cancer samples have higher survival probability and longer median survival time ( P <0.05) with activated IFN-gamma response, Wound Healing and Cytotoxic lymphocytes signal; 456 differentially expressed genes were acquired in C1 and C2 subtypes using limma (3.40.6) package, among which 419 were up-regulated and 37 were down-regulated, in TCGA dataset. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) functional enrichment analysis revealed that these genes were actively involved in ECM-receptor interaction, PI3K-Akt signaling pathway interaction KEGG pathway. Compared with the existing immune subtype, the Cluster2 sample showed a substantial increase in the proportion of the existing C2 immune subtype, accounting for 81.37%, which was associated with good prognosis. Our C1 subtype contains only 56.49% of the existing immune C1 and C4, which also explains the poor prognosis of C1. Furthermore, 52 immune-related lncRNAs were used to divide the TCGA-endometrial cancer and cervical cancer samples into two categories, and C2 had a good prognosis. The differentially expressed genes were highly correlated with immune-cell-related pathways. Based on lncRNA, two molecular subtypes of ovarian cancer were identified and had significant prognostic differences and immunological characteristics.

Tumor sidedness and intrinsic subtypes in patients with stage II/III colon cancer: Analysis of NSABP C-07 (NRG Oncology).

2017 ◽  
Vol 35 (15_suppl) ◽  
pp. 3514-3514 ◽  
Author(s):  
S. Rim Kim ◽  
Nan Song ◽  
Greg Yothers ◽  
Patrick Gavin ◽  
Carmen Joseph Allegra ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Colon Cancer ◽  
Molecular Subtypes ◽  
Molecular Subtype ◽  
Therapy Response ◽  
Stage Ii ◽  
Intrinsic Subtypes ◽  
Treatment Benefit ◽  
Cancer Subtypes ◽  
Metastatic Setting

3514 Background: The predictive value of tumor sidedness in colorectal cancer is currently of interest especially in metastatic setting for anti-EGFR therapy response. We tested whether intrinsic molecular subtype classification predictive of treatment benefit in stage II/III colon cancer is an independent novel marker in association with tumor sidedness. Methods: All available cases included in the NSABP/NRG C-07 trial for which we had both gene expression data and anatomical data (n=1603) were used to determine the molecular subtypes using the following classifiers; the Colorectal Cancer Assigner (CRCA), the Colon Cancer Subtypes (CCS) and the Consensus Molecular Subtypes (CMS). Frequency of tumor sidedness in each subtype and recurrence-free survival were analyzed. Results: Intrinsic subtypes were differentially distributed in right- and left-colon tumors with the exception of the stem-like or CMS4 (mesenchymal) subtype (Table 1). Sidedness was not associated with prognosis (p=0.82, HR: 1.022 [CI: 0.851-1.227]) or prediction of patients with greater benefit from oxaliplatin when combined with 5-Fu+LV (interaction p=0.484). Conclusions: Although tumor sidedness is associated with distribution of intrinsic subtypes in stage II/III colon cancer, it is not predictive of survival benefit from oxaliplatin in C-07. Support: -180868, -180822, U24-CA196067; HI13C2162; PA DOH; Sanofi-Synthelabo Clinical trial information: NCT00004931. [Table: see text]

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