Dataset Information

Identification of Four Immune Subtypes in Bladder Cancer Based on Immune Gene Sets.

ABSTRACT: Molecular classification of bladder cancer is becoming increasingly important for its clinical management. And, the current classifications are primarily based on gene expression profiles. We identified four immunotypes of bladder cancer (referred to as C1-C4) based on gene expression profiles performed by immune-related gene sets in three independent data sets, and proved that this classification is effective and reproducible. We found that C2 is an immune-infiltrating type and C4 is an immune "desert" type. These types are characterized by the up- and downregulation of genes encoding numerous immune checkpoint proteins and HLA and regulating human immune cell subgroups. The survival rate was better for the C2 subtype than for other subtypes. We believe that this can be explained by the antitumor effects of CD4 memory T cells and CD8 T cells as well as their ability to circumvent M0 macrophage antitumor immunity. In addition, C2 was most sensitive to not only anti-PD-1 immunosuppressive therapy, but also conventional chemotherapeutics such as gemcitabine and bleomycin. The C4 subtype was most sensitive to the chemotherapy drugs cisplatin and doxorubicin. This theoretical framework may guide the personalized treatment of bladder cancer in the future. It is worth noting that the C2 immune infiltration type positively correlates with a variety of stromal components, such as enrichment of endothelial cells and fibroblasts, epithelial-mesenchymal transition, and angiogenesis, together with enrichment of seven kinds of stem cells. We further identified tumor-related JAK-STAT and other signaling pathways in the C2 subtype, along with important mutations in the proteins involved in these pathways, revealing the complex mechanism underlying tumor immune escape. Our results, and particularly the identification of hub genes specific to the C2 and C4 subtypes, provide a reference for the development of immunotherapeutic agents against bladder cancer.

SUBMITTER: Tang C

PROVIDER: S-EPMC7571508 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Identification of Four Immune Subtypes in Bladder Cancer Based on Immune Gene Sets.

Tang Chaozhi C Ma Jiakang J Liu Xiuli X Liu Zhengchun Z

Frontiers in oncology 20201005

Molecular classification of bladder cancer is becoming increasingly important for its clinical management. And, the current classifications are primarily based on gene expression profiles. We identified four immunotypes of bladder cancer (referred to as C1-C4) based on gene expression profiles performed by immune-related gene sets in three independent data sets, and proved that this classification is effective and reproducible. We found that C2 is an immune-infiltrating type and C4 is an immune ...[more]

PMID: 33117683

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Project description:BackgroundMolecular subtypes predict prognosis in muscle-invasive bladder cancer (MIBC) and are explored as predictive markers. To provide a common base for molecular subtyping and facilitate clinical applications, a consensus classification has been developed. However, methods to determine consensus molecular subtypes require validation, particularly when FFPE specimens are used. Here, we aimed to evaluate two gene expression analysis methods on FFPE samples and to compare reduced gene sets to classify tumors into molecular subtypes.MethodsRNA was isolated from FFPE blocks of 15 MIBC patients. Massive analysis of 3' cDNA ends (MACE) and the HTG transcriptome panel (HTP) were used to retrieve gene expression. We used normalized, log2-transformed data to call consensus and TCGA subtypes with the consensusMIBC package for R using all available genes, a 68-gene panel (ESSEN1), and a 48-gene panel (ESSEN2).ResultsFifteen MACE-samples and 14 HTP-samples were available for molecular subtyping. The 14 samples were classified as Ba/Sq in 7 (50%), LumP in 2 (14.3%), LumU in 1 (7.1%), LumNS in 1 (7.1%), stroma-rich in 2 (14.3%) and NE-like in 1 (7.1%) case based on MACE- or HTP-derived transcriptome data. Consensus subtypes were concordant in 71% (10/14) of cases when comparing MACE with HTP data. Four cases with aberrant subtypes had a stroma-rich molecular subtype with either method. The overlap of the molecular consensus subtypes with the reduced ESSEN1 and ESSEN2 panels were 86% and 100%, respectively, with HTP data and 86% with MACE data.ConclusionDetermination of consensus molecular subtypes of MIBC from FFPE samples is feasible using various RNA sequencing methods. Inconsistent classification mainly involves the stroma-rich molecular subtype, which may be the consequence of sample heterogeneity with (stroma)-cell sampling bias and highlights the limitations of bulk RNA-based subclassification. Classification is still reliable when analysis is reduced to selected genes.

Project description:Purpose: The hypoxic tumor microenvironment was reported to be involved in different tumorigenesis mechanisms of breast cancer (BC). We aimed to establish a hypoxia-related gene signature to identify a new BC subtype through the clustering analysis and explore potential compounds targeting the BC subtypes. Methods: Gene expression data and clinical features of BC and adjacent non-tumor tissues were downloaded from the Cancer Genome Atlas-Breast cancer (TCGA-BRCA) database. We comprehensively revealed the activity changes of Gene Ontology (GO) biological processes (BP) gene sets in BC by gene set variation analysis (GSVA) and identified three hypoxia-related BC subtypes. We then matched the differentially expressed gene profile of each subtype with the gene profile in CMap database to identify the potential agents targeting the BC subtypes. Results: 562 of Gene Ontology biological processes gene sets significantly correlated with hypoxia score in breast cancer. 969 BC patients were clustered into three subtypes based on the enrichment score of hypoxia-associated gene sets. Subtype 1 patients displayed better survival than subtype 2 and 3. KEGG pathway enrichment analysis of each subtype was performed based on the unique differential expression genes profile. In subtype 1, the upregulated genes were associated with lipid and amino acid metabolism regulation; in subtype 2, the upregulated genes were associated with metabolic energy regulation, while in subtype 3, the upregulated genes were associated with apoptosis and protein process. Using the CMap database, 55, 111 and 63 compounds were identified, targeting subtype 1, 2, and 3, respectively. Conclusion: In this study, novel hypoxia-related subtypes were developed for patients with BC. In addition, biological processes associated with differential expression genes profile and potential therapeutic target compounds were identified in each subtype. The new classification might provide a better understanding of the role of hypoxia in breast cancer and more individualized treatment for patients.

Project description:The tumor environment is of vital importance for the incidence and development of colorectal cancer. Increasing evidence in recent years has elaborated the vital role of the tumor environment in cancer subtype classification and patient prognosis, but a comprehensive understanding of the colorectal tumor environment that is purely dependent on the stromal compartment is lacking. To decipher the tumor environment in colorectal cancer and explore the role of its immune context in cancer classification, we performed a gene expression microarray on the stromal compartment of colorectal cancer and adjacent normal tissues. Through the integrated analysis of our data with public gene expression microarray data of stromal and epithelial colorectal cancer tissues processed through laser capture microdissection, we identified four highly connected gene modules representing the biological features of four tissue compartments by applying a weighted gene coexpression network analysis algorithm and classified colorectal cancers into three immune subtypes by adopting a nearest template prediction algorithm. A systematic analysis of the four identified modules mainly reflected the close interplay between the biological changes of intrinsic and extrinsic characteristics at the initiation of colorectal cancer. Colorectal cancers were stratified into three immune subtypes based on gene templates identified from representative gene modules of the stromal compartment: active immune, active stroma, and mixed type. These immune subtypes differed by the immune cell infiltration pattern, expression of immune checkpoint inhibitors, mutation landscape, extent of mutation burden, extent of copy number burden, prognosis and chemotherapeutic sensitivity. Further analysis indicated that activation of the NF-kB signaling pathway was the major mechanism causing the no immune infiltration milieu in the active stroma subtype and that inhibitors of the NF-kB signaling pathway could be candidate drugs for treating patients with an active stroma. Overall, these results suggest that characterizing colorectal cancer by the tumor environment is of vital importance in predicting patients' clinical outcomes and helping guide precision and personalized treatment.

Dataset Information

Identification of Four Immune Subtypes in Bladder Cancer Based on Immune Gene Sets.

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Identification of Four Immune Subtypes in Bladder Cancer Based on Immune Gene Sets.

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