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Identification of immune-based prostate cancer subtypes using mRNA expression.

ABSTRACT: Immune infiltration in Prostate Cancer (PCa) was reported to be strongly associated with clinical outcomes. However, previous research could not elucidate the diversity of different immune cell types that contribute to the functioning of the immune response system. In the present study, the CIBERSORT method was employed to evaluate the relative proportions of immune cell profiling in PCa samples, adjacent tumor samples and normal samples. Three types of molecular classification were identified in tumor samples using the 'CancerSubtypes' package of the R software. Each subtype had specific molecular and clinical characteristics. In addition, functional enrichment was analyzed in each subtype. The submap and Tumor Immune Dysfunction and Exclusion (TIDE) algorithms were also used to predict clinical response to the immune checkpoint blockade. Moreover, the Genomics of Drug Sensitivity in Cancer (GDSC) database was employed to screen for potential chemotherapeutic targets for the treatment of PCa. The results showed that Cluster I was associated with advanced PCa and was more likely to respond to immunotherapy. The findings demonstrated that differences in immune responses may be important drivers of PCa progression and response to treatment. Therefore, this comprehensive assessment of the 22 immune cell types in the PCa Tumor Environment (TEM) provides insights on the mechanisms of tumor response to immunotherapy and may help clinicians explore the development of new drugs.

SUBMITTER: Song J

PROVIDER: S-EPMC7785043 | biostudies-literature | 2021 Jan

REPOSITORIES: biostudies-literature

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Identification of immune-based prostate cancer subtypes using mRNA expression.

Song Jukun J Wang Wei W Yuan Yiwen Y Ban Yong Y Su Jiaming J Yuan Dongbo D Chen Weihong W Zhu Jianguo J

Bioscience reports 20210101 1

Immune infiltration in Prostate Cancer (PCa) was reported to be strongly associated with clinical outcomes. However, previous research could not elucidate the diversity of different immune cell types that contribute to the functioning of the immune response system. In the present study, the CIBERSORT method was employed to evaluate the relative proportions of immune cell profiling in PCa samples, adjacent tumor samples and normal samples. Three types of molecular classification were identified i ...[more]

PMID: 33289508

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Project description:BackgroundPoor prognosis, resistance to chemotherapy, insensitivity to radiotherapy, and a high prevalence of adverse drug reactions remain urgent issues for breast cancer (BC) patients. Increased knowledge of tumor immunobiology and vaccine development suggests the possibility of cancer vaccination. Here, we investigated potential BC-associated antigens for the development of an anti-BC mRNA vaccine and populations suitable for mRNA vaccination.MethodsGene expression and clinical data were obtained from The Cancer Genome Atlas (TCGA) and Molecular Taxonomy of Breast Cancer International Consortium (METABRIC). The single-cell sequencing data were obtained from the Single Cell Portal platform. cBioPortal was used to visualize and compare genetic alterations. Correlations between immune cell infiltration and antigen expression were visualized with the Tumor Immune Estimation Resource (TIMER). Immune subtypes were identified by consensus clustering and analysis of immune infiltration. Biomarkers for the assessment of mRNA vaccination suitability were investigated.ResultsThree tumor-associated antigens, CD74, IRF1, and PSME2, that showed overexpression, amplification, and mutation and were linked with prognosis and immune cell infiltration, were identified. Single-cell sequencing analysis showed the expression of the three tumor-associated antigens in different cells of BC. Three immune subtypes were identified among BC patients, with Cluster B patients having a tumor microenvironment conducive to immunotherapy. These subtypes also showed different expression patterns of immune checkpoints, immune cell death-promoting genes, and response to immune checkpoint inhibitor (ICI) therapy. Thus, we identified five biomarkers that could be applied for assessing vaccination suitability and predicted drugs that would be appropriate for patients unsuited for vaccination.ConclusionsOur findings suggest new directions for the development of mRNA vaccines against breast cancer.

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.

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Identification of immune-based prostate cancer subtypes using mRNA expression.

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Identification of immune-based prostate cancer subtypes using mRNA expression.

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