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

Abstract

Background: Increasing studies suggest that tumor immune infiltration is a relative factor of prognosis in ovarian cancer (OvCa). This 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 anti-cancer 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.

Classification and Clinical Value of Three Immune Subtypes of Ovarian Cancer Based on Transcriptome Data

“…More and more pieces of evidence show that tumor immune infiltration is related to the prognosis of ovarian cancer 33,34 M1 macrophages could exert a pro-inflammatory function and boost the Th1 response and were inclined to identify and arrest tumor cells, therefore they emerged as the most prognostic immune cell type in ovarian cancer 37,38 . The subsets of memory T cells include CD4 + and CD8 + memory T cells.…”

Shaping Immune Responses in the Tumor Microenvironment of Ovarian Cancer

“…The tumor immune microenvironment (TIME) is the immune contexture acting as a crucial orchestrator for cancer development, progression and metastasis, mainly composed with the infiltrated immune cells, their chemokines and cytokines (12). The relationship of TIME function and the clinical correlation were analyzed in ovarian carcinoma based on The Cancer Genome Atlas (TCGA) cohort, and four TIME molecular subtypes of the global immune-related genes were obtained, the high immune scoring subtype with the upregulated tumourinfiltrating immune cells had a high BRCA1 mutation, high expression of immune checkpoints, and optimal survival prognosis (15,16). Candido et al evaluated the immune response patterns through analysis of type 1 (Th1), type 1 (Th2), and type 17(Th17) cytokines in patients with epithelial ovarian cancer (EOC), and found higher levels of TNF-a/IL-4/ IL-6/IL-10 in EOC patients compared to the control, IL-10 and TNF-a concentrations were higher in stage III/IV and associated with higher CA125, higher Th1 immune response was observed when the cytoreduction was considered optimal, while higher concentrations of Th2 cytokines were associated with unsatisfactory cytoreductive surgery and undifferentiated tumors (17).…”

“…The tumor immune microenvironment (TIME) is the immune contexture acting as a crucial orchestrator for cancer development, progression and metastasis, mainly composed with the infiltrated immune cells, their chemokines and cytokines ( 12 ). The relationship of TIME function and the clinical correlation were analyzed in ovarian carcinoma based on The Cancer Genome Atlas (TCGA) cohort, and four TIME molecular subtypes of the global immune-related genes were obtained, the high immune scoring subtype with the upregulated tumour-infiltrating immune cells had a high BRCA1 mutation, high expression of immune checkpoints, and optimal survival prognosis ( 15 , 16 ). Cândido et al.…”

Transcriptome-based stemness indices analysis reveals platinum-based chemo-theraputic response indicators in advanced-stage serous ovarian cancer

“…First, compared with tumor tissue samples, the sample size of normal tissue in the GTEx database is small. Although multiple prognostic markers of OC have been identified based on the GTEx database [50][51][52], we need to further expand the sample size from our center in the future. Second, the generation of chemoresistance was a complex process involving networks of genes and pathways.…”