Dataset Information

Siglec15 shapes a non-inflamed tumor microenvironment and predicts the molecular subtype in bladder cancer.

ABSTRACT: Rationale: Siglec15 is an emerging target for normalization cancer immunotherapy. However, pan-cancer anti-Siglec15 treatment is not yet validated and the potential role of Siglec15 in bladder cancer (BLCA) remains elusive. Methods: We comprehensively evaluated the expression pattern and immunological role of Siglec15 using pan-cancer analysis based on RNA sequencing data obtained from The Cancer Genome Atlas. We then systematically correlated Siglec15 with immunological characteristics in the BLCA tumor microenvironment (TME), including immunomodulators, cancer immunity cycles, tumor-infiltrating immune cells (TIICs), immune checkpoints, and T cell inflamed score. We also analyzed the role of Siglec15 in predicting the molecular subtype and the response to several treatment options in BLCA. Our results were validated in several public cohorts as well as our BLCA tumor microarray cohort, the Xiangya cohort. We developed an immune risk score (IRS), validated it, and tested its ability to predict the prognosis and response to cancer immunotherapy. Results: We found that Siglec15 was specifically overexpressed in the TME of various cancers. We hypothesize that Siglec15 designs a non-inflamed TME in BLCA based on the evidence that Siglec15 negatively correlated with immunomodulators, TIICs, cancer immunity cycles, immune checkpoints, and T cell inflamed score. Bladder cancer with high Siglec15 expression was not sensitive to cancer immunotherapy, but exhibited a higher incidence of hyperprogression. High Siglec15 levels indicated a luminal subtype of BLCA characterized by lower immune infiltration, lower response to cancer immunotherapy and neoadjuvant chemotherapy, but higher response to anti-angiogenic therapy and targeted therapies such as blocking Siglec15, ?-catenin, PPAR-?, and FGFR3 pathways. Notably, a combination of anti-Siglec15 and cancer immunotherapy may be a more effective strategy than monotherapy. IRS can accurately predict the prognosis and response to cancer immunotherapy. Conclusions: Anti-Siglec15 immunotherapy might be suitable for BLCA treatment as Siglec15 correlates with a non-inflamed TME in BLCA. Siglec15 could also predict the molecular subtype and the response to several treatment options.

SUBMITTER: Hu J

PROVIDER: S-EPMC7847675 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature

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Siglec15 shapes a non-inflamed tumor microenvironment and predicts the molecular subtype in bladder cancer.

Hu Jiao J Yu Anze A Othmane Belaydi B Qiu Dongxu D Li Huihuang H Li Chao C Liu Peihua P Ren Wenbiao W Chen Minfeng M Gong Guanghui G Guo Xi X Zhang Huihui H Chen Jinbo J Zu Xiongbing X

Theranostics 20210101 7

<b>Rationale:</b> Siglec15 is an emerging target for normalization cancer immunotherapy. However, pan-cancer anti-Siglec15 treatment is not yet validated and the potential role of Siglec15 in bladder cancer (BLCA) remains elusive. <b>Methods:</b> We comprehensively evaluated the expression pattern and immunological role of Siglec15 using pan-cancer analysis based on RNA sequencing data obtained from The Cancer Genome Atlas. We then systematically correlated Siglec15 with immunological characteri ...[more]

PMID: 33537076

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Project description:IntroductionMethylenetetrahydrofolate dehydrogenase 2 (MTHFD2), whose aberrant expression is common in cancers, has recently been identified as a potential regulator of immune response. However, its immune-related role in bladder cancer (BLCA) and its association with immunotherapy efficacy remain unclear.MethodsRNA sequencing data from The Cancer Genome Atlas (TCGA) was applied to analyze the immunological roles and prognostic value of MTHFD2 in pan-cancers. The association of MTHFD2 with several immunological features of tumor microenvironment (TME), including cancer-immunity cycle, immune cells infiltration, immune checkpoints expression, and T cell inflamed score was analyzed in TCGA-BLCA cohort. The predictors of cancer treatments effectiveness, including the expression and mutation of certain genes, molecular subtypes, and several signatures were evaluated as well. These results were validated by another independent cohort (GSE48075). Finally, the predictive value of MTHFD2 for TME and immunotherapy efficacy were validated using immunohistochemistry assay and RNA sequencing data from IMvigor210 cohort, respectively.ResultsMTHFD2 was found to be positively associated with several immunological features of an inflamed tumor microenvironment (TME) in various cancers and could predict BLCA patients' prognosis. In BLCA, high expression of MTHFD2 was observed to be positively related with the cancer-immunity cycle, the infiltration of several immune cells, and the expression of immunoregulators and T-cell inflamed scores, indicating a positive correlation with the inflamed TME. Moreover, patients with high MTHFD2 expression were more likely to be basal-like subtypes and respond to BLCA treatments, including immunotherapy, chemotherapy, and target therapy. The clinical data of the IMvigor210 cohort confirmed the higher response rates and better survival benefits of immunotherapy in high-MTHFD2-expression patients.ConclusionCollectively, high MTHFD2 predicts an inflamed TME, a basal-like subtype, and a better response to various therapeutic strategies, especially the ICB therapy, in bladder cancer.

Project description:Background Thioesterase superfamily member 6 (THEM6) has been implicated in the development and progression of various cancers. However, prior research emphasized on its regulatory role merely, we aim to investigate the effect of THEM6 gene on the immunological role and its relationship with molecular subtype in bladder cancer (BLCA). Methods Through pan-cancer analysis, we explored the THEM6 expression pattern and immunological role using The Cancer Genome Atlas (TCGA) database. In addition, we performed a correlation of THEM6 and its immunological functions, including immunomodulators, immune checkpoints, cancer immunity cycles, T cell inflamed score, and tumor-infiltrating immune cells in the BLCA tumor microenvironment (TME) based on TCGA and BLCA microarray cohort from Xiangya Hospital. We also assessed the accuracy of THEM6 in predicting the molecular subtype and its response to different interventions in BLCA. Finally, we computed and validated a prediction model established by THEM6-related different expressed immune-related genes that might help in BLCA prognosis. Results THEM6 led to immunosuppression in BLCA TME. Furthermore, there was a downregulation in the immunological functions. Besides, THEM6 could effectively distinguish BLCA molecular subtypes, and THEM6 low expression implied basal subtype that was more effective to several interventions, such as immune checkpoint blockade (ICB) therapies, neoadjuvant chemotherapy, and radiotherapy. While THEM6 high expression indicated luminal subtype, hyperprogression and better response to targeted therapies, such as blocking THEM6 and several immune-inhibited oncogenic pathways. Conclusions THEM6 may be with potential immune-modulating properties and may become a potential new immunotherapy target for BLCA. THEM6 could accurately predict the molecular subtype of BLCA, which was helpful for guiding the treatment. Simultaneously, the prediction model may exhibit an excellent predictive value in patients with BLCA.

Project description:Background: Epigenetic dysregulation via aberrant DNA methylation has gradually become recognized as an efficacious signature for predicting tumor prognosis and response to therapeutic targets. However, reliable DNA methylation biomarkers describing tumorigenesis remain to be comprehensively explored regarding their prognostic and therapeutic potential in breast cancer (BC). Methods: Whole-genome methylation datasets integrated from the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) database were profiled (n = 1,268). A three-stage selection procedure (discovery, training, and external validation) was utilized to screen out the prominent biomarkers and establish a robust risk score from more than 300,000 CpG sites after quality control, rigorous filtering, and reducing dimension. Moreover, gene set enrichment analyses guided us to systematically correlate this epigenetic risk score with immunological characteristics, including immunomodulators, anti-cancer immunity cycle, immune checkpoints, tumor-infiltrating immune cells and a series of signatures upon modulating components within BC tumor microenvironment (TME). Multi-omics data analyses were performed to decipher specific genomic alterations in low- and high-risk patients. Additionally, we also analyzed the role of risk score in predicting response to several treatment options. Results: A 10-CpG-based prognostic signature which could significantly and independently categorize BC patients into distinct prognoses was established and sufficiently validated. And we hypothesize that this signature designs a non-inflamed TME in BC based on the evidence that the derived risk score is negatively correlated with tumor-associated infiltrating immune cells, anti-cancer immunity cycle, immune checkpoints, immune cytolytic activity, T cell inflamed score, immunophenoscore, and the vast majority of immunomodulators. The identified high-risk patients were characterized by upregulation of immune inhibited oncogenic pathways, higher TP53 mutation and copy number burden, but lower response to cancer immunotherapy and chemotherapy. Conclusion: Our work highlights the complementary roles of 10-CpG-based signature in estimating overall survival in BC patients, shedding new light on investigating failed events concerning immunotherapy at present.

Project description:BackgroundSUMOylation is an important component of post-translational protein modifications (PTMs), and bladder cancer (BCa) is the ninth most common cancer around the world. But the comprehensive role of SUMOylation in shaping tumor microenvironment (TME) and influencing tumor clinicopathological features and also the prognosis of patients remains unclear.MethodsUsing the data downloaded from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO), we comprehensively evaluated the SUMOylation patterns of 570 bladder cancer samples, and systematically correlated these SUMOylation patterns with TME immune cell infiltrating characteristics. The SUMO score was constructed to quantify SUMOylation patterns of individuals using principal component analysis (PCA) algorithms.ResultsTwo distinct SUMOylation patterns and gene clusters were finally determined. Significant differences in the prognosis of patients were found among two different SUMOylation patterns and gene clusters, so were in the mRNA transcriptome and the landscape of TME immune cell infiltration. We also established a set of scoring system named SUMO score to quantify the SUMOylation pattern of individuals with BCa, which was discovered to be tightly connected with tumor clinicopathological characteristics and could predict the prognosis of patients with BCa. Moreover, SUMO score was a considerable predictive indicator for the survival outcome independent of tumor mutation burden (TMB) and low SUMO score was related to better response to immunotherapy using PD-1 blockade. We also found that there existed a significant relationship between sensitivity to commonly used chemotherapy drugs and SUMO score. Finally, a nomograph based on five features, namely, SUMO score, age, gender, T category, and M category was constructed to predict the survival probability of patients with BCa in 1, 3, and 5 years, respectively.ConclusionsOur work demonstrated and overviewed the complicated regulation mechanisms of SUMOylation in bladder cancer, and better understanding and evaluating SUMOylation patterns could be helpful in guiding clinical therapeutic strategy and improving the prognosis of patients with BCa.

Dataset Information

Siglec15 shapes a non-inflamed tumor microenvironment and predicts the molecular subtype in bladder cancer.

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Siglec15 shapes a non-inflamed tumor microenvironment and predicts the molecular subtype in bladder cancer.

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