Dataset Information

Tumor immune microenvironment-based classifications of bladder cancer for enhancing the response rate of immunotherapy.

ABSTRACT: Immunotherapy is a potential way to save the lives of patients with bladder cancer, but it only benefits approximately 20% of them. A total of 4,028 bladder cancer patients were collected for this study. Unsupervised non-negative matrix factorization and the nearest template prediction algorithms were employed for the classification. We identified the immune and non-immune classes from The Cancer Genome Atlas Bladder Urothelial Carcinoma (TCGA-BLCA) training cohort. The 150 most differentially expressed genes between these two classes were extracted, and the classification reappeared in 20 validation cohorts. For the activated and exhausted subgroups, a stromal activation signature was assessed by the NTP algorithm. Patients in the immune class showed highly enriched signatures of immunocytes, while the exhausted subgroup also exhibited activated transforming growth factor (TGF)-?1, and cancer-associated extracellular matrix signatures. Patients in the immune-activated subgroup showed a lower genetic alteration and better overall survival. Anti-PD-1/PD-L1 immunotherapy was more beneficial for the immune-activated subgroup, while immune checkpoint blockade therapy plus a TGF-? inhibitor or an EP300 inhibitor might achieve greater efficacy for patients in the immune-exhausted subgroup. Novel immune molecular classifier was identified for the innovative immunotherapy of patients with bladder cancer.

SUBMITTER: Meng J

PROVIDER: S-EPMC7900642 | biostudies-literature | 2021 Mar

REPOSITORIES: biostudies-literature

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Tumor immune microenvironment-based classifications of bladder cancer for enhancing the response rate of immunotherapy.

Meng Jialin J Lu Xiaofan X Zhou Yujie Y Zhang Meng M Ge Qintao Q Zhou Jun J Hao Zongyao Z Gao Shenglin S Yan Fangrong F Liang Chaozhao C

Molecular therapy oncolytics 20210204

Immunotherapy is a potential way to save the lives of patients with bladder cancer, but it only benefits approximately 20% of them. A total of 4,028 bladder cancer patients were collected for this study. Unsupervised non-negative matrix factorization and the nearest template prediction algorithms were employed for the classification. We identified the immune and non-immune classes from The Cancer Genome Atlas Bladder Urothelial Carcinoma (TCGA-BLCA) training cohort. The 150 most differentially e ...[more]

PMID: 33665361

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Project description:BACKGROUND:The efficacy of PD-(L)1 blockade depends on the composition of the tumor immune microenvironment (TIME) and is generally higher in tumors with pre-existing cytotoxic T cells (CTL) than in those with low CTL numbers. Nonetheless, a significant proportion of patients with pre-existing immunity fail to respond, indicating a therapeutic potential for combining PD-(L)1 blockade with additional immunomodulatory agents in both CTL-high and -low immune phenotypes. Here, we evaluated domatinostat (4SC-202), a class I-selective histone deacetylase (HDAC) inhibitor, for its effect on the TIME and its antitumoral efficacy using syngeneic mouse models with CTL-high or CTL-low tumors. METHODS:Domatinostat was evaluated in PD-1 blockade-insensitive CTL-low (CT26) and CTL-high (C38) syngeneic models alone and in combination with different immune-inhibitory and -stimulatory approaches. Effects on the immunophenotype were assessed via flow cytometry and RNA-seq analyses. The changes in RNA-seq-based immune signatures determined in a murine setting were investigated in patient samples from the first-dose cohort of the SENSITIZE trial (NCT03278665) evaluating domatinostat combined with pembrolizumab in advanced-stage melanoma patients refractory/nonresponding to PD-1 blockade. RESULTS:Domatinostat increased the expression of antigen-presenting machinery (APM) genes and MHC class I and II molecules, along with CTL infiltration, in tumors of both immune phenotypes. In combination with PD-(L)1 blockade, domatinostat augmented antitumor effects substantially above the effects of single-agent therapies, displaying greater benefit in tumors with pre-existing CTLs. In this setting, the combination of domatinostat with agonistic anti-4-1BB or both PD-1 and LAG3 blockade further increased the antitumor efficacy. In CTL-low tumors, domatinostat enhanced the expression of genes known to reinforce immune responses against tumors. Specifically, domatinostat increased the expression of Ifng and genes associated with responses to pembrolizumab and nivolumab. Clinically, these findings were confirmed in patients with advanced melanoma treated with domatinostat for 14?days, who demonstrated elevated expression of APM and MHC genes, the IFNG gene, and the IFN-? and pembrolizumab response signatures in individual tumor samples. CONCLUSION:In summary, these data suggest a promising potential of domatinostat in combination with immunotherapy to improve the outcome of refractory cancer patients.

Project description:BackgroundAberrant DNA methylation is a major characteristic of cancer genomes. It remains unclear which biological processes determine epigenetic reprogramming and how these processes influence the variants in the cancer methylome, which can further impact cancer phenotypes.MethodsWe performed pairwise permutations of 381,900 loci in 569 paired DNA methylation profiles of cancer tissue and matched normal tissue from The Cancer Genome Atlas (TCGA) and defined conserved differentially methylated positions (DMPs) based on the resulting null distribution. Then, we derived independent methylation signatures from 2,465 cancer-only methylation profiles from the TCGA and 241 cell line-based methylation profiles from the Genomics of Drug Sensitivity in Cancer (GDSC) cohort using nonnegative matrix factorization (NMF). We correlated DNA methylation signatures with various clinical and biological features, including age, survival, cancer stage, tumor immune microenvironment factors, and immunotherapy response. We inferred the determinant genes of these methylation signatures by integrating genomic and transcriptomic data and evaluated the impact of these signatures on cancer phenotypes in independent bulk and single-cell RNA/methylome cohorts.ResultsWe identified 7,364 differentially methylated positions (2,969 Hyper-DMPs and 4,395 Hypo-DMPs) in nine cancer types from the TCGA. We subsequently retrieved three highly conserved, independent methylation signatures (Hyper-MS1, Hypo-MS1, and Hypo-MS4) from cancer tissues and cell lines based on these Hyper and Hypo-DMPs. Our data suggested that Hypo-MS4 activity predicts poor survival and is associated with immunotherapy response and distant tumor metastasis, and Hypo-MS4 activity is related to TP53 mutation and FOXA1 binding specificity. In addition, we demonstrated a correlation between the activities of Hypo-MS4 in cancer cells and the fractions of regulatory CD4 + T cells with the expression levels of immunological genes in the tumor immune microenvironment.ConclusionsOur findings demonstrated that the methylation signatures of distinct biological processes are associated with immune activity in the cancer microenvironment and predict immunotherapy response.

Project description:Background: Bladder cancer (BC) is a leading cause of death from malignancy, with significant heterogeneity in the immunotherapeutic responsiveness of advanced status. Pyroptosis, a newly discovered inflammatory programmed cell death, is confirmed to play an indispensable role in tumorigenesis and anti-tumor activity. However, the effect of pyroptosis on the tumor-immune landscape remodeling and immunotherapy in BC remains elusive. Methods: We comprehensively evaluated the mRNA expression and genomic alterations of 33 pyroptosis-related genes (PRGs) in BC and evaluated the patterns of pyroptosis in publicly available BC datasets. An unsupervised clustering method was used to classify patients into distinct patterns. Then, we established a pyroptosis-related signature score (PS-score) model to quantify the pyroptosis-related patterns of individual BC patients using principal component analysis. Furthermore, we correlated the patterns with the immune landscape and response efficacy of immunotherapy. Results: Two pyroptosis-related patterns were identified in BC, and distinct patterns showed various immune characteristics. Patterns with a high expression level of PRGs exhibited a survival advantage and showed higher infiltration of cytotoxic lymphocytes. Tumors with a low PS-score were characterized by high tumor-infiltrating lymphocytes and considered "hot." Further analysis revealed that the PS-score was an independent prognostic factor and could predict the response to immunotherapy for patients with advanced BC. We found a significant positive association between AHNAK2, AHNAK nucleoprotein 2, expression, and PS-score. Functional assays showed that AHNAK2 knockdown was correlated with attenuated invasive ability. Conclusion: This work comprehensively demonstrated the potential function of pyroptosis-related patterns in the bladder tumor-immune landscape and identified their therapeutic liability in immunotherapy. Our study enhanced our understanding of the immune landscape and provided a new approach toward more effective immunotherapy strategies.

Project description:Background: The efficiency of immune checkpoint inhibitors (ICIs) in bladder cancer (BLCA) treatment has been widely validated; however, the tumor response to ICIs was generally low. It is critical and urgent to find biomarkers that can predict tumor response to ICIs. The tumor microenvironment (TME), which may play important roles to either dampen or enhance immune responses, has been widely concerned. Methods: The cancer genome atlas BLCA (TCGA-BLCA) cohort (n = 400) was used in this study. Based on the proportions of 22 types of immune cells calculated by CIBERSORT, TME was classified by K-means Clustering and differentially expressed genes (DEGs) were determined. Based on DEGs, patients were classified into three groups, and cluster signature genes were identified after reducing redundant genes. Then TMEscore was calculated based on cluster signature genes, and the samples were classified to two subtypes. We performed somatic mutation and copy number variation analysis to identify the genetic characteristics of the two subtypes. Correlation analysis was performed to explore the correlation between TMEscore and the tumor response to ICIs as well as the prognosis of BLCA. Results: According to the proportions of immune cells, two TME clusters were determined, and 1,144 DEGs and 138 cluster signature genes were identified. Based on cluster signature genes, samples were classified into TMEscore-high (n = 199) and TMEscore-low (n = 201) subtypes. Survival analysis showed patients with TMEscore-high phenotype had better prognosis. Among the 45 differentially expressed micro-RNAs (miRNAs) and 1,033 differentially expressed messenger RNAs (mRNAs) between the two subtypes, 16 miRNAs and 287 mRNAs had statistically significant impact on the prognosis of BLCA. Furthermore, there were 94 genes with significant differences between the two subtypes, and they were enriched in RTK-RAS, NOTCH, WNT, Hippo, and PI3K pathways. The Tumor Immune Dysfunction and Exclusion (TIDE) score of TMEscore-high BLCA was statistically lower than that of TMEscore-low BLCA. Receiver operating characteristic (ROC) curve analysis showed that the area under the curve (AUC) of TMEscore and tumor mutation burden (TMB) is 0.6918 and 0.5374, respectively. Conclusion: We developed a method to classify BLCA patients to two TME subtypes, TMEscore-high and TMEscore-low, and we found TMEscore-high subtype of BLCA had a good prognosis and a good response to ICIs.

Dataset Information

Tumor immune microenvironment-based classifications of bladder cancer for enhancing the response rate of immunotherapy.

Publications

Tumor immune microenvironment-based classifications of bladder cancer for enhancing the response rate of immunotherapy.

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