The prognostic value of six survival-related genes in bladder cancer

Transcriptome-Based Network Analysis Related to Histone Deacetylase Genes and Identified EMP1 as a Potential Biomarker for Prognosis in Bladder Cancer

BACKGROUND

Abnormal expression and function of histone deacetylases (HDACs) are closely associated with the development of bladder cancer (BCa). Systematic elucidation of the role of HDACs in BCa is expected to improve BCa prognosis and treatment strategies.

METHODS

We explored the correlation and expression patterns of HDAC family genes in BCa. Consensus clustering was employed to categorize BCa into subtypes based on HDAC expression profiles. Differential analysis, pathway enrichment analysis, and drug responsiveness evaluation were conducted to characterize HDAC subtypes. Then, a prognostic model based on HDAC cluster related genes was constructed and validated across multiple cohorts.

RESULTS

We identified distinct HDAC expression patterns and correlations with immune cell infiltration and enrichment of pathways in cancer, highlighting their role in BCa. Consensus clustering revealed 2 HDAC gene subtypes. Gene cluster 1 showed worse survival, higher clinical stage, and lower immune cell infiltration compared to gene cluster 2. Additionally, pathway enrichment analysis revealed differences in tumor-promoting pathways between the clusters. Moreover, gene cluster 1 exhibited higher resistance to Rho kinase inhibitor drugs. Multi-omic analysis unveiled unique mutation and CNV profiles between the clusters, indicating distinct molecular features. Furthermore, a HDAC gene-related prognostic model demonstrated robust predictive accuracy and identified EMP1 as a key prognostic gene associated with poor survival and enriched metastatic pathways.

CONCLUSION

Our study provides comprehensive insights into the landscape of HDACs in BCa, elucidating their roles in tumor heterogeneity, immune modulation, drug responsiveness, and molecular features. EMP1 is a potential therapeutic target and prognostic marker for BCa.

Microbiota-induced inflammatory responses in bladder tumors promote epithelial-mesenchymal transition and enhanced immune infiltration

The intratumoral microbiota can modulate the tumor immune microenvironment (TIME); however, the underlying mechanism by which intratumoral microbiota influences the TIME in urothelial carcinoma of the bladder (UCB) remains unclear. To address this, we collected samples from 402 patients with UCB, including paired host transcriptome and tumor microbiome data, from The Cancer Genome Atlas (TCGA). We found that the intratumoral microbiome profiles were significantly correlated with the expression pattern of epithelial-mesenchymal transition (EMT)-related genes. Furthermore, we detected that the genera Lachnoclostridium and Sutterella in tumors could indirectly promote the EMT program by inducing an inflammatory response. Moreover, the inflammatory response induced by these two intratumoral bacteria further enhanced intratumoral immune infiltration, affecting patient survival and response to immunotherapy. In addition, an independent immunotherapy cohort of 348 patients with bladder cancer was used to validate our results. Collectively, our study elucidates the potential mechanism by which the intratumoral microbiota influences the TIME of UCB and provides a new guiding strategy for the targeted therapy of UCB.NEW & NOTEWORTHY The intratumoral microbiota may mediate the bladder tumor inflammatory response, thereby promoting the epithelial-mesenchymal transition program and influencing tumor immune infiltration.

EMP1 correlated with cancer progression and immune characteristics in pan-cancer and ovarian cancer

This study examines the prognostic role and immunological relevance of EMP1 (epithelial membrane protein-1) in a pan-cancer analysis, with a focus on ovarian cancer. Utilizing data from TCGA, CCLE, and GTEx databases, we assessed EMP1 mRNA expression and its correlation with tumor progression, prognosis, and immune microenvironment across various cancers. Our results indicate that EMP1 expression is significantly associated with poor prognosis in multiple cancer types, including ovarian, bladder, testicular, pancreatic, breast, brain, and uveal melanoma. Immune-related analyses reveal a positive correlation between EMP1 and immune cell infiltration, particularly neutrophils, macrophages, and dendritic cells, as well as high expression of immune checkpoint such as CD274, HAVCR2, IL10, PDCD1LG2, and TGFB1 in most tumors. In vivo experiments confirm that EMP1 promotes ovarian cancer cell proliferation, metastasis, and invasion. In conclusion, EMP1 emerges as a potential prognostic biomarker and therapeutic target in various cancers, particularly ovarian cancer, due to its influence on tumor progression and immune cell dynamics. Further research is warranted to elucidate the precise mechanisms of EMP1 in cancer biology and to translate these findings into clinical applications.

Risk Classification of Bladder Cancer by Gene Expression and Molecular Subtype

This study evaluated a panel including the molecular taxonomy subtype and the expression of 27 genes as a diagnostic tool to stratify bladder cancer patients at risk of aggressive behavior, using a well-characterized series of non-muscle invasive bladder cancer (NMIBC) as well as muscle-invasive bladder cancer (MIBC). The study was conducted using the novel NanoString nCounter gene expression analysis. This technology allowed us to identify the molecular subtype and to analyze the gene expression of 27 bladder-cancer-related genes selected through a recent literature search. The differential gene expression was correlated with clinicopathological variables, such as the molecular subtypes (luminal, basal, null/double negative), histological subtype (conventional urothelial carcinoma, or carcinoma with variant histology), clinical subtype (NMIBC and MIBC), tumor stage category (Ta, T1, and T2–4), tumor grade, PD-L1 expression (high vs. low expression), and clinical risk categories (low, intermediate, high and very high). The multivariate analysis of the 19 genes significant for cancer-specific survival in our cohort study series identified TP53 (p = 0.0001), CCND1 (p = 0.0001), MKI67 (p < 0.0001), and molecular subtype (p = 0.005) as independent predictors. A scoring system based on the molecular subtype and the gene expression signature of TP53, CCND1, or MKI67 was used for risk assessment. A score ranging from 0 (best prognosis) to 7 (worst prognosis) was obtained and used to stratify our patients into two (low [score 0–2] vs. high [score 3–7], model A) or three (low [score 0–2] vs. intermediate [score 3–4] vs. high [score 5–7], model B) risk categories with different survival characteristics. Mean cancer-specific survival was longer (122 + 2.7 months) in low-risk than intermediate-risk (79.4 + 9.4 months) or high-risk (6.2 + 0.9 months) categories (p < 0.0001; model A); and was longer (122 + 2.7 months) in low-risk than high-risk (58 + 8.3 months) (p < 0.0001; model B). In conclusion, the molecular risk assessment model, as reported here, might be used better to select the appropriate management for patients with bladder cancer.

Integrated proteogenomic characterization of urothelial carcinoma of the bladder

Background

Urothelial carcinoma (UC) is the most common pathological type of bladder cancer, a malignant tumor. However, an integrated multi-omics analysis of the Chinese UC patient cohort is lacking.

Methods

We performed an integrated multi-omics analysis, including whole-exome sequencing, RNA-seq, proteomic, and phosphoproteomic analysis of 116 Chinese UC patients, comprising 45 non-muscle-invasive bladder cancer patients (NMIBCs) and 71 muscle-invasive bladder cancer patients (MIBCs).

Result

Proteogenomic integration analysis indicated that SND1 and CDK5 amplifications on chromosome 7q were associated with the activation of STAT3, which was relevant to tumor proliferation. Chromosome 5p gain in NMIBC patients was a high-risk factor, through modulating actin cytoskeleton implicating in tumor cells invasion. Phosphoproteomic analysis of tumors and morphologically normal human urothelium produced UC-associated activated kinases, including CDK1 and PRKDC. Proteomic analysis identified three groups, U-I, U-II, and U-III, reflecting distinct clinical prognosis and molecular signatures. Immune subtypes of UC tumors revealed a complex immune landscape and suggested the amplification of TRAF2 related to the increased expression of PD-L1. Additionally, increased GARS, related to subtype U-II, was validated to promote pentose phosphate pathway by inhibiting activities of PGK1 and PKM2.

Conclusions

This study provides a valuable resource for researchers and clinicians to further identify molecular pathogenesis and therapeutic opportunities in urothelial carcinoma of the bladder.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13045-022-01291-7.

An HDAC9-associated immune-related signature predicts bladder cancer prognosis

Background

The close relationship between histone deacetylase 9 (HDAC9) and immunity has attracted attention. We constructed an immune signature for HDAC9, a vital epigenetic modification, to predict the survival status and treatment benefits in bladder cancer (BC).

Methods

An exhaustive analysis of HDAC9 and immunology via the tumor and immune system interaction database (TISIDB) was performed, and an immune prognostic risk signature was developed based on genes enriched in the top five immune-related pathways under high HDAC9 status. Comprehensive analysis of survival curves and Cox regression were used to estimate the effectiveness of the risk signature. The relationship between immunological characteristics and the risk score was evaluated, and the mechanisms were also explored.

Results

In the TISIDB, HDAC9 was closely related to various immunological characteristics. The risk signature was obtained based on genes related to prognosis enriched in the top five immune-related pathways under high HDAC9 status. The survival rate of the high-risk BC patients was poor. The risk score was closely related to multiple immunological characteristics, drug sensitivity, immunotherapy benefits and biofunctions.

Conclusion

An immune-related prognostic signature established for HDAC9 expression status could independently predict the prognosis of BC patients. The use of this signature could help clinicians make personalized treatment decisions.

Accounting for B-cell Behavior and Sampling Bias Predicts Anti-PD-L1 Response in Bladder Cancer

Cancer immunotherapy is predominantly based on T cell-centric approaches. At the same time, the adaptive immune response in the tumor environment also includes clonally produced immunoglobulins and clonal effector/memory B cells that participate in antigen-specific decisions through their interactions with T cells. Here, we investigated the role of infiltrating B cells in bladder cancer via patient dataset analysis of intratumoral immunoglobulin repertoires. We showed that the IgG1/IgA ratio is a prognostic indicator for several subtypes of bladder cancer and for the whole IMVigor210 anti-PD-L1 immunotherapy study cohort. A high IgG1/IgA ratio associated with the prominence of a cytotoxic gene signature, T-cell receptor signaling, and IL21-mediated signaling. Immunoglobulin repertoire analysis indicated that effector B-cell function, rather than clonally produced antibodies, was involved in antitumor responses. From the T-cell side, we normalized a cytotoxic signature against the extent of immune cell infiltration to neutralize the artificial sampling-based variability in immune gene expression. Resulting metrics reflected proportion of cytotoxic cells among tumor-infiltrating immune cells and improved prediction of anti-PD-L1 responses. At the same time, the IgG1/IgA ratio remained an independent prognostic factor. Integration of the B-cell, natural killer cell, and T-cell signatures allowed for the most accurate prediction of anti-PD-L1 therapy responses. On the basis of these findings, we developed a predictor called PRedIctive MolecUlar Signature (PRIMUS), which outperformed PD-L1 expression scores and known gene signatures. Overall, PRIMUS allows for reliable identification of responders among patients with muscle-invasive urothelial carcinoma, including the subcohort with the low-infiltrated "desert" tumor phenotype.

A novel 6-gene signature derived from tumor-infiltrating T cells and neutrophils predicts survival of bladder urothelial carcinoma

Intratumoral immune cells were reported to be associated with prognosis of bladder urothelial carcinoma (BUC). However, the role of immune cells related genes in BUC prognosis is less well defined. In the study, we analyzed data retrieved from the Cancer Genome Atlas database and found higher neutrophils and lower T cells infiltration in BUC tumor tissues were significantly correlated with patients’ worse prognosis. Additionally, the expression levels of 164 genes were significantly correlated with T cells and neutrophils proportions. A Cox proportional-hazards model integrating 6 genes expression (EMP1, RASGRP4, HSPA1L, AHNAK, SLC1A6, and PRSS8) was identified. The 6-gene signature outperformed other clinical factors in risk prediction and was an independent prognostic factor for BUC. The findings were further conformed in three Gene Expression Omnibus datasets (n=331) and Jiangsu Province Hospital cohort (n = 46). Gene set enrichment analysis revealed that the model was highly involved in some immune-related pathways. A comprehensive nomogram combining the model and other clinical parameters was finally constructed to facilitate clinical application. In conclusion, a T cell and neutrophil-associated 6-gene prognostic model was identified for the survival prediction of BUC patients.

Construction and analysis of a ceRNA network and patterns of immune infiltration in bladder cancer

Background

Bladder cancer (BC) is the ninth most common malignant tumor, accounting for an estimate of 549,000 new BC cases and 200,000 BC-related deaths worldwide in 2018. The prognosis of BC has not substantially improved despite significant advances in the diagnosis and treatment of the disease.

Methods

The RNA sequencing (RNA-seq) data and clinical information of BC patients were downloaded from The Cancer Genome Atlas (TCGA) database. The Cell-type Identification By Estimating Relative Subsets Of RNA Transcripts (CIBERSORT) algorithm was used to assess immune infiltration. The survival analyses were performed using the selected components of a ceRNA network and selected immune cell types by least absolute shrinkage and selection operator (LASSO) Cox regression to calculate the risk score. The accuracy of prognosis prediction was determined by receiver operating characteristic (ROC) curves, survival curves, and nomograms. Finally, the correlation analysis was performed to investigate the relationships between the signature components of the ceRNA network and the immune cell signature.

Results

Two completed survival analyses included selected components of the ceRNA network (ELN, SREBF1, DSC2, TTLL7, DIP2C, SATB1, hsa-miR-20a-5p, and hsa-miR-29c-3p) and selected immune cell types (M0 macrophages, M2 macrophages, resting mast cells, and neutrophils). ROC curves, survival curves (all P values <0.05), nomograms, and calibration curves indicated that the accuracy of the two survival analyses was acceptable. Moreover, the correlations between TTLL7 and resting mast cells (R=0.24, P<0.001), DSC2 and resting mast cells (R=−0.23, P<0.001), ELN and resting mast cells (R=0.44, P<0.001), and hsa-miR-29c-3p and M0 macrophages (R=−0.29, P<0.001) were significant, indicating that interactions of these factors may play significant roles in the prognosis of BC.

Conclusions

TTLL7, DSC2, ELN, hsa-miR-29c-3p, resting mast cells, and M0 macrophages may play an important role in the development of BC. However, additional studies are needed to confirm this hypothesis.