A novel signature constructed by differential genes of muscle-invasive and non-muscle-invasive bladder cancer for the prediction of prognosis in bladder cancer

Prediction of immunotherapy response of bladder cancer with a pyroptosis-related signature indicating tumor immune microenvironment

Background

Although prognostic models based on pyroptosis-related genes (PRGs) have been constructed in bladder cancer (BLCA), the comprehensive impact of these genes on tumor microenvironment (TME) and immunotherapeutic response has yet to be investigated.

Methods

Based on expression profiles of 52 PRGs, we utilized the unsupervised clustering algorithm to identify PRGs subtypes and ssGSEA to quantify immune cells and hallmark pathways. Moreover, we screened feature genes of distinct PRGs subtypes and validated the associations with immune infiltrations in tissue using the multiplex immunofluorescence. Univariate, LASSO, and multivariate Cox regression analyses were employed to construct the scoring scheme.

Results

Four PRGs clusters were identified, samples in cluster C1 were infiltrated with more immune cells than those in others, implying a favorable response to immunotherapy. While the cluster C2, which shows an extremely low level of most immune cells, do not respond to immunotherapy. CXCL9/CXCL10 and SPINK1/DHSR2 were identified as feature genes of cluster C1 and C2, and the specimen with high CXCL9/CXCL10 was characterized by more CD8 + T cells, macrophages and less Tregs. Based on differentially expressed genes (DEGs) among PRGs subtypes, a predictive model (termed as PRGs score) including five genes (CACNA1D, PTK2B, APOL6, CDK6, ANXA2) was built. Survival probability of patients with low-PRGs score was significantly higher than those with high-PRGs score. Moreover, patients with low-PRGs score were more likely to benefit from anti-PD1/PD-L1 regimens.

Conclusion

PRGs are closely associated with TME and oncogenic pathways. PRGs score is a promising indicator for predicting clinical outcome and immunotherapy response.

Identification of Crotonylation Metabolism Signature Predicting Overall Survival for Clear Cell Renal Cell Carcinoma

Background

Immunotherapy shows promise in treating cancer by leveraging the immune system to combat cancer cells. However, the influence of crotonylation metabolism on the prognosis and tumor environment in ccRCC patients is not fully understood.

Methods

We conducted various systematic analyses, including prognosis and cluster analyses, to investigate the role of KAT2A in immunotherapy. We used qRT-PCR to compare KAT2A expression in cancer and adjacent tissues and among different cell lines. Additionally, we employed Cell Counting Kit-8, wound healing, and Transwell chamber assays to assess changes in the proliferative and metastatic ability of A498 and 786-O cells.

Results

We identified three clusters related to crotonylation metabolism, each with distinct prognosis and immune characteristics in ccRCC. We categorized CT1 as immune-inflamed, CT2 as immune-excluded, and CR3 as immune-desert. A new system, CRS, emerged as an effective predictor of patient outcomes with differing immune characteristics. Moreover, qRT-PCR revealed elevated KAT2A levels in ccRCC tissues and cell lines. KAT2A was found to promote ccRCC and correlate significantly with immunosuppressive elements and checkpoints. Reducing KAT2A expression hindered ccRCC cell growth and metastasis.

Conclusion

Our study highlights the critical role of crotonylation metabolism in cancer development and progression, particularly its link to poor prognosis. CRS proves to be an accurate predictor of patient outcomes and immune features in ccRCC. KAT2A shows strong associations with clinical factors and the immunosuppressive environment, suggesting potential for innovative immunotherapies in ccRCC treatment.