BackgroundT-cell–T-cell interactions play important roles in the regulation of T-cells’ cytotoxic function, further impacting the anti-tumor efficacy of immunotherapy. There is a lack of comprehensive studies of T-cell types in bladder urothelial carcinoma (BLCA) and T-cell-related signatures for predicting prognosis and monitoring immunotherapy efficacy.MethodsMore than 3,400 BLCA patients were collected and used in the present study. The ssGSEA algorithm was applied to calculate the infiltration level of 19 T-cell types. A cell pair algorithm was applied to construct a T-cell-related prognostic index (TCRPI). Survival analysis was performed to measure the survival difference across TCRPI-risk groups. Spearman’s correlation analysis was used for relevance assessment. The Wilcox test was used to measure the expression level difference.ResultsNineteen T-cell types were collected; 171 T-cell pairs (TCPs) were established, of which 26 were picked out by the least absolute shrinkage and selection operator (LASSO) analysis. Based on these TCPs, the TCRPI was constructed and validated to play crucial roles in survival stratification and the dynamic monitoring of immunotherapy effects. We also explored several candidate drugs targeting TCRPI. A composite TCRPI and clinical prognostic index (CTCPI) was then constructed, which achieved a more accurate estimation of BLCA’s survival and was therefore a better choice for prognosis prediction in BLCA.ConclusionsAll in all, we constructed and validated TCRPI based on cell pair algorithms in this study, which might put forward some new insights to increase the survival estimation and clinical response to immune therapy for individual BLCA patients and contribute to the personalized precision immunotherapy strategy of BLCA.

BackgroundMounting evidence has demonstrated that an imbalance in liquid–liquid phase separation (LLPS) can induce alteration in the spatiotemporal coordination of biomolecular condensates, which plays a role in carcinogenesis and cachexia. However, the role of LLPS in the occurrence and progression of bladder cancer (BLCA) remains to be elucidated. Identifying the role of LLPS in carcinogenesis may aid in cancer therapeutics.MethodsA total of 1,351 BLCA samples from six cohorts were retrieved from publicly available databases like The Cancer Genome Atlas, Gene Expression Omnibus, and ArrayExpress. The samples were divided into three distinct clusters, and their multi-dimensional heterogeneities were explored. The LLPS patterns of all patients were determined based on the LLPS-related risk score (LLPSRS), and its multifaceted landscape was depicted and experimentally validated at the multi-omics level. Finally, a cytotoxicity-related and LLPSRS-based classifier was established to predict the patient’s response to immune checkpoint blockade (ICB) treatment.ResultsThree LLPS-related subtypes were identified and validated. The differences in prognosis, tumor microenvironment (TME) features, cancer hallmarks, and certain signatures of the three LLPS-related subtypes were validated. LLPSRS was calculated, which could be used as a prognostic biomarker. A close correlation was observed between clinicopathological features, genomic variations, biological mechanisms, immune infiltration in TME, chemosensitivity, and LLPSRS. Furthermore, our classifier could effectively predict immunotherapy response in patients with BLCA.ConclusionsOur study identified a novel categorization of BLCA patients based on LLPS. The LLPSRS could predict the prognosis of patients and aid in designing personalized medicine. Further, our binary classifier could effectively predict patients’ sensitivity to immunotherapy.

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Purpose In China, many patients with hepatocellular carcinoma (HCC) are diagnosed at an advanced stage. Several studies have shown that triple therapy [transarterial chemoembolization (TACE) combined with tyrosine kinase inhibitors (TKIs) and immune checkpoint inhibitors (ICIs)] is beneficial for patient survival. In this study, we aimed to evaluate the efficacy of triple therapy (TACE + TKIs + ICIs) for unresectable HCC (uHCC) and the conversion rate of surgical resection (SR). The primary endpoints were objective response rate (ORR) and disease control rate (DCR) based on the modified Response Evaluation Criteria in Solid Tumors (mRECIST) and RECIST v1.1 and adverse events (AEs), while the secondary endpoint was the conversion rate of patients with uHCC treated with triple therapy followed by SR. Patients and Methods Forty-nine patients with uHCC who received triple therapy at Fujian Provincial Hospital between January 2020 and June 2022 were retrospectively included. The treatment efficacy, SR conversion rate, and associated AEs were recorded. Results Among the 49 patients enrolled, the ORRs assessed by mRECIST and RECIST v1.1 were 57.1% (24/42) and 14.3% (6/42), respectively, and the DCRs were 92.9% (39/42) and 88.1% (37/42), respectively. Seventeen (34.7%) patients met the criteria for resectable HCC and underwent resection. The median interval between the start of triple therapy and resection was 113.5 days (range 94.75 to 182 d), and the median number of TACE was 2 (range 1 to 2.5). The patients did not achieve median overall survival or median progression-free survival. Treatment-related AEs occurred in 48 (98%) patients, and 18 (36.7%) patients had grade ≥3 AEs. Conclusion Triple combination therapy resulted in a relatively high ORR and conversion resection rate following uHCC treatment.