Inflammatory cancer-associated fibroblasts (iCAFs) are closely related to progression, anticancer therapeutic resistance, and poor prognosis of bladder cancer (BCa). However, the functional role of iCAFs in BCa has been poorly studied. In our study, two BCa scRNA-seq datasets (GSE130001 and GSE146137) were obtained and integrated by the Seurat pipeline. Based on reported markers (COL1A1 and PDGFRA), iCAFs were identified and the related signature of 278 markers was developed. Following unsupervised consensus clustering, two molecular subtypes of TCGA-BLCA were identified and characterized by distinct dysregulated cancer hallmarks, immunological tumor microenvironments, prognoses, responses to chemotherapy/immunotherapy, and stemness. Subsequently, the robustness of the signature-based clustering, in terms of prognosis and therapeutic response prediction, was validated in a GEO-meta cohort with seven independent GEO datasets of 519 BCa patients, and three immune checkpoint inhibitor (ICI)-treated cohorts. Considering the heterogeneity, re-clustering of iCAFs was performed and a subpopulation, named “LOXL2+ iCAFs”, was identified. Co-culture CM derived from LOXL2 overexpression/silencing CAFs with T24 cells revealed that overexpression of LOXL2 in CAFs promoted while silencing LOXL2 inhibited the proliferation, migration, and invasion of T24 cells through IL32. Moreover, the positive correlation between LOXL2 and CD206, an M2 macrophage polarization marker, has been observed and validated. Collectively, integrated single-cell and bulk RNA sequencing analyses revealed an iCAF-related signature that can predict prognosis and response to immunotherapy for BCa. Additionally, the hub gene LOXL2 may serve as a promising target for BCa treatment.

Mesenchymal stem cells (MSCs) and cancer stem cells (CSCs) maintain bladder cancer (BCa) stemness and facilitate the progression, metastasis, drug resistance, and prognosis. Therefore, we aimed to decipher the communication networks, develop a stemness-related signature (Stem. Sig.), and identify a potential therapeutic target. BCa single-cell RNA-seq datasets (GSE130001 and GSE146137) were used to identify MSCs and CSCs. Pseudotime analysis was performed by Monocle. Stem. Sig. was developed by analyzing the communication network and gene regulatory network (GRN) that were decoded by NicheNet and SCENIC, respectively. The molecular features of the Stem. Sig. were evaluated in TCGA-BLCA and two PD-(L)1 treated datasets (IMvigor210 and Rose2021UC). A prognostic model was constructed based on a 101 machine-learning framework. Functional assays were performed to evaluate the stem traits of the hub gene. Three subpopulations of MSCs and CSCs were first identified. Based on the communication network, the activated regulons were found by GRN and regarded as the Stem. Sig. Following unsupervised clustering, two molecular subclusters were identified and demonstrated distinct cancer stemness, prognosis, immunological TME, and response to immunotherapy. Two PD-(L)1 treated cohorts further validated the performance of Stem. Sig. in prognosis and immunotherapeutic response prediction. A prognostic model was then developed, and a high-risk score indicated a poor prognosis. Finally, the hub gene SLC2A3 was found exclusively upregulated in extracellular matrix-related CSCs, predicting prognosis, and shaping an immunosuppressive tumor microenvironment. Functional assays uncovered the stem traits of SLC2A3 in BCa by tumorsphere formation and western blotting. The Stem. Sig. derived from MSCs and CSCs can predict prognosis and response to immunotherapy for BCa. Besides, SLC2A3 may serve as a promising stemness target facilitating cancer effective management.

Transcription factor binding to IGHM enhancer 3 (TFE3) break-apart fluorescence in situ hybridization (FISH) is the gold standard for the diagnosis of Xp11.2 translocation renal cell carcinoma (tRCC). However, FISH is costly and not accessible in all laboratories. We aimed to develop a surrogate immunohistochemical panel to recognize Xp11.2 tRCC. We retrospectively enrolled 84 patients who underwent surgery for renal lesions from September 2017 to August 2022. Both immunohistochemistry and FISH analysis were performed on their specimens. The sensitivity, specificity, and accuracy of each immunohistochemical marker and combinatorial immunohistochemical panels were calculated. A total of 17 patients were diagnosed with Xp11.2 tRCC using FISH. In patients with Xp11.2 tRCC, 77% (13/17), 100% (17/17), 88% (15/17), 88% (15/17), 100% (17/17), and 71% (12/17) were tested positive for AE1/AE3, CD10, P504S, PAX8, TFE3, and vimentin, respectively, while 94% (16/17) were tested negative for cytokeratin 7 (CK7). The immunohistochemical panel combining negative CK7, positive CD10, positive P504S, and positive TFE3 exhibited a sensitivity of 0.824, a specificity of 0.672, and a highest accuracy of 0.702. The immunohistochemical panel combining negative CK7, positive CD10, positive P504S, and positive TFE3 was a potentially useful tool for the diagnosis of Xp11.2 tRCC.