Background: Chemokine (C-X-C motif) ligand 13 (CXCL13) was known as a selective chemotaxis for B cells, a product of follicular helper CD4⁺T cells (T_FH) and a contributor to tertiary lymphoid structures (TLS). Although secretion and function of CXCL13 produced by T_FH have been deeply explored, the immune function and prognostic significance of CXCL13 secreted by CD8⁺T cells still remain unrevealed. This study aims to investigate the clinical merit of CXCL13⁺CD8⁺T cells in clear cell renal cell carcinoma (ccRCC). Methods: We analyzed prognostic value and immune contexture that associated with CXCL13⁺CD8⁺T cells infiltration level in a total of 755 patients from Zhongshan Hospital cohort (n=223) and The Cancer Genome Atlas cohort (n=532). In vitro analyses were conducted on 42 samples of resected tumor tissue from Zhongshan Hospital in order to detect the immune status of CXCL13⁺CD8⁺T cells and total CD8⁺T cells. Immunohistochemistry (IHC) and flow cytometry were applied to characterize immune cells and portray the tumor microenvironment (TME) in ccRCC. Results: Intratumoral CXCL13⁺CD8⁺T cells abundance was associated with inferior overall survival and disease-free survival. CXCL13⁺CD8⁺T cells possessed higher level of immune checkpoints like programmed cell-death protein 1 (PD-1), T-cell immunoglobulin mucin 3 (Tim-3), T cell immunoreceptor with Ig and ITIM domains (TIGIT) and cytotoxic T-lymphocyte-associated protein 4 (CTLA-4), higher Ki-67 expression and lower tumor necrosis factor α (TNF-α), interferon γ (IFN-γ) expression. Total CD8⁺T cells in high-level CXCL13⁺CD8⁺T cells infiltration subgroup exhibited elevated exhausted markers (PD-1, Tim-3, TIGIT) and descended activated markers (TNF-α, IFN-γ) without quantity variance. Furthermore, the abundance of intratumoral CXCL13⁺CD8⁺T cell was correlated with immunoevasive TME accompanied by increased T helper 2 cells, tumor-associated macrophages, Foxp3⁺ regulatory T cells, TLS and decreased natural killer cells, GZMB⁺ cells. Conclusions: Intratumoral CXCL13⁺CD8⁺T cells infiltration indicated inferior clinical outcome in patients with ccRCC. CXCL13⁺CD8⁺T cells possessed increased exhausted markers, decreased effector molecules and better proliferation ability. CXCL13⁺CD8⁺T cells abundance impaired total CD8⁺T cells’ immune function. Intratumoral CXCL13⁺CD8⁺T cells abundance was associated with immunoevasive contexture. The abundance of CXCL13⁺CD8⁺T cells was an independent prognosticator and a potential immunotherapeutic target marker for ccRCC treatment.

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.

Treatment decisions for an incidental renal mass are mostly made with pathologic uncertainty. Improving the diagnosis of benign renal masses and distinguishing aggressive cancers from indolent ones is key to better treatment selection. We analyze 13261 pre-operative computed computed tomography (CT) volumes of 4557 patients. Two multi-phase convolutional neural networks are developed to predict the malignancy and aggressiveness of renal masses. The first diagnostic model designed to predict the malignancy of renal masses achieves area under the curve (AUC) of 0.871 in the prospective test set. This model surpasses the average performance of seven seasoned radiologists. The second diagnostic model differentiating aggressive from indolent tumors has AUC of 0.783 in the prospective test set. Both models outperform corresponding radiomics models and the nephrometry score nomogram. Here we show that the deep learning models can non-invasively predict the likelihood of malignant and aggressive pathology of a renal mass based on preoperative multi-phase CT images.