Background: UBASH3B (STS1) is an important gene that negatively regulates T-cell receptor signaling in activated T-lymphocytes that involved in cancers. However, the function of UBASH3B in prostate cancer (PCa) and the correlation between UBASH3B and tumor-infiltrating immune cells still remain unclear. Methods: Real-time PCR and immunohistochemistry were applied to detect mRNA and protein expression of UBASH3B in PCa patients and benign prostate hyperplasia patients (BPH). Clinical features of patients with PCa were recorded and Kaplan Meier curve was subsequently plotted. Based on mRNA expression of UBASH3B, patients with PCa from TCGA database were divided into low-UBASH3B-expression group and high-UBASH3B-expression group for construct lncRNA-miRNA-mRNA network and analyzing GO and KEGG pathways. Single gene analysis method was performed by using GSEA to interpret gene expression data in PCa. The PPI network was constructed using STRING and the correlation between UBASH3B and tumor-infiltrating immune cells was analyzed by TIMER and CIBERSORT. Results: The mRNA and protein expression of UBASH3B were upregulated in PCa. The abundant expression of UBASH3B is associated with poor prognosis in PCa. The subnetwork of UBASH3B contains three lncRNAs (MIAT, LINC01297, MYLK-AS1) and four miRNAs (hsa-miR-200a-3p, hsa-miR-455-5p, hsa-miR-192-5p, hsamiR- 215-5P). The mRNA expression of UBASH3B was involved in 28 KEGG pathways. GSEA analysis showed that 18 hallmark gene sets were significantly enriched in high-UBASH3B-expression, whereas 1 gene set was enriched in low-UBASH3B-expression. PPI network revealed a tightly interaction between UBASH3B and LCP2 (an immune related gene). TIMER and CIBERSORT database indicated that UBASH3B was correlated with 11 types of tumor-infiltrating immune cells (naïve B cell, memory B cells, resting CD4⁺ memory T cell, activated CD4⁺ memory T cell, regulatory T cell, activated NK cell, M2 macrophages, resting dendritic cells, activated dendritic cells, resting mast cells, neutrophils). Conclusions: In conclusion, UBASH3B may be a novel potential prognostic biomarker and is associated with tumor-infiltrating immune cells in tumor microenvironment, suggesting UBASH3B as a potential target for future treatment of PCa.

Background: Tyrosine kinase inhibitors (TKIs) such as sunitinib are multitarget antiangiogenic agents in clear cell renal cell carcinoma (ccRCC). They are widely used in the treatment of advanced/metastatic renal cancer. However, resistance to TKIs is common in the clinic, particularly after long-term treatment. YTHDC1 is the main nuclear reader protein that binds with m⁶A to regulate the splicing, export and stability of mRNA. However, the specific role and corresponding mechanism of YTHDC1 in renal cancer cells are still unclear. Methods: The Cancer Genome Atlas (TCGA) dataset was used to study the expression of YTHDC1 in ccRCC. Cell counting kit-8 (CCK-8), wound healing, Transwell and xenograft assays were applied to explore the biological function of YTHDC1 in ccRCC. Western blot, quantitative real time PCR (RT‒qPCR), RNA immunoprecipitation PCR (RIP-qPCR), methylated RIP-qPCR (MeRIP-qPCR) and RNA sequencing (RNA-seq) analyses were applied to study the YY1/HDAC2/YTHDC1/ANXA1 axis in renal cancer cells. The CCK-8 assay and xenograft assay were used to study the role of YTHDC1 in determining the sensitivity of ccRCC to sunitinib. Results: Our results demonstrated that YTHDC1 is downregulated in ccRCC tissues compared with normal tissues. Low expression of YTHDC1 is associated with a poor prognosis in patients with ccRCC. Subsequently, we showed that YTHDC1 inhibits the progression of renal cancer cells via downregulation of the ANXA1/MAPK pathways. Moreover, we also showed that the YTHDC1/ANXA1 axis modulates the sensitivity of tyrosine kinase inhibitors. We then revealed that HDAC2 inhibitors resensitize ccRCC to tyrosine kinase inhibitors through the YY1/HDAC2 complex. We have identified a novel YY1/HDAC2/YTHDC1/ANXA1 axis modulating the progression and chemosensitivity of ccRCC. Conclusion: We identified a novel YY1/HDAC2/YTHDC1/ANXA1 axis modulating the progression and chemosensitivity of ccRCC.

Lymphocyte cytosolic protein 2 (LCP2) is one of the SLP-76 family of adapters, which are critical intermediates in signal cascades downstream of several receptors. LCP2 regulates immunoreceptor signaling (such as T-cell receptors) and is also required for integrin signaling in neutrophils and platelets. However, the role of LCP2 in the tumor microenvironment is still unknown. In this study, we found a significant increase of mRNA and protein expression of LCP2 in metastatic skin cutaneous melanoma compared to normal skin. The upregulation of LCP2 was associated with good overall survival of patients with metastatic skin cutaneous melanoma, who received pharmacotherapy and radiation. GSEA signaling pathways analysis showed that LCP2 was involved in multiple pathways of immune response and correlation analysis revealed LCP2 was positively correlated with molecules in TCR signaling and 11 immune checkpoints, while LCP2 negatively correlated with 2 immune checkpoints in the metastatic skin cutaneous melanoma. According to the different expressions of LCP2, high LCP2 expression was positively correlated with more tumor-infiltrating CD8⁺ T cells. Furthermore, Kaplan–Meier plot indicated that LCP2 acted as a prognostic biomarker for progression-free survival of patients with metastatic skin cutaneous melanoma receiving anti-PD1 immunotherapy. In conclusion, our results integrated both the expression and function of LCP2 in melanoma using multiple tools, shedding light on the potential role of LCP2 in melanoma, and suggesting LCP2 serves as a prognostic biomarker and therapeutic target in anti-tumor immunity.

Immune checkpoint blockade (ICB) has become a promising therapy for multiple cancers. However, only a small proportion of patients display a limited antitumor response. The present study aimed to classify distinct immune subtypes and investigate the tumor microenvironment (TME) of urothelial carcinoma, which may help to understand treatment failure and improve the immunotherapy response. RNA-seq data and clinical parameters were obtained from TCGA-BLCA, E-MTAB-4321, and IMVigor210 datasets. A consensus cluster method was used to distinguish different immune subtypes of patients. Infiltrating immune cells, TME signatures, immune checkpoints, and immunogenic cell death modulators were evaluated in distinct immune subtypes. Dimension reduction analysis was performed to visualize the immune status of urothelial carcinoma based on graph learning. Weighted gene co-expression network analysis (WGCNA) was performed to obtain hub genes to predict responses after immunotherapy. Patients with urothelial carcinoma were classified into four distinct immune subtypes (C1, C2, C3 and C4) with various types of molecular expression, immune cell infiltration, and clinical characteristics. Patients with the C3 immune subtype displayed abundant immune cell infiltrations in the tumor microenvironment and were typically identified as “hot” tumor phenotypes, whereas those with the C4 immune subtype with few immune cell infiltrations were identified as “cold” tumor phenotypes. The immune-related and metastasis-related signaling pathways were enriched in the C3 subtype compared to the C4 subtype. In addition, tumor mutation burden, inhibitory immune checkpoints, and immunogenic cell death modulators were highly expressed in the C3 subtype. Furthermore, patients with the C4 subtype had a better probability of overall survival than patients with the C3 subtype in TCGA-BLCA and E-MTAB-4321 cohorts. Patients with the C1 subtype had the best prognosis when undergoing anti-PD-L1 antibody treatment. Finally, the immune landscape of urothelial carcinoma showed the immune status in each patient, and TGFB3 was identified as a potential biomarker for the prediction of immunotherapy resistance after anti-PD-L1 monoclonal antibody treatment. The present study provided a bioinformatics basis for understanding the immune landscape of the tumor microenvironment of urothelial carcinoma.

Background: Long non-coding RNA (lncRNA) functions as a competitive endogenous RNA (ceRNA) and plays an important role in the biological processes underlying tumorigenesis. However, studies describing the function of lncRNA in pheochromocytoma and paraganglioma (PCPG) remain largely unknown. Our study aims to construct a regulatory ceRNA network and explore prognostic biomarkers for PCPG through a comprehensive analysis. Methods: PCPG data from The Cancer Genome Atlas (TCGA) were utilized to obtain differentially expressed lncRNAs (DElncRNAs), microRNAs (DEmiRNAs), and mRNAs (DEmRNAs). Kaplan-Meier analysis was used to detect prognostic biomarkers and Cytoscape was utilized to construct a regulatory network of ceRNA. Potential lncRNA-miRNA-mRNA axes were inferred by correlation analysis. GO and KEGG pathways were constructed using "clusterProfiler" and "DOSE" R-packages. Immunohistochemistry (IHC) staining was performed to validate differential protein expression levels of genes in the axes. Finally, the GSE19422 dataset and Pan-Cancer data were applied to validate the expression pattern and survival status of mRNAs, respectively. Results: A total of 334 DElncRNAs, 116 DEmiRNAs, and 3496 DEmRNAs were identified and mainly enriched in hormone secretion, metabolism signaling, metastatic and proliferative pathways. Among these differentially expressed genes, 16 mRNAs, six lncRNAs, and two miRNAs were associated with overall survival of patients with PCPG and sequentially enrolled in the ceRNA network. Two IncRNA-miRNA-mRNA regulatory axes were predicted: AP001486.2/hsa-miR-195-5p/RCAN3 and AP006333.2/hsa-miR-34a-5p/PTPRJ. The GSE19422 dataset and IHC analysis validated that mRNA and protein levels of RCAN3 and PTPRJ were upregulated in PCPG tissues compared with adjacent adrenal gland medulla tissues. Pan-Cancer data showed that the upregulated expression of RCAN3 and PTPRJ was associated with favorable overall survival and disease-free survival. Conclusion: A regulatory lncRNA-miRNA-mRNA ceRNA network was successfully constructed and 24 prognostic biomarkers were identified for PCPG patients. These findings may contribute toward a better understanding of the biological mechanism of tumorigenesis and enable further evaluation of the prognosis of patients with PCPG.

Background: Venous thromboembolism (VTE) is the second leading cause for death of radical prostatectomy. We aimed to establish new nomogram to predict the VTE risk after robot-assisted radical prostatectomy (RARP). Methods: Patients receiving RARP in our center from November 2015 to June 2021, were enrolled in study. They were randomly divided into training and testing cohorts by 8:2. Univariate and multivariate logistic regression (model A) and stepwise logistic regression (model B) were used to fit two models. The net reclassification improvement (NRI), integrated discrimination improvement (IDI), and receiver operating characteristic (ROC) curve were used to compare predictive abilities of two new models with widely used Caprini risk assessment (CRA) model. Then, two nomograms were constructed and received internal validation. Results: Totally, 351 patients were included. The area under ROC of model A and model B were 0.967 (95% confidence interval: 0.945–0.990) and 0.978 (95% confidence interval: 0.960–0.996), which also were assayed in the testing cohorts. Both the prediction and classification abilities of the two new models were superior to CRA model (NRI > 0, IDI > 0, p < 0.05). The C-index of Model A and Model B were 0.968 and 0.978, respectively. For clinical usefulness, the two new models offered a net benefit with threshold probability between 0.08 and 1 in decision curve analysis, suggesting the two new models predict VTE events more accurately. Conclusions: Both two new models have good prediction accuracy and are superior to CRA model. Model A has an advantage of less variable. This easy-to-use model enables rapid clinical decision-making and early intervention in high-risk groups, which ultimately benefit patients.