Immune checkpoint gene signature assesses immune infiltration profiles in bladder cancer and identifies KRT23 as an immunotherapeutic target.

BACKGROUND: In the past few decades, researchers have made promising progress, including the development of immune checkpoint inhibitors (ICIs) in the therapy of bladder cancer (BLCA). Existing studies mainly focus on single immune checkpoint inhibitors but lack relevant studies on the gene expression profiles of multiple immune checkpoints. METHODS: RNA-sequencing profiling data and clinical information of BLCA patients and normal human bladder samples were acquired from the Cancer Genome Atlas and Gene Expression Omnibus databases and analyzed to identify different expression profiles of immune checkpoint genes (ICGs) after consensus clustering analysis. Based on the 526 intersecting differentially expressed genes, the LASSO Cox regression analysis was utilized to construct the ICG signature. RESULTS: According to the expression of ICGs, BLCA patients were divided into three subtypes with different phenotypic and mechanistic characteristics. Furthermore, the developed ICG signature were independent predictors of outcome in BLCA patients, and was correlated with the immune infiltration, the expression of ICGs and chemotherapeutic effect. CONCLUSIONS: This study systematically and comprehensively analyzed the expression profile of immune checkpoint genes, and established the ICG signature to investigate the differences in ICGs expression and tumor immune microenvironment, which will help risk stratification and accelerate precision medicine. Finally, we identified KRT23 as the most critical model gene, and highlighted KRT23 as a potential target to enhance immunotherapy against BLCA.

Corrigendum: Identification of an immune-related gene prognostic index for predicting survival and immunotherapy efficacy in papillary renal cell carcinoma.

[This corrects the article DOI: 10.3389/fgene.2022.970900.].

Identification of bladder cancer subtypes and predictive signature for prognosis, immune features, and immunotherapy based on immune checkpoint genes.

Immunotherapy based on immune checkpoint genes (ICGs) has recently made significant progress in the treatment of bladder cancer patients, but many patients still cannot benefit from it. In the present study, we aimed to perform a comprehensive analysis of ICGs in bladder cancer tissues with the aim of evaluating patient responsiveness to immunotherapy and prognosis. We scored ICGs in each BLCA patient from TCGA and GEO databases by using ssGSEA and selected genes that were significantly associated with ICGs scores by using the WCGNA algorithm. NMF clustering analysis was performed to identify different bladder cancer molecular subtypes based on the expression of ICGs-related genes. Based on the immune related genes differentially expressed among subgroups, we further constructed a novel stratified model containing nine genes by uni-COX regression, LASSO regression, SVM algorithm and multi-COX regression. The model and the nomogram constructed based on the model can accurately predict the prognosis of bladder cancer patients. Besides, the patients classified based on this model have large differences in sensitivity to immunotherapy and chemotherapy, which can provide a reference for individualized treatment of bladder cancer.

Unveiling the Mystery of SUMO-activating enzyme subunit 1: A Groundbreaking Biomarker in the Early Detection and Advancement of Hepatocellular Carcinoma.

Hepatocellular carcinoma (HCC) is one of the leading causes of cancer-related deaths worldwide. The discovery and research of effective biomarkers have become prevailing trends. SUMO-activating enzyme subunit 1 (sae1), an E1-activating enzyme, is indispensable for protein SUMOylation. In this study, we conducted a comprehensive analysis of database contents and found that sae1 is highly expressed in HCC and is correlated with poor prognosis. We also identified its regulated transcription factor, rad51, and related signaling pathways. We conclude that sae1 is a promising cancer metabolic biomarker with diagnostic and prognostic value in HCC.

Identification of an immune-related gene prognostic index for predicting survival and immunotherapy efficacy in papillary renal cell carcinoma.

Despite considerable progress has been made in the understanding of the genetics and molecular biology of renal cell carcinoma (RCC), therapeutic options of patients with papillary renal cell carcinoma (PRCC) are limited. Immunotherapy based on immune checkpoint inhibitors (ICIs) has become a hot point in researching new drug for tumor and been tested in a number of human clinical trials. In this study, an immune-related gene prognostic index (IRGPI) was developed and provided a comprehensive and systematic analysis of distinct phenotypic and molecular portraits in the recognition, surveillance, and prognosis of PRCC. The reliability of the IRGPI was evaluated using independent datasets from GEO database and the expression levels of the genes in the IRGPI detected by real-time PCR. Collectively, the currently established IRGPI could be used as a potential biomarker to evaluate the response and efficacy of immunotherapy in PRCC.

Evaluation of the value of Preoperative Sialic Acid Levels in Diagnosis and Localization of Urothelial Tumors.

Objective: To explore SA levels in the serum of urothelial tumor patients and their correlation with clinical pathological features and localization. Materials and Methods: Our research retrospectively collected data from 591 patients with urothelial tumors between July 2014 and April 2018. The SA levels in the serum of urothelial tumor patients and their correlation with clinical pathological features and localization were investigated. Univariate and multivariate logistic regression analyses were further performed to identify independent associations. Results: The levels of SA were significantly associated with the malignant degree (tumor grade and infiltration) of bladder cancer and tumor localization (all p < 0.05). The multivariate logistic regression model showed that SA levels were independently associated with the presence of high-grade urothelial carcinoma (BUC: HR = 1.941, UTUC: HR = 3.820, all p <0.05) and upper urinary tract urothelial carcinoma (HR = 2.047, p < 0.05). Finally, we validated the diagnosis and localization value of SA in an independent cohort from another institutions. Conclusions: Elevated serum SA levels are an independent predictor of high-grade urothelial carcinoma and upper urinary tract urothelial carcinoma, indicating that SA levels may be a potential biomarker for the diagnosis, prognosis and localization of urothelial tumors.

The Value of Preoperative Alpha-L-Fucosidase Levels in Evaluation of Malignancy and Differential Diagnosis of Urothelial Neoplasms.

PURPOSE: To evaluate the role of Alpha-L-fucosidase (AFU) in diagnosis and differential diagnosis of pure urothelial carcinoma (UC), urothelial carcinoma with squamous differentiation (UCSD), and squamous cell carcinoma (SqCC). METHODS: A retrospective study was performed for 599 patients who were histologically confirmed with urothelial tumor. Preoperative AFU levels were compared across the distinct subgroups with different clinicopathological parameters. ROC curve analysis and logistic regression analysis were performed to further evaluate the clinical application value of serum AFU levels in diagnosis and differential diagnosis of urothelial tumors. RESULTS: There were no statistically significant differences in the AFU levels between different groups with different malignant degrees (UC versus papilloma and papillary urothelial neoplasm of low malignant potential [PUNLMP], high-grade UC versus low-grade UC, invasive versus noninvasive malignant uroepithelial tumor) and different pathological types (UC, UCSD, and SqCC) (all P > 0.05). ROC curve analysis and logistic regression analysis showed that there was no statistically significant association between AFU levels and the tumor characteristics (all P > 0.05). CONCLUSIONS: Preoperative AFU levels cannot serve as a reliable predictor for malignant degree and differential diagnosis, including pure UC, UCSD, and SqCC of urothelial tumors.

Bioinformatics Analysis to Screen the Key Prognostic Genes in Tumor Microenvironment of Bladder Cancer.

Bladder cancer (BLCA) is the fifth most common cancer and has the features of low survival rate and high morbidity and mortality. The Cancer Genome Atlas (TCGA) is a pool of global gene expression profile and contains huge amounts of cancer genomics data, which makes it possible to inquire the relationship between gene expression and prognosis of a series of malignant tumors including BLCA. Immune and stromal cells are two major components of tumor microenvironment (TME) which play an important role in judging the prognosis of tumor and influencing the progression of malignant, inflammatory, and metabolic disorders. In our study, we conducted a quantitative analysis of immune and stromal elements based on the ESTIMATE algorithm and thus divided BLCA cases into high and low groups. Then the differentially expressed genes closely related to tumor prognosis between groups were identified and had been shown to correlate with immune response and stromal alterations, which was further confirmed by functional enrichment analysis and protein-protein interaction networks. We validated those genes through BLCA dates downloaded from ArrayExpress and thus got the marker genes to predict prognosis of BLCA. Additionally, immune cell infiltration analysis explored the correlation between the verified genes and immune cells. In conclusion, we identified a series of TME-related genes that assess the prognosis and explored the interaction between TME and tumor prognosis to guide clinical individualized treatment.

Downregulation of HDGF inhibits the tumorigenesis of bladder cancer cells by inactivating the PI3K-AKT signaling pathway.

BACKGROUND: Hepatoma-derived growth factor (HDGF) is a heparin-binding protein that has been observed to be abnormally expressed in numerous malignancies, but the definite role of HDGF in bladder cancer (BCa) has not been clarified. Here, we conduct the present study to evaluate correlations between HDGF and BCa. METHODS: Bioinformatics analysis was used to evaluate HDGF expression levels in BCa tissues. The effect of HDGF on cell proliferation, migration, invasion, cell cycle and apoptosis was analyzed utilizing CCK-8, clone formation, Transwell assays and flow cytometry, respectively. In addition, the xenograft tumor model was established. RESULTS: Based on bioinformatics analysis, we noticed that HDGF was highly expressed in BCa tissues and was positively correlated with poor prognosis in patients. Knockdown of HDGF markedly reduced tumorigenesis in BCa cells. Furthermore, the results of flow cytometry showed that HDGF deletion enhanced apoptosis in T24 and 253J cells and led to cell cycle arrest in G1 phase. In further studies, we found that tumor growth was inhibited in xenograft nude mouse models with HDGF deletion. The results of RNA-seq analysis revealed that the PI3K-AKT signaling pathway-related genes were obviously changed in HDGF-deficient 253J cells, and this result was further confirmed by Western blot analysis. CONCLUSION: In summary, we suggest that HDGF plays a substantial role in BCa and promotes tumor development and progression by regulating the PI3K-AKT signaling pathway, which provides a promising target for BCa treatment.

Elevated Serum Sialic Acid Levels Predict Prostate Cancer As Well As Bone Metastases.

Objective: To evaluate the value of serum sialic acid (SA) in diagnosis of benign prostatic hyperplasia (BPH), prostate cancer (PCa), and bone metastases in PCa patients. Materials and Methods: Data from 540 patients who were newly diagnosed with PCa or BPH between November 2014 and March 2018 were retrospectively collected and analyzed. Pretreatment SA levels were compared across various groups, then, associations between SA levels and clinic parameters of patients were analyzed as well. Univariate and multivariate logistic regression analyses were further used to identify independent associations. Results: The mean SA levels in patients with PCa were significantly higher than with BPH (p = 0.013). Furthermore, PCa patients with bone metastases showed elevated SA levels compared with PCa without bone metastases (p < 0.001). A multivariate logistic regression model showed that: SA level > 52.35 mg/dL was identified to be independently associated with the diagnosis of PCa (HR = 1.645, p = 0.036), and SA level > 59 mg/dL was identified to be independent association with the presence of bone metastases in PCa patients (HR = 6.421, p = 0.012). Conclusions: Elevated SA level is an independent predictor of prostate cancer as well as its bone metastases. Therefore, SA level may be a promising diagnostic and prognostic biomarker for prostate cancer and bone metastases.

Bladder cancer stage-associated hub genes revealed by WGCNA co-expression network analysis.

BACKGROUND: Bladder cancer was a malignant disease in patients, our research aimed at discovering the possible biomarkers for the diseases. RESULTS: The gene chip GSE31684, including 93samples, was downloaded from the GEO datasets and co-expression network was constructed by the data. Molecular complex detection(MCODE) was used to identify hub genes. The most significant cluster including 16 genes: CDH11, COL3A1, COL6A3, COL5A1, AEBP1, COL1A2, NTM, COL11A1, THBS2, COL8A1, COL1A1, BGN, MMP2, PXDN, THY1, and TGFB1I1 was identified. After annotated by BiNGO, they were suggested associated with collagen fibril organization and blood vessel development. In addition, the Kaplan Meier curves were obtained by UALCAN. The high expression of THY1, AEBP1, CDH11, COL1A1, COL1A2, COL11A1, MMP2, PXDN, BGN, COL5A1, COL8A1, and TGFB1I1 indicated poor prognosis of the patients(P < 0.05). Finally, we examined genes' expression between low and high tumor stage by the Wilcoxon test(P < 0.05), TGFB1I1 was excluded. CONCLUSION: THY1, AEBP1, CDH11, COL1A1, COL1A2, COL11A1, MMP2, PXDN, BGN, COL5A1, COL8A1 associated with the tumor stage as well as tumor patients' prognosis. COL5A1, COL8A1(P < 0.01) may serve as therapeutic targets for the disease.