Exploring the oncogenic potential of circSOD2 in clear cell renal cell carcinoma: a novel positive feedback loop.

BACKGROUND: Existing studies have found that circular RNAs (circRNAs) act as sponges for micro RNAs (miRNAs) to control downstream genes. However, the specific functionalities and mechanisms of circRNAs in human clear cell renal cell carcinoma (ccRCC) have yet to be thoroughly investigated. METHODS: Patient cohorts from online databases were used to screen candidate circRNAs, while another cohort from our hospital was obtained for validation. CircSOD2 was identified as a potential oncogenic target, and its relevant characteristics were investigated during ccRCC progression through various assays. A positive feedback loop containing downstream miRNA and its target gene were identified using bioinformatics and validated by luciferase reporter assays, RNA pull-down, and high-throughput sequencing. RESULTS: CircSOD2 expression was elevated in tumor samples and significantly correlated with overall survival (OS) and the tumor stage of ccRCC patients, which appeared in the enhanced proliferation, invasion, and migration of tumor cells. Through competitive binding to circSOD2, miR-532-3p can promote the expression of PAX5 and the progression of ccRCC, and such regulation can be salvaged by miR-532-3p inhibitor. CONCLUSION: A novel positive feedback loop, PAX5/circSOD2/miR-532-3p/PAX5 was identified in the study, indicating that the loop may play an important role in the diagnosis and prognostic prediction in ccRCC patients.

A new thinking: extended application of genomic selection to screen multiomics data for development of novel hypoxia-immune biomarkers and target therapy of clear cell renal cell carcinoma.

Increasing evidences show the clinical significance of the interaction between hypoxia and immune in clear cell renal cell carcinoma (ccRCC) microenvironment. However, reliable prognostic signatures based on a combination of hypoxia and immune have not been well established. Moreover, many studies have only used RNA-seq profiles to screen the prognosis feature of ccRCC. Presently, there is no comprehensive analysis of multiomics data to mine a better one. Thus, we try and get it. First, t-SNE and ssGSEA analysis were used to establish tumor subtypes related to hypoxia-immune, and we investigated the hypoxia-immune-related differences in three types of genetic or epigenetic characteristics (gene expression profiles, somatic mutation, and DNA methylation) by analyzing the multiomics data from The Cancer Genome Atlas (TCGA) portal. Additionally, a four-step strategy based on lasso regression and Cox regression was used to construct a satisfying prognostic model, with average 1-year, 3-year and 5-year areas under the curve (AUCs) equal to 0.806, 0.776 and 0.837. Comparing it with other nine known prognostic biomarkers and clinical prognostic scoring algorithms, the multiomics-based signature performs better. Then, we verified the gene expression differences in two external databases (ICGC and SYSU cohorts). Next, eight hub genes were singled out and seven hub genes were validated as prognostic genes in SYSU cohort. Furthermore, it was indicated high-risk patients have a better response for immunotherapy in immunophenoscore (IPS) analysis and TIDE algorithm. Meanwhile, estimated by GDSC and cMAP database, the high-risk patients showed sensitive responses to six chemotherapy drugs and six candidate small-molecule drugs. In summary, the signature can accurately predict the prognosis of ccRCC and may shed light on the development of novel hypoxia-immune biomarkers and target therapy of ccRCC.

Fatty acids metabolism affects the therapeutic effect of anti-PD-1/PD-L1 in tumor immune microenvironment in clear cell renal cell carcinoma.

BACKGROUND: Clear cell renal cell carcinoma (ccRCC) is a highly invasive and metastatic subtype of kidney malignancy and is correlated with metabolic reprogramming for adaptation to the tumor microenvironment comprising infiltrated immune cells and immunomodulatory molecules. The role of immune cells in the tumor microenvironment (TME) and their association with abnormal fatty acids metabolism in ccRCC remains poorly understood. METHOD: RNA-seq and clinical data of KIRC from The Cancer Genome Atlas (TCGA) and E-MTAB-1980 from the ArrayExpress dataset. The Nivolumab group and Everolimus group of the CheckMate 025 study, the Atezolizumab arm of IMmotion150 and the Atezolizumab plus Bevacizumab group of IMmotion151 cohort were obtained for subsequent analysis. After differential expression genes identification, the signature was constructed through univariate Cox proportional hazard regression and simultaneously the least absolute shrinkage and selection operator (Lasso) analysis and the predictive performance of our signature was assessed by using receiver operating characteristic (ROC), Kaplan-Meier (KM) survival analysis, nomogram, drug sensitivity analysis, immunotherapeutic effect analysis and enrichment analysis. Immunohistochemistry (IHC), qPCR and western blot were performed to measure related mRNA or protein expression. Biological features were evaluated by wound healing, cell migration and invasion assays and colony formation test and analyzed using coculture assay and flow cytometry. RESULTS: Twenty fatty acids metabolism-related mRNA signatures were constructed in TCGA and possessed a strong predictive performance demonstrated through time-dependent ROC and KM survival analysis. Notably, the high-risk group exhibited an impaired response to anti-PD-1/PD-L1 (Programmed death-1 receptor/Programmed death-1 receptor-ligand) therapy compared to the low-risk group. The overall levels of the immune score were higher in the high-risk group. Additionally, drug sensitivity analysis observed that the model could effectively predict efficacy and sensitivity to chemotherapy. Enrichment analysis revealed that the IL6-JAK-STAT3 signaling pathway was a major pathway. IL4I1 could promote ccRCC cells' malignant features through JAK1/STAT3 signaling pathway and M2-like macrophage polarization. CONCLUSION: The study elucidates that targeting fatty acids metabolism can affect the therapeutic effect of PD-1/PD-L1 in TME and related signal pathways. The model can effectively predict the response to several treatment options, underscoring its potential clinical utility.

m6A-immune-related lncRNA prognostic signature for predicting immune landscape and prognosis of bladder cancer.

BACKGROUND: N6-methyladenosine (m6A) related long noncoding RNAs (lncRNAs) may have prognostic value in bladder cancer for their key role in tumorigenesis and innate immunity. METHODS: Bladder cancer transcriptome data and the corresponding clinical data were acquired from the Cancer Genome Atlas (TCGA) database. The m6A-immune-related lncRNAs were identified using univariate Cox regression analysis and Pearson correlation analysis. A risk model was established using least absolute shrinkage and selection operator (LASSO) Cox regression analyses, and analyzed using nomogram, time-dependent receiver operating characteristics (ROC) and Kaplan-Meier survival analysis. The differences in infiltration scores, clinical features, and sensitivity to Talazoparib of various immune cells between low- and high-risk groups were investigated. RESULTS: Totally 618 m6A-immune-related lncRNAs and 490 immune-related lncRNAs were identified from TCGA, and 47 lncRNAs of their intersection demonstrated prognostic values. A risk model with 11 lncRNAs was established by Lasso Cox regression, and can predict the prognosis of bladder cancer patients as demonstrated by time-dependent ROC and Kaplan-Meier analysis. Significant correlations were determined between risk score and tumor malignancy or immune cell infiltration. Meanwhile, significant differences were observed in tumor mutation burden and stemness-score between the low-risk group and high-risk group. Moreover, high-risk group patients were more responsive to Talazoparib. CONCLUSIONS: An m6A-immune-related lncRNA risk model was established in this study, which can be applied to predict prognosis, immune landscape and chemotherapeutic response in bladder cancer.

A panel of eight autophagy-related long non-coding RNAs is a good predictive parameter for clear cell renal cell carcinoma.

Clear-cell renal cell carcinoma (ccRCC) carries a variable prognosis. Prognostic biomarkers can stratify patients according to risk, and can provide crucial information for clinical decision-making. We screened for an autophagy-related long non-coding lncRNA (lncRNA) signature to improve postoperative risk stratification in The Cancer Genome Atlas (TCGA) database. We confirmed this model in ICGC and SYSU cohorts as a significant and independent prognostic signature. Western blotting, autophagic-flux assay and transmission electron microscopy were used to verify that regulation of expression of 8 lncRNAs related to autophagy affected changes in autophagic flow in vitro. Our data suggest that 8-lncRNA signature related to autophagy is a promising prognostic tool in predicting the survival of patients with ccRCC. Combination of this signature with clinical and pathologic parameters could aid accurate risk assessment to guide clinical management, and this 8-lncRNAs signature related to autophagy may serve as a therapeutic target.

circCHST15 is a novel prognostic biomarker that promotes clear cell renal cell carcinoma cell proliferation and metastasis through the miR-125a-5p/EIF4EBP1 axis.

BACKGROUND: Circular RNAs (circRNAs) have been indicated as potentially critical mediators in various types of tumor progression, generally acting as microRNA (miRNA) sponges to regulate downstream gene expression. However, the aberrant expression profile and dysfunction of circRNAs in human clear cell renal cell carcinoma (ccRCC) need to be further investigated. This study mined key prognostic circRNAs and elucidates the potential role and molecular mechanism of circRNAs in regulating the proliferation and metastasis of ccRCC. METHODS: circCHST15 (hsa_circ_0020303) was identified by mining two circRNA microarrays from the Gene Expression Omnibus database and comparing matched tumor versus adjacent normal epithelial tissue pairs or matched primary versus metastatic tumor tissue pairs. These results were validated by quantitative real-time polymerase chain reaction and agarose gel electrophoresis. We demonstrated the biological effect of circCHST15 in ccRCC both in vitro and in vivo. To test the interaction between circCHST15 and miRNAs, we conducted a number of experiments, including RNA pull down assay, dual-luciferase reporter assay and fluorescence in situ hybridization. RESULTS: The expression of circCHST15 was higher in ccRCC tissues compared to healthy adjacent kidney tissue and higher in RCC cell lines compared to normal kidney cell lines. The level of circCHST15 was positively correlated with aggressive clinicopathological characteristics, and circCHST15 served as an independent prognostic indicator for overall survival and progression-free survival in patients with ccRCC after surgical resection. Our in vivo and in vitro data indicate that circCHST15 promotes the proliferation, migration, and invasion of ccRCC cells. Mechanistically, we found that circCHST15 directly interacts with miR-125a-5p and acts as a microRNA sponge to regulate EIF4EBP1 expression. CONCLUSIONS: We found that sponging of miR-125a-5p to promote EIF4EBP1 expression is the underlying mechanism of hsa_circ_0020303-induced ccRCC progression. This prompts further investigation of circCHST15 as a potential prognostic biomarker and therapeutic target for ccRCC.

Histone lysine demethylase KDM4B regulates the alternative splicing of the androgen receptor in response to androgen deprivation.

Alternative splicing is emerging as an oncogenic mechanism. In prostate cancer, generation of constitutively active forms of androgen receptor (AR) variants including AR-V7 plays an important role in progression of castration-resistant prostate cancer (CRPC). AR-V7 is generated by alternative splicing that results in inclusion of cryptic exon CE3 and translation of truncated AR protein that lacks the ligand binding domain. Whether AR-V7 can be a driver for CRPC remains controversial as the oncogenic mechanism of AR-V7 activation remains elusive. Here, we found that KDM4B promotes AR-V7 and identified a novel regulatory mechanism. KDM4B is phosphorylated by protein kinase A under conditions that promote castration-resistance, eliciting its binding to the splicing factor SF3B3. KDM4B binds RNA specifically near the 5'-CE3, upregulates the chromatin accessibility, and couples the spliceosome to the chromatin. Our data suggest that KDM4B can function as a signal responsive trans-acting splicing factor and scaffold that recruits and stabilizes the spliceosome near the alternative exon, thus promoting its inclusion. Genome-wide profiling of KDM4B-regulated genes also identified additional alternative splicing events implicated in tumorigenesis. Our study defines KDM4B-regulated alternative splicing as a pivotal mechanism for generating AR-V7 and a contributing factor for CRPC, providing insight for mechanistic targeting of CRPC.

Contrast-enhanced transrectal ultrasound can reduce collection of unnecessary biopsies when diagnosing prostate cancer and is predictive of biochemical recurrence following a radical prostatectomy in patients with localized prostate cancer.

BACKGROUND: To investigate the value of using contrast-enhanced transrectal ultrasound (CETRUS) to reduce unnecessary collection of biopsies during prostate cancer diagnosis and its utility in predicting biochemical recurrence in patients with localized prostate cancer. METHODS: This was a prospective study of suspected prostate cancer patients who were evaluated with CETRUS followed by a prostate biopsy. Prostate blood flow via CETRUS was graded using a 5-point scale. The relationship between CETRUS score and biopsy outcome was then analyzed for all patients; univariate and multi-variate analyses were used to determine the probable prognostic factors for biochemical recurrence in patients with localized prostate cancer that underwent a radical prostatectomy. RESULTS: A total of 347 patients were enrolled in the study. Prostate cancer was found in 164 patients. A significant positive correlation (r = 0.69, p < 0.001) was found between CETRUS scores and prostate cancer incidence. Using CETRUS scores ≥2 as the threshold for when to biopsy could have safely reduced the number of biopsies taken overall by 12.1% (42/347) and spared 23.0% (42/183) of patients from undergoing an unnecessary biopsy. 77 patients with localized prostate cancer underwent a radical prostatectomy. The median follow-up time was 30 months (range: 8-56 months) and 17 of these 77 patients exhibited biochemical recurrence during the follow-up period. 3-year biochemical recurrence-free survival rates were 86% for patients with low CETRUS scores (≤ 3) and 59% for patients with high scores (> 3; p = 0.015). Multivariate Cox regression analysis indicated that CETRUS score was an independent predictor of biochemical recurrence (HR: 7.02; 95% CI: 2.00-24.69; p = 0.002). CONCLUSIONS: CETRUS scores may be a useful tool for reducing the collection unnecessary biopsy samples during prostate cancer diagnosis and are predictive of biochemical recurrence in patients with localized prostate cancer following a radical prostatectomy.

Overexpression of EIF5A2 in upper urinary tract urothelial carcinoma is a new independent prognostic marker of survival.

Aim: To study the expression of EIF5A2 in urinary tract urothelial carcinoma and its clinicopathological features and prognosis. Methods: EIF5A2 expression was detected via immunohistochemistry in 101 patients. Results: Kaplan-Meier analysis showed that the EIF5A2 low expression group had significantly longer overall survival (OS; p < 0.001) and progression-free survival (PFS; p < 0.001) than the EIF5A2 high expression group. The high expression of EIF5A2 significantly predict poor OS and PFS in the subset patients (p < 0.05). EIF5A2 was an independent prognostic factor for OS and PFS (p = 0.003 and p = 0.001). The established nomogram model and its calibration curve predicted the probability of survival accurately. Conclusion: EIF5A2 is a potential molecular marker of poor prognosis in urinary tract urothelial carcinoma.

Pelvic mass: Schwannoma of the left seminal vesicle.

Schwannomas rarely occur in seminal vesicles. Here, we report a schwannoma of the left seminal vesicle. A 55-year-old man presented no clinical symptoms, and a mass in the left region of the seminal vesicle was found incidentally in a medical examination. A computed tomography and magnetic resonance imaging of pelvic were obtained and revealed a 5.17 × 2.59 × 3.5 cm mass on the left seminal vesicle. Transrectal ultrasound-guided seminal biopsy revealed a diagnosis of seminal vesical schwannoma. Laparoscopic resection of the tumour was performed. Postoperative pathology and immunohistochemical analysis revealed schwannoma arising from seminal vesical.

A nomogram based on TFE3 IHC results and clinical factors as a preliminary screening scheme for TFE3-rearranged renal cell carcinoma.

BACKGROUND: TFE3 immunohistochemistry (TFE3-IHC) is controversial in the diagnosis of TFE3-rearranged renal cell carcinoma (TFE3-rearranged RCC). This study is to investigate the accuracy and sensitivity of IHC and establish a predictive model to diagnose TFE3-rearranged RCC. METHODS: Retrospective analysis was performed by collecting IHC and fluorescence in situ hybridization (FISH) results from 228 patients. IHC results were evaluated using three scoring systems. Scoring system 1 is graded based on nuclear staining intensity, scoring system 2 is graded based on the percentage of stained tumor cell nuclei, and scoring system 3 is graded based on both the nuclear staining intensity and the percentage. We collected patients' IHC results and clinical information. Important variables were screened based on univariate logistic regression analysis. Then, independent risk factors were established through multivariate logistic regression, and a nomogram model was constructed. The model was validated in internal test set and external validation set. The receiver operating characteristic curve (ROC curve), calibration curve, and decision curve analysis (DCA) were generated to assess discriminative ability of the model. RESULTS: The accuracy of IHC based on three scoring systems were 0.829, 0.772, and 0.807, respectively. The model included four factors including age, gender, lymph node metastasis and IHC results. Area under the curve (AUC) values were 0.935 for the training set, 0.934 for the internal test set, 0.933 for all 228 patients, and 0.916 for the external validation set. CONCLUSIONS: TFE3 IHC has high accuracy in the diagnosis of TFE3-rearranged RCC. Clinical information such as age and lymph node metastasis are independent risk factors, which can be used as a supplement to the results of TFE3 IHC. This study confirms the value of IHC in the diagnosis of TFE3-rearranged RCC. The accuracy of the diagnosis can be improved by incorporating IHC with other clinical risk factors.

LRP1 induces anti-PD-1 resistance by modulating the DLL4-NOTCH2-CCL2 axis and redirecting M2-like macrophage polarisation in bladder cancer.

The tumour microenvironment (TME) drives bladder cancer (BLCA) progression. Targeting the TME has emerged as a promising strategy for BLCA treatment in recent years. Furthermore, checkpoint blockade therapies are only beneficial for a minority of patients with BLCA, and drug resistance is a barrier to achieving significant clinical effects of anti-programmed cell death protein-1 (PD-1)/programmed death protein ligand-1 (PD-L1) therapy. In this study, higher low-density lipoprotein receptor-related protein 1 (LRP1) levels were related to a poorer prognosis for patients with various cancers, including those with higher grades and later stages of BLCA. Enrichment analysis demonstrated that LRP1 plays a role in the epithelial-mesenchymal transition (EMT), NOTCH signalling pathway, and ubiquitination. LRP1 knockdown in BLCA cells delayed BLCA progression both in vivo and in vitro. Furthermore, LRP1 knockdown suppressed EMT, reduced DLL4-NOTCH2 signalling activity, and downregulated M2-like macrophage polarisation. Patients with BLCA and higher LRP1 levels responded weakly to anti-PD-1 therapy in the IMvigor210 cohort. Moreover, LRP1 knockdown enhanced the therapeutic effects of anti-PD-1 in mice. Taken together, our findings suggest that LRP1 is a potential target for improving the efficacy of anti-PD-1/PD-L1 therapy by preventing EMT and M2-like macrophage polarisation by blocking the DLL4-NOTCH2 axis.

Development and external validation of the multichannel deep learning model based on unenhanced CT for differentiating fat-poor angiomyolipoma from renal cell carcinoma: a two-center retrospective study.

PURPOSE: There are undetectable levels of fat in fat-poor angiomyolipoma. Thus, it is often misdiagnosed as renal cell carcinoma. We aimed to develop and evaluate a multichannel deep learning model for differentiating fat-poor angiomyolipoma (fp-AML) from renal cell carcinoma (RCC). METHODS: This two-center retrospective study included 320 patients from the First Affiliated Hospital of Sun Yat-Sen University (FAHSYSU) and 132 patients from the Sun Yat-Sen University Cancer Center (SYSUCC). Data from patients at FAHSYSU were divided into a development dataset (n = 267) and a hold-out dataset (n = 53). The development dataset was used to obtain the optimal combination of CT modality and input channel. The hold-out dataset and SYSUCC dataset were used for independent internal and external validation, respectively. RESULTS: In the development phase, models trained on unenhanced CT images performed significantly better than those trained on enhanced CT images based on the fivefold cross-validation. The best patient-level performance, with an average area under the receiver operating characteristic curve (AUC) of 0.951 ± 0.026 (mean ± SD), was achieved using the "unenhanced CT and 7-channel" model, which was finally selected as the optimal model. In the independent internal and external validation, AUCs of 0.966 (95% CI 0.919-1.000) and 0.898 (95% CI 0.824-0.972), respectively, were obtained using the optimal model. In addition, the performance of this model was better on large tumors (≥ 40 mm) in both internal and external validation. CONCLUSION: The promising results suggest that our multichannel deep learning classifier based on unenhanced whole-tumor CT images is a highly useful tool for differentiating fp-AML from RCC.

Hsa_circ_0057105 modulates a balance of epithelial-mesenchymal transition and ferroptosis vulnerability in renal cell carcinoma.

BACKGROUND: The incidence of renal cell carcinoma (RCC) has increased in recent years. Metastatic RCC is common and remains a major cause of mortality. A regulatory role for circular RNAs (circRNAs) in the occurrence and progression of RCC has been identified, but their function, molecular mechanisms, and potential clinical applications remain poorly understood. METHODS: High-throughput RNA sequencing was used to explore the differential expression of circRNAs and their related pathways in RCC patients. Transwell and CCK-8 assays were used to assess the function of hsa_circ_0057105 in RCC cells. The clinical relevance of hsa_circ_0057105 was evaluated in a cohort of RCC patients. The hsa_circ_0057105 regulatory axis was defined using RNA pull-down, luciferase reporter assays, and fluorescence in situ hybridization assays, and the in vivo effect of hsa_circ_0057105 was validated using animal experiments. RESULTS: Single-sample gene set enrichment analysis and correlation analysis of RNA-seq data showed that hsa_circ_0057105 was potentially oncogenic and may serve to regulate epithelial-mesenchymal transition (EMT) activation in RCC. Hsa_circ_0057105 expression was associated with advanced TNM stages and was an independent prognostic factor for poor RCC patient survival. Phenotypic studies show that hsa_circ_0057105 can enhance the migration and invasion abilities of RCC cells. Further, hsa_circ_0057105 was shown to inhibit the expression of miR-577, a miRNA that regulated the expression of both COL1A1, which induced EMT activation, and VDAC2, which modulated ferroptosis sensitivity. The dual regulatory roles of hsa_circ_0057105 on EMT and ferroptosis sensitivity were verified using rescue experiments. Animal studies confirmed that hsa_circ_0057105 increased the metastatic ability and ferroptosis sensitivity of RCC cells in vivo. CONCLUSIONS: In RCC, hsa_circ_0057105 regulates COL1A1 and VDAC2 expression through its sponge effect on miR-577, acting like a 'double-edged sword'. These findings provide new insight into the relationship between EMT and ferroptosis in RCC and provide potential biomarkers for RCC surveillance and treatment.

Development and validation of a novel defined mutation classifier based on Lasso logistic regression for predicting the overall survival of immune checkpoint inhibitor therapy in renal cell carcinoma.

Background: Currently, immune checkpoint inhibitor (ICI)-based therapy has become the first-line treatment for advanced renal cell carcinoma (RCC). However, few biomarkers have been identified to predict the response to ICI therapy in RCC patients. Herein, our research aimed to build a gene mutation prognostic indicator for ICI therapy. Methods: This multi-cohort study explored the mutation patterns in 2 publicly available advanced RCC ICI therapy cohorts, the Memorial Sloan Kettering Cancer Center (MSKCC) advanced RCC ICI therapy cohort and the CheckMate ICI therapy cohort. A total of 261 patients in the CheckMate ICI therapy cohort were randomly assigned to either the training or validation set. Least absolute shrinkage and selection operator (Lasso) logistic regression analysis was subsequently used to develop a mutation classifier utilizing the training set. The classifier was then validated internally in the validation set and externally in 2 ICI therapy cohorts and 2 non-ICI therapy cohorts. Survival analysis, receiver operator characteristic curves and Harrell's concordance index were performed to assess the prognostic value of the classifier. Function and immune microenvironment analysis in each subgroup defined by the classifier were performed. Results: A 10-gene mutation classifier was constructed based on the CheckMate ICI therapy cohort to separate patients into 2 risk groups, with patients in the high-risk group showing significantly lower overall survival probability than those in the low-risk group [the training set (HR: 1.791; 95% CI: 1.207-2.657; P=0.003), the validation set (HR: 1.842; 95% CI: 1.133-2.996; P=0.012) and combination set (HR: 1.819; 95% CI: 1.339-2.470; P<0.001)]. Further validation confirmed that the mutation classifier only showed predictive value for patients receiving ICI therapy instead of non-ICI therapy. Combined with the clinical characteristics, the risk score was proven to be an independent prognostic factor for overall survival in ICI therapy by multivariate Cox regression analysis. Functional and immune infiltration analysis demonstrated that lower risk scores tended to associate with immunologically "hot" status in RCC. Conclusions: Our 10-gene mutation classifier was found to be a biomarker for predicting the overall survival of patients with advanced RCC to ICI therapy.

Neoadjuvant and adjuvant chemotherapy share equivalent efficacy in improving overall survival and cancer-specific survival among muscle invasive bladder cancer patients who undergo radical cystectomy: a retrospective cohort study based on SEER database.

Background: Although neoadjuvant chemotherapy (NAC) followed by radical cystectomy (RC) have been reported an 6% absolute improvement in 5-year overall survival (OS) for muscle invasive bladder cancer (MIBC), criticism still exists including the delay of surgery and the lack of accurate pathological evidence guidance. Trials have instead focused on adjuvant chemotherapy (AC) but encountered with many difficulties. Convincing data directly compared the treatment efficacy of these 2 strategies are lacking. Methods: We conducted a retrospective cohort study to compare the effectiveness of NAC versus AC among patients with T2-4N0-3M0 bladder cancer using the Surveillance, Epidemiology, and End Results (SEER) database. OS and cancer-specific survival (CSS) were compared using Kaplan-Meier (KM) survival estimators and univariate Cox proportional hazards regression models adjusted for inverse probability of treatment weighting (IPTW). The baseline between groups were compared using standardized mean differences (SMD) approach and kernel density plot. Sensitivity analysis was performed to test the robustness of our results. Results: In total, 1,620 (38.9%) of all eligible patients (4,169) received NAC and 2,549 (61.1%) received AC. After adjusted for propensity score, all baseline characteristics were balanced with SMD <10%. The IPTW-adjusted survival analyses revealed no significant difference in OS between the 2 groups [adjusted hazard ratio (AHR) 1.09, 95% confidence interval (CI): 0.99-1.20, P=0.1]. Exploratory subgroup analysis indicated longer OS among lymph node-negative patients treated with NAC (AHR 1.25, 95% CI: 1.1-1.4, P=0.001), whereas lymph node-positive patients were in favor of AC (AHR 0.85, 95% CI: 0.72-0.99, P=0.043). This treatment heterogeneity according to lymph node status is associated with better prognosis in Stage II (T2N0) patients receiving NAC (AHR 1.28, 95% CI: 1.1-1.6, P=0.014). Meanwhile, in stage III-IV (T3-T4 and/or N+) diseases, NAC shares similar treatment efficacy to AC (AHR 0.98, 95% CI: 0.87-1.1, P=0.762). The analyses of CSS yielded similar, robust results on the effect of potential unmeasured confounding variables. Conclusions: Our population-based study suggests that NAC and AC might be interchangeable in MIBC management, especially in patients with Stage III-IV (T3-T4 and/or N+) diseases. However, this conclusion needs further validation from powerful, robust randomized trials.

Overexpression of TREM1 is Associated with the Immune-Suppressive Microenvironment and Unfavorable Prognosis in Pan-Cancer.

Background: Triggering receptors expressed by myeloid cells-1 (TREM1) is a receptor belonging to the immunoglobulin superfamily and plays an important role in pro-inflammation in acute and chronic inflammatory disorders. However, the understanding of the immunomodulatory roles of TREM1 in the tumor microenvironment remains incomplete. Methods: The expression patterns of TREM1 mRNA in tumors and adjacent normal tissues were compared by analyzing data obtained from the Genotype-Tissue Expression and The Cancer Genome Atlas datasets. Survival analysis was performed to determine the prognostic value of TREM1. Functional enrichment analysis was applied to decipher the discrepancy in biological processes between high- and low-TREM1 groups across various cancers. The correlation between TREM1 and immune cell infiltration determined by using multiple algorithms was evaluated with the Pearson method. Four independent immunotherapy cohorts were adopted to validate the role of TREM1 as a biomarker. Results: TREM1 was elevated in most cancers as verified with clinical samples. Overexpression of TREM1 was linked with undesirable prognosis in patients. Further analysis revealed that TREM1 was positively correlated with immune response, pro-tumor pathways, and myeloid cell infiltration, while being negatively correlated with CD8+ T cell (including infiltration level and biological processes). Concordantly, tumors with high TREM1 levels were more resistant to immunotherapy. Through connective map analysis, therapeutically potential compounds like tozasertib and TPCA-1 were identified, which can be used synergistically with immunotherapy to improve the poor prognosis of patients with high TREM1 levels. Conclusion: Through a systematic and comprehensive pan-cancer analysis, we demonstrated that overexpression of TREM1 in tumors correlated closely with unfavorable outcome, infiltration of immune-suppressive cells, and immune regulation, which highlights its potential use as a tumor prognostic biomarker and a novel target for immunotherapy.

Therapeutic targeting of histone lysine demethylase KDM4B blocks the growth of castration-resistant prostate cancer.

Epigenetics is an emerging mechanism for tumorigenesis. Treatment that targets epigenetic regulators is becoming an attractive strategy for cancer therapy. The role of epigenetic therapy in prostate cancer (PCa) remains elusive. Previously we demonstrated that upregulation of histone lysine demethylase KDM4B correlated with the appearance of castration resistant prostate cancer (CRPC) and identified a small molecular inhibitor of KDM4B, B3. In this study, we further investigated the role of KDM4B in promoting PCa progression and tested the efficacy of B3 using clinically relevant PCa models including PCa cell line LNCaP and 22Rv1 and xenografts derived from these cell lines. In loss and gain-functional studies of KDM4B in PCa cells, we found that overexpression of KDM4B in LNCaP cells enhanced its tumorigenicity whereas knockdown of KDM4B in 22Rv1 cells reduced tumor growth in castrated mice. B3 suppressed the growth of 22Rv1 xenografts and sensitized tumor to anti-androgen receptor (AR) antagonist enzalutamide inhibition. B3 also inhibited 22Rv1 tumor growth synergistically with rapamycin, leading to cell apoptosis. Comparative transcriptomic analysis performed on KDM4B knockdown and B3-treated 22Rv1 cells revealed that B3 inhibited both H3K9me3 and H3K27me3 demethylase activities. Our studies establish KDM4B as a target for CRPC and B3 as a potential therapeutic agent. B3 as monotherapy or in combination with other anti-PCa therapeutics offers proof of principle for the clinical translation of epigenetic therapy targeting KDMs for CRPC patients.

A novel 7-chemokine-genes predictive signature for prognosis and therapeutic response in renal clear cell carcinoma.

Background: Renal clear cell carcinoma (ccRCC) is one of the most prevailing type of malignancies, which is affected by chemokines. Chemokines can form a local network to regulate the movement of immune cells and are essential for tumor proliferation and metastasis as well as for the interaction between tumor cells and mesenchymal cells. Establishing a chemokine genes signature to assess prognosis and therapy responsiveness in ccRCC is the goal of this effort. Methods: mRNA sequencing data and clinicopathological data on 526 individuals with ccRCC were gathered from the The Cancer Genome Atlas database for this investigation (263 training group samples and 263 validation group samples). Utilizing the LASSO algorithm in conjunction with univariate Cox analysis, the gene signature was constructed. The Gene Expression Omnibus (GEO) database provided the single cell RNA sequencing (scRNA-seq) data, and the R package "Seurat" was applied to analyze the scRNA-seq data. In addition, the enrichment scores of 28 immune cells in the tumor microenvironment (TME) were calculated using the "ssGSEA" algorithm. In order to develop possible medications for patients with high-risk ccRCC, the "pRRophetic" package is employed. Results: High-risk patients had lower overall survival in this model for predicting prognosis, which was supported by the validation cohort. In both cohorts, it served as an independent prognostic factor. Annotation of the predicted signature's biological function revealed that it was correlated with immune-related pathways, and the riskscore was positively correlated with immune cell infiltration and several immune checkpoints (ICs), including CD47, PDCD1, TIGIT, and LAG-3, while it was negatively correlated with TNFRSF14. The CXCL2, CXCL12, and CX3CL1 genes of this signature were shown to be significantly expressed in monocytes and cancer cells, according to scRNA-seq analysis. Furthermore, the high expression of CD47 in cancer cells suggested us that this could be a promising immune checkpoint. For patients who had high riskscore, we predicted 12 potential medications. Conclusion: Overall, our findings show that a putative 7-chemokine-gene signature might predict a patient's prognosis for ccRCC and reflect the disease's complicated immunological environment. Additionally, it offers suggestions on how to treat ccRCC using precision treatment and focused risk assessment.

LZTFL1 inhibits kidney tumor cell growth by destabilizing AKT through ZNRF1-mediated ubiquitin proteosome pathway.

LZTFL1 is a tumor suppressor located in chromosomal region 3p21.3 that is deleted frequently and early in various cancer types including the kidney cancer. However, its role in kidney tumorigenesis remains unknown. Here we hypothesized a tumor suppressive function of LZTFL1 in clear cell renal cell carcinoma (ccRCC) and its mechanism of action based on extensive bioinformatics analysis of patients' tumor data and validated it using both gain- and loss-functional studies in kidney tumor cell lines and patient-derive xenograft (PDX) model systems. Our studies indicated that LZTFL1 inhibits kidney tumor cell proliferation by destabilizing AKT through ZNRF1-mediated ubiquitin proteosome pathway and inducing cell cycle arrest at G1. Clinically, we found that LZTFL1 is frequently deleted in ccRCC. Downregulation of LZTFL1 is associated with a poor ccRCC outcome and may be used as prognostic maker. Furthermore, we show that overexpression of LZTFL1 in PDX via lentiviral delivery suppressed PDX growth, suggesting that re-expression of LZTFL1 may be a therapeutic strategy against ccRCC.