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.

Diagnostic performance of machine learning in systemic infection following percutaneous nephrolithotomy and identification of associated risk factors.

Objective: This study aims to investigate the predictive performance of machine learning in predicting the occurrence of systemic inflammatory response syndrome (SIRS) and urosepsis after percutaneous nephrolithotomy (PCNL). Methods: A retrospective analysis was conducted on patients who underwent PCNL treatment between January 2016 and July 2022. Machine learning techniques were employed to establish and select the best predictive model for postoperative systemic infection. The feasibility of using relevant risk factors as predictive markers was explored through interpretability with Machine Learning. Results: A total of 1067 PCNL patients were included in this study, with 111 (10.4 %) patients developing SIRS and 49 (4.5 %) patients developing urosepsis. In the validation set, the risk model based on the GBM protocol demonstrated a predictive power of 0.871 for SIRS and 0.854 for urosepsis. Preoperative and postoperative platelet changes were identified as the most significant predictors. Both thrombocytopenia and thrombocytosis were found to be risk factors for SIRS or urosepsis after PCNL. Furthermore, it was observed that when the change in platelet count before and after PCNL surgery exceeded 30*109/L (whether an increase or decrease), the risk of developing SIRS or urosepsis significantly increased. Conclusion: Machine learning can be effectively utilized for predicting the occurrence of SIRS or urosepsis after PCNL. The changes in platelet count before and after PCNL surgery serve as important predictors.

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.

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.

PABPC1L Induces IDO1 to Promote Tryptophan Metabolism and Immune Suppression in Renal Cell Carcinoma.

The tumor microenvironment (TME) in renal cell carcinomas (RCC) is marked by substantial immunosuppression and immune resistance despite having extensive T-cell infiltration. Elucidation of the mechanisms underlying immune evasion could help identify therapeutic strategies to boost the efficacy of immune checkpoint blockade (ICB) in RCC. This study uncovered a mechanism wherein the polyadenylate-binding protein PABPC1L modulates indoleamine 2,3-dioxygenase 1 (IDO1), a prospective target for immunotherapy. PABPC1L was markedly upregulated in RCC, and high PABPC1L expression correlated with unfavorable prognosis and resistance to ICB. PABPC1L bolstered tryptophan metabolism by upregulating IDO1, inducing T-cell dysfunction and Treg infiltration. PABPC1L enhanced the stability of JAK2 mRNA, leading to increased JAK2-STAT1 signaling that induced IDO1 expression. Additionally, PABPC1L-induced activation of the JAK2-STAT1 axis created a positive feedback loop to promote PABPC1L transcription. Conversely, loss of PABPC1L diminished IDO1 expression, mitigated cytotoxic T-cell suppression, and enhanced responsiveness to anti-PD-1 therapy in patient-derived xenograft models. These findings reveal the crucial role of PABPC1L in facilitating immune evasion in RCC and indicate that inhibiting PABPC1L could be a potential immunotherapeutic approach in combination with ICB to improve patient outcomes. SIGNIFICANCE: PABPC1L functions as a key factor in renal cell carcinoma immune evasion, enhancing IDO1 and impeding T-cell function, and represents a potential target to enhance the efficacy of immune checkpoint blockade therapy.

Human papillomavirus infection affects treatment outcomes and the immune microenvironment in patients with advanced penile squamous cell carcinoma receiving programmed cell death protein 1 inhibitor-based combination therapy.

BACKGROUND: Penile squamous cell carcinoma (PSCC) is a human papillomavirus (HPV)-associated malignancy. Immunotherapy is emerging as a potential treatment for advanced PSCC. In this study, the authors analyzed the association of HPV status with outcomes and the immune microenvironment in patients with advanced PSCC undergoing programmed cell death protein 1 (PD1) inhibitor-based combination therapy (PCT). METHODS: HPV status was assessed using quantitative polymerase chain reaction in 87 patients with advanced PSCC treated with PCT. Objective response rate (ORR), disease control rate (DCR), progression-free survival (PFS), and overall survival (OS) in the HPV+ and HPV- groups were compared. Additionally, bulk RNA sequencing was performed to investigate the potential impact of HPV on the immune microenvironment in advanced PSCC. RESULTS: Among patients receiving first-line PCT, ORR (91.7% vs. 64.6%, p = .014) and DCR (100.0% vs. 79.2%, p = .025) in the HPV+ group were higher compared to the HPV- group. Kaplan-Meier curves demonstrated that the HPV+ group exhibited superior PFS (p = .005) and OS (p = .004) for patients in the first-line setting. However, these advantages of HPV infection were not observed in multi-line PCT (p > .050). HPV status remained an independent prognostic factor for predicting better ORR (p = .024), PFS (p = .002), and OS (p = .020) in the multivariate analyses. Landmark analyses showed that the HPV-induced superiority of PFS occurred at an early stage (within 3 months) and OS occurred at a relatively late stage (within 9 months). Bioinformatic analyses identified potential immune-activated genes (GLDC, CYP4F12, etc.) and pathways (RAGE, PI3K/AKT, etc.), antitumor immune cell subtypes, and lower tumor immune dysfunction and exclusion scores in HPV+ tissues. CONCLUSIONS: HPV infection may confer treatment efficacy and survival benefits in patients with advanced PSCC receiving first-line PCT because of the possible stimulation of the antitumor immune microenvironment. PLAIN LANGUAGE SUMMARY: Human papillomavirus (HPV) infection may induce better objective response rate, progression-free survival (PFS), and overall survival (OS) for advanced penile squamous cell carcinoma (PSCC) patients receiving first-line programmed cell death protein 1 inhibitor-based combination therapy (PCT) instead of multi-line PCT. HPV infection-induced PFS advantage occurs at an early stage (within 3 months) whereas OS superiority occurs at a relatively late stage (within 9 months). Antitumor immune microenvironment could be stimulated by HPV infection in advanced PSCC tissues.

A novel multimodal prediction model based on DNA methylation biomarkers and low-dose computed tomography images for identifying early-stage lung cancer.

Objective: DNA methylation alterations are early events in carcinogenesis and immune signalling in lung cancer. This study aimed to develop a model based on short stature homeobox 2 gene (SHOX2)/prostaglandin E receptor 4 gene (PTGER4) DNA methylation in plasma, appearance subtype of pulmonary nodules (PNs) and low-dose computed tomography (LDCT) images to distinguish early-stage lung cancers. Methods: We developed a multimodal prediction model with a training set of 257 individuals. The performance of the multimodal prediction model was further validated in an independent validation set of 42 subjects. In addition, we explored the association between SHOX2/PTGER4 DNA methylation and driver gene mutations in lung cancer based on data from The Cancer Genome Atlas (TCGA) portal. Results: There were significant differences between the early-stage lung cancers and benign groups in the methylation levels. The area under a receiver operator characteristic curve (AUC) of SHOX2 in patients with solid nodules, mixed ground-glass opacity nodules and pure ground-glass opacity nodules were 0.693, 0.497 and 0.864, respectively, while the AUCs of PTGER4 were 0.559, 0.739 and 0.619, respectively. With the highest AUC of 0.894, the novel multimodal prediction model outperformed the Mayo Clinic model (0.519) and LDCT-based deep learning model (0.842) in the independent validation set. Database analysis demonstrated that patients with SHOX2/PTGER4 DNA hypermethylation were enriched in TP53 mutations. Conclusions: The present multimodal prediction model could more efficiently distinguish early-stage lung cancer from benign PNs. A prognostic index based on DNA methylation and lung cancer driver gene alterations may separate the patients into groups with good or poor prognosis.

Bladder cancer intrinsic LRFN2 drives anticancer immunotherapy resistance by attenuating CD8+ T cell infiltration and functional transition.

BACKGROUND: Immune checkpoint inhibitor (ICI) therapy improves the survival of patients with advanced bladder cancer (BLCA); however, its overall effectiveness is limited, and many patients still develop immunotherapy resistance. The leucine-rich repeat and fibronectin type-III domain-containing protein (LRFN) family has previously been implicated in regulating brain dysfunction; however, the mechanisms underlying the effect of LRFN2 on the tumor microenvironment (TME) and immunotherapy remain unclear. METHODS: Here we combined bulk RNA sequencing, single-cell RNA sequencing, ProcartaPlex multiple immunoassays, functional experiments, and TissueFAXS panoramic tissue quantification assays to demonstrate that LRFN2 shapes a non-inflammatory TME in BLCA. RESULTS: First, comprehensive multiomics analysis identified LRFN2 as a novel immunosuppressive target specific to BLCA. We found that tumor-intrinsic LRFN2 inhibited the recruitment and functional transition of CD8+ T cells by reducing the secretion of pro-inflammatory cytokines and chemokines, and this mechanism was verified in vitro and in vivo. LRFN2 restrained antitumor immunity by inhibiting the infiltration, proliferation, and differentiation of CD8+ T cells in vitro. Furthermore, a spatial exclusivity relationship was observed between LRFN2+ tumor cells and CD8+ T cells and cell markers programmed cell death-1 (PD-1) and T cell factor 1 (TCF-1). Preclinically, LRFN2 knockdown significantly enhanced the efficacy of ICI therapy. Clinically, LRFN2 can predict immunotherapy responses in real-world and public immunotherapy cohorts. Our results reveal a new role for LRFN2 in tumor immune evasion by regulating chemokine secretion and inhibiting CD8+ T-cell recruitment and functional transition. CONCLUSIONS: Thus, LRFN2 represents a new target that can be combined with ICIs to provide a potential treatment option for BLCA.

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.

Mitochondria-ER contact mediated by MFN2-SERCA2 interaction supports CD8+ T cell metabolic fitness and function in tumors.

Metabolic fitness of T cells is essential for their vitality, which is largely dependent on the behavior of the mitochondria. The nature of mitochondrial behavior in tumor-infiltrating T cells remains poorly understood. In this study, we show that mitofusin-2 (MFN2) expression is positively correlated with the prognosis of multiple cancers. Genetic ablation of Mfn2 in CD8+ T cells dampens mitochondrial metabolism and function and promotes tumor progression. In tumor-infiltrating CD8+ T cells, MFN2 enhances mitochondria-endoplasmic reticulum (ER) contact by interacting with ER-embedded Ca2+-ATPase SERCA2, facilitating the mitochondrial Ca2+ influx required for efficient mitochondrial metabolism. MFN2 stimulates the ER Ca2+ retrieval activity of SERCA2, thereby preventing excessive mitochondrial Ca2+ accumulation and apoptosis. Elevating mitochondria-ER contact by increasing MFN2 in CD8+ T cells improves the efficacy of cancer immunotherapy. Thus, we reveal a tethering-and-buffering mechanism of organelle cross-talk that regulates the metabolic fitness of tumor-infiltrating CD8+ T cells and highlights the therapeutic potential of enhancing MFN2 expression to optimize T cell function.

Therapeutic implications for localized prostate cancer by multiomics analyses of the ageing microenvironment landscape.

Background: Numerous studies have substantiated the association between aging and the progression of malignant tumors in humans, notably prostate cancer (PCa). Nevertheless, to the best of our knowledge, no studies have comprehensively elucidated the intricate characteristics of the aging microenvironment (AME) in PCa. Methods: AME regulatory patterns were determined using the NMF algorithm. Then an ageing microenvironment index (AMI) was constructed, with excellent prognostic and immunotherapy prediction ability, and its' clinical relevance was surveyed through spatial transcriptomics. Further, the drug response was analysed using the Genomics of Drug Sensitivity in Cancer (GDSC), the Connectivity Map (CMap) and CellMiner database for patients with PCa. Finally, the AME was studied using in vitro and vivo experiments. Results: Three different AME regulatory patterns were identified across 813 PCa patients, associated with distinct clinical prognosis and physiological pathways. Based on the AMI, patients with PCa were divided into the high-score and low-score subsets. Higher AMI score was significantly infiltrated with more immune cells, higher rate of biochemical recurrence (BCR) and worse response to immunotherapy, antiandrogen therapy and chemotherapy in PCa. In addition, we found that the combination of bicalutamide and embelin was capable of suppressing tumor growth of PCa. Besides, as the main components of AMI, COL1A1 and BGLAP act as oncogenes and were verified via in vivo and in vitro experiments. Conclusions: AME regulation is significantly associated with the diversity and complexity of TME. Quantitative evaluation of the AME regulatory patterns may provide promising novel molecular markers for individualised therapy in PCa.

PD-L1 Expression is Linked to Tumor-Infiltrating T-Cell Exhaustion and Adverse Pathological Behavior in Pheochromocytoma/Paraganglioma.

Pheochromocytoma/paraganglioma (PPGL) is an endocrine-related tumor associated with excessive catecholamine release and has limited treatment options once metastasis occurs. Although recent phase 2 clinical trials of immune checkpoint inhibitors in the treatment of PPGL have preliminarily shown promising results, the fundamentals of immunotherapy for PPGL have not yet been established. In the early research, using bulk RNA sequencing of tumor samples from 7 PPGL patients, we found that PPGL tumor tissues exhibited high PD-L1 mRNA expression compared with adjacent normal adrenal medulla tissues, and this was related to T-cell exhaustion biomarkers. To further validate the association, in this study (n = 60), we first stratified all PPGL samples according to PD-L1 expression as determined by immunohistochemical staining, and then subjected 23 fresh PPGL tumor samples from the cohort to a quantitative polymerase chain reaction (n = 16), flow cytometry (n = 7), and multiplex-immunofluorescence staining. Subsequently, we evaluated the pathological manifestations of all 60 PPGL tumor samples and analyzed the correlation among PD-L1 expression, adverse pathological behavior, various clinicopathological data, and genotypes in PPGL. The results showed that PD-L1-positive expression correlated with the exhaustion of tumor-infiltrating T cells, preoperative abnormal elevation of plasma norepinephrine, high Ki67 index, and adverse pathological behavior in PPGL but not with genetic mutation or metastatic disease, possibly due to the limitation of the small number of patients with metastatic disease (n = 4) in the study cohort. In conclusion, our findings reveal that PD-L1 expression is associated with T-cell exhaustion and adverse pathological behavior in PPGL. These results are expected to provide a new theoretical basis and clinical guidance for the treatment of PPGL.

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.

Multimodal recurrence scoring system for prediction of clear cell renal cell carcinoma outcome: a discovery and validation study.

BACKGROUND: Improved markers for predicting recurrence are needed to stratify patients with localised (stage I-III) renal cell carcinoma after surgery for selection of adjuvant therapy. We developed a novel assay integrating three modalities-clinical, genomic, and histopathological-to improve the predictive accuracy for localised renal cell carcinoma recurrence. METHODS: In this retrospective analysis and validation study, we developed a histopathological whole-slide image (WSI)-based score using deep learning allied to digital scanning of conventional haematoxylin and eosin-stained tumour tissue sections, to predict tumour recurrence in a development dataset of 651 patients with distinctly good or poor disease outcome. The six single nucleotide polymorphism-based score, which was detected in paraffin-embedded tumour tissue samples, and the Leibovich score, which was established using clinicopathological risk factors, were combined with the WSI-based score to construct a multimodal recurrence score in the training dataset of 1125 patients. The multimodal recurrence score was validated in 1625 patients from the independent validation dataset and 418 patients from The Cancer Genome Atlas set. The primary outcome measured was the recurrence-free interval (RFI). FINDINGS: The multimodal recurrence score had significantly higher predictive accuracy than the three single-modal scores and clinicopathological risk factors, and it precisely predicted the RFI of patients in the training and two validation datasets (areas under the curve at 5 years: 0·825-0·876 vs 0·608-0·793; p<0·05). The RFI of patients with low stage or grade is usually better than that of patients with high stage or grade; however, the RFI in the multimodal recurrence score-defined high-risk stage I and II group was shorter than in the low-risk stage III group (hazard ratio [HR] 4·57, 95% CI 2·49-8·40; p<0·0001), and the RFI of the high-risk grade 1 and 2 group was shorter than in the low-risk grade 3 and 4 group (HR 4·58, 3·19-6·59; p<0·0001). INTERPRETATION: Our multimodal recurrence score is a practical and reliable predictor that can add value to the current staging system for predicting localised renal cell carcinoma recurrence after surgery, and this combined approach more precisely informs treatment decisions about adjuvant therapy. FUNDING: National Natural Science Foundation of China, and National Key Research and Development Program of China.

Single-cell and spatial transcriptomics reveal 5-methylcytosine RNA methylation regulators immunologically reprograms tumor microenvironment characterizations, immunotherapy response and precision treatment of clear cell renal cell carcinoma.

Clear cell Renal Cell Carcinoma (ccRCC) is a highly heterogeneous disease, making it challenging to predict prognosis and therapy efficacy. In this study, we aimed to explore the role of 5-methylcytosine (m5C) RNA modification in ccRCC and its potential as a predictor for therapy response and overall survival (OS). We established a novel 5-methylcytosine RNA modification-related gene index (M5CRMRGI) and studied its effect on the tumor microenvironment (TME) using single-cell sequencing data for in-depth analysis, and verified it using spatial sequencing data. Our results showed that M5CRMRGI is an independent predictor of OS in multiple datasets and exhibited outstanding performance in predicting the OS of ccRCC. Distinct mutation profiles, hallmark pathways, and infiltration of immune cells in TME were observed between high- and low-M5CRMRGI groups. Single-cell/spatial transcriptomics revealed that M5CRMRGI could reprogram the distribution of tumor-infiltrating immune cells. Moreover, significant differences in tumor immunogenicity and tumor immune dysfunction and exclusion (TIDE) were observed between the two risk groups, suggesting a better response to immune checkpoint blockade therapy of the high-risk group. We also predicted six potential drugs binding to the core target of the M5CRMRGI signature via molecular docking. Real-world treatment cohort data proved once again that high-risk patients were appropriate for immune checkpoint blockade therapy, while low-risk patients were appropriate for Everolimus. Our study shows that the m5C modification landscape plays a role in TME distribution. The proposed M5CRMRGI-guided strategy for predicting survival and immunotherapy efficacy, we reported here, might also be applied to more cancers other than ccRCC.

MFN2 suppresses clear cell renal cell carcinoma progression by modulating mitochondria-dependent dephosphorylation of EGFR.

BACKGROUND: Clear cell renal cell carcinoma (ccRCC) is the most lethal renal cancer. An overwhelming increase of patients experience tumor progression and unfavorable prognosis. However, the molecular events underlying ccRCC tumorigenesis and metastasis remain unclear. Therefore, uncovering the underlying mechanisms will pave the way for developing novel therapeutic targets for ccRCC. In this study, we sought to investigate the role of mitofusin-2 (MFN2) in supressing ccRCC tumorigenesis and metastasis. METHODS: The expression pattern and clinical significance of MFN2 in ccRCC were analyzed by using the Cancer Genome Atlas datasets and samples from our independent ccRCC cohort. Both in vitro and in vivo experiments, including cell proliferation, xenograft mouse models and transgenic mouse model, were used to determine the role of MFN2 in regulating the malignant behaviors of ccRCC. RNA-sequencing, mass spectrum analysis, co-immunoprecipitation, bio-layer interferometry and immunofluorescence were employed to elucidate the molecular mechanisms for the tumor-supressing role of MFN2. RESULTS: we reported a tumor-suppressing pathway in ccRCC, characterized by mitochondria-dependent inactivation of epidermal growth factor receptor (EGFR) signaling. This process was mediated by the outer mitochondrial membrane (OMM) protein MFN2. MFN2 was down-regulated in ccRCC and associated with favorable prognosis of ccRCC patients. in vivo and in vitro assays demonstrated that MFN2 inhibited ccRCC tumor growth and metastasis by suppressing the EGFR signaling pathway. In a kidney-specific knockout mouse model, loss of MFN2 led to EGFR pathway activation and malignant lesions in kidney. Mechanistically, MFN2 preferably binded small GTPase Rab21 in its GTP-loading form, which was colocalized with endocytosed EGFR in ccRCC cells. Through this EGFR-Rab21-MFN2 interaction, endocytosed EGFR was docked to mitochondria and subsequently dephosphorylated by the OMM-residing tyrosine-protein phosphatase receptor type J (PTPRJ). CONCLUSIONS: Our findings uncover an important non-canonical mitochondria-dependent pathway regulating EGFR signaling by the Rab21-MFN2-PTPRJ axis, which contributes to the development of novel therapeutic strategies for ccRCC.

Robot-assisted partial nephrectomy for large complex renal cancer: step-by-step segmental artery unclamping

ABSTRACT Introduction Main renal artery clamping and selective arterial clamping are two conventional devascularization methods for robot-assisted partial nephrectomy (RAPN) (1, 2). Decreasing warm ischemic (WI) time (3, 4) and improving clear surgical visualization (5) are the main surgically modifiable factors for RAPN, especially in large complex renal cancer (6). In this study, we described our surgical technique, focusing on gradual segmental artery unclamping on patients with large renal tumors. Material and methods Two patients (R.E.N.A.L score 10 and 11) underwent RAPN with gradual segmental artery unclamping (Figures 1 and 2). The unclamping included five key steps. First, all renal segmental arteries were identified as tumor feeding vessel(s) and the vessels for normal kidney parenchyma under the guidance of CT angiography (CTA) 3-division (3D) reconstruction. Second, all segmental arteries were isolated, and the feeding one(s) should be blocked before other arteries were blocked. Third, the tumor was resected outside the pseudocapsule, and the deep resection bed was sutured for initial hemostasis. Fourth, the segmental arteries were reopened except for the tumor feeding one(s), and normal kidney parenchyma restored blood supply. And fifth, the resection bed was completely sutured, and the feeding vessel supplying the tumor was opened after the suture. Warm ischemia time (WIT) was defined as the time measured between clamping and unclamping of the renal artery. WIT1 was the time for normal kidney parenchyma and WIT2 was the time for resection area. Patient demographics, perioperative variables, and warm ischemic time were included in our study. And we presented the details of gradual segmental artery unclamping in the video. Results In both cases, the total operation times were 215 and 130 mins for patient 1 and patient 2, respectively. WIT1 and WIT2 for patient 1 were 15 min and 33 min., and WIT1 and WIT2 for patient 2 were 21 min and 32 min, respectivelly. The maximum diameters of the masses resected were 10.8 and 7.3 cm, and surgical margins were negative. No patient had complications after operation. Preoperative and postoperative eGFR did not change significantly. Pre- and postoperative eGFR were 111 and 108 mL/min for patient 1, 91 and 83 mL/min for patient 2, respectively. Key hints for outcomes optimization during RAPN on patients with large complex renal tumors: 1) Each segmental renal artery is precised clamped before we excise the tumor, and an excellent surgical vision is essential for precising excision and shortening clamping time, 2) Other segmental renal arteries are unclamped except tumor feeding branch after suturing deep layer of parenchyma, and most normal parenchyma restores blood supply, 3) Preoperative high-resolution computed tomography angiography (CTA) and 3D reconstructive renal structure serve as a guide to clear the approach to find the tumor and segmental arteries (7, 8). Conclusions Gradual segmental artery unclamping is feasible and efficient to excise large complex renal cancer. Compared with main renal artery clamping, it can shorten the warm ischemic time of normal parenchyma; On the other hand, compared with selective segmental arterial clamping, the technique can reduce bleeding from the deep resection bed, keep a clear surgical vision, and decrease the incidence of positive margin.

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.

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.

Exosomal circSPIRE1 mediates glycosylation of E-cadherin to suppress metastasis of renal cell carcinoma.

Metastasis is the main cause of mortality in renal cell carcinoma (RCC). Circular RNAs (circRNAs) involvement in RCC metastasis has been described, although the underlying mechanisms remain unknown. We evaluated recurring lung-metastasis cases using patient-derived xenograft models and isolated a highly metastatic clone. CircSPIRE1 was identified as a metastasis-inhibiting circRNA in clinical cohort and xenograft models. Mechanistically, circSPIRE1 suppressed mesenchymal state through regulating ELAV like RNA binding protein 1-mRNA binding, and upregulating polypeptide N-acetylgalactosaminyltransferase 3 (GALNT3) and KH domain RNA binding protein (QKI) expression. GALNT3 promoted glycosylation and cytomembrane localization of E-cadherin. QKI formed a positive feedback loop to enhance circSPIRE1 expression. Meanwhile, exosomal circSPIRE1 suppressed angiogenesis and vessel permeability. Our work reveals a non-canonical route for circRNAs in RCC to suppress metastasis. Furthermore, a nanomedicine consisting of circSPIRE1 plasmid suppressed metastasis formation. In conclusion, circSPIRE1 may be a predictor of metastasis and a potential therapeutic target of metastatic RCC.