Exosome-related lncRNA score: A value-based individual treatment strategy for predicting the response to immunotherapy in clear cell renal cell carcinoma.

BACKGROUND: Exosomes play a crucial role in intercellular communication in clear cell renal cell carcinoma (ccRCC), while the long non-coding RNAs (lncRNAs) are implicated in tumorigenesis and progression. AIMS: The purpose of this study is to construction a exosomes-related lncRNA score and a ceRNA network to predict the response to immunotherapy and potential targeted drug in ccRCC. METHODS: Data of ccRCC patients were obtained from the TCGA database. Pearson correlation analysis was used to identify eExosomes-related lncRNAs (ERLRs) from Top10 exosomes-related genes that have been screened. The entire cohort was randomly divided into a training cohort and a validation cohort in equal scale. LASSO regression and multivariate cox regression was used to construct the ERLRs-based score. Differences in clinicopathological characteristics, immune microenvironment, immune checkpoints, and drug susceptibility between the high- and low-risk groups were also investigated. Finally, the relevant ceRNA network was constructed by machine learning to analyze their potential targets in immunotherapy and drug use of ccRCC patients. RESULTS: A score consisting of 4ERLRs was identified, and patients with higher ERLRs-based score tended to have a worse prognosis than those with lower ERLRs-based score. ROC curves and multivariate Cox regression analysis demonstrated that the score could be considered as a risk factor for prognosis in both training and validation cohorts. Moreover, patients with high scores are predisposed to experience poor overall survival, a larger prevalence of advanced stage (III-IV), a greater tumor mutational burden, a higher infiltration of immunosuppressive cells, and a greater likelihood of responding favorably to immunotherapy. The importance of EMX2OS was determined by mechanical learning, and the ceRNA network was constructed, and EMX2OS may be a potential therapeutic target, possibly exerting its function through the EMX2OS/hsa-miR-31-5p/TLN2 axis. CONCLUSIONS: Based on machine learning, a novel ERLRs-based score was constructed for predicting the survival of ccRCC patients. The ERLRs-based score is a promising potential independent prognostic factor that is closely correlated with the immune microenvironment and clinicopathological characteristics. Meanwhile, we screened out key lncRNAEMX2OS and identified the EMX2OS/hsa-miR-31-5p/TLN2 axis, which may provide new clues for the targeted therapy of ccRCC.

High serum sodium predicts immunotherapy response in metastatic renal cell and urothelial carcinoma.

OBJECTIVES: The development of reliable biomarkers for the prediction of immune checkpoint inhibition (ICI) response in patients with metastatic renal cell carcinoma (mRCC) and urothelial carcinoma (mUC) remains an unresolved challenge. Conventional ICI biomarkers typically focus on tumor-related factors such as PD-L1 expression. However, a comprehensive evaluation of the predictive value of serum electrolyte levels, a so far widely unexplored area, is still pending. METHODS: We conducted a post-hoc analysis of baseline sodium, potassium, chloride, magnesium and calcium levels in two independent phase 3 clinical trials: IMvigor211 for mUC comparing atezolizumab to chemotherapy, and IMmotion151 for mRCC comparing atezolizumab+bevacizumab to sunitinib. This analysis aimed to evaluate the prognostic and predictive value of these electrolyte levels in these clinical settings. A total of 1787 patients (IMvigor211 n = 901; IMmotion151 n = 886) were analyzed. RESULTS: We found a linear correlation of baseline serum sodium and chloride with prognosis across both trials, which was not found for potassium, magnesium and calcium. In multivariate analysis, the prognostic capacity of sodium was limited to patients receiving ICI as compared to the control group. Interestingly, in both studies, the chance of achieving an objective response was highest in the patient subgroup with high baseline serum sodium levels of > 140 mmol/L (IMmotion151: Complete response in 17.9% versus 2.0% in patients with mRCC with baseline sodium < 135 mmol/L). Serum sodium outperformed tumor PD-L1 expression as a predictor for immunotherapy efficacy. CONCLUSIONS: Patients exhibiting elevated serum sodium levels derive the greatest benefit from immunotherapy, suggesting that baseline serum concentration could serve as a valuable and cost-effective predictive biomarker for immunotherapy across entities.

Prognostic impact and immunotherapeutic implications of NETosis-related prognostic model in clear cell renal cell carcinoma.

BACKGROUND: The ramifications of necroptosis on the prognostication of clear cell renal cell carcinoma (ccRCC) remain inadequately expounded. METHODS: A prognostic model delineating the facets of necroptosis in ccRCC was constructed, employing a compendium of algorithms. External validation was effectuated using the E-MTAB-1980 dataset. The exploration of immune infiltration scores was undertaken through the exploitation of multiple algorithms. Single-cell RNA sequencing data were procured from the GSE171306 dataset. Real-time quantitative PCR (RT-qPCR) was engaged to scrutinize the differential expression of SLC25A37 across cancer and paracancer tissues, as well as diverse cell lines. Assessments of proliferative and metastatic alterations in 769-P and 786-O cells were accomplished through Cell Counting Kit-8 (CCK8) and wound healing assays. RESULTS: The necroptosis-related signature (NRS) emerges as a discerning metric, delineating patients' immune attributes, tumor mutation burden, immunotherapy response, and drug susceptibility. Single-cell RNA sequencing analysis unveils the marked enrichment of SLC25A37 in tumor cells. Concurrently, RT-qPCR discloses the overexpression of SLC25A37 in both ccRCC tissues and cell lines. SLC25A37 knockdown mitigates the proliferative and metastatic propensities of 769-P and 786-O cells, as evidenced by CCK8 and wound healing assays. CONCLUSION: The NRS assumes a pivotal role in ascertaining the prognosis, tumor mutation burden, immunotherapy response, drug susceptibility, and immune cell infiltration features of ccRCC patients. SLC25A37 emerges as a putative player in immunosuppressive microenvironments, thereby providing a prospective avenue for the design of innovative immunotherapeutic targets for ccRCC.

Construction of exosome-related genes risk model in kidney cell carcinoma predicts prognosis and immune therapy response.

Renal cell carcinoma (RCC) is one of the most prevalent types of urological cancer. Exosomes are vesicles derived from cells and have been found to promote the development of RCC, but the potential biomarker and molecular mechanism of exosomes on RCC remain ambiguous. Here, we first screened differentially expressed exosome-related genes (ERGs) by analyzing The Cancer Genome Atlas (TCGA) database and exoRBase 2.0 database. We then determined prognosis-related ERGs (PRERGs) by univariate Cox regression analysis. Gene Dependency Score (gDS), target development level, and pathway correlation analysis were utilized to examine the importance of PRERGs. Machine learning and lasso-cox regression were utilized to screen and construct a 5-gene risk model. The risk model showed high predictive accuracy for the prognosis of patients and proved to be an independent prognostic factor in three RCC datasets, including TCGA-KIRC, E-MTAB-1980, and TCGA-KIRP datasets. Patients with high-risk scores showed worse outcomes in different clinical subgroups, revealing that the risk score is robust. In addition, we found that immune-related pathways are highly enriched in the high-risk group. Activities of immune cells were distinct in high-/low-risk groups. In independent immune therapeutic cohorts, high-risk patients show worse immune therapy responses. In summary, we identified several exosome-derived genes that might play essential roles in RCC and constructed a 5-gene risk signature to predict the prognosis of RCC and immune therapy response.

Tumor microenvironment and clinical efficacy of first line immunotherapy-based combinations in metastatic renal cell carcinoma.

The impact of tumor microenvironment (TME) in influencing clinical response to first-line immune checkpoint inhibitor (ICI)-based treatment in advanced renal cell carcinoma (RCC) is unclear. Immunohistochemistry (IHC) could identify biomarkers related to immune checkpoints and immune cell population. This study retrospectively characterized TME from 28 RCC patients who received first line ICI-based therapy through IHC assessment of selected markers and explored preliminary evidence about their possible correlation with treatment efficacy. We found a significantly higher count of CD80+, CD163+ cells and their ratio in RCC with clear cell component compared to those without clear cell features; additionally, patients with metastatic disease at diagnosis were associated with higher expression of CD163+ cells, while higher count of CD4+ cells and CD4+/CD8+ ratio were found in RCC with sarcomatoid features. Patients achieving partial or complete response were associated with lower expression of CD163+ cells (median 28 vs 47; p = 0.049). Furthermore, lower expression of CD163+ was associated with better PFS (median PFS 20.0 vs 4.7 months; HR 0.22 p = 0.011) and OS (median OS NR vs 14.4 months; HR 0.28 p = 0.036). A longer OS was reported in PD-L1 CPS negative patients (median OS NR vs 11.8 months; HR 0.20 p = 0.024). High infiltration of CD163+ macrophages, who typically present "anti-inflammatory" M2-like phenotype, could identify a subgroup of patients with poor survival after receiving first-line ICI.

Banana-shaped survival curves of metastatic renal cell carcinoma treated with first-line immune-combinations, not just a matter of "palateau".

The first-line therapy of metastatic renal cell carcinoma (mRCC) has revolutionized with the approval of immune checkpoint inhibitors (ICIs) in combination with or without tyrosine kinase inhibitors (TKIs). The choice among the many different immuno-combinations (ICI-ICI or ICI-TKI) is challenging due to the lack of predictive factors. The different shapes of the Kaplan-Meier survival curves (e.g. "banana-shaped curves") have raised many questions on the long-term survival benefit. Here, we analyzed the factors that could have impacted the different long-term survival, including the prognostic factors distribution (IMDC score), histological factors (sarcomatoid features, PD-L1 expression), and treatment characteristics (mechanism of action, duration, discontinuation rate). This overview highlights the factors that should be considered in the first-line setting for the patients' therapeutic choice and prognostic assessment. They are also fundamental parameters to examined for head-to-head studies and real-life, large-scale studies.

Tumor infiltrating B lymphocytes (TIBs) associate with poor clinical outcomes, unfavorable therapeutic benefit and immunosuppressive context in metastatic clear cell renal cell carcinoma (mccRCC) patients treated with anti-PD-1 antibody plus Axitinib.

PURPOSE: Immune checkpoint inhibitors (ICIs) plus tyrosine kinase inhibitors (TKIs) has become first-line therapy for metastatic renal cell carcinoma patients. This study aims to investigate the effect of tumor infiltrating B lymphocytes (TIBs) on the combination therapy. METHODS: The retrospective analysis was conducted on the clinical records of 115 metastatic clear cell renal cell carcinoma (mccRCC) patients treated with anti-PD-1 antibody plus Axitinib between March 2020 and June 2023. Observation target: objective response rate (ORR), and overall survival (OS), progression-free survival (PFS) and immune profile. RESULTS: Patients with high TIBs portended lower ORR of the combination therapy (p = 0.033). TIBs was an independent predictor for poorer OS (p = 0.013) and PFS (p = 0.021) in mccRCC patients with combination treatment. TIBs infiltration was associated with more CD4+T (p < 0.001), CD8+T (p < 0.001), M2 macrophages (p = 0.020) and regulatory T cells (Tregs) (p = 0.004). In TIBs high patients, the percentages of PD-1, CTLA-4 and TIM-3 positive rate were significantly increased in CD4+T (p = 0.038, 0.029 and 0.002 respectively) and CD8+T cells (p = 0.006, 0.026 and < 0.001 respectively). CONCLUSIONS: Our study revealed TIBs infiltration predicted adverse outcomes in mccRCC patients treated with anti-PD-1 antibody plus Axitinib. As a corollary, TIBs positively associated with M2 macrophages and Tregs, leading to subsequent multiple immune checkpoints related exhaustion of T cells. Thus, only PD-1 blockade are inadequate to reverse T cells exhaustion effectively in high TIBs mccRCC patients.

MOICS, a novel classier deciphering immune heterogeneity and aid precise management of clear cell renal cell carcinoma at multiomics level.

Recent studies have indicated that the tumor immune microenvironment plays a pivotal role in the initiation and progression of clear cell renal cell carcinoma (ccRCC). However, the characteristics and heterogeneity of tumor immunity in ccRCC, particularly at the multiomics level, remain poorly understood. We analyzed immune multiomics datasets to perform a consensus cluster analysis and validate the clustering results across multiple internal and external ccRCC datasets; and identified two distinctive immune phenotypes of ccRCC, which we named multiomics immune-based cancer subtype 1 (MOICS1) and subtype 2 (MOICS2). The former, MOICS1, is characterized by an immune-hot phenotype with poor clinical outcomes, marked by significant proliferation of CD4+ and CD8+ T cells, fibroblasts, and high levels of immune inhibitory signatures; the latter, MOICS2, exhibits an immune-cold phenotype with favorable clinical characteristics, characterized by robust immune activity and high infiltration of endothelial cells and immune stimulatory signatures. Besides, a significant negative correlation between immune infiltration and angiogenesis were identified. We further explored the mechanisms underlying these differences, revealing that negatively regulated endopeptidase activity, activated cornification, and neutrophil degranulation may promote an immune-deficient phenotype, whereas enhanced monocyte recruitment could ameliorate this deficiency. Additionally, significant differences were observed in the genomic landscapes between the subtypes: MOICS1 exhibited mutations in TTN, BAP1, SETD2, MTOR, MUC16, CSMD3, and AKAP9, while MOICS2 was characterized by notable alterations in the TGF-ß pathway. Overall, our work demonstrates that multi-immune omics remodeling analysis enhances the understanding of the immune heterogeneity in ccRCC and supports precise patient management.

Bispecific fibrous glue synergistically boosts vascular normalization and antitumor immunity for advanced renal carcinoma therapy.

Immune checkpoint blockade therapy represented by programmed cell death ligand 1 (PD-L1) inhibitor for advanced renal carcinoma with an objective response rate (ORR) in patients is less than 20%. It is attributed to abundant tumoral vasculature with abnormal structure limiting effector T cell infiltration and drug penetration. We propose a bispecific fibrous glue (BFG) to regulate tumor immune and vascular microenvironments simultaneously. The bispecific precursor glue peptide-1 (pre-GP1) can penetrate tumor tissue deeply and self-assemble into BFG in the presence of neuropilin-1 (NRP-1) and PD-L1. The resultant fibrous glue is capable of normalizing tumoral vasculature as well as restricting immune escape. The pre-GP1 retains a 6-fold higher penetration depth than that of antibody in the multicellular spheroids (MCSs) model. It also shows remarkable tumor growth inhibition (TGI) from 19% to 61% in a murine advanced large tumor model compared to the clinical combination therapy. In addition, in the orthotopic renal tumor preclinical model, the lung metastatic nodules are reduced by 64% compared to the clinically used combination. This pre-GP1 provides a promising strategy to control the progression and metastasis of advanced renal carcinoma.

Validation of the Lung Immune Prognostic Index (LIPI) as a prognostic biomarker in metastatic renal cell carcinoma.

BACKGROUND: The Lung Immune Prognostic Index (LIPI) is associated with immune checkpoint inhibitors (ICI) outcomes across different solid tumors, particularly in non-small cell lung cancer. Data regarding the prognostic and/or predictive role of LIPI in metastatic renal cell carcinoma (mRCC) are still scarce. The aim of this study was to evaluate whether LIPI could be predictive of survival in mRCC patients. METHODS: We used patient level data from three different prospective studies (NIVOREN trial: nivolumab; TORAVA trial: VEGF/VEGFR-targeted therapy (TT); CheckMate 214: nivolumab-ipilimumab vs sunitinib). LIPI was calculated based on a derived neutrophils/(leukocyte-neutrophil) ratio > 3 and lactate-dehydrogenase >upper limit of normal, classifying patients into three groups (LIPI good, 0 factors;LIPI intermediate (int), 1 factor;LIPI poor, 2 factors) and/or into two groups (LIPI good, 0 factors;LIPI int/poor, 1-2 factors) according to trial sample size. Primary and secondary endpoints were overall survival (OS) and progression-free survival (PFS). RESULTS: In the Nivolumab dataset (n = 619), LIPI was significantly associated with OS (LIPI-good 30.1 vs 13.8 months in the LIPI int/poor; HR= 0.47) and PFS (HR=0.74). In the VEGF/VEGFR-TT dataset (n = 159), only a correlation with PFS was observed. In the CheckMate214 dataset (n = 1084), LIPI was significantly associated with OS (nivolumab-ipilimumab OS LIPI good vs int/poor: HR=0.55, p < 0.0001; sunitinib: OS LIPI good vs int/poor: 0.38, p < 0.0001) in both treatment groups in univariate and multivariate analysis. CONCLUSIONS: Pretreatment-LIPI correlated with worse survival outcomes in mRCC treated with either ICI or antiangiogenic therapy, confirming LIPI's prognostic role in mRCC irrespective of systemic treatment used.

Crosstalk of disulfidptosis-related subtypes identifying a prognostic signature to improve prognosis and immunotherapy responses of clear cell renal cell carcinoma patients.

BACKGROUND: Disulfidptosis is a novel form of programmed cell death induced by high SLC7A11 expression under glucose starvation conditions, unlike other known forms of cell death. However, the roles of disulfidptosis in cancers have yet to be comprehensively well-studied, particularly in ccRCC. METHODS: The expression profiles and somatic mutation of DGs from the TCGA database were investigated. Two DGs clusters were identified by unsupervised consensus clustering analysis, and a disulfidptosis-related prognostic signature (DR score) was constructed. Furthermore, the predictive capacity of the DR score in prognosis was validated by several clinical cohorts. We also developed a nomogram based on the DR score and clinical features. Then, we investigated the differences in the clinicopathological information, TMB, tumor immune landscapes, and biological characteristics between the high- and low-risk groups. We evaluated whether the DR score is a robust tool for predicting immunotherapy response by the TIDE algorithm, immune checkpoint genes, submap analysis, and CheckMate immunotherapy cohort. RESULTS: We identified two DGs clusters with significant differences in prognosis, tumor immune landscapes, and clinical features. The DR score has been demonstrated as an independent risk factor by several clinical cohorts. The high-risk group patients had a more complicated tumor immune microenvironment and suffered from more tumor immune evasion in immunotherapy. Moreover, patients in the low-risk group had better prognosis and response to immunotherapy, particularly in anti-PD1 and anti-CTLA-4 inhibitors, which were verified in the CheckMate immunotherapy cohort. CONCLUSION: The DR score can accurately predict the prognosis and immunotherapy response and assist clinicians in providing a personalized treatment regime for ccRCC patients.

A three-gene expression score for predicting clinical benefit to anti-PD-1 blockade in advanced renal cell carcinoma.

In the advanced renal cell carcinoma (RCC) scenario, there are no consistent biomarkers to predict the clinical benefit patients derived from immune checkpoint blockade (ICB). Taking this into consideration, herein, we conducted a retrospective study in order to develop and validate a gene expression score for predicting clinical benefit to the anti-PD-1 antibody nivolumab in the context of patients diagnosed with advanced clear cell RCC enrolled in the CheckMate-009, CheckMate-010, and CheckMate-025 clinical trials. First, a three-gene expression score (3GES) with prognostic value for overall survival integrating HMGA1, NUP62, and ARHGAP42 transcripts was developed in a cohort of patients treated with nivolumab. Its prognostic value was then validated in the TCGA-KIRC cohort. Second, the predictive value for nivolumab was confirmed in a set of patients from the CheckMate-025 phase 3 clinical trial. Lastly, we explored the correlation of our 3GES with different clinical, molecular, and immune tumor characteristics. If the results of this study are definitively validated in other retrospective and large-scale, prospective studies, the 3GES will represent a valuable tool for guiding the design of ICB-based clinical trials in the aRCC scenario in the near future.

Impact of renal cell carcinoma molecular subtypes on immunotherapy and targeted therapy outcomes.

Saliby et al. show that a machine learning approach can accurately classify clear cell renal cell carcinoma (RCC) into distinct molecular subtypes using transcriptomic data. When applied to tumors biospecimens from the JAVELIN Renal 101 (JR101) trial, a benefit is observed with immune checkpoint inhibitor (ICI)-based therapy across all molecular subtypes.

Machine learning-based integration develops a stress response stated T cell (Tstr)-related score for predicting outcomes in clear cell renal cell carcinoma.

BACKGROUND: Establishment of a reliable prognostic model and identification of novel biomarkers are urgently needed to develop precise therapy strategies for clear cell renal cell carcinoma (ccRCC). Stress response stated T cells (Tstr) are a new T-cell subtype, which are related to poor disease stage and immunotherapy response in various cancers. METHODS: 10 machine-learning algorithms and their combinations were applied in this work. A stable Tstr-related score (TCs) was constructed to predict the outcomes and PD-1 blockade treatment response in ccRCC patients. A nomogram based on TCs for personalized prediction of patient prognosis was constructed. Functional enrichment analysis and TimiGP algorithm were used to explore the underlying role of Tstr in ccRCC. The key TCs-related gene was identified by comprehensive analysis, and the bioinformatics results were verified by immunohistochemistry using a tissue microarray. RESULTS: A robust TCs was constructed and validated in four independent cohorts. TCs accurately predicted the prognosis and PD-1 blockade treatment response in ccRCC patients. The novel nomogram was able to precisely predict the outcomes of ccRCC patients. The underlying biological process of Tstr was related to acute inflammatory response and acute-phase response. Mast cells were identified to be involved in the role of Tstr as a protective factor in ccRCC. TNFS13B was shown to be the key TCs-related gene, which was an independent predictor of unfavorable prognosis. The protein expression analysis of TNFSF13B was consistent with the mRNA analysis results. High expression of TNFSF13B was associated with poor response to PD-1 blockade treatment. CONCLUSIONS: This study provides a Tstr cell-related score for predicting outcomes and PD-1 blockade therapy response in ccRCC. Tstr cells may exert their pro-tumoral role in ccRCC, acting against mast cells, in the acute inflammatory tumor microenvironment. TNFSF13B could serve as a key biomarker related to TCs.

Quantification of CD3, FoxP3, and granzyme B immunostaining in canine renal cell carcinoma.

Tumor-infiltrating lymphocyte (TIL) density plays an important role in anti-tumor immunity and is associated with patient outcome in various human and canine malignancies. As a first assessment of the immune landscape of the tumor microenvironment in canine renal cell carcinoma (RCC), we retrospectively analyzed clinical data and quantified CD3, FoxP3, and granzyme B immunostaining in formalin-fixed paraffin-embedded tumor samples from 16 dogs diagnosed with renal cell carcinoma treated with ureteronephrectomy. Cell density was low for all markers evaluated. Increased numbers of intratumoral FoxP3 labelled (+) cells, as well as decreased granzyme B+: FoxP3+ TIL ratio, were associated with poor patient outcomes. Our initial study of canine RCC reveals that these tumors are immunologically cold and Tregs may play an important role in immune evasion.

Targeting STING elicits GSDMD-dependent pyroptosis and boosts anti-tumor immunity in renal cell carcinoma.

While Stimulator-of-interferon genes (STING) is an innate immune adapter cruicial for sensing cytosolic DNA and modulating immune microenvironment, its tumor-promoting role in tumor survival and immune evasion remains largely unknown. Here we reported that renal cancer cells are exceptionally dependent on STING for survival and evading immunosurveillance via suppressing ER stress-mediated pyroptosis. We found that STING is significantly amplified and upregulated in clear cell renal cell carcinoma (ccRCC), and its elevated expression is associated with worse clinical outcomes. Mechanically, STING depletion in RCC cells specifically triggers activation of the PERK/eIF2α/ATF4/CHOP pathway and activates cleavage of Caspase-8, thereby inducing GSDMD-mediated pyroptosis, which is independent of the innate immune pathway of STING. Moreover, animal study revealed that STING depletion promoted infiltration of CD4+ and CD8+ T cells, consequently boosting robust antitumor immunity via pyroptosis-induced inflammation. From the perspective of targeted therapy, we found that Compound SP23, a PROTAC STING degrader, demonstrated comparable efficacy to STING depletion both in vitro and in vivo for treatment of ccRCC. These findings collectively unveiled an unforeseen function of STING in regulating GSDMD-dependent pyroptosis, thus regulating immune response in RCC. Consequently, pharmacological degradation of STING by SP23 may become an attractive strategy for treatment of advanced RCC.

Identify CTBP1-DT as an immunological biomarker that promotes lipid synthesis and apoptosis resistance in KIRC.

Recently, mounting evidence has highlighted the essential function of the C-terminal binding protein-1 divergent transcript (CTBP1-DT) in malignancies. However, its role in kidney renal clear cell carcinoma (KIRC) remains largely unknown. Our study aimed to identify the potential function of CTBP1-DT in KIRC. RT-qPCR, Kaplan-Meier survival analysis, Cox regression analysis, and nomogram analysis were utilized to determine the expression and effects of CTBP1-DT on survival. The subcellular localization of CTBP1-DT was determined using RNA fluorescence in situ hybridization (FISH). To investigate the functions of CTBP1-DT in regulating KIRC cell proliferation, migration, invasion, lipid synthesis, and apoptosis, we conducted CCK8, EdU, Transwell, and Oil Red O staining and cell apoptosis staining assays. The relationships between CTBP1-DT and the tumor microenvironment were investigated with multiple bioinformatics analysis algorithms and databases, including CYBERSORT, TIMER2, Spearman correlation test, tumor mutation burden (TMB), microsatellite instability (MSI), and immunophenoscore (IPS). According to our results, CTBP1-DT is a lncRNA located in the nucleus that is significantly upregulated in KIRC and is correlated with better clinical outcomes. Downregulating CTBP1-DT inhibited cell viability, migration, invasion, and lipid synthesis but triggered cell apoptosis. Additionally, we explored the potential effect of CTBP1-DT in regulating immune cell infiltration in KIRC and other malignancies. Furthermore, CTBP1-DT could be used to predict the effectiveness of targeted drugs and immune checkpoint inhibitors. In conclusion, we identified CTBP1-DT as a potential immunological biomarker and discovered the potential role of CTBP1-DT in regulating lipid synthesis and apoptosis resistance.

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.

Utilizing a novel model of PANoptosis-related genes for enhanced prognosis and immune status prediction in kidney renal clear cell carcinoma.

Kidney renal clear cell carcinoma (KIRC) is the most common histopathologic type of renal cell carcinoma. PANoptosis, a cell death pathway that involves an interplay between pyroptosis, apoptosis and necroptosis, is associated with cancer immunity and development. However, the prognostic significance of PANoptosis in KIRC remains unclear. RNA-sequencing expression and mutational profiles from 532 KIRC samples and 72 normal samples with sufficient clinical data were retrieved from the Cancer Genome Atlas (TCGA) database. A prognostic model was constructed using differentially expressed genes (DEGs) related to PANoptosis in the TCGA cohort and was validated in a Gene Expression Omnibus (GEO) cohorts. Incorporating various clinical features, the risk model remained an independent prognostic factor in multivariate analysis, and it demonstrated superior performance compared to unsupervised clustering of the 21 PANoptosis-related genes alone. Further mutational analysis showed fewer VHL and more BAP1 alterations in the high-risk group, with alterations in both genes also associated with patient prognosis. The high-risk group was characterized by an unfavorable immune microenvironment, marked by reduced levels of CD4 + T cells and natural killer cells, but increased M2 macrophages and regulatory T cells. Finally, the risk model was predictive of response to immune checkpoint blockade, as well as sensitivity to sunitinib and paclitaxel. The PANoptosis-related risk model developed in this study enables accurate prognostic prediction in KIRC patients. Its associations with the tumor immune microenvironment and drug efficacy may offer potential therapeutic targets and inform clinical decisions.

m1A Regulatory gene signatures are associated with certain immune cell compositions of the tumor microenvironment and predict survival in kidney renal clear cell carcinoma.

Adenosine N1 methylation (m1A) of RNA, a type of post-transcriptional modification, has been shown to play a significant role in the progression of cancer. The objective of the current research was to analyze the genetic alteration and prognostic significance of m1A regulators in kidney renal clear cell carcinoma (KIRC). Genomic and clinicopathological characteristics were obtained from 558 KIRC patients in the Cancer Genome Atlas (TCGA) and Gene Omnibus Expression (GEO) databases. Alterations in the gene expression of ten m1A-regulators were analyzed and survival analysis was performed using the Cox regression method. We also identified three clusters of patients based on their distinct m1A alteration patterns, using integrated analysis of the ten m1A-related regulators, which were significantly related to overall survival (OS), disease-free survival (DFS) and tumor microenvironment (TME) immune cell infiltration cells in KIRC. Our findings showed that m1A alteration patterns have critical roles in determining TME complexity and its immune cell composition. Furthermore, different m1A expression patterns were significantly associated with DFS and OS rates in KIRC patients. In conclusion, the identified m1A RNA modification patterns offer a potentially effective way to classify KIRC patients based on their TME immune cell infiltration, enabling the development of more personalized and successful treatment strategies for these patients.