Format-tuning of in vivo-launched bispecific T cell engager enhances efficacy against renal cell carcinoma.

BACKGROUND: Advanced clear cell renal cell carcinoma (ccRCC) is a prevalent kidney cancer for which long-term survival rates are abysmal, though immunotherapies are showing potential. Not yet clinically vetted are bispecific T cell engagers (BTEs) that activate T cell-mediated cancer killing through intercellular synapsing. Multiple BTE formats exist, however, with limited cross-characterizations to help optimize new drug design. Here, we developed BTEs to treat ccRCC by targeting carbonic anhydrase 9 (CA9) while characterizing the persistent BTE (PBTE) format and comparing it to a new format, the persistent multivalent T cell engager (PMTE). These antibody therapies against ccRCC are developed as both recombinant and synthetic DNA (synDNA) medicines. METHODS: Antibody formatting effects on binding kinetics were assessed by flow cytometry and intercellular synaptic strength assays while potency was tested using T-cell activation and cytotoxicity assays. Mouse models were used to study antibody plasma and tumor pharmacokinetics, as well as antitumor efficacy as both recombinant and synDNA medicines. Specifically, three models using ccRCC cell line xenografts and human donor T cells in immunodeficient mice were used to support this study. RESULTS: Compared with a first-generation BTE, we show that the PBTE reduced avidity, intercellular synaptic strength, cytotoxic potency by as much as 33-fold, and ultimately efficacy against ccRCC tumors in vivo. However, compared with the PBTE, we demonstrate that the PMTE improved cell avidity, restored intercellular synapses, augmented cytotoxic potency by 40-fold, improved tumor distribution pharmacokinetics by 2-fold, and recovered synDNA efficacy in mouse tumor models by 20-fold. All the while, the PMTE displayed a desirable half-life of 4 days in mice compared with the conventional BTE's 2 hours. CONCLUSIONS: With impressive efficacy, the CA9-targeted PMTE is a promising new therapy for advanced ccRCC, which can be effectively delivered through synDNA. The highly potent PMTE format itself is a promising new tool for future applications in the multispecific antibody space.

Stemness related lncRNAs signature for the prognosis and tumor immune microenvironment of ccRCC patients.

Long non-coding RNAs (lncRNAs) and cancer stem cells (CSCs) are crucial for the growth, migration, recurrence, and medication resistance of tumors. However, the impact of lncRNAs related to stemness on the outcome and tumor immune microenvironment (TIME) in clear cell renal cell carcinoma (ccRCC) is still unclear. In this study, we aimed to predict the outcome and TIME of ccRCC by constructing a stem related lncRNAs (SRlncRNAs) signature. We firstly downloaded ccRCC patients' clinical data and RNA sequencing data from UCSC and TCGA databases, and abtained the differentially expressed lncRNAs highly correlated with stem index in ccRCC through gene expression differential analysis and Pearson correlation analysis. Then, we selected suitable SRlncRNAs for constructing a prognostic signature of ccRCC patients by LASSO Cox regression. Further, we used nomogram and Kaplan Meier curves to evaluate the SRlncRNA signature for the prognose in ccRCC. At last, we used ssGSEA and GSVA to evaluate the correlation between the SRlncRNAs signature and TIME in ccRCC. Finally, We obtained a signtaure based on six SRlncRNAs, which are correlated with TIME and can effectively predict the ccRCC patients' prognosis. The SRlncRNAs signature may be a noval prognostic indicator in ccRCC.

Sex and survival outcomes in patients with renal cell carcinoma receiving first-line immune-based combinations.

BACKGROUND: There is an ongoing debate as to whether sex could be associated with immune checkpoint inhibitor (ICI) benefit. Existing literature data reveal contradictory results, and data on first-line immune combinations are lacking. METHOD: This was a real-world, multicenter, international, observational study to determine the sex effects on the clinical outcomes in metastatic renal cell carcinoma (mRCC) patients treated with immuno-oncology combinations as first-line therapy. RESULTS: A total of 1827 mRCC patients from 71 cancer centers in 21 countries were included. The median OS was 38.7 months (95% CI 32.7-44.2) in the overall study population: 40.0 months (95% CI 32.7-51.6) in males and 38.7 months (95% CI 26.4-41.0) in females (p = 0.202). The median OS was higher in males vs. females in patients aged 18-49y (36.9 months, 95% CI 29.0-51.6, vs. 24.8 months, 95% CI 16.8-40.4, p = 0.426, with + 19% of 2y-OS rate, 72% vs. 53%, p = 0.006), in the clear cell histology subgroup (44.2 months, 95% CI 35.8-55.7, vs. 38.7 months, 95% CI 26.0-41.0, p = 0.047), and in patients with sarcomatoid differentiation (34.4 months, 95% CI 26.4-59.0, vs. 15.3 months, 95% CI 8.9-41.0, p < 0.001). Sex female was an independent negative prognostic factor in the sarcomatoid population (HR 1.72, 95% CI 1.15 - 2.57, p = 0.008). CONCLUSIONS: Although the female's innate and adaptive immunity has been observed to be more active than the male's, women in the subgroup of clear cell histology, sarcomatoid differentiation, and those under 50 years of age showed shorter OS than males.

ZEB family is a prognostic biomarker and correlates with anoikis and immune infiltration in kidney renal clear cell carcinoma.

BACKGROUND: Zinc finger E-box binding homEeobox 1 (ZEB1) and ZEB2 are two anoikis-related transcription factors. The mRNA expressions of these two genes are significantly increased in kidney renal clear cell carcinoma (KIRC), which are associated with poor survival. Meanwhile, the mechanisms and clinical significance of ZEB1 and ZEB2 upregulation in KIRC remain unknown. METHODS: Through the Cancer Genome Atlas (TCGA) database and Gene Expression Omnibus (GEO) database, expression profiles, prognostic value and receiver operating characteristic curves (ROCs) of ZEB1 and ZEB2 were evaluated. The correlations of ZEB1 and ZEB2 with anoikis were further assessed in TCGA-KIRC database. Next, miRTarBase, miRDB, and TargetScan were used to predict microRNAs targeting ZEB1 and ZEB2, and TCGA-KIRC database was utilized to discern differences in microRNAs and establish the association between microRNAs and ZEBs. TCGA, TIMER, TISIDB, and TISCH were used to analyze tumor immune infiltration. RESULTS: It was found that ZEB1 and ZEB2 expression were related with histologic grade in KIRC patient. Kaplan-Meier survival analyses showed that KIRC patients with low ZEB1 or ZEB2 levels had a significantly lower survival rate. Meanwhile, ZEB1 and ZEB2 are closely related to anoikis and are regulated by microRNAs. We constructed a risk model using univariate Cox and LASSO regression analyses to identify two microRNAs (hsa-miR-130b-3p and hsa-miR-138-5p). Furthermore, ZEB1 and ZEB2 regulate immune cell invasion in KIRC tumor microenvironments. CONCLUSIONS: Anoikis, cytotoxic immune cell infiltration, and patient survival outcomes were correlated with ZEB1 and ZEB2 mRNA upregulation in KIRC. ZEB1 and ZEB2 are regulated by microRNAs.

Troponin T1 in tumorigenesis and immune modulation: Insights into multiple cancers and kidney renal clear cell carcinoma.

Troponin T1 (TNNT1) plays a crucial role in muscle contraction but its role in cancer, particularly in kidney renal clear cell carcinoma (KIRC), is not well-understood. This study explores the expression, clinical significance and biological functions of TNNT1 in various cancers, with an emphasis on its involvement in KIRC. We analysed TNNT1 expression in cancers using databases like TCGA and GTEx, assessing its prognostic value, mutation patterns, methylation status and functional implications. The study also examined TNNT1's effect on the tumour microenvironment and drug sensitivity in KIRC, complemented by in vitro TNNT1 knockdown experiments in KIRC cells. TNNT1 is overexpressed in several cancers and linked to adverse outcomes, showing frequent upregulation mutations and abnormal methylation. Functionally, TNNT1 connects to muscle and cancer pathways, affects immune infiltration and drug responses, and its overexpression in KIRC is associated with advanced disease and reduced survival. Knocking down TNNT1 curbed KIRC cell growth. TNNT1's aberrant expression plays a significant role in tumorigenesis and immune modulation, highlighting its value as a prognostic biomarker and a potential therapeutic target in KIRC and other cancers. Further studies are essential to understand TNNT1's oncogenic mechanisms in KIRC.

[Identification of key genes in Wilms tumor based on high-throughput RNA sequencing and their impacts on prognosis and immune responses].

OBJECTIVE: To identify the key genes differentially expressed in Wilms tumor and analyze their potential impacts on prognosis and immune responses of the patients. METHODS: High-throughput RNA sequencing was used to identify the differentially expressed mRNAs in clinical samples of Wilms tumor and paired normal tissues, and their biological functions were analyzed using GO, KEGG and GSEA enrichment analyses. The hub genes were identified using STRING database, based on which a prognostic model was constructed using LASSO regression. The mutations of the key hub genes were analyzed and their impacts on immunotherapy efficacy was predicted using the cBioPortal platform. RT-qPCR was used to verify the differential expressions of the key hub genes in Wilms tumor. RESULTS: Of the 1612 differentially expressed genes identified in Wilms tumor, 1030 were up-regulated and 582 were down-regulated, involving mainly cell cycle processes and immune responses. Ten hub genes were identified, among which 4 genes (TP53, MED1, CCNB1 and EGF) were closely related to the survival of children with Wilms tumor. A 3-gene prognostic signature was constructed through LASSO regression analysis, and the patients stratified into with high- and low-risk groups based on this signature had significantly different survival outcomes (HR=1.814, log-rank P=0.002). The AUCs of the 3-, 5- and 7-year survival ROC curves of this model were all greater than 0.7. The overall mutations in the key hub genes or the individual mutations in TP53/CCNB1 were strongly correlated with a lower survival rates, and a high TP53 expression was correlated with a poor immunotherapy efficacy. RT-qPCR confirmed that the key hub genes had significant differential expressions in Wilms tumor tissues and cells. CONCLUSION: TP53 gene plays an important role in the Wilms tumor and may potentially serve as a new immunotherapeutic biomarker as well as a therapeutic target.

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.

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.

SLC11A1 promotes kidney renal clear cell carcinoma (KIRC) progression by remodeling the tumor microenvironment.

Kidney renal clear cell carcinoma (KIRC) is a highly immune-infiltrated kidney cancer with the highest mortality rate and the greatest potential for invasion and metastasis. Solute carrier family 11 member1 (SLC11A1) is a phagosomal membrane protein located in monocytes and plays a role in innate immunity, autoimmune diseases, and infection, but its expression and biological role in KIRC is still unknown. In this study, we sought to investigate the potential value of SLC11A1 according to tumor growth and immune response in KIRC. TIMER and UALCAN database was used to analyze the expression feature and prognostic significance of SLC11A1 and its correlation with immune-related biomarkers in KIRC. Proliferation, migration, and invasion were measured using colony formation, EdU, and transwell assays. Role of SLC11A1 on KIRC tumor growth was examined by the xenograft tumor model in vivo. Effects of KIRC cells on macrophage polarization and the proliferation and apoptosis of CD8+ T cells were analyzed using flow cytometry assays. Herein, SLC11A1 was highly expressed in KIRC tissues and cell lines. SLC11A1 downregulation repressed KIRC cell proliferation, migration, invasion, macrophage, and lymphocyte immunity in vitro, as well as hindered tumor growth in vivo. SLC11A1 is significantly correlated with immune cell infiltration and immune-related biomarkers. In KIRC patients, SLC11A1 is highly expressed and positively correlated with the immune-related factors CCL2 and PD-L1. SLC11A1 induced CCL2 and PD-L1 expression, thereby activating the JAK/STAT3 pathway. SLC11A1 deficiency constrained KIRC cell malignant phenotypes and immune response via regulating CCL2 and PD-L1-mediated JAK/STAT3 pathway, providing a promising therapeutic target for KIRC treatment.

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.

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.

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.

Construction and Validation of a Mutation-Related Model in Papillary Renal Cell Carcinoma and Associated Immune Infiltration.

BACKGROUND: To improve the clinical evaluation of the prognosis of papillary renal cell carcinoma (PRCC), we screened a model to predict the survival of patients with mutations in related genes. METHODS: We downloaded RNA sequencing information from all patients with PRCC in TCGA. We first analyzed the differences in genes and the enrichment of these differences. Then, by selecting mutant genes, constructing a protein-protein interaction network, least absolute shrinkage and selection operator regression, and multivariable Cox regression, a prognosis model was constructed. Additionally, the model was validated using external data sets. We analyzed the immune infiltration of PRCC and the correlation between the model and popular targets. Finally, we performed tissue microarray analysis and immunohistochemistry to verify the expression levels of the three genes. RESULTS: We constructed a three-gene (never in mitosis gene A-related kinase 2 [NEK2], centromere protein A [CENPA], and GINS complex subunit 2 [GINS2]) model. The verification results indicated that the model had a good prediction effect. We also developed a visual nomogram. Enrichment analysis revealed the major pathways involved in muscle system processes. Immunoassays showed that the expression level of CENPA was positively correlated with PD-1 and CTLA4 expression levels. Immunohistochemical and tissue microarray results showed that these three genes were highly expressed in PRCC, which was consistent with the predicted results in the database. CONCLUSION: We constructed and verified a three-gene model to predict the patient survival. The results show that the model has a good prediction effect.

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.

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.

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.

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.

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.