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.

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.

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.

EHBP1L1 Drives Immune Evasion in Renal Cell Carcinoma through Binding and Stabilizing JAK1.

High lymphocyte infiltration and immunosuppression characterize the tumor microenvironment (TME) in renal cell carcinoma (RCC). There is an urgent need to elucidate how tumor cells escape the immune attack and to develop novel therapeutic targets to enhance the efficacy of immune checkpoint blockade (ICB) in RCC. Overactivated IFN-γ-induced JAK/STAT signaling involves in such TME, but the underlying mechanisms remain elusive. Here, EH domain-binding protein 1-like protein 1 (EHBP1L1) is identified as a crucial mediator of IFN-γ/JAK1/STAT1/PD-L1 signaling in RCC. EHBP1L1 is highly expressed in RCC, and high EHBP1L1 expression levels are correlated with poor prognosis and resistance to ICB. EHBP1L1 depletion significantly inhibits tumor growth, which is attributed to enhanced CD8+ T cell-mediated antitumor immunity. Mechanistically, EHBP1L1 interacts with and stabilizes JAK1. By competing with SOCS1, EHBP1L1 protects JAK1 from proteasomal degradation, which leads to elevated JAK1 protein levels and JAK1/STAT1/PD-L1 signaling activity, thereby forming an immunosuppressive TME. Furthermore, the combination of EHBP1L1 inhibition and ICB reprograms the immunosuppressive TME and prevents tumor immune evasion, thus significantly reinforcing the therapeutic efficacy of ICB in RCC patient-derived xenograft (PDX) models. These findings reveal the vital role of EHBP1L1 in immune evasion in RCC, which may be a potential complement for ICB therapy.

Identification of mRNA vaccines and conserved ferroptosis related immune landscape for individual precision treatment in bladder cancer.

Background: The aim of this study was to identify the ferroptosis induced tumor microenvironment (FeME) landscape in bladder cancer (BCa) for mRNA vaccine development and selecting suitable patients for precision treatment. Methods: Gene expression profiles and clinical information of 1216 BCa patients were extracted from TCGA-BLCA, three GEO databases and IMvigor210 cohort. We comprehensively established the FeME landscape of 1216 BCa samples based on 290 ferroptosis related genes (FRGs), and systematically correlated these regulation patterns with TME cell-infiltrating characteristics. Besides, we identified the patients' ferroptosis risk index (FRI) to predict the prognosis of BCa for precise treatment. Results: Six over-expressed and mutated tumor antigens associated with poor prognosis and infiltration of antigen presenting cells were identified in BCa. Furthermore, we demonstrated the evaluation of FeME within individual tumors could predict stages of tumor inflammation, subtypes, genetic variation, and patient prognosis. Then, 5-lncRNA signature was mined to produce the FRI. Low FRI was also linked to increased mutation load, better prognosis and enhanced response to anti-PD-L1 immunotherapy. Besides, an immunotherapy cohort confirmed patients with lower FRI demonstrated significant therapeutic advantages and clinical benefits. Conclusions: TFRC, SCD, G6PD, FADS2, SQLE, and SLC3A2 are potent antigens for developing anti-BCa mRNA vaccine. Establishment of FRI will contribute to enhancing our cognition of TME infiltration characterization and guiding more effective immunotherapy strategies and selecting appropriate patients for tumor vaccine therapy. Supplementary Information: The online version contains supplementary material available at 10.1186/s40537-022-00641-z.

An Aging and Senescence-Related Gene Signature for Prognosis Prediction in Clear Cell Renal Cell Carcinoma.

Background: Clear cell renal cell carcinoma (ccRCC) is the most common solid lesion in the kidney. This study aims to establish an aging and senescence-related mRNA model for risk assessment and prognosis prediction in ccRCC patients. Methods: ccRCC data were obtained from The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) datasets. By applying univariate Cox regression, least absolute shrinkage and selection operator (LASSO), and multivariate Cox regression, a new prognostic model based on aging and senescence-related genes (ASRGs) was established. Depending on the prognostic model, high- and low-risk groups were identified for further study. The reliability of the prediction was evaluated in the validation cohort. Pan-cancer analysis was conducted to explore the role of GNRH1 in tumors. Results: A novel prognostic model was established based on eight ASRGs. This model was an independent risk factor and significantly correlated with the prognosis and clinicopathological features of ccRCC patients. The high- and low-risk groups exhibited distinct modes in the principal component analysis and different patterns in immune infiltration. Moreover, the nomogram combining risk score and other clinical factors showed excellent predictive ability, with AUC values for predicting 1-, 3-, and 5-year overall survival in the TCGA cohort equal to 0.88, 0.82, and 0.81, respectively. Conclusion: The model and nomogram based on the eight ASRGs had a significant value for survival prediction and risk assessment for ccRCC patients, providing new insights into the roles of aging and senescence in ccRCC.

The impact of tumor size on the survival of patients with small renal masses: A population-based study.

BACKGROUND: Active surveillance (AS) with delayed intervention has gained acceptance as a management strategy for small renal masses (SRMs). However, during AS, there is a risk of tumor growth. Thus, we aim to investigate whether tumor growth in patients with SRMs leads to tumor progress. METHODS: In this study, we enrolled 16,070 patients from the Surveillance, Epidemiology, and End Results database with T1a renal cell carcinoma (RCC) between 2004 and 2017. The 16,070 patients were divided into three groups: 10,526 in the partial nephrectomy (PN) group, 2768 in the local ablation (LA) group, and 2776 in the AS group. Associations of tumor size with all-cause and cancer-specific mortality were evaluated using Kaplan-Meier analyses and Cox regression models. RESULTS: Four tumor size categories were delineated (≤1, >1-2, >2-3, and > 3-4 cm in diameter), and 10-year all-cause and cancer-specific mortality both significantly increased with increasing tumor size in the PN, LA, and AS groups (all p < 0.05). Tumors were substaged based on diameter: T1aA (≤2 cm) and T1aB (>2-4 cm). All-cause and cancer-specific mortality were significantly higher in T1aB tumors than T1aA tumors in each group (hazard ratio = 1.395 and 1.538, respectively; all p < 0.05). CONCLUSIONS: Tumor growth relates to worse prognosis of T1a RCC, and 2 cm serves as a size threshold that is prognostically relevant for patients with T1a RCC. Because of the lack of accurate predictors of tumor growth rate, AS for patients with SRMs incurs a risk of tumor progression.

Identification of ZDHHC1 as a Pyroptosis Inducer and Potential Target in the Establishment of Pyroptosis-Related Signature in Localized Prostate Cancer.

Pyroptosis or cellular inflammatory necrosis is a programmed cell death kind. Accumulating evidence shows that pyroptosis plays a crucial role in the invasion, metastasis, and proliferation of tumor cells, thus affecting the prognosis of tumors and therapeutic effects. Prostate cancer (PCa), a common malignancy among men, is associated with inflammation. Pathophysiological effects of pyroptosis on tumor development and progression, as well as the mediation of PCa, are known, but its effects on the potential prognosis for PCa warrant in-depth investigation. Herein, we built a risk model of six pyroptosis-related genes and verified their predictive abilities for prognostic and therapeutic effects. Higher risk scores indicated a higher probability of biochemical recurrence (BCR), higher immune infiltration, and worsened clinicopathological features. To derive scientific and reliable predictions for BCR in patients having PCa, the findings of the current study were verified in the Gene Expression Omnibus (GEO) cohort following evaluation in The Cancer Genome Atlas (TCGA) dataset. Additionally, after evaluating the six genes in the model, ZDHHC1 was found to be an important component. Its antitumor role was further assessed through in vivo and in vitro experiments, and its promoting effect on pyroptosis was further evaluated and verified. The above results provided a new perspective for further studies on pyroptosis and its clinical utility for PCa.

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

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

Predictive Model for Systemic Infection After Percutaneous Nephrolithotomy and Related Factors Analysis.

Objectives: To investigate the factors associated with systemic infection after percutaneous nephrolithotomy (PCNL) and establish a predictive model to provide theoretical basis for the prevention of systemic inflammatory response syndrome (SIRS) and urosepsis correlate to percutaneous nephrostomy. Methods: Patients received PCNL between January 2016 and December 2020 were retrospectively enrolled. All patients were categorized into groups according to postoperative SIRS and urosepsis status. Single factor analysis and multivariate logistic regression analysis were performed to determine the predictive factors of SIRS and urosepsis after PCNL. The nomograms were generated using the predictors respectively and the discriminative ability of was assessed by analyses of receiver operating characteristic curves (ROC curves). Results: A total of 758 PCNL patients were enrolled in this study, including 97 (12.8%) patients with SIRS and 42 (5.5%) patients with urosepsis. Multivariate logistic regression analysis suggested that there were 5 factors related to SIRS, followed by preoperative neutrophil to lymphocyte ratio (NLR) (odds ratio, OR = 1.721, 95% confidence interval, CI [1.116-2.653], p = 0.014), S.T.O.N.E. score (OR = 1.902, 95% CI [1.473-2.457], p < 0.001), female gender (OR = 2.545, 95% CI [1.563-4.144], p < 0.001), diabetes history (OR = 1.987, 95% CI [1.051-3.755], p = 0.035), positive urine culture (OR = 3.184, 95% CI [1.697-5.974], p < 0.001). And there were four factors related to urosepsis, followed by preoperative NLR (OR = 1.604, 95% CI [1.135-2.266], p = 0.007), S.T.O.N.E. score (OR = 1.455, 95% CI [1.064-1.988], p = 0.019), female gender (OR = 2.08, 95% CI [1.063-4.07], p = 0.032), positive urine culture (OR = 2.827, 95% CI [1.266-6.313], p = 0.011). A nomogram prediction model was established to calculate the cumulative probability of SIRS and urosepsis after PCNL and displayed favorable fitting by Hosmer-Lemeshow test (p = 0.953, p = 0.872). The area under the ROC curve was 0.784 (SIRS) and 0.772 (urosepsis) respectively. Conclusion: Higher preoperative NLR, higher S.T.O.N.E. score, female gender, and positive urine culture are the most significant predictors of SIRS and urosepsis. Diabetes history is the predictor of SIRS. These data will help identify high-risk individuals and facilitate early detection of SIRS and urosepsis post-PCNL.

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

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

N6-Methyladenosine Modification of LncRNA DUXAP9 Promotes Renal Cancer Cells Proliferation and Motility by Activating the PI3K/AKT Signaling Pathway.

Most localized human renal clear cell carcinoma (ccRCC)-related deaths result from cancer recurrence and metastasis. However, the precise molecular mechanisms largely remain unknown. In recent years, an increasing number of long noncoding RNAs (lncRNAs) have been shown to be vital regulators of tumorigenesis. In this study, we characterized a lncRNA DUXAP9 and the upregulation of DUXAP9 was analyzed by quantitative real-time PCR in 112 pairs of localized ccRCC tumor tissues compared with adjacent normal tissues. Kaplan-Meier curves showed that patients of localized ccRCC with high DUXAP9 expression had poorer overall survival (P<0.01) and progression-free survival (P<0.05) than cases with low DUXAP9 expression. Multivariate Cox regression analysis also showed that high DUXAP9 expression was an independent risk factor for poor prognosis in localized ccRCC (p<0.05). DUXAP9 knockdown in renal cancer cells inhibited renal cancer cells proliferation and motility capacities in vitro and reversed epithelial-mesenchymal transition (EMT), whereas overexpression of DUXAP9 promoted renal cancer cells proliferation and motility capacities in vitro and induced EMT. Pull-down, RNA immunoprecipitation and RNA stability assays (involving actinomycin D) showed that DUXAP9 was methylated at N6-adenosine and binds to IGF2BP2, which increases its stability. DUXAP9 activate PI3K/AKT pathway and Snail expression in renal cancer cells. DUXAP9 may be useful as a prognostic marker and/or therapeutic target in localized ccRCC.

Identification of an Immune-Related Risk Signature Correlates With Immunophenotype and Predicts Anti-PD-L1 Efficacy of Urothelial Cancer.

Immune checkpoint inhibitor (ICI) treatment has been used to treat advanced urothelial cancer. Molecular markers might improve risk stratification and prediction of ICI benefit for urothelial cancer patients. We analyzed 406 cases of bladder urothelial cancer from The Cancer Genome Atlas (TCGA) data set and identified 161 messenger RNAs (mRNAs) as differentially expressed immunity genes (DEIGs). Using the LASSO Cox regression model, an eight-mRNA-based risk signature was built. We validated the prognostic and predictive accuracy of this immune-related risk signature in 348 metastatic urothelial cancer (mUC) samples treated with anti-PD-L1 (atezolizumab) from IMvigor210. We built an immune-related risk signature based on the eight mRNAs: ANXA1, IL22, IL9R, KLRK1, LRP1, NRG3, SEMA6D, and STAP2. The eight-mRNA-based risk signature successfully categorizes patients into high-risk and low-risk groups. Overall survival was significantly different between these groups, regardless if the initial TCGA training set, the internal TCGA testing set, all TCGA set, or the ICI treatment set. The hazard ratio (HR) of the high-risk group to the low-risk group was 3.65 (p < 0.0001), 2.56 (p < 0.0001), 3.36 (p < 0.0001), and 2.42 (p = 0.0009). The risk signature was an independent prognostic factor for prediction survival. Moreover, the risk signature was related to immunity characteristics. In different tumor mutational burden (TMB) subgroups, it successfully categorizes patients into high-risk and low-risk groups, with significant differences of clinical outcome. Our eight-mRNA-based risk signature is a stable biomarker for urothelial cancer and might be able to predict which patients benefit from ICI treatment. It might play a role in precision individualized immunotherapy.

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

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