CD4 + T cells promote renal cell carcinoma proliferation via modulating YBX1

Comprehensive assessment of the association between tumor-infiltrating immune cells and the prognosis of renal cell carcinoma

BACKGROUND

According to current statistics, renal cancer accounts for 3% of all cancers worldwide. Renal cell carcinoma (RCC) is the most common solid lesion in the kidney and accounts for approximately 90% of all renal malignancies. Increasing evidence has shown an association between immune infiltration in RCC and clinical outcomes. To discover possible targets for the immune system, we investigated the link between tumor-infiltrating immune cells (TIICs) and the prognosis of RCC.

AIM

To investigate the effects of 22 TIICs on the prognosis of RCC patients and identify potential therapeutic targets for RCC immunotherapy.

METHODS

The CIBERSORT algorithm partitioned the 22 TIICs from the Cancer Genome Atlas cohort into proportions. Cox regression analysis was employed to evaluate the impact of 22 TIICs on the probability of developing RCC. A predictive model for immunological risk was developed by analyzing the statistical relationship between the subpopulations of TIICs and survival outcomes. Furthermore, multivariate Cox regression analysis was used to investigate independent factors for the prognostic prediction of RCC. A value of P < 0.05 was regarded as statistically significant.

RESULTS

Compared to normal tissues, RCC tissues exhibited a distinct infiltration of immune cells. An immune risk score model was established and univariate Cox regression analysis revealed a significant association between four immune cell types and the survival risk connected to RCC. High-risk individuals were correlated to poorer outcomes according to the Kaplan-Meier survival curve (P = 1^E−05). The immunological risk score model was demonstrated to be a dependable predictor of survival risk (area under the curve = 0.747) via the receiver operating characteristic curve. According to multivariate Cox regression analysis, the immune risk score model independently predicted RCC patients' prognosis (hazard ratio = 1.550, 95%CI: 1.342–1.791; P < 0.001). Finally, we established a nomogram that accurately and comprehensively forecast the survival of patients with RCC.

CONCLUSION

TIICs play various roles in RCC prognosis. The immunological risk score is an independent predictor of poor survival in kidney cancer cases.

A Notch signaling-related lncRNA signature for predicting prognosis and therapeutic response in clear cell renal cell carcinoma

Increasing evidence has confirmed the vital role of Notch signaling in the tumorigenesis of clear cell renal cell carcinoma (ccRCC). The underlying function of long non-coding RNA (lncRNA) related to Notch signaling in ccRCC remains unclear. In present study, the prognostic value and therapeutic strategy of Notch signaling-related lncRNA are comprehensively explored in ccRCC. In total, we acquired 1422 NSRlncRNAs, of which 41 lncRNAs were identified the key NSRlncRNAs associated with the occurrence of ccRCC. The prognostic signature containing five NSRlncRNAs (AC092611.2, NNT-AS1, AGAP2-AS1, AC147651.3, and AC007406.3) was established and validated, and the ccRCC patients were clustered into the high- and low-risk groups. The overall survival of patients in the low-risk group were much more favorable than those in the high-risk group. Multivariate Cox regression analysis indicated that the risk score was an independent prognostic biomarker. Based on the risk score and clinical variables, a nomogram for predicting prognosis of ccRCC patients was constructed, and the calibration curves and DCA curves showed the superior predictive ability of nomogram. The risk score was correlated with immune cell infiltration, targeted therapy or chemotherapy sensitivity, and multiple oncogenic pathways. Additionally, consensus clustering analysis stratified the ccRCC patients into four clusters with obvious different outcomes, immune microenvironments, and expression of immune checkpoints. The constructed NSRlncRNA-based signature might serve as a potential biomarker for predicting prognosis and response to immunotherapy or targeted therapy in patients with ccRCC.

Mathematical and Machine Learning Models of Renal Cell Carcinoma: A Review

This review explores the multifaceted landscape of renal cell carcinoma (RCC) by delving into both mechanistic and machine learning models. While machine learning models leverage patients' gene expression and clinical data through a variety of techniques to predict patients' outcomes, mechanistic models focus on investigating cells' and molecules' interactions within RCC tumors. These interactions are notably centered around immune cells, cytokines, tumor cells, and the development of lung metastases. The insights gained from both machine learning and mechanistic models encompass critical aspects such as signature gene identification, sensitive interactions in the tumors' microenvironments, metastasis development in other organs, and the assessment of survival probabilities. By reviewing the models of RCC, this study aims to shed light on opportunities for the integration of machine learning and mechanistic modeling approaches for treatment optimization and the identification of specific targets, all of which are essential for enhancing patient outcomes.

Integrative transcriptome and proteome analyses of clear cell renal cell carcinoma develop a prognostic classifier associated with thrombus

Clear cell renal cell carcinoma (ccRCC) with venous tumor thrombus (VTT) is associated with poor prognosis. Our integrative analyses of transcriptome and proteome reveal distinctive molecular features of ccRCC with VTT, and yield the development of a prognostic classifier to facilitate ccRCC molecular subtyping and treatment. The RNA sequencing and mass spectrometry were performed in normal-tumor-thrombus tissue triples of five ccRCC patients. Statistical analysis, GO and KEGG enrichment analysis, and protein-protein interaction network construction were used to interpret the transcriptomic and proteomic data. A six-gene-based classifier was developed to predict patients' survival using Cox regression, which was validated in an independent cohort. Transcriptomic analysis identified 1131 tumorigenesis-associated differentially expressed genes (DEGs) and 856 invasion-associated DEGs. Overexpression of transcription factor EGR2 in VTT indicated its important role in tumor invasion. Furthermore, proteomic analysis showed 597 tumorigenesis-associated differentially expressed proteins (DEPs) and 452 invasion-associated DEPs. The invasion-associated DEPs showed unique enrichment in DNA replication, lysine degradation, and PPAR signaling pathway. Integration of transcriptome and proteome reveals 142 tumorigenesis-associated proteins and 84 invasion-associated proteins displaying changes consistent with corresponding genes in transcriptomic profiling. Based on their different expression patterns among normal-tumor-thrombus triples, RAB25 and GGT5 were supposed to play a consistent role in both tumorigenesis and invasion processes, while SHMT2 and CADM4 might play the opposite roles in tumorigenesis and thrombus invasion. A prognostic classifier consisting of six DEGs (DEPTOR, DPEP1, NAT8, PLOD2, SLC7A5, SUSD2) performed satisfactorily in predicting survival of ccRCC patients (HR = 4.41, P < 0.001), which was further validated in an independent cohort of 40 cases (HR = 5.52, P = 0.026). Our study revealed the transcriptomic and proteomic profiles of ccRCC patients with VTT, and identified the distinctive molecular features associated with VTT. The six-gene-based prognostic classifier developed by integrative analyses may facilitate ccRCC molecular subtyping and treatment.

Identification of immune cell infiltration profiles in renal cell carcinoma and their clinical significance

Renal cell carcinoma (RCC) is the most common malignancy of the urinary system, accounting for 3.7% of all new malignancies. The prognosis of RCC patients is still poor, especially patients in advanced stage. Limited studies have fully clarified the role of immune cell infiltration profiles in the prognosis and immunotherapy of RCC. In current study, we evaluated the abundance of the 22 tumor-infiltrating immune cells (TIICs) with CIBERSORT methods. The correlation between TIICs and clinicopathological parameters, tumor immune dysfunction and exclusion (TIDE) score and immunophenoscore (IPS) of RCC patients were also explored. Significant correlations were obtained between TIICs subpopulation and specific clinicopathologic parameters of RCC, including age, gender, tumor grade, clinical stage, T stage and distant metastasis. Moreover, RCC patients with high level of memory activated CD4 T cells, follicular helper T cells and regulatory T cells had a worse overall survival (OS) rate. RCC patients with high level of CD 8 + T cells and M1 macrophages had a lower TIDE score and higher anti-CTLA IPS, higher anti-PD1 IPS as well as higher anti-PD1/CTLA4 IPS. Our results clarified the immune cell infiltration profiles of RCC. RCC patients with high level of CD 8 + T cell and M1 macrophages had a lower TIDE score and higher IPS, suggesting that RCC patients with high level of CD 8 + T cell and M1 macrophages may benefit from immunotherapy.

C1QC is a prognostic biomarker with immune-related value in kidney renal clear cell carcinoma

Background: Kidney renal clear cell carcinoma (KIRC) is a representative histologic subtype of renal cell carcinoma (RCC). RCC exhibits a strong immunogenicity with a prominent dysfunctional immune infiltration. Complement C1q C chain (C1QC) is a polypeptide in serum complement system and is involved in tumorigenesis and the modulation of tumor microenvironment (TME). However, researches have not explored the effect of C1QC expression on prognosis and tumor immunity of KIRC. Methods: The difference in a wide variety of tumor tissues and normal tissues in terms of the C1QC expression was detected using TIMER and TCGA portal databases, and further validation of protein expression of C1QC was conducted via Human Protein Atlas. Then, the associations of C1QC expression with clinicopathological data and other genes were studied with the use of UALCAN database. Subsequently, the association of C1QC expression with prognosis was predicted by searching the Kaplan-Meier plotter database. A protein-protein interaction (PPI) network with the Metascape database was built using STRING software, such that the mechanism underlying the C1QC function can be studied in depth. The TISCH database assisted in the evaluation of C1QC expression in different cell types in KIRC at the single-cell level. Moreover, the association of C1QC and the infiltration level of tumor immune cell was assessed using TIMER platform. The TISIDB website was selected to deeply investigate the Spearman correlation between C1QC and immune-modulator expression. Lastly, how C1QC affected the cell proliferation, migration, and invasion in vitro was assessed using knockdown strategies. Results: KIRC tissues had notably upregulated C1QC level in comparison with adjacent normal tissues, with showed a positive relevance to clinicopathological features including tumor stage, grade, and nodal metastasis, and a negative relevance to clinical prognosis in KIRC. C1QC knockdown inhibited KIRC cell proliferation, migration, and invasion, as indicated by the results of the in vitro experiment. Furthermore, functional and pathway enrichment analysis demonstrated that C1QC was involved in immune system-related biological processes. According to single-cell RNA analysis, C1QC exhibited a specific upregulation in macrophages cluster. Additionally, there was an obvious association of C1QC and a wide variety of tumor-infiltrating immune cells in KIRC. Also, high C1QC expression presented inconsistent prognosis in different enriched immune cells subgroups in KIRC. Immune factors might contribute to C1QC function in KIRC. Conclusion: C1QC is qualified to predict KIRC prognosis and immune infiltration biologically. Targeting C1QC may bring new hope for the treatment of KIRC.

Low gamma-butyrobetaine dioxygenase (BBOX1) expression as a prognostic biomarker in patients with clear cell renal cell carcinoma: a machine learning approach

Gamma-butyrobetaine dioxygenase (BBOX1) is a catalyst for the conversion of gamma-butyrobetaine to l-carnitine, which is detected in normal renal tubules. The purpose of this study was to analyze the prognosis, immune response, and genetic alterations associated with low BBOX1 expression in patients with clear cell renal cell carcinoma (RCC). We analyzed the relative influence of BBOX1 on survival using machine learning and investigated drugs that can inhibit renal cancer cells with low BBOX1 expression. We analyzed clinicopathologic factors, survival rates, immune profiles, and gene sets according to BBOX1 expression in a total of 857 patients with kidney cancer from the Hanyang University Hospital cohort (247 cases) and The Cancer Genome Atlas (610 cases). We employed immunohistochemical staining, gene set enrichment analysis, in silico cytometry, pathway network analyses, in vitro drug screening, and gradient boosting machines. BBOX1 expression in RCC was decreased compared with that in normal tissues. Low BBOX1 expression was associated with poor prognosis, decreased CD8+ T cells, and increased neutrophils. In gene set enrichment analyses, low BBOX1 expression was related to gene sets with oncogenic activity and a weak immune response. In pathway network analysis, BBOX1 was linked to regulation of various T cells and programmed death-ligand 1. In vitro drug screening showed that midostaurin, BAY-61-3606, GSK690693, and linifanib inhibited the growth of RCC cells with low BBOX1 expression. Low BBOX1 expression in patients with RCC is related to short survival time and reduced CD8+ T cells; midostaurin, among other drugs, may have enhanced therapeutic effects in this context.

High expression of TTC21A predicts unfavorable prognosis and immune infiltrates in clear cell renal cell carcinoma

Background: Clear cell renal cell carcinoma (ccRCC) is the most common pathological type of renal cell carcinoma. Tetratricopeptide repeat domain 21A (TTC21A), known as a component of intraflagellar transport complex A which is essential for the function of cilia, However, the role of TTC21A remains unclear in ccRCC. For the first time, we explore the role and potential mechanism of TTC21A in ccRCC based on multiple databases.

Methods: TTC21A expression across all TCGA tumor was analyzed via Tumor Immune Estimation Resource (TIMER) site. The correlation between TTC21A and clinicopathologic characteristics of ccRCC was analyzed with TCGA database. The diagnostic and prognostic value of TTC21A was evaluated by receiver operation characteristic curve, Kaplan-Meier plotter and Cox regression respectively. Moreover, functional enrichment analysis of TTC21A and the co-expression genes were performed by Gene Set Enrichment Analysis. The correlation of TTC21A and immune infiltration were evaluated by single sample Gene Set Enrichment Analysis.

Results: Pan-cancer analysis indicated that TTC21A was highly expressed in ccRCC and other cancer. In addition, elevated expression of TTC21A was associated with worse overall survival in ccRCC patients. Functional enrichment analysis showed that TTC21A and the co-expressed genes enriched in glucose metabolism and energy metabolism. Moreover, TTC21A expression was associated with infiltrating levels of dendritic cell, nature killer cell and other immune marker sets.

Conclusion: The results of analysis indicate that expression of TTC21A is associated with poor prognosis and immune infiltrating in ccRCC, which suggested TTC21A might be used as a potential predictor and target of treatment in ccRCC.

Comprehensive analysis to identify the RP11-478C19.2/ E2F7 axis as a novel biomarker for treatment decisions in clear cell renal cell carcinoma

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LncRNA RP11–478C19.2 promotes the progression of ccRCC via the RP11–478C19.2/hsa-miR-181b-5p, hsa-miR-181a-5p, hsa-miR-181c-5p/E2F7 axis.

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E2F7 could be detected in patients with ccRCC to aid treatment regimen selection, particularly in advanced and metastatic disease.

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Individuals who overexpress E2F7 may have a greater response to some first-line therapy for ccRCC, including cabozantinib, pazopanib, and sunitinib.

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Patients with higher expression of E2F7 may have a higher percentage of ICB responses.

Clear cell renal cell carcinoma (ccRCC), accounting for 70–80% of all renal cell carcinomas, is a common malignancy. Survival rates decrease significantly in patients with advanced and metastatic ccRCC. Furthermore, ccRCC is less responsive to radiation and chemotherapy than other cancers. Therefore, targeted therapy and immunotherapy are particularly important for ccRCC management. A growing body of literature recognizes that competitive endogenous RNA (ceRNA) regulatory networks play a crucial role in various cancers. However, the biological functions of the ceRNA network in ccRCC require further investigation. In this study, we built the ceRNA network for ccRCC using the “GDCRNATools” package. After survival analysis, the RP11–478C19.2/hsa-miR-181b-5p, hsa-miR-181a-5p, and hsa-miR-181c-5p/E2F7 axes were obtained for further analysis. Unsupervised clustering was conducted basing on this ceRNA network. The results indicated that the prognosis and immune infiltration levels differed between the two clusters. Furthermore, we conducted correlation analysis, immune infiltration analysis, tumor mutation burden analysis, GSEA analysis, drug sensitivity analysis and pan-cancer analysis of E2F7 to explore its potential role in oncogenesis. Experiments in vitro were performed to confirm the pro-oncogenic impact of E2F7. The results suggest that the RP11–478C19.2/E2F7 axis might be a biomarker for the inclusion of cabozantinib, pazopanib, sunitinib, and immunotherapy in the therapeutic regimen. In summary, we found that the ceRNA-based RP11–478C19.2/E2F7 axis is involved in ccRCC and that it could be a novel biomarker for treatment decisions and a possible therapeutic target to increase the success of targeted therapy and immunotherapy in ccRCC.

Decoding the Immune Microenvironment of Clear Cell Renal Cell Carcinoma by Single-Cell Profiling to Aid Immunotherapy

Clear cell renal cell carcinoma (ccRCC) is the most common subtype of kidney cancer, and it is the major cause of kidney cancer death. Understanding tumor immune microenvironments (TMEs) is critical in cancer immunotherapies. Here, we studied the immune characterization at single-cell resolution by integrating public data of ccRCC across different tissue types, and comparing the transcriptome features and tumor TME differences in tumors, normal adjacent tissue, and peripheral blood. A total of 16 different types of cell components of ccRCC were identified. We revealed that there is an overall increase in T-cell and myeloid populations in tumor-infiltrated immune cells compared to normal renal tissue, and the B-cell population in the tumor showed a sharp decrease, which indicates that the cells in tumor tissue undergo strong immune stress. In addition, the cell-cell communication analysis revealed specific or conserved signals in different tissue types, which may aid to uncover the distinct immune response. By combining and analyzing publicly available ccRCC bulk RNA-seq datasets, 10 genes were identified as marker genes in specific cell types, which were significantly associated with poor prognosis. Of note, UBE2C, which may be a good indicator of tumor proliferation, is positively associated with reductions in overall survival and highly associated with tumor grade. Our integrated analysis provides single-cell transcriptomic profiling of ccRCC and their TME, and it unmasked new correlations between gene expression, survival outcomes, and immune cell-type components, enabling us to dissect the dynamic variables in the tumor development process. This resource provides deeper insight into the transcriptome features and immune response of ccRCC and will be helpful in kidney cancer immunotherapy.

Prognostic Characteristics and Immune Effects of N6-Methyladenosine and 5-Methylcytosine-Related Regulatory Factors in Clear Cell Renal Cell Carcinoma

In recent years, methylation modification regulators have been found to have essential roles in various tumor mechanisms. However, the relationships between N⁶-methyladenosine (m6A) and 5-methylcytosine (m5C) regulators and clear cell renal cell carcinoma (ccRCC) remain unknown. This study investigated these relationships using the data from The Cancer Genome Atlas database. We calculated risk scores using a Lasso regression analysis and divided the patient samples into two risk groups (tumor vs. normal tissues). Furthermore, we used univariate and multivariate Cox analyses to determine independent prognostic indicators and explore correlations between the regulatory factors and immune infiltrating cell characteristics. Finally, quantitative reverse transcriptase–polymerase chain reaction (PCR) and The Human Protein Atlas were used to verify signature-related gene expression in clinical samples. We identified expression differences in 35 regulatory factors between the tumor and normal tissue groups. Next, we constructed a five-gene risk score signature (NOP2 nucleolar protein [NOP2], methyltransferase 14, N6-adenosine-methyltransferase subunit [METTL14], NOP2/Sun RNA methyltransferase 5 [NSUN5], heterogeneous nuclear ribonucleoprotein A2/B1 [HNRNPA2B1], and zinc finger CCCH-type containing 13 [ZC3H13]) using the screening criteria (p < 0.01), and then divided the cases into high- and low-risk groups based on their median risk score. We also screened for independent prognostic factors related to age, tumor grade, and risk score. Furthermore, we constructed a Norman diagram prognostic model by combining two clinicopathological characteristics, which demonstrated good prediction efficiency with prognostic markers. Then, we used a single-sample gene set enrichment analysis and the cell-type identification by estimating relative subsets of RNA transcripts (CIBERSORT) method to evaluate the tumor microenvironment of the regulatory factor prognostic characteristics. Moreover, we evaluated five risk subgroups with different genetic signatures for personalized prognoses. Finally, we analyzed the immunotherapy and immune infiltration response and demonstrated that the high-risk group was more sensitive to immunotherapy than the low-risk group. The PCR results showed that NSUN5 and HNRNPA2B1 expression was higher in tumor tissues than in normal tissues. In conclusion, we identified five m6A and m5C regulatory factors that might be promising biomarkers for future research.

RNA-binding proteins and their role in kidney disease

RNA-binding proteins (RBPs) are of fundamental importance for post-transcriptional gene regulation and protein synthesis. They are required for pre-mRNA processing and for RNA transport, degradation and translation into protein, and can regulate every step in the life cycle of their RNA targets. In addition, RBP function can be modulated by RNA binding. RBPs also participate in the formation of ribonucleoprotein complexes that build up macromolecular machineries such as the ribosome and spliceosome. Although most research has focused on mRNA-binding proteins, non-coding RNAs are also regulated and sequestered by RBPs. Functional defects and changes in the expression levels of RBPs have been implicated in numerous diseases, including neurological disorders, muscular atrophy and cancers. RBPs also contribute to a wide spectrum of kidney disorders. For example, human antigen R has been reported to have a renoprotective function in acute kidney injury (AKI) but might also contribute to the development of glomerulosclerosis, tubulointerstitial fibrosis and diabetic kidney disease (DKD), loss of bicaudal C is associated with cystic kidney diseases and Y-box binding protein 1 has been implicated in the pathogenesis of AKI, DKD and glomerular disorders. Increasing data suggest that the modulation of RBPs and their interactions with RNA targets could be promising therapeutic strategies for kidney diseases.

Decreased CDKL2 Expression in Clear Cell Renal Cell Carcinoma Predicts Worse Overall Survival

Background: Clear cell renal cell carcinoma (ccRCC) is the most frequent and lethal type of kidney cancer. Although differential expression of cyclin-dependent kinase-like 2 (CDKL2) has been reported to be associated with tumor progression in other cancers, its prognostic value, and potential mechanism in patients with ccRCC still remain unknown.

Methods: Gene expression analysis was conducted using The Cancer Genome Atlas (TCGA), Gene Expression Omnibus, and International Cancer Genome Consortium databases. Further, clinicopathologic analysis; Kaplan–Meier survival analysis; weighted gene co-expression network analysis; gene set enrichment analysis; gene ontology enrichment; methylation; and immune infiltration analyses were performed using TCGA-kidney renal clear cell carcinoma profiles. CDKL2 translational levels were analyzed using The Human Protein Atlas database.

Results:CDKL2 expression was decreased in ccRCC samples retrieved from the four databases. Gender, survival status, histologic grade, clinical stage, TNM classification, and tumor status were closely related to CDKL2 expression. In addition, CDKL2 downregulation was an independent prognostic factor for poor prognosis in multivariate analysis. Enrichment analyses using multiple tests revealed that CDKL2 is not just closely related to immune response but this association is highly correlated as well. Further, we found that CDKL2 expression was significantly correlated with the infiltration levels of T cell CD4 memory resting; monocytes; macrophages M0, M1, and M2; dendritic cells resting; mast cells resting; plasma cells; T cell CD8; and T cell regulatory.

Conclusion: This is the first report to study the expression of CDKL2 in ccRCC, wherein we suggest that decreased CDKL2 expression is closely correlated with poor prognosis in ccRCC. We consider that CDKL2 is a novel and potential prognostic biomarker associated with immune infiltrates in ccRCC.

TBC1D3 family is a prognostic biomarker and correlates with immune infiltration in kidney renal clear cell carcinoma

The TBC1D3 family is overexpressed in many cancers, including kidney renal clear cell carcinoma (KIRC), which is associated with tumor-infiltrating lymphocytes. However, the expression and prognosis of TBC1D3 family and tumor-infiltrating lymphocytes in KIRC remain unknown. In the present study, we systematically explored and validated the expression and prognostic value of TBC1D3 family expression in KIRC using multiple public databases. In addition, the function of the TBC1D3 family members and the correlations between TBC1D3 family expression and KIRC immune infiltration levels were investigated. We found that TBC1D3 family members were rarely mutated (less than 5 frequencies). TBC1D3 family was overexpressed in KIRC; high expression of the TBC1D3 family members was correlated with poor prognosis. In addition, TBC1D3D may positively regulate proliferation, and overexpression of TBC1D3 promoted clear cell renal cell carcinoma proliferation in vitro. In terms of immune infiltrating levels, TBC1D3 family expression was positively associated with CD4⁺ T cells infiltrating levels. These findings suggest that the TBC1D3 family expression is correlated with prognosis and immune infiltrating levels. Therefore, the TBC1D3 family can be used as a biomarker for KIRC and a prognostic biomarker for determining the prognosis and immune infiltration levels in KIRC.

Prognostic Value of a Glycolytic Signature and Its Regulation by Y-Box-Binding Protein 1 in Triple-Negative Breast Cancer

Triple-negative breast cancer (TNBC) is the most malignant subtype of breast cancer as it shows a high capacity for metastasis and poor prognoses. Metabolic reprogramming is one of the hallmarks of cancer, and aberrant glycolysis was reported to be upregulated in TNBC. Thus, identifying metabolic biomarkers for diagnoses and investigating cross-talk between glycolysis and invasiveness could potentially enable the development of therapeutics for patients with TNBC. In order to determine novel and reliable metabolic biomarkers for predicting clinical outcomes of TNBC, we analyzed transcriptome levels of glycolysis-related genes in various subtypes of breast cancer from public databases and identified a distinct glycolysis gene signature, which included ENO1, SLC2A6, LDHA, PFKP, PGAM1, and GPI, that was elevated and associated with poorer prognoses of TNBC patients. Notably, we found a transcription factor named Y-box-binding protein 1 (YBX1) to be strongly associated with this glycolysis gene signature, and it was overexpressed in TNBC. A mechanistic study further validated that YBX1 was upregulated in TNBC cell lines, and knockdown of YBX1 suppressed expression of those glycolytic genes. Moreover, YBX1 expression was positively associated with epithelial-to-mesenchymal transition (EMT) genes in breast cancer patients, and suppression of YBX1 downregulated expressions of EMT-related genes and tumor migration and invasion in MDA-MB-231 and BT549 TNBC cells. Our data revealed an YBX1-glycolysis-EMT network as an attractive diagnostic marker and metabolic target in TNBC patients.

Landscape of immune cell infiltration in clear cell renal cell carcinoma to aid immunotherapy

The tumor microenvironment, comprised of tumor cells and tumor-infiltrating immune cells, is closely associated with the clinical outcome of clear cell renal cell carcinoma (ccRCC) patients. However, the landscape of immune infiltration in ccRCC has not been fully elucidated. Herein, we applied multiple computational methods and various datasets to reveal the immune infiltrative landscape of ccRCC patients. The tumor immune infiltration (TII) levels of 525 ccRCC patients using a single-sample gene were examined and further categorized into immune infiltration subgroups. The TII score was characterized by distinct clinical traits and showed a significant divergence based on gender, grade, and stage. A high TII score was associated with the ERBB signaling pathway, the TGF-β signaling pathway, and the MTOR signaling pathway, as well as a better prognosis. Furthermore, patients with high TII scores exhibited greater sensitivity to pazopanib. The low TII score was characterized by a high immune infiltration level of CD8+ T cells, T follicular helper cells, and regulatory T cells (Tregs). Moreover, the immune check point genes, including CTLA-4, LAG3, PD-1, and IDO1, presented a high expression level in the low TII score group. Patients in the high TII score group demonstrated significant therapeutic advantages and clinical benefits. The findings in this study have the potential to assist in the strategic design of immunotherapeutic treatments for ccRCC.

Identification and immunoprofiling of key prognostic genes in the tumor microenvironment of hepatocellular carcinoma

Tumor microenvironment (TME) is involved in the occurrence and development of hepatocellular carcinoma (HCC), and immune cells in the TME have been implicated in its progression and treatment. However, the association of genes involved in the TME with HCC prognosis remains unclear. Thus, in this study, we obtained transcriptomic and clinicopathological data of patients with HCC from The Cancer Genome Atlas to identify key genes in TME associated with HCC prognosis. Stromal and immune cell scores were calculated using the ESTIMATE method, and differentially expressed genes (DEGs) were determined. We identified 830 DEGs, which were further subjected to survival analyses and functional enrichment analysis. Next, we identified prognostic TME-associated DEGs, established a protein-protein interaction (PPI) network, and performed Cox analysis.Consequently, four key prognostic genes (CXCL5, CXCL8, IL18RAP, and TREM2) associated with TME, were identified, in which CXCL5 and IL18RAP may be potential independent prognostic factors. Age, clinical stage, N stage, and risk score were also determined as significant prognostic variables. CIBERSORT was used to predict the constitution and relative content of the immune cells, wherein M0 macrophages were the most closely related to the key genes. In conclusion, CXCL5, CXCL8, IL18RAP, and TREM2 were associated with HCC prognosis and were important for immune cell invasion into the TME. Additionally, IL18RAP expression may contribute toward favorable prognosis in patients with HCC. Consequently, these genes may serve as potential biomarkers and immunotherapeutic targets for HCC.

Exploration of immune-related genes in high and low tumor mutation burden groups of chromophobe renal cell carcinoma

Renal cell carcinoma (RCC) is one of most common cancers with gradually increasing incidence and high mortality. Chromogenic RCC (chRCC) is the third most common histological subtype of RCC, accounting for approximately 5–7% of RCC. In our study, the transcriptome expression profile data (n=89) of chRCC, corresponding clinical data (n=113) and the somatic mutation data (n=66) were obtained from the TCGA database. We first analyzed the mutation data of chRCC patients and divided chRCC patients into high and low tumor mutation burden (TMB) groups based on the median TMB. We found that high TMB was significantly associated with worse prognosis and could promote tumor metastasis and development. Moreover, four different immune-related genes (BIRC5, PDGFRL, INHBE, IL20RB) were also identified. We found that BIRC5 was significantly overexpressed in the high TMB group and correlated with worse prognosis. The results of univariate and multivariate COX analyses demonstrated that BIRC5 (hazard ratio (HR) = 2.094) may serve as a prognostic indicator for patients with chRCC with high TMB. In addition, we identified the possible functional pathways of BIRC5 through gene set enrichment analysis (GSEA) enrichment. A positive correlation was obtained between BIRC5 and the abundance of CD4⁺ T cells. The results of our study revealed their correlation between the immune-related genes and clinicopathologic features as well as potential functional pathways as well as immune infiltrating cells, which may provide more data about the development of chRCC immunotherapy.

Prognostic value of aberrantly expressed methylation genes in human hepatocellular carcinoma

Objectives: To identify the prognostic value of aberrantly methylated differentially expressed genes (DEGs) in hepatocellular carcinoma (HCC) and to explore the underlying mechanisms of tumorigenesis.

Methods: Gene expression profiles (GSE65372 and GSE37988) were analyzed using GEO2R to obtain aberrantly methylated DEGs. Functional enrichment analysis of screened genes was performed by the Database for Annotation, Visualization, and Integrated Discovery (DAVID). Cytoscape software was used to analyze the PPI network and to select hub genes. Transcriptional and proteinic expression data of hub genes were obtained through UALCAN and the Human Protein Reference Database. Finally, we analyzed the prognostic value of hub genes with the Kaplan–Meier Plotter and MethSurv database.

Results: In total, 24 up-hypomethylated oncogenes and 37 down-hypermethylated tumor suppressor genes (TSGs) were identified, and 8 hub genes, including 4 up-hypomethylated oncogenes (CDC5L, MERTK, RHOA and YBX1) and 4 down-hypermethylated TSGs (BCR, DFFA, SCUBE2 and TP63), were selected by PPI. Higher expression of methylated CDC5L-cg05671347, MERTK-cg08279316, RHOA-cg05657651 and YBX1-cg16306148, and lower expression of methylated BCR-cg25410636, DFFA-cg20696875, SCUBE2-cg19000089 and TP63-cg06520450, were associated with better overall survival (OS) in HCC patients. Multivariate analysis also showed they were independent prognostic factors for OS of HCC patients.

Conclusions: In summary, different expression of methylated genes above mentioned were associated with better prognosis in HCC patients. Altering the methylation status of these genes may be a therapeutic target for HCC, but it should be further evaluated in clinical studies.

Tumor microenvironment immune subtypes for classification of novel clear cell renal cell carcinoma profiles with prognostic and therapeutic implications

Currently, no effective prognostic model of clear cell renal cell carcinoma (ccRCC) based on immune cell infiltration has been developed. Recent studies have identified 6 immune groups (IS) in 33 solid tumors. We aimed to characterize the expression pattern of IS in ccRCC and evaluate the potential in predicting patient prognosis. The clinical information, immune subgroup, somatic mutation, copy number variation, and methylation score of patients with TCGA ccRCC cohort were downloaded from UCSC Xena for further analysis. The most dominant IS in ccRCC was the inflammatory subgroup (immune C3) (86.5%), regardless of different pathological stages, pathological grades, and genders. In the C3 subgroup, stage IV (69.1%) and grade 4 (69.9%) were the least presented. Survival analysis showed that the IS could effectively predict the overall survival (OS) (P < .0001) and disease-specific survival (DSS) (P < .0001) of ccRCC alone, of which group C3 (OS, HR = 2.3, P < .001; DSS, HR = 2.84, P < .001) exhibited the best prognosis. Among the most frequently mutated ccRCC genes, only VHL and PBRM1 were found to be common in the C3 group. The homologous recombination deficiency score was also lower. High heterogeneity was observed in immune cells and immunoregulatory genes of IS. Notably, CD4+ memory resting T cells were highly infiltrating, regulatory T cells (Treg) showed low infiltration, and most immunoregulatory genes (such as CX3CL1, IFNA2, TLR4, SELP, HMGB1, and TNFRSF14) were highly expressed in the C3 subgroup than in other subgroups. Enrichment analysis showed that adipogenesis, apical junction, hypoxia, IL2 STAT5 signaling, TGF-beta signaling, and UV response DN were activated, whereas E2F targets, G2M checkpoint, and MYC targets V2 were downregulated in the C3 group. Immune classification can more accurately classify ccRCC patients and predict OS and DSS. Thus, IS-based classification may be a valuable tool that enables individualized treatment of patients with ccRCC.

MMP9 and IGFBP1 Regulate Tumor Immune and Drive Tumor Progression in Clear Cell Renal Cell Carcinoma

Immunotherapy is a novel approach and has been used in various diseases, especially in cancers. Recently, immunotherapy has gradually been used to treat advanced clear cell renal cell carcinoma (ccRCC) or metastatic ccRCC. However, the efficacy of immunotherapy is not satisfying due to the influence of the tumor microenvironment. In this study, we mainly focused on the abundance and function of tumor-infiltrating immune cells (TIICs). Monocyte and TNM stage were identified as independent prognostic factors via CIBERSORT and Cox regression analysis. Then, ccRCC patients were divided into high risk/TNMhighMonocyteslow cluster and low risk/TNMlowMonocyteshigh cluster. Further differential gene analysis, protein-protein interaction (PPI) network, and survival analysis screened nine hub genes between the above two clusters. MMP9 and IGFBP1 were selected for further study through sample validation. Moreover, gene set enrichment analysis revealed that MMP9 and IGFBP1 were involved in tumor immune via mediating cell surface receptor signal pathway, cytokine production pathway, or monocyte signal pathway. In conclusion, these findings suggested that monocyte acted as a protective factor and MMP9/IGFBP1 played a vital role in tumor immune, which might become potential novel biomarkers and therapeutic targets for immunotherapy in ccRCC.

Effect of myeloid ecotropic viral integration site (MEIS) family genes on tumor microenvironment remodeling and its potential therapeutic effect

Background

The myeloid ecotropic viral integration site (MEIS) family of genes is related to the occurrence, development, and outcome of many cancers. However, its role in the immune and tumor microenvironment (TME) is unclear. This study explored the relationship between the expression of MEIS genes and patient survival, immune subtypes, TME, tumor stem cell correlation, and drug sensitivity in cancer.

Methods

We used The Cancer Genome Atlas pan-cancer data to analyze the expression of the MEIS family genes. Kaplan-Meier analysis and univariate Cox proportional hazard regression model were used to detect the relationship between gene expression and overall survival. Analysis of variance was used to explore the relationship between the MEIS family and the immune components in the tumor, and the ESTIMATE algorithm was used to calculate the proportion and level of tumor-infiltrating immune cells. Spearman and Pearson’s correlation tests were carried out to detect the relationship between MEIS and the characteristics of tumor stem cells and drug sensitivity.

Results

The MEIS family of genes shows different expression profiles in different cancers, with substantial inter- and intra-cancer heterogeneity. Among them, MEIS3 was upregulated in most cancers, whereas MEIS2 was downregulated. The change in MEIS gene expression was usually related to overall survival, but whether a member of the MEIS family was a risk factor or a protective factor was cancer-dependent. Immune component analysis suggested that the role of MEIS genes in promoting or inhibiting cancer may be related to different degrees of immune silencing. Further, there were varying degrees of correlation between MEIS gene expression and cancer cell stemness characteristics. It was also found that MEIS genes, especially MEIS1 and MEIS2, may be related to chemotherapy resistance.

Conclusions

We explored the expression, prognostic relationship, molecular characteristics, and effects on immunity and TME of the MEIS gene family in cancer. Our results suggest that MEIS members should be studied as independent entities in different types of cancer. The MEIS gene family may be a potential target for cancer therapy, but further experiments are needed to confirm this.

Comprehensive analysis of glutathione peroxidase-1 (GPX1) expression and prognostic value in three different types of renal cell carcinoma

Background

Glutathione peroxidase-1 (GPX1) is generally expressed in tissues with high oxygen tension such as the kidneys and lungs, and its main function is to degrade reactive oxygen species (ROS) and protect cells from oxidative stress. Studies have shown that GPX1 is upregulated in many tumor tissues and is closely related to tumor progression and metastasis. This study aimed to explore the possibility of GPX1 as a biomarker for kidney chromophobe cell carcinoma (KICH), kidney renal papillary cell carcinoma (KIRP), and kidney renal clear cell carcinoma (KIRC).

Methods

The Oncomine and GEPIA databases were used to analyze the GPX1 expression differences between tumor and normal tissues, and the UALCAN, GEPIA and DriverDBv3 databases were used to perform the survival analyses. The GeneMANIA interactive tool was then used to find the GPX1-related protein-protein interaction (PPI). Following this, the LinkedOmics database was used for the enrichment analysis of GPX1, and the Timer database was used to estimate the abundance of immune infiltration. Finally, quantitative polymerase chain reaction (qPCR) was performed on patient specimens collected in the clinic to confirm the database findings.

Results

In our study, we found that the expression of GPX1 in three types of renal cell carcinoma (RCC) were upregulated, and the high expression of GXP1 was related to the poor prognosis of patients with KICH and KIRC. On the contrary, KIRP patients with a high expression of GPX1 had a better prognosis. In addition, GPX1 was related to the abundance of immune cell infiltration. The results of the qPCR analysis confirmed that the expression of GPX1 in RCC was increased compared with the control group (P<0.05).

Conclusions

Our results indicate that the expression of GPX1 is related to the prognosis of three types of RCC. As such, GPX1 expression could be a reliable diagnostic and prognostic biomarker for RCC and, more importantly, may provide a new direction for therapeutic strategies.

Caspase 4 Overexpression as a Prognostic Marker in Clear Cell Renal Cell Carcinoma: A Study Based on the Cancer Genome Atlas Data Mining

The dysregulation of caspase 4 (CASP4) expression is related to the occurrence, development, and outcome of many malignant tumors; however, its role in clear cell renal cell carcinoma (ccRCC) remains unclear. Herein, we investigated the expression of CASP4 in tumor tissues and its relationship with clinical prognosis, immune infiltration, and drug sensitivity status of ccRCC patients. Oncomine and The Cancer Genome Atlas (TCGA) databases were used to determine CASP4 mRNA expression in ccRCC patients. The correlation between CASP4 expression and disease prognosis was evaluated using Kaplan–Meier analysis. Related pathways were obtained from TCGA database via gene set enrichment analysis (GSEA) and gene set variation analysis (GSVA). Meanwhile, genes co-expressing with CASP4 in ccRCC were investigated. Finally, we analyzed the proportion of tumor-infiltrating immune cells (TICs) using the CIBERSORT computational method and assessed CASP4 methylation and its relationship with drug sensitivity. Immunohistochemical analysis of 30 paired ccRCC and adjacent normal tissues confirmed the in silico results. CASP4 mRNA expression in ccRCC was significantly higher than that in the normal tissues, positively correlated with clinicopathological features (clinical stage and pathological grade), and negatively correlated with patient overall survival (OS). GSEA and GSVA showed that the genes in the CASP4-high expression group were primarily enriched in immune-related activities. Moreover, CIBERSORT analysis of TIC proportions revealed that activated CD4 memory T cells were positively correlated with CASP4 expression. Notably, methylation analysis revealed that the abnormal upregulation of CASP4 might be caused by hypomethylation. Finally, we found that the abnormal expression of CASP4 may be related to tumor drug resistance. Overall, our study shows that CASP4 is overexpressed in ccRCC and is an important factor affecting disease prognosis. Hence, CASP4 may serve as a potential prognostic biomarker and therapeutic target in ccRCC.

Renal Cell Carcinoma Associated with Mycosis Fungoides: A Paraneoplastic Syndrome

Patients with mycosis fungoides have an increased risk for additional malignancies, particularly hematologic malignancies. Of the malignancies that have been associated with mycosis fungoides, renal cell carcinoma and other solid tumor malignancies have not been studied extensively. In this case series, we describe three mycosis fungoides patients who were diagnosed with clear cell renal cell carcinoma and discuss the potential pathophysiology underlying this association.

Critical Role for Cold Shock Protein YB-1 in Cytokinesis

Simple Summary

Y-box-binding protein-1, YB-1, plays an important role in regulating the cell cycle, although precisely how it does the is unknown. Using live cell imaging, we show that YB-1 is essential for initiating the last step of cell division (cytokinesis), required for creation of two daughter cells. Using confocal microscopy we showed that YB-1 regulates the spatial distribution of key proteins essential for cytokinesis to occur and that this required YB-1 to be phosphorylated on several residues. In-silico modeling demonstrated that modifications at these residues resulted in conformational changes in YB-1 protein allowing it to interact with proteins essential for cytokinesis. As many cancers have high levels YB-1 and these are associated with poor prognosis, our data suggest developing small molecule inhibitors to block YB-1 phosphorylation could be a novel approach to cancer therapy.

Abstract

High levels of the cold shock protein Y-box-binding protein-1, YB-1, are tightly correlated with increased cell proliferation and progression. However, the precise mechanism by which YB-1 regulates proliferation is unknown. Here, we found that YB-1 depletion in several cancer cell lines and in immortalized fibroblasts resulted in cytokinesis failure and consequent multinucleation. Rescue experiments indicated that YB-1 was required for completion of cytokinesis. Using confocal imaging we found that YB-1 was essential for orchestrating the spatio-temporal distribution of the microtubules, β-actin and the chromosome passenger complex (CPC) to define the cleavage plane. We show that phosphorylation at six serine residues was essential for cytokinesis, of which novel sites were identified using mass spectrometry. Using atomistic modelling we show how phosphorylation at multiple sites alters YB-1 conformation, allowing it to interact with protein partners. Our results establish phosphorylated YB-1 as a critical regulator of cytokinesis, defining precisely how YB-1 regulates cell division.

An immune scores-based nomogram for predicting overall survival in patients with clear cell renal cell carcinoma

The role of immune cell infiltration in the prognosis of clear cell renal cell carcinoma (ccRCC) has received increasing attention. However, immune scores have not yet been introduced into routine clinical practice of ccRCC patients. The principal objective of our research was to study the correlation between immune scores and overall survival (OS) of ccRCC.In this study, Cox regression analyses were used to identify risk factors associated with OS of ccRCC based on the Cancer Genome Atlas datasets. Furthermore, an integrated nomogram combining immune scores and clinicopathologic factors was built for predicting 3- and 5-year OS of ccRCC patients. The receiver operating characteristic curve, concordance index, and calibration curves were used for the evaluation of our nomogram. Also, Kaplan-Meier (KM) survival analysis of immune scores, stromal scores, and different clinicopathological factors was performed.A total of 514 patients were divided into the low- or high-immune scores group. KM and multivariate Cox regression analyses demonstrated that ccRCC patients with high-immune scores had significantly poor OS compared with those with low-immune scores. Calibration curves showed good consistency between the predicted OS and the actual OS probability. Areas under the receiver operating characteristic curves for 3- and 5-year OS were 0.816 and 0.769, and the concordance index was 0.775, indicating that our nomogram had good accuracy for predicting OS of ccRCC patients. Additionally, KM analysis showed that older age, later T stage, distant metastasis, advanced tumor lymph node metastasis stage, higher tumor grade, left site, and low stromal scores were associated with worse OS in ccRCC patients.High-immune scores show a significant correlation with unsatisfactory prognosis in ccRCC patients. Furthermore, the immune scores-based nomogram may be helpful in predicting ccRCC prognosis.

TRPV1 acts as a Tumor Suppressor and is associated with Immune Cell Infiltration in Clear Cell Renal Cell Carcinoma: evidence from integrated analysis

Differential expression of TRPV1 has been detected in many cancer types, including clear cell renal cell carcinoma (ccRCC). However, the clinical significance of TRPV1 expression profile in ccRCC has not been comprehensively elucidated. In this study, TRPV1 expression in ccRCC and other cancer types was analyzed based on data from the GEO and Oncomine databases. Immunohistochemical (IHC) staining was performed for further validation in human ccRCC tissue chips. Survival and correlation analyses of TRPV1 were conducted using Kaplan-Meier Plotter (KM-Plotter) and the Tumor IMmune Estimation Resource (TIMER) database. TRPV1 exhibited a low expression profile in 2 GEO datasets (GSE6344, GSE36895) and 4 Oncomine datasets (Gumz, Lenburg, Beroukhim 1 and Beroukhim 2), as also confirmed by IHC staining. Survival analysis indicated that high enrichment of TRPV1 significantly predicted a better overall survival (OS) and disease-free survival (DFS) of 1, 3, 5 and 10 years in ccRCC patients. TIMER analysis showed that TRPV1 copy number alterations (CNA) were closely related to immune cell infiltration. The detailed results indicated that TRPV1 expression was positively correlated with the infiltration level of CD4+ T cells, but negatively correlated with B cells, macrophages, and dendritic cells infiltration. In addition, TRPV1 might also be inversely related to abundance of the regulatory T cells (Treg) and the M2 subset of macrophages. Finally, we found that TRPV1 expression was tightly associated with several key molecules of the classical pathways in ccRCC, such as VHL, TP53, HIF1A, MTOR, MAPK1, MET, CTNNB1, etc. Our research work suggests that TRPV1 is a novel tumor suppressor and prognosis marker for ccRCC and is of great value for further exploration.

Novel molecular signatures and potential therapeutics in renal cell carcinomas: Insights from a comparative analysis of subtypes

Renal cell carcinomas (RCCs) are among the highest causes of cancer mortality. Although transcriptome profiling studies in the last decade have made significant molecular findings on RCCs, effective diagnosis and treatment strategies have yet to be achieved due to lack of adequate screening and comparative profiling of RCC subtypes. In this study, a comparative analysis was performed on RNA-seq based transcriptome data from each RCC subtype, namely clear cell RCC (KIRC), papillary RCC (KIRP) and kidney chromophobe (KICH), and mutual or subtype-specific reporter biomolecules were identified at RNA, protein, and metabolite levels by the integration of expression profiles with genome-scale biomolecular networks. This approach revealed already-known biomarkers in RCCs as well as novel biomarker candidates and potential therapeutic targets. Our findings also pointed out the incorporation of the molecular mechanisms of KIRC and KIRP, whereas KICH was shown to have distinct molecular signatures. Furthermore, considering the Dipeptidyl Peptidase 4 (DPP4) receptor as a potential therapeutic target specific to KICH, several drug candidates such as ZINC6745464 were identified through virtual screening of ZINC molecules. In this study, we reported valuable data for further experimental and clinical efforts, since the proposed molecules have significant potential for screening and therapeutic purposes in RCCs.

Data Mining of Prognostic Microenvironment-Related Genes in Clear Cell Renal Cell Carcinoma: A Study with TCGA Database

Clear cell renal cell carcinoma (ccRCC) is one of the most prevalent kidney malignancies. The tumor microenvironment (TME) is highly related to the oncogenesis, progress, and prognosis of ccRCC. The aim of this study was to infer the level of infiltrating stromal and immune cells and assess the prognostic value of them. The gene expression profile was obtained from TCGA and used for calculating the stromal and immune scores. Based on a cut-off value, patients were divided into low- and high-stromal/immune score groups. Survival analysis was performed to evaluate the prognostic value of stromal and immune scores. Moreover, differentially expressed genes (DEGs) that are highly related to TME were determined and applied for functional enrichment analysis and protein-protein interaction (PPI) network. The Kaplan-Meier plot demonstrated that patients with high-immune scores and stromal scores had poorer clinical outcome. In addition, a total of 89 DEGs were identified and mainly involved in 5 pathways. The top 5 degree genes were extracted from the PPI network; among them, IL10 and XCR1 were highly associated with prognosis of ccRCC. The results of the present study demonstrated that ESTIMATE algorithm-based stromal and immune scores may be a credible indicator of cancer prognosis and IL10 along with XCR1 may be a potential key regulator for the TME of ccRCC.

Identification of novel prognostic alternative splicing signature in papillary renal cell carcinoma

Papillary renal cell carcinoma (pRCC) is a heterogeneous disease containing multifocal or solitary tumors with an aggressive phenotype. Increasing evidence has indicated the involvement of aberrant splicing variants in renal cell cancer, while systematic profiling of aberrant alternative splicing (AS) in pRCC was lacking and largely unknown. In the current study, comprehensive profiling of AS events were performed based on the integration of pRCC cohort from the Cancer Genome Atlas database and SpliceSeq software. With rigorous screening and univariate Cox analysis, a total of 2077 prognoses AS events from 1642 parent genes were identified. Then, stepwise least absolute shrinkage and selection operator method-penalized Cox regression analyses with 10-fold cross-validation followed by multivariate Cox regression were used to construct the prognostic AS signatures within each AS type. And a final 21 AS event-based signature was proposed which showed potent prognostic capability in stratifying patients into low- and high-risk subgroups (P < .0001). Furthermore, time-dependent receiver operating characteristics curves confirmed that the final AS signature was effective and robust in predicting overall survival for pRCC patients with the area under the curve above 0.9 from 1 to 5 years. In addition, splicing correlation network was built to uncover the potential regulatory pattern among prognostic splicing factors and candidate AS events. Besides, gene set enrichment analysis revealed the involvement of these candidates AS events in tumor-related pathways including extracellular matrix organization, oxidative phosphorylation, and P53 signaling pathways. Taken together, our results could contribute to elucidating the underlying mechanism of AS in the oncogenesis process and broaden the novel field of prognostic and clinical application of molecule-targeted approaches in pRCC.

Immune infiltration in renal cell carcinoma

Immune infiltration of tumors is closely associated with clinical outcome in renal cell carcinoma (RCC). Tumor‐infiltrating immune cells (TIICs) regulate cancer progression and are appealing therapeutic targets. The purpose of this study was to determine the composition of TIICs in RCC and further reveal the independent prognostic values of TIICs. CIBERSORT, an established algorithm, was applied to estimate the proportions of 22 immune cell types based on gene expression profiles of 891 tumors. Cox regression was used to evaluate the association of TIICs and immune checkpoint modulators with overall survival (OS). We found that CD8+ T cells were associated with prolonged OS (hazard ratio [HR] = 0.09, 95% confidence interval [CI].01‐.53; P = 0.03) in chromophobe carcinoma (KICH). A higher proportion of regulatory T cells was associated with a worse outcome (HR = 1.59, 95% CI 1.23‐.06; P < 0.01) in renal clear cell carcinoma (KIRC). In renal papillary cell carcinoma (KIRP), M1 macrophages were associated with a favorable outcome (HR = .43, 95% CI .25‐.72; P < 0.01), while M2 macrophages indicated a worse outcome (HR = 2.55, 95% CI 1.45‐4.47; P < 0.01). Moreover, the immunomodulator molecules CTLA4 and LAG3 were associated with a poor prognosis in KIRC, and IDO1 and PD‐L2 were associated with a poor prognosis in KIRP. This study indicates TIICs are important determinants of prognosis in RCC meanwhile reveals potential targets and biomarkers for immunotherapy development.