Unveiling the hidden role of disulfidptosis in kidney renal clear cell carcinoma: a prognostic signature for personalized treatment

The role of disulfidptosis in kidney renal clear cell carcinoma (KIRC) remains unknown. This study investigated disulfidptosis-related biomarkers for KIRC prognosis prediction and individualized treatment. KIRC patients were clustered by disulfidptosis profiles. Differential expression analysis, survival models, and machine learning were used to construct the disulfidptosis-related prognostic signature (DRPS). Characterizations of the tumor immune microenvironment, genetic drivers, drug sensitivity, and immunotherapy response were explored according to the DRPS risk stratification. Markers included in the signature were validated using single-cell, spatial transcriptomics, quantitative RT-qPCR, and immunohistochemistry. In the discovery cohort, we unveiled two clusters of KIRC patients that differed significantly in disulfidptosis regulator expressions and overall survival (OS). After multiple feature selection steps, a DRPS prognostic model with four features (CHAC1, COL7A1, FOXM1, SHOX2) was constructed and validated. Combined with clinical factors, the model demonstrated robust performance in the discovery and external validation cohorts (5-year AUC = 0.793 and 0.846, respectively). KIRC patients with high-risk scores are characterized by inferior OS, less tumor purity, and increased infiltrations of fibroblasts, M1 macrophages, and B cells. High-risk patients also have higher frequencies of BAP1 and AHNAK2 mutation. Besides, the correlation between the DRPS score and the chemotherapy-response signature indicated the potential effect of Gefitinib for high-risk patients. Among the signature genes, FOXM1 is highly expressed in cycling tumor cells and exhibits spatial aggregation, while others are expressed sparsely within tumor samples. The DRPS model enables improved clinical management and personalized KIRC therapy. The identified biomarkers and immune characteristics offer new mechanistic insight into disulfidptosis in KIRC.

zDHHC3-mediated S-palmitoylation of SLC9A2 regulates apoptosis in kidney clear cell carcinoma

PURPOSE

Kidney clear cell carcinoma (KIRC) has a poor prognosis, high morbidity and mortality rates, and high invasion and metastasis rate, and effective therapeutic targets are lacking. zDHHC3 has been implicated in various cancers, but its specific role in KIRC remains unclear.

METHODS

In this study, we performed a pan-cancer analysis, bioinformatics analysis, and cell experiment to detect the role of zDHHC3 in KIRC.

RESULTS

zDHHC3 was significantly down-regulated in KIRC, and that its high expression was associated with favorable patient outcomes. We identified 202 hub genes that were most relevant to high zDHHC3 expression and KIRC, and found that they were involved mainly in ion transport and renal cell carcinoma. Among these hub genes, SLC9A2 was identified as a downstream gene of zDHHC3. zDHHC3 suppression led to decreased expression and S-palmitoylation of SLC9A2, which further inhibited the apoptosis of Caki-2 cells.

CONCLUSION

Our findings suggest that zDHHC3 plays an important role in KIRC, due partly to its regulation of SLC9A2 S-palmitoylation. The targeting of the zDHHC3-SLC9A2 axis may provide a new option for the clinical treatment of KIRC.

Elevated ADH5 expression suggested better prognosis in kidney renal clear cell carcinoma (KIRC) and related to immunity through single-cell and bulk RNA-sequencing

BACKGROUND

Despite the rapid advances in modern medical technology, kidney renal clear cell carcinoma (KIRC) remains a challenging clinical problem in urology. Researchers urgently search for useful markers to break through the therapeutic conundrum due to its high lethality. Therefore, the study explores the value of ADH5 on overall survival (OS) and the immunology of KIRC.

METHODS

The gene expression matrix and clinical information on ADH5 in the TCGA database were validated using external databases and qRT-PCR. To confirm the correlation between ADH5 and KIRC prognosis, univariate/multivariate Cox regression analysis was used. We also explored the signaling pathways associated with ADH5 in KIRC and investigated its association with immunity.

RESULTS

The mRNA and protein levels showed an apparent downregulation of ADH5 in KIRC. Correlation analysis revealed that ADH5 was directly related to histological grade, clinical stage, and TMN stage (p < 0.05). Univariate and multivariate Cox regression analysis identified ADH5 as an independent factor affecting the prognosis of KIRC. Enrichment analysis looked into five ADH5-related signaling pathways. The results showed no correlation between ADH5 and TMB, TNB, and MSI. From an immunological perspective, ADH5 was found to be associated with the tumor microenvironment, immune cell infiltration, and immune checkpoints. Lower ADH5 expression was associated with greater responsiveness to immunotherapy. Single-cell sequencing revealed that ADH5 is highly expressed in immune cells.

CONCLUSION

ADH5 could be a promising prognostic biomarker and a potential therapeutic target for KIRC. Besides, it was found that KIRC patients with low ADH5 expression were more sensitive to immunotherapy.

Novel inhibitors targeting the PGK1 metabolic enzyme in glycolysis exhibit effective antitumor activity against kidney renal clear cell carcinoma in vitro and in vivo

Our previous research has revealed phosphoglycerate kinase 1 (PGK1) enhances tumorigenesis and sorafenib resistance of kidney renal clear cell carcinoma (KIRC) by regulating glycolysis, so that PGK1 is a promising drug target. Herein we performed structure-based virtual screening and series of anticancer pharmaceutical experiments in vitro and in vivo to identify novel small-molecule PGK1-targeted compounds. As results, the compounds CHR-6494 and Z57346765 were screened and confirmed to specifically bind to PGK1 and significantly reduced the metabolic enzyme activity of PGK1 in glycolysis, which inhibited KIRC cell proliferation in a dose-dependent manner. While CHR-6494 showed greater anti-KIRC efficacy and fewer side effects than Z57346765 on nude mouse xenograft model. Mechanistically, CHR-9464 impeded glycolysis by decreasing the metabolic enzyme activity of PGK1 and suppressed histone H3T3 phosphorylation to inhibit KIRC cell proliferation. Z57346765 induced expression changes of genes related to cell metabolism, DNA replication and cell cycle. Overall, we screened two novel PGK1 inhibitors, CHR-6494 and Z57346765, for the first time and discovered their potent anti-KIRC effects by suppressing PGK1 metabolic enzyme activity in glycolysis.

Identification of cuproptosis-related lncRNAs signature for predicting the prognosis in patients with kidney renal clear cell carcinoma

BACKGROUND

Kidney renal clear cell carcinoma (KIRC), with low survival rate, is the most frequent subtype of renal cell carcinoma. Recently, more and more studies indicate that cuproptosis-related genes (CRGs) and long non-coding RNAs (lncRNAs) play a vital role in the occurrence and development of many types of cancers. However, the roles of cuproptosis-related lncRNAs (CRlncRNAs) in the KIRC was uncertain.

RESULTS

In our study, CRlncRNAs were obtained by coexpression between differentially expressed and prognostic CRGs and differentially expressed and prognostic lncRNAs, and an 8-CRlncRNAs (AC007743.1, AC022915.1, AP005136.4, APCDD1L-DT, HAGLR, LINC02027, MANCR and SMARCA5-AS1) risk model was established according to least absolute shrinkage and selection operator (LASSO) and multivariate Cox regression. This risk model could differentiate immune cell infiltration, immune function and gene mutation.

CONCLUSIONS

This 8-CRlncRNAs risk model may be promising for the clinical prediction of prognoses, tumor immune, immunotherapy response and chemotherapeutic response in KIRC patients.

A Novel KIF4A-Related Model for Predicting Immunotherapy Response and Prognosis in Kidney Renal Clear Cell Carcinoma

BACKGROUND

The efficacy of chemotherapy in treating Kidney Renal Clear Cell Carcinoma (KIRC) is limited, whereas immunotherapy has shown some promising clinical outcomes. In this context, KIF4A is considered a potential therapeutic target for various cancers. Therefore, identifying the mechanism of KIF4A that can predict the prognosis and immunotherapy response of KIRC would be of significant importance.

METHODS

Based on the TCGA Pan-Cancer dataset, the prognostic significance of the KIF4A expression across 33 cancer types was analyzed by univariate Cox algorithm. Furthermore, overlapping differentially expressed genes (DEGs1) between the KIF4A high- and lowexpression groups and DEGs2 between the KIRC and normal groups were also analyzed. Machine learning and Cox regression algorithms were performed to obtain biomarkers and construct a prognostic model. Finally, the role of KIF4A in KIRC was analyzed using quantitative real-time PCR, transwell assay, and EdU experiment.

RESULTS

Our analysis revealed that KIF4A was significant for the prognosis of 13 cancer types. The highest correlation with KIF4A was found for KICH among the tumour mutation burden (TMB) indicators. Subsequently, a prognostic model developed with UBE2C, OTX1, PPP2R2C, and RFLNA was obtained and verified with the Renal Cell Cancer-EU/FR dataset. There was a positive correlation between risk score and immunotherapy. Furthermore, the experiment results indicated that KIF4A expression was considerably increased in the KIRC group. Besides, the proliferation, migration, and invasion abilities of KIRC tumor cells were significantly weakened after KIF4A was knocked out.

CONCLUSION

We identified four KIF4A-related biomarkers that hold potential for prognostic assessment in KIRC. Specifically, early implementation of immunotherapy targeting these biomarkers may yield improved outcomes for patients with KIRC.

Low expression of fatty acid oxidation related gene ACADM indicates poor prognosis of renal clear cell carcinoma and is related to tumor immune infiltration

This research aims to identify the key fatty acid beta-oxidation (FAO) genes that are altered in kidney renal clear cell carcinoma (KIRC) and to analyze the role of these genes in KIRC. The Gene Expression Omnibus (GEO) and FAO datasets were used to identify these key genes. Wilcoxon rank sum test was used to assess the levels of acyl-CoA dehydrogenase medium chain (ACADM) between KIRC and non-cancer samples. The logistic regression and Wilcoxon rank sum test were used to explore the association between ACADM and clinical features. The diagnostic performance of ACADM for KIRC was assessed using a diagnostic receiver operating characteristic (ROC) curve. The co-expressed genes of ACADM were identified in LinkedOmics database, and their function and pathway enrichment were analyzed. The correlation between ACADM expression level and immune infiltration was analyzed by Gene Set Variation Analysis (GSVA) method. Additionally, the proliferation, migration, and invasion abilities of KIRC cells were assessed after overexpressing ACADM. Following differential analysis and intersection, we identified six hub genes, including ACADM. We found that the expression level of ACADM was decreased in KIRC tissues and had a better diagnostic effect (AUC = 0.916). Survival analysis suggested that patients with decreased ACADM expression had a worse prognosis. According to correlation analysis, a variety of clinical features were associated with the expression level of ACADM. By analyzing the infiltration level of immune cells, we found that ACADM may be related to the enrichment of immune cells. Finally, ACADM overexpression inhibited proliferation, migration, and invasion of KIRC cells. In conclusion, our findings suggest that reduced ACADM expression in KIRC patients is indicative of poor prognosis. These results imply that ACADM may be a diagnostic and prognostic marker for individuals with KIRC, offering a reference for clinicians in diagnosis and treatment.

Low expression of PRRG2 in kidney renal clear cell carcinoma: an immune infiltration-associated prognostic biomarker

OBJECTIVE

This study aims to explore the prognostic significance of Proline-rich γ-carboxyglutamic acid protein 2 (PRRG2) in Kidney Renal Clear Cell Carcinoma (KIRC), a prevalent and deadly cancer, and its association with immune cell infiltration, a key strategy in developing effective biomarkers.

METHODS

The study meticulously elucidated the prognostic significance and potential role of PRRG2 in KIRC, correlating its expression with patient sex, age, metastasis, and pathological stage. Utilizing Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and Gene Set Enrichment Analysis (GSEA), the involvement of PRRG2 in immune response was investigated. The association between PRRG2 expression and immune cell infiltration was also scrutinized. Ultimately, cellular and tissue identity were confirmed via immunohistochemical staining and quantitative real-time PCR.

RESULTS

The study elucidates a notable decrease in PRRG2 expression in KIRC patients, correlating with demographic factors, metastasis, and pathological staging, and portending an unfavorable prognosis. Bioinformatic analyses underscore PRRG2's role in immune response, with its expression significantly tied to immune cell infiltration and marker expression.

CONCLUSION

PRRG2 may potentially impact prognosis in KIRC patients by regulating immune infiltration, thus rendering PRRG2 a promising candidate prognostic biomarker for KIRC-associated immune infiltration.

Comprehensive analysis reveals dual biological function roles of EpCAM in kidney renal clear cell carcinoma

Background

Epithelial cell adhesion molecule (EpCAM), a well-established marker for circulating tumor cells, plays a crucial role in the complex process of cancer metastasis. The primary objective of this investigation is to study EpCAM expression in pan-cancer and elucidate its significance in the context of kidney renal clear cell carcinoma (KIRC).

Methods

Data obtained from the public database was harnessed for the comprehensive assessment of the EpCAM expression levels and prognostic and clinicopathological correlations in thirty-three types of cancer. EpCAM was validated in our own KIRC sequencing and immunohistochemical cohorts. Subsequently, an in-depth exploration was conducted to scrutinize the interrelationship between EpCAM and various facets, including immune cells, immune checkpoints, and chemotherapy drugs. We employed Cox regression analysis to identify prognostic immunomodulators associated with EpCAM, which were subsequently utilized in the development of a prognostic model. The model was validated in our own clinical cohort and public datasets, and compared with 137 published models. The role of EpCAM in KIRC was explored by biological function experiments in vitro.

Results

While EpCAM exhibited pronounced overexpression across a wide spectrum of cancer types, a notable reduction was observed in KIRC tissues. As grade increased, EpCAM expression decreased. EpCAM expression decreased in patients without metastasis. EpCAM mRNA and protein levels were used as independent, favorable prognostic factors in patients with KIRC in our own cohort. The expression of EpCAM exhibited strong associations with immune-related pathways, demonstrating an inverse correlation with the majority of immune cell types. Immune checkpoint inhibitors exert better therapeutic effects on patients with low EpCAM expression. In addition, EpCAM can be used as a drug resistance indicator and guide the clinical medication of patients with KIRC. A robust model, which had good predictive accuracy and applicability, showed significant superiority over other models. Importantly, EpCAM played the dual roles of promoting proliferation and resisting metastasis in KIRC.

Conclusion

In the context of KIRC, EpCAM assumes a surprising dual role, where it not only facilitates cell proliferation but also exerts resistance against the metastatic process. EpCAM serves as a standalone prognostic marker for patients with KIRC, and related models can also effectively predict prognosis. These discoveries offer novel perspectives on the functional significance of EpCAM in the context of KIRC.

A serum panel of three microRNAs may serve as possible biomarkers for kidney renal clear cell carcinoma

BACKGROUND

Although non-invasive radiological techniques are widely applied in kidney renal clear cell carcinoma (KIRC) diagnosis, more than 50% of KIRCs are detected incidentally during the diagnostic procedures to identify renal cell carcinoma (RCC). Thus, sensitive and accurate KIRC diagnostic methods are required. Therefore, in this study, we aimed to identify KIRC-associated microRNAs (miRNAs).

METHODS

This three-phase study included 224 participants (112 each of patients with KIRC and healthy controls (NCs)). RT-qPCR was used to evaluate miRNA expression in KIRC and NC samples. Receiver operating characteristic (ROC) curves and the area under the ROC curve (AUC) were used to predict the usefulness of serum miRNAs in KIRC diagnosis. In addition, we performed survival and bioinformatics analyses.

RESULTS

We found that miR-1-3p, miR-129-5p, miR-146b-5p, miR-187-3p, and miR-200a-3p were significantly differentially expressed in patients with KIRC. A panel consisting of three miRNAs (miR-1-3p, miR-129-5p, and miR-146b-5p) had an AUC of 0.895, ranging from 0.848 to 0.942. In addition, using the GEPIA database, we found that the miRNAs were associated with CREB5. According to the survival analysis, miR-146b-5p overexpression was indicative of a poorer prognosis in patients with KIRC.

CONCLUSIONS

The identified three-miRNA panel could serve as a non-invasive indicator for KIRC and CREB5 as a potential target gene for KIRC treatment.

Upregulated PPP1R14B is connected to cancer progression and immune infiltration in kidney renal clear cell carcinoma

BACKGROUND

Protein phosphatase 1 regulatory subunit 14B (PPP1R14B) is an oncogenic gene found in a variety of tumors, but its role in the prognosis and development of kidney renal clear cell carcinoma (KIRC) remains unknown. Our study aimed to determine whether PPP1R14B could be a prognostic biomarker for KIRC and its role in the development of KIRC.

METHODS

In this work, we used The Cancer Genome Atlas (TCGA) database to explore the expression of PPP1R14B in tumor tissues, its relationship with the prognosis of tumor patients, and its role in tumor occurrence and development. We validated our findings using the International Cancer Genome Consortium (ICGC) cohort, our clinical samples, and in vitro experiments.

RESULTS

PPP1R14B was upregulated in KIRC compared to adjacent normal tissue. Moreover, multivariate analysis revealed that upregulated PPP1R14B expression was an independent risk factor for KIRC progression. High-PPP1R14B groups had shorter overall survival (OS) and disease-free survival (DFS) in TCGA and ICGC cohorts. We used Cell Counting Kit-8 (CCK8) and scratch wound healing assay to explore the proliferation and migration of KIRC cells following PPP1R14B knockdown. Our results indicated that PPP1R14B knockdown significantly reduced the proliferation and migration of KIRC cells in vitro. We also explored the possible cellular mechanisms of PPP1R14B through the Kyoto Encyclopedia of Genes and Genomes (KEGG), Gene ontology (GO) analysis, and TISIDB analysis. The function enrich analysis revealed that PPP1R14B-related genes were mainly enriched in purine metabolism and the macromolecule catabolic process. PPP1R14B expression was associated with tumor-infiltrating immune cells (TIICs) in the TCGA cohort, and the results of single-cell RNA-seq (scRNA) further demonstrated that PPP1R14B expression was associated with the enhanced infiltration of CD8 + T lymphocytes.

CONCLUSION

PPP1R14B may serve as a prognostic biomarker in KIRC, affect purine metabolism, activate immune infiltration, and promote KIRC cell migration.

CD72, a new immune checkpoint molecule, is a novel prognostic biomarker for kidney renal clear cell carcinoma

BACKGROUND

The incidence and mortality of clear cell carcinoma of the kidney increases yearly. There are limited screening methods and advances in treating kidney renal clear cell carcinoma (KIRC). It is important to find new biomarkers to screen, diagnose and predict the prognosis of KIRC. Some studies have shown that CD72 influences the development and progression of colorectal cancer, nasopharyngeal cancer, and acute lymphoid leukemia. However, there is a lack of research on the role of CD72 in the pathogenesis of KIRC. This study aimed to determine whether CD72 is associated with the prognosis and immune infiltration of KIRC, providing an essential molecular basis for the early non-invasive diagnosis and immunotherapy of KIRC.

METHODS

Using TCGA, GTE, GEO, and ImmPort databases, we obtained the differentially expressed mRNA (DEmRNA) associated with the prognosis and immunity of KIRC patients. We used the Kruskal-Wallis test to identify clinicopathological parameters associated with target gene expression. We performed univariate and multivariate COX regression analyses to determine the effect of target gene expression and clinicopathological parameters on survival. We analyzed the target genes' relevant functions and signaling pathways through enrichment analysis. Finally, the correlation of target genes with tumor immune infiltration was explored by ssGSEA and Spearman correlation analysis.

RESULTS

The results revealed that patients with KIRC with higher expression of CD72 have a poorer prognosis. CD72 was associated with the Pathologic T stage, Pathologic stage, Pathologic M stage, Pathologic N stage, Histologic grade in KIRC patients, Laterality, and OS event. It was an independent predictor of the overall survival of KIRC patients. Functional enrichment analysis showed that CD72 was significantly enriched in oncogenic and immune-related pathways. According to ssGSEA and Spearman correlation analysis, CD72 expression was significantly associated with tumor immune cells and immune checkpoints.

CONCLUSION

Our study suggests that CD72 is associated with tumor immunity and may be a biomarker relevant to the diagnosis and prognosis of KIRC patients.

Selection of M7G-related lncRNAs in kidney renal clear cell carcinoma and their putative diagnostic and prognostic role

BACKGROUND

Kidney renal clear cell carcinoma (KIRC) is a common malignant tumor of the urinary system. This study aims to develop new biomarkers for KIRC and explore the impact of biomarkers on the immunotherapeutic efficacy for KIRC, providing a theoretical basis for the treatment of KIRC patients.

METHODS

Transcriptome data for KIRC was obtained from the The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) databases. Weighted gene co-expression network analysis identified KIRC-related modules of long noncoding RNAs (lncRNAs). Intersection analysis was performed differentially expressed lncRNAs between KIRC and normal control samples, and lncRNAs associated with N(7)-methylguanosine (m7G), resulting in differentially expressed m7G-associated lncRNAs in KIRC patients (DE-m7G-lncRNAs). Machine Learning was employed to select biomarkers for KIRC. The prognostic value of biomarkers and clinical features was evaluated using Kaplan-Meier (K-M) survival analysis, univariate and multivariate Cox regression analysis. A nomogram was constructed based on biomarkers and clinical features, and its efficacy was evaluated using calibration curves and decision curves. Functional enrichment analysis was performed to investigate the functional enrichment of biomarkers. Correlation analysis was conducted to explore the relationship between biomarkers and immune cell infiltration levels and common immune checkpoint in KIRC samples.

RESULTS

By intersecting 575 KIRC-related module lncRNAs, 1773 differentially expressed lncRNAs, and 62 m7G-related lncRNAs, we identified 42 DE-m7G-lncRNAs. Using XGBoost and Boruta algorithms, 8 biomarkers for KIRC were selected. Kaplan-Meier survival analysis showed significant survival differences in KIRC patients with high and low expression of the PTCSC3 and RP11-321G12.1. Univariate and multivariate Cox regression analyses showed that AP000696.2, PTCSC3 and clinical characteristics were independent prognostic factors for patients with KIRC. A nomogram based on these prognostic factors accurately predicted the prognosis of KIRC patients. The biomarkers showed associations with clinical features of KIRC patients, mainly localized in the cytoplasm and related to cytokine-mediated immune response. Furthermore, immune feature analysis demonstrated a significant decrease in immune cell infiltration levels in KIRC samples compared to normal samples, with a negative correlation observed between the biomarkers and most differentially infiltrating immune cells and common immune checkpoints.

CONCLUSION

In summary, this study discovered eight prognostic biomarkers associated with KIRC patients. These biomarkers showed significant correlations with clinical features, immune cell infiltration, and immune checkpoint expression in KIRC patients, laying a theoretical foundation for the diagnosis and treatment of KIRC.

The potential of targeting cuproptosis in the treatment of kidney renal clear cell carcinoma

Renal cell carcinoma (RCC) is one of the top ten malignancies and tumor-related causes of death worldwide. The most common histologic subtype is kidney renal clear cell carcinoma (KIRC), accounting for approximately 75% of all RCC cases. Early resection is considered the basic treatment for patients with KIRC. However, approximately 30% of these patients experience recurrence post-operation. Cuproptosis, an autonomous mechanism for controlling cell death, encompasses various molecular mechanisms and multiple cellular metabolic pathways. These pathways mainly include copper metabolic signaling pathways, mitochondrial metabolism signaling pathways, and lipoic acid pathway signaling pathways. Recent evidence shows that cuproptosis is identified as a key cell death modality that plays a meaningful role in tumor progression. However, there is no published systematic review that summarizes the correlation between cuproptosis and KIRC, despite the fact that investigations on cuproptosis and the pathogenesis of KIRC have increased in past years. Researchers have discovered that exogenous copper infusion accelerates the dysfunction of mitochondrial dysfunction and suppresses KIRC cells by inducing cuproptosis. The levels of tricarboxylic acid cycle proteins, lipoic acid protein, copper, and ferredoxin 1 (FDX1) were dysregulated in KIRC cells, and the prognosis of patients with high FDX1 expression is better than that of patients with low expression. Cuproptosis played an indispensable role in the regulation of tumor microenvironment features, tumor progression, and long-term prognosis of KIRC. In this review, we summarized the systemic and cellular metabolic processes of copper and the copper-related signaling pathways, highlighting the potential targets related to cuproptosis for KIRC treatment.

The hsa-miR-3613-5p, a potential oncogene correlated with diagnostic and prognostic merits in kidney renal clear cell carcinoma

MicroRNA-3613 (hsa-miR-3613-5p), a biomarker with a dual role as an oncogenic or tumor suppressor, is associated with different types of cancer. This study aimed to determine the correlation between the hsa-miR-3613-5p gene expression and Kidney renal clear cell carcinoma (KIRC). Utilizing several bioinformatics tools, we examined the expression level and clinicopathological value of hsa-miR-3613-5p in patients with KIRC compared to normal tissues. Other bioinformatic measures, including survival analysis, diagnostic merit of hsa-miR-3613-5p, downstream target prediction, potential upstream lncRNAs, network construction, and functional enrichment analysis of hsa-miR-3613-5p, were performed. We observed that overexpression of hsa-miR-3613-5p in KIRC tissues had valuable diagnostic merit and was significantly correlated with the poor overall survival of KIRC patients. We also realized a correlation between abnormal expression of hsa-miR-3613-5p and several clinical parameters such as pathological stage, race, age, and histological grades in patients with KIRC. Moreover, we constructed the most potential regulatory network of hsa-miR-3613-5p in KIRC with 17 different axes, including four pseudogenes, two lncRNAs, and three mRNAs. Besides, we uncovered six variants in the mature form of hsa-miR-3613-5p. Finally, pathway enrichment analysis demonstrated that the top-ranked pathways for hsa-miR-3613-5p are cell cycle, cell adhesion molecules (CAMs), and hepatocellular carcinoma pathways. The present report suggests that the higher expression of hsa-miR-3613-5p is associated with the progression of KIRC. Therefore, it may be considered a valuable indicator for the early detection, risk stratification, and targeted treatment of patients with KIRC.

Necroptosis-related genes are associated with prognostic features of kidney renal clear cell carcinoma

INTRODUCTION

Renal clear cell carcinoma is a common type of cancer in the adult urological system. It has a high mortality rate, with 30% of patients developing metastasis and 60% dying within 1-2 years of diagnosis. Recent advancements in tumor immunology and necroptosis have provided new insights into kidney cancer therapy. Therefore, it is crucial to identify potential targets for combining immunotherapy with necroptosis.

MATERIALS AND METHODS

Using the GSE168845 dataset and necroptosis-related genes, we identified genes that are differentially expressed in relation to necroptosis. We analyzed the prognostic value of these genes through differential expression analysis, prognostic analysis, and Cox regression analysis. The expression levels of the MYCN and CDKN2A genes were verified using the GSE53757 dataset. We also examined the association between the differentially expressed genes and clinicopathological features, as well as overall survival in our cohorts. In addition, we constructed a lasso Cox regression model to assess the correlation between these genes and immune score, ICP, and OCLR score. We conducted qRT-PCR to detect the expression of MYCN, CDKN2A, and ZBP1 in different samples of kidney renal clear cell carcinoma (KIRC). The expression levels of these genes were verified in a normal kidney cell line (HK-2 cells) and two KIRC cell lines (786-O, ACHN). The protein levels of MYCN and CDKN2A were detected using immunohistochemistry (IHC). SiRNA was used to silence the expression of MYCN and CDKN2A in the ACHN cell line, and wound healing assays were performed to measure cell migration.

RESULTS

MYCN, CDKN2A, and ZBP1 were identified as necroptosis-related genes with independent prognostic value, leading to the development of a risk prognostic model. The expression of the CDKN2A gene was significantly higher in KIRC tissues compared to normal tissues, while the expression of the MYCN gene was significantly lower in KIRC tissues. The expression of MYCN and CDKN2A was associated with tumor stage, metastasis, and overall survival in our cohort. Furthermore, MYCN, CDKN2A, and ZBP1 were significantly correlated with immune score, ICP, and OCLR score. The expression levels of CDKN2A and ZBP1 were higher in KIRC cells compared to normal kidney cells, while the expression of MYCN was lower in KIRC cells. The protein expression of MYCN and CDKN2A was also higher in KIRC tissues, as confirmed by IHC. The results of the wound healing assay indicated that silencing CDKN2A inhibited cell migration, while silencing MYCN enhanced cell migration.

CONCLUSIONS

MYCN and CDKN2A are potential targets and valuable prognostic biomarkers for combining immunotherapy with necroptosis in kidney renal clear cell carcinoma. CDKN2A promotes the migration of renal cancer cells, while MYCN inhibits their migration.

Development and validation of a kidney renal clear cell carcinoma prognostic model relying on pyroptosis-related LncRNAs-A multidimensional comprehensive bioinformatics exploration

BACKGROUND

Renal cell carcinoma (RCC) is a malignant tumour that may develop in the kidney. RCC is one of the most common kinds of tumours of this sort, and its most common pathological subtype is kidney renal clear cell carcinoma (KIRC). However, the aetiology and pathogenesis of RCC still need to be clarified. Exploring the internal mechanism of RCC contributes to diagnosing and treating this disease. Pyroptosis is a critical process related to cell death. Recent research has shown that pyroptosis is a critical factor in the initiation and progression of tumour formation. Thus far, researchers have progressively uncovered evidence of the regulatory influence that long noncoding RNAs (lncRNAs) have on pyroptosis.

METHODS

In this work, a comprehensive bioinformatics approach was used to produce a predictive model according to pyroptosis-interrelated lncRNAs for the purpose of predicting the overall survival and molecular immune specialties of patients diagnosed with KIRC. This model was verified from multiple perspectives.

RESULTS

First, we discovered pyroptosis-associated lncRNAs in KIRC patients using the TCGA database and a Sankey diagram. Then, we developed and validated a KIRC patient risk model based on pyroptosis-related lncRNAs. We demonstrated the grouping power of PLnRM through PCA and used PLnRM to assess the tumour immune microenvironment and response to immunotherapy. Immunological and molecular traits of diverse PLnRM subgroups were evaluated, as were clinical KIRC patient characteristics and predictive risk models. On this basis, a predictive nomogram was developed and analyzed, and novel PLnRM candidate compounds were identified. Finally, we investigated possible medications used by KIRC patients.

CONCLUSIONS

The results demonstrate that the model generated has significant value for KIRC in clinical practice.

Elevated CDC45 Expression Predicts Poorer Overall Survival Prognoses and Worse Immune Responses for Kidney Renal Clear Cell Carcinoma via Single-Cell and Bulk RNA-Sequencing

The main objective of this paper is to analyze the prognostic and immunological value of CDC45 in kidney renal clear cell carcinoma (KIRC) using single-cell and bulk RNA-sequencing approaches. The expression of CDC45 in KIRC was evaluated by the HPA database, the TCGA-KIRC dataset and verified by PCR analysis and single-cell RNA-sequencing. The ability of CDC45 to independently predict prognosis in KIRC was confirmed by univariate/multivariate regression analysis. Gene set enrichment analysis (GSEA) was employed to explore CDC45-related pathways in KIRC. In addition, Relationships between CDC45 and immunity were also examined. Elevated CDC45 expression in KIRC was demonstrated at mRNA and protein levels. The results of the correlation analysis showed that as CDC45 expression increased, so did the histological grade, clinical stage, and TNM stage of the patients (p < 0.05). Univariate/multivariate regression analysis suggested CDC45 as an independent prognostic factor for KIRC. Seven pathways related to CDC45 were screened through GSEA. Meanwhile, we found that CDC45 was correlated with tumor mutational burden (TMB) and microsatellite instability (MSI) but not tumor neoantigen burden (TNB). Regarding immunity, CDC45 exhibited correlations with the tumor microenvironment, immune cell infiltration, and immune checkpoints. Besides, low CDC45 expression was shown to be associated with a better response to immunotherapy. Single-cell RNA-sequencing revealed that CDC45 was differently expressed in T cells (p < 0.05). CDC45 showed potential as a prognostic biomarker and therapeutic target for KIRC. Meanwhile, the CDC45 low expression group was more sensitive to immunotherapy.

Restoring gluconeogenesis by TEF inhibited proliferation and promoted apoptosis and immune surveillance in kidney renal clear cell carcinoma

BACKGROUND

Kidney renal clear cell carcinoma (KIRC) is the major histological subtype of kidney tumor which covers approximately 80% of the cases. Although various therapies have been developed, the clinical outcome remains unsatisfactory. Metabolic dysregulation is a key feature of KIRC, which impacts progression and prognosis of the disease. Therefore, understanding of the metabolic changes in KIRC is of great significance in improving the treatment outcomes.

METHODS

The glycolysis/gluconeogenesis genes were analyzed in the KIRC transcriptome from the Cancer Genome Atlas (TCGA) by the different expression genes (DEGs) test and survival analysis. The gluconeogenesis-related miRNAs were identified by ImmuLncRNA. The expression levels of indicated genes and miRNAs were validated in KIRC tumor and adjunct tissues by QPCR. The effects of miR-4477b and PCK1 on cell proliferation and apoptosis were examined using the cell viability assay, cell apoptosis assay, and clone information. The interaction of miR-4477b with TEF was tested by the luciferase report gene assay. The different gluconeogenesis statuses of tumor cells and related signatures were investigated by single-cell RNA sequencing (scRNA-seq) analysis.

RESULTS

The 11 gluconeogenesis genes were found to be suppressed in KIRC (referring as PGNGs), and the less suppression of PGNGs indicated better survival outcomes. Among the 11 PGNGs, we validated four rate-limiting enzyme genes in clinical tumor patients. Moreover, restoring gluconeogenesis by overexpressing PCK1 or TEF through miR-4477b inhibition significantly inhibited tumor cell proliferation, colony formation, and induced cell apoptosis in vitro. Independent single-cell RNA sequencing (scRNA-seq) data analysis revealed that the tumor cells had high levels of PGNG expression (PGNG + tumor cells) represented a phenotype of early stage of neoplasia and prompted immune surveillance.

CONCLUSIONS

Our study suggests that the deficiency of gluconeogenesis is a key metabolic feature of KIRC, and restoring gluconeogenesis could effectively inhibit the proliferation and progression of KIRC cells.

Immune-pyroptosis-related genes predict the prognosis of kidney renal clear cell carcinoma

BACKGROUND

Kidney renal clear cell carcinoma (KIRC) is a common cancer of the adult urological system. Recent developments in tumor immunology and pyroptosis biology have provided new directions for kidney cancer treatment. Therefore, there is an urgent need to identify potential targets and prognostic biomarkers for the combination of immunotherapy and pyroptosis-targeted therapy.

METHODS

The expression of immune-pyroptosis-related differentially expressed genes (IPR-DEGs) between KIRC and healthy tissues was examined using the Gene Expression Omnibus datasets. The GSE168845 dataset was selected for subsequent analyses. Data of 1793 human immune-related genes were downloaded from the ImmPort database (https://www.immport.org./home), while those of 33 pyroptosis-related genes were extracted from previous reviews. The independent prognostic value of IPR-DEGs was determined using differential expression, prognostic, and univariate and multivariate Cox regression analyses. The GSE53757 dataset was used to further verify the GSDMB and PYCARD levels. In our cohorts, the association among DEGs and clinicopathological features and overall survival was analyzed. The least absolute shrinkage and selection operator Cox regression model was established to evaluate the correlation of IPR-DEGs with the immune score, immune checkpoint gene expression, and one-class logistic regression (OCLR) score. KIRC cells and clinical tissue samples were subjected to quantitative real-time polymerase chain reaction to examine the GSDMB and PYCARD mRNA levels. The GSDMB and PYCARD levels in a healthy kidney cell line (HK-2 cells) and two KIRC cell lines (786-O and Caki-1 cells) were verified. The tissue levels of GSDMB and PYCARD were evaluated using immunohistochemical analysis. GSDMB and PYCARD were knocked down in 786-O cells using short-interfering RNA. Cell proliferation was examined using the cell counting kit-8 assay. Cell migration was measured by transwell migration assays RESULTS: GSDMB and PYCARD were determined to be IPR-DEGs with independent prognostic values. A risk prognostic model based on GSDMB and PYCARD was successfully established. In the GSE53757 dataset, the GSDMB and PYCARD levels in KIRC tissues were significantly higher than those in healthy tissues. The GSDMB and PYCARD expression was related to T stage and OS in our cohort. The GSDMB and PYCARD levels were significantly correlated with the immune score, immune checkpoint gene expression, and OCLR score. The results of experimental studies were consistent with those of bioinformatics analysis. The GSDMB and PYCARD levels in KIRC cells were significantly upregulated when compared with those in healthy kidney cells. Consistently, GSDMB and PYCARD in KIRC tissues were significantly upregulated when compared with those in adjacent healthy kidney tissues. GSDMB and PYCARD knockdown significantly decreased 786-O cell proliferation (p < 0.05). Transwell migration result reflects that silencing GSDMB and PYCARD inhibited 786-O cell migration (p < 0.05) .

CONCLUSIONS

GSDMB and PYCARD are potential targets and effective prognostic biomarkers for the combination of immunotherapy and pyroptosis-targeted therapy in KIRC.

Downregulation of RAB17 have a poor prognosis in kidney renal clear cell carcinoma and its expression correlates with DNA methylation and immune infiltration

BACKGROUND

RAB17 is one of the RAB family members. It has been reported to be closely associated with a variety of tumors and has different roles in various tumors. However, the effect of RAB17 in KIRC remains unclear.

MATERIALS AND METHODS

We analyzed the differential expression of RAB17 in kidney renal clear cell carcinoma (KIRC) tissues and normal tissues using the public databases. The prognostic role of RAB17 in KIRC was analyzed using the Cox regression methods, and a prognostic model was constructed based on the results of the Cox analysis. In addition, further analysis of RAB17 in KIRC was performed in relation to genetic alterations, DNA methylation m6A methylation and immune infiltration. Finally, RAB17 mRNA and protein expression levels were analyzed in tissue samples (KIRC tissues and normal tissues) and cell lines (normal renal tubular cell and KIRC cells), and in vitro functional assays were performed.

RESULTS

RAB17 was low-expressed in KIRC. Downregulation of RAB17 expression is correlated with unfavorable clinicopathological characteristics and a worse prognosis in KIRC. The RAB17 gene alteration in KIRC was primarily characterized by copy number alteration. Six CpG sites of RAB17 DNA methylation levels are higher in KIRC tissues than in normal tissues, and are correlated with RAB17 mRNA expression levels, showing a significant negative correlation. cg01157280 site DNA methylation levels are associated with pathological stage and overall survival, and it may be the only CpG site with independent prognostic significance. Functional mechanism analysis revealed that RAB17 is closely associated with immune infiltration. RAB17 expression was found to be negatively correlated with most immune cell infiltration according to two different methods. Furthermore, most immunomodulators were significantly negatively correlated with RAB17 expression, and significantly positively correlated with RAB17 DNA methylation levels. RAB17 was significantly low expression in KIRC cells and KIRC tissues. In vitro, silencing of RAB17 promoted KIRC cell migration.

CONCLUSION

RAB17 can be used as a potential prognostic biomarker for patients with KIRC and for assessing immunotherapy response.

ApoM suppresses kidney renal clear cell carcinoma growth and metastasis via the Hippo-YAP signaling pathway

Renal cell carcinoma is one of the most common malignancies worldwide, and kidney renal clear cell carcinoma (KIRC) is the most common histopathological type of renal cell carcinoma. However, the mechanism of KIRC progression remains poorly understood. Apolipoprotein M (ApoM) is a plasma apolipoprotein and a member of the lipid transport protein superfamily. Lipid metabolism is essential for tumor progression, and its related proteins can be used as therapeutic targets for tumors. ApoM influences the development of several cancers, but its relationship with KIRC remains unclear. In this study, we aimed to investigate the biological function of ApoM in KIRC and to reveal its potential molecular mechanisms. We found that ApoM expression was significantly reduced in KIRC and was strongly correlated with patient prognosis. ApoM overexpression significantly inhibited KIRC cell proliferation in vitro, suppressed the epithelial mesenchymal transition (EMT) of KIRC cells, and decreased their metastatic capacity. Additionally, the growth of KIRC cells was inhibited by ApoM overexpression in vivo. In addition, we found that overexpression of ApoM in KIRC attenuated Hippo-YAP protein expression and YAP stability and thus inhibited KIRC growth and progression. Therefore, ApoM may be a potential target for the treatment of KIRC.

HIGD1A inactivated by DNA hypermethylation promotes invasion of kidney renal clear cell carcinoma

Hypoxia contributes to the tumorigenesis and metastasis of the tumor. However, the detailed mechanisms underlying hypoxia and kidney renal clear cell carcinoma (KIRC) development and progression remain unclear. Here, we investigated the role of the system HIG1 hypoxia inducible domain family member 1 A (HIGD1A) in the proliferation and metastasis of KIRC and elucidated the underlying molecular mechanisms. The expression of HIGD1A is significantly downregulated in KIRC due to promoter hypermethylation. HIGD1A could serve as a valuable diagnostic biomarker in KIRC. In addition, ectopic overexpression of HIGD1A significantly suppressed the growth and invasive capacity of KIRC cells in vitro under normal glucose conditions. Interestingly, the suppressive efficacy in invasion is much more significant when depleted glucose, but not in proliferation. Furthermore, mRNA expression of HIGD1A positively correlates with CDH1 and EPCAM, while negatively correlated with VIM and SPARC, indicating that HIGD1A impedes invasion of KIRC by regulating epithelial-mesenchymal transition (EMT). Our data suggest that HIGD1A is a potential diagnostic biomarker and tumor suppressor in KIRC.

MKRN1/2 serve as tumor suppressors in renal clear cell carcinoma by regulating the expression of p53

BACKGROUND

Kidney renal clear cell carcinoma (KIRC) belongs to renal cell carcinoma which is a very aggressive malignant tumor with poor prognosis and high mortality. The MKRN family includes three members MKRN1, MKRN2 and MKRN3, which are closely related to cancers, and have been involved in many studies.

OBJECTIVE

This study aimed to explore the roles of MKRN family in KIRC.

METHODS

The expression of MKRNs was analyzed using the UALCAN database, prognostic analysis was performed with the GEPIA2 and Kaplan-Meier Plotter database, and correlation analysis was assessed by GEPIA2. The CCK-8 and colony formation assay were performed to detect cell proliferation, wound healing assays were performed to detect cell migration, cell cycles were detected by flow cytometry analysis, GST pull-down and co-immunoprecipitation assays were performed to detect the interaction of proteins, and the expression of MKRNs, p53 and other proteins were detect by immunoblotting analysis or quantitative PCR (qPCR).

RESULTS

MKRN1 and MKRN2 were lowly expressed in KIRC samples compared to the corresponding normal tissues, and KIRC patients with high levels of MKRN1 and MKRN2 showed higher overall survival (OS) and disease free survival (DFS) rates. The overexpression of MKRN1 and MKRN2 inhibited the proliferation of human KIRC cells by arresting the cell cycles, but shows little effect on cells migration. The expression of MKRN1 and MKRN2 are correlated, and MKRN1 directly interacts with MKRN2. Moreover, both MKRN1 and MKRN2 were closely correlated with the expression of TP53 in KIRC tumor, and promoted the expression of p53 both at protein and mRNA levels.

CONCLUSIONS

Our study suggests that MKRN1 and MKRN2 serve as tumor suppressors in KIRC, and act as promising therapeutic targets for KIRC treatment.

Integrated analysis of the relation to tumor immune microenvironment and predicted value of Stonin1 gene for immune checkpoint blockage and targeted treatment in kidney renal clear cell carcinoma

BACKGROUND

Stonin1 (STON1) is an endocytic protein but its role in cancer remains unclear. Here, we investigated the immune role of STON1 in kidney renal clear cell carcinoma (KIRC).

METHODS

We undertook bioinformatics analyses of the expression and clinical significance of STON1 in KIRC through a series of public databases, and the role of STON1 in the tumor microenvironment and the predictive value for immunotherapy and targeted treatment in KIRC were identified with R packages. STON1 expression was validated in clinical KIRC tissues as well as in KIRC and normal renal tubular epithelial cells.

RESULTS

Through public databases, STON1 mRNA was found to be significantly downregulated in KIRC compared with normal controls, and decreased STON1 was related to grade, TNM stage, distant metastasis and status of KIRC patients. Compared with normal controls, STON1 was found to be downregulated in KIRC tissues and cell lines. Furthermore, OncoLnc, Kaplan-Meier, and GEPIA2 analyses also suggested that KIRC patients with high STON1 expression had better overall survival. The high STON1 group with enriched immune cells had a more favorable prognosis than the low STON1 group with decreased immune cells. Single sample Gene Set Enrichment Analysis and Gene Set Variation Analysis indicated that STON1 creates an immune non-inflamed phenotype in KIRC. Moreover, STON1 was positively associated with mismatch repair proteins and negatively correlated with tumor mutational burden. Furthermore, Single sample Gene Set Enrichment Analysis algorithm and Pearson analysis found that the low STON1 group was more sensitive to immune checkpoint blockage whereas the high STON1 group was relatively suitable for targeted treatment.

CONCLUSIONS

Decreased STON1 expression in KIRC leads to clinical progression and poor survival. Mechanically, low STON1 expression is associated with an aberrant tumor immune microenvironment. Low STON1 is likely to be a favorable indicator for immunotherapy response but adverse indicator for targeted therapeutics in KIRC.

Elevated PTTG1 predicts poor prognosis in kidney renal clear cell carcinoma and correlates with immunity

Background

PTTG1 has been reported to be linked with the prognosis and progression of various cancers, including kidney renal clear cell carcinoma (KIRC). In this article, we mainly investigated the associations between prognosis, immunity, and PTTG1 in KIRC patients.

Method

We downloaded transcriptome data from the TCGA-KIRC database. PCR and immunohistochemistry were used, respectively, to validate the expression of PTTG1 in KIRC at the cell line and the protein levels. Survival analyses as well as univariate or multivariate Cox hazard regression analyses were used to prove whether PTTG1 alone could affect the prognosis of KIRC. The most important point was to study the relationship between PTTG1 and immunity.

Results

The results of the paper revealed that the expression levels of PTTG1 were elevated in KIRC compared with para-cancerous normal tissues, validated by PCR and immunohistochemistry at the cell line and the protein levels (P < 0.05). High PTTG1 expression was related to shorter overall survival (OS) in patients with KIRC (P < 0.05). Through univariate or multivariate regression analysis, PTTG1 was confirmed to be an independent prognostic factor for OS of KIRC (P < 0.05), and its related seven pathways were obtained through gene set enrichment analysis (GSEA; P < 0.05). Moreover, tumor mutational burden (TMB) and immunity were found to be significantly connected with PTTG1 in KIRC (P < 0.05). Correlations between PTTG1 and immunotherapy responses implied that the low-PTTG1 group was more sensitive to immunotherapy (P < 0.05).

Conclusions

PTTG1 was closely associated with TMB or immunity, and it had a superior ability to forecast the prognosis of KIRC patients.

COLGALT1 is a potential biomarker for predicting prognosis and immune responses for kidney renal clear cell carcinoma and its mechanisms of ceRNA networks

Background

As precision medicine gradually played an inaccessible role in cancer treatment, there was an urgent need to explore biomarkers or signatures for predicting cancer prognosis. Currently, little was known about the associations between COLGALT1 and kidney renal clear cell carcinoma (KIRC). Hence, this study was performed to reveal its roles in KIRC and to identify potential mechanisms of competing endogenous RNA (ceRNA) networks.

Methods

R 4.1.1 software was utilized to conduct bioinformatics analyses with the data derived from online databases. Difference analysis, survival analysis, univariate/multivariate cox regression analysis and correlation analysis were carried out successively in this article. Besides, we also investigated potential effects and mechanisms of COLGALT1 in KIRC.

Results

COLGALT1 expression was overexpressed in KIRC samples compared with the normal samples and it was associated with poor OS (P < 0.001). COLGALT1 was also found to be significantly related to clinicopathological characteristics such as grade, T, N, M, stage and Cox regression analysis with univariate and multivariate data suggested it might be an independent prognostic parameter in KIRC (P < 0.001). Furthermore, Seven significantly enriched pathways were identified. Interestingly, correlation analyses revealed an association between COLGALT1 and microsatellite instability (MSI), tumor mutational burden (TMB) and immunity (P < 0.001). In addition, we used TIDE and TCIA databases to predict the immune response of COLGALT1 in KIRC and it suggested low expression of COLGALT1 is more likely to benefit from immunotherapy. Besides, we identified a ceRNA network of SLC16A1-AS1/hsa-mir-502-3p/COLGALT1 for its potential mechanism. Finally, experiments in vitro indicated that COLGALT1 was significantly related to cell proliferation.

Conclusions

COLGALT1 could act as a valid immune-related prognostic indicator for KIRC and participated in a ceRNA network of SLC16A1-AS1/hsa-mir-502-3p/COLGALT1, offering one potential biomarker to investigate the mechanism and clinical therapeutic value of KIRC.

Supplementary Information

The online version contains supplementary material available at 10.1186/s40001-022-00745-5.

Identifying the role of transient receptor potential channels (TRPs) in kidney renal clear cell carcinoma and their potential therapeutic significances using genomic and transcriptome analyses

Kidney renal clear cell carcinoma (KIRC) is among the major causes of cancer-caused mortality around the world. Transient receptor potential channels (TRPs), due to their role in various human diseases, might become potential drug targets in cancer. The mRNA expression, copy number variation, single-nucleotide variation, prognostic values, drug sensitivity, and pathway regulation of TRPs were studied across cancer types. The ArrayExpress and The Cancer Genome Atlas (TCGA) databases were used to retrieve KIRC samples. Simultaneously, training, internal, and external cohorts were grouped. In KIRC, a prognostic signature with superior survival prediction in contrast with other well-established signatures was created after a stepwise screening of optimized genes linked to TRPs using univariate Cox, weighted gene co-expression network analysis, multivariate Cox, and least absolute shrinkage and selection operator regression analyses. Subsequent to the determination of risk levels, the variations in the expression of immune checkpoint genes, tumor mutation burden, and immune subtypes and response between low-risk and high-risk subgroups were studied using a variety of bioinformatics algorithms, including ESTIMATE, XCELL, EPIC, CIBERSORT-ABS, CIBERSORT, MCPCOUNTER, TIMER, and QUANTISEQ. Gene set enrichment analysis helped in the identification of abnormal pathways across the low- and high-risk subgroups. Besides, high-risk KIRC patients might benefit from ABT888, AZD6244, AZD7762, Bosutinib, Camptothecin, CI1040, JNK inhibitor VIII, KU55933, Lenalidomide, Nilotinib, PLX4720, RO3306, Vinblastine, and ZM.447439; however, low-risk populations might benefit from Bicalutamide, FH535, and OSI906. Finally, calibration curves were used to validate the nomogram with a satisfactory predictive survival probability. In conclusion, this research provides useful insight that can aid and guide clinical practice and scientific research.

LPAR2 correlated with different prognosis and immune cell infiltration in head and neck squamous cell carcinoma and kidney renal clear cell carcinoma

Background

Lysophosphatidic acid (LPA) and its receptors play a key role in regulating cancer progression. Upregulation of LPA receptor 2 (LPAR2) plays a role in carcinogenesis; however, the exact role of LPAR2 in tumors remains elusive. This study aims to explore the correlation between LPAR2 expression with tumor prognosis and immune infiltration in pan-cancers.

Materials and methods

The expression of LPAR2 in pan-cancers was analyzed using the Online Cancer Microarray Database (Oncomine), Tumor Immune Estimation Resource (TIMER), and UALCAN databases. The effects of LPAR2 on the clinical prognosis in pan-cancer were examined using the Kaplan–Meier plotter (KM plotter) as well as Gene Expression Profiling Interactive Analysis (GEPIA), UALCAN, and Human Protein Atlas (HPA) databases. Moreover, the R software program was applied for validation of expression and prognostic value of LPAR2 in tumor patients in the Cancer Genome Atlas (TCGA) dataset and the Gene Expression Omnibus (GEO) database. The relationship between the expression level of LPAR2 and the clinical and molecular criteria of head and neck squamous cell carcinoma (HNSC) and kidney renal clear cell carcinoma (KIRC) was analyzed using UALCAN, whereas the relationship between LPAR2 expression and prognosis in patients with HNSC and KIRC with different clinical characteristics was examined using the KM plotter. Furthermore, the correlation between LPAR2 expression and tumor immune infiltration was examined using TIMER. The correlation between LPAR2 expression and gene markers of tumor immune infiltrates was analyzed using TIMER and GEPIA. In addition, the cBioPortal for Cancer Genomics was used to calculate the mutations, methylations, and altered neighbor genes of LPAR2.

Results

The expression of LPAR2 was significantly correlated with the outcome of multiple types of cancer, especially HNSC and KIRC. Furthermore, high expression of LPAR2 was significantly associated with various immune markers in the immune cell subsets of HNSC and KIRC.

Conclusions

High expression of LPAR2 plays significantly different prognostic roles in HNSC and KIRC possibly owing to its association with different immune markers. LPAR2 is correlated with tumor immune cell infiltration and is a valuable prognostic biomarker for HNSC and KIRC. However, further experiments are required to validate these findings.

Supplementary Information

The online version contains supplementary material available at 10.1186/s41065-022-00229-w.

Prognostic implication and immunotherapy response prediction of a costimulatory molecule signature in kidney renal clear cell carcinoma

Costimulatory molecules were considered to be promising and important targets in immunotherapy for various cancers. The present study was intended for generating a costimulatory molecule signature in kidney renal clear cell carcinoma (KIRC), to investigate prognostic implication, elucidate immune atlas, and predict immunotherapy response. All the KIRC samples from the TCGA were randomly divided into the training dataset and the testing dataset in the ratio of 7:3. The Cox and least absolute shrinkage and selection operator (LASSO) regression analysis were used to identify 7 key costimulatory molecules which were associated with prognosis and construct a costimulatory molecule prognostic index (CMsPI), which was validated by internal and external datasets and an independent cohort. Patients in the high-CMsPI group had high mortality. Mutation analysis showed the most common mutational genes and variant types. Immune analysis demonstrated CD8⁺ T cells were infiltrated at a high level in the high-CMsPI group. In combination of analysis of the immune relevant gene signature and the biomarkers of immunotherapy, we may infer there were more dysfunctional CD8⁺ T cells in the high-CMsPI group, and the patients of this group were less sensitive to immunotherapy. A nomogram was constructed, and the concordance index was 0.77 (95% CI: 0.74-0.79). Three key signaling pathways were identified to facilitate tumor progression. The CMsPI can be regarded as a promising biomarker for predicting individual prognosis and assessing immunotherapy response in KIRC patients.

Tumor antigens and immune subtypes guided mRNA vaccine development for kidney renal clear cell carcinoma

Current treatment strategy for kidney renal clear cell carcinoma (KIRC) is limited. Tumor-associated antigens, especially neoantigen-based personalized mRNA vaccines represent new strategies and manifest clinical benefits in solid tumors, but only a small proportion of patients could benefit from them, which prompts us to identify effective antigens and suitable populations to facilitate mRNA vaccines application in cancer therapy. Through performing expression, mutation, survival and correlation analyses in TCGA-KIRC dataset, we identified four genes including DNA topoisomerase II alpha (TOP2A), neutrophil cytosol factor 4 (NCF4), formin-like protein 1 (FMNL1) and docking protein 3 (DOK3) as potential KIRC-specific neoantigen candidates. These four genes were upregulated, mutated and positively associated with survival and antigen-presenting cells in TCGA-KIRC. Furthermore, we identified two immune subtypes, named renal cell carcinoma immune subtype 1 (RIS1) and RIS2, of KIRC. Distinct clinical, molecular and immune-related signatures were observed between RIS1 and RIS2. Patients of RIS2 had better survival outcomes than those of RIS1. Further comprehensive immune-related analyses indicated that RIS1 is immunologically “hot” and represent an immunosuppressive phenotype, whereas RIS2 represents an immunologically “cold” phenotype. RIS1 and RIS2 also showed differential features with regard to tumor infiltrating immune cells and immune checkpoint-related genes. Moreover, the immune landscape construction identified the immune cell components of each KIRC patient, predicted their survival outcomes, and assisted the development of personalized mRNA vaccines. In summary, our study identified TOP2A, NCF4, FMNL1 and DOK3 as potential effective neoantigens for KIRC mRNA vaccine development, and patients with RIS2 tumor might benefit more from mRNA vaccination.

Screening Novel Drug Candidates for Kidney Renal Clear Cell Carcinoma Treatment: A Study on Differentially Expressed Genes through the Connectivity Map Database

OBJECTIVE

Kidney renal clear cell carcinoma (KIRC) is a common cancer with high morbidity and mortality in renal cancer. Thus, the transcriptome data of KIRC patients in The Cancer Genome Atlas (TCGA) database were analyzed and drug candidates for the treatment of KIRC were explored through the connectivity map (CMap) database.

METHODS

The transcriptome data of KIRC patients were downloaded from TCGA database, and KIRC-associated hub genes were screened out through differential analysis and protein-protein interaction (PPI) network analysis. Afterward, the CMap database was used to select drug candidates for KIRC treatment, and the drug-targeted genes were obtained through the STITCH database. A PPI network was constructed by combining drug-targeted genes with hub genes that affected the pathogenesis of KIRC to obtain final hub genes. Finally, combining hub genes and KIRC-associated hub genes, the pathways affected by drugs were explored by pathway enrichment analysis.

RESULTS

A total of 2,312 differentially expressed genes were found in patients, which were concentrated in immune cell activity, cytokine, and chemokine secretion pathways. Drug screening disclosed 5 drug candidates for KIRC treatment: fedratinib, Ly344864, geldanamycin, AS-605240, and luminespib. Based on drug-targeted genes and KIRC-associated hub genes, 16 hub genes were screened out. Pathway enrichment analysis revealed that drugs mainly affected pathways such as neuroactive ligand pathways, cell adhesion, and chemokines.

CONCLUSION

The above results indicated that fedratinib, LY 344864, geldanamycin, AS-605240, and luminespib could be used as candidates for KIRC therapy. The findings from this study will make contributions to the treatment of KIRC in the future.

RHBDF2 gene functions are correlated to facilitated renal clear cell carcinoma progression

Background

The rhomboids are a family of multi-transmembrane proteins, many of which have been implicated in facilitating tumor progression. Little is yet known, however, about rhomboid-associated biomarkers in cancers. An analysis of such biomarkers could yield important insights into the role of the rhomboids in cancer pathology.

Methods

In this study, we carried out the univariate Cox regression analysis and compared gene expression patterns of several rhomboid genes in 30 types of cancers by using The Cancer Genome Atlas (TCGA) database and the methods delineated in Gene Expression Profiling Interactive Analysis (GEPIA). We then used datasets GSE47032, GSE126964, GSE68417 and 75 paired pathological specimens to verify the influences of the rhomboid genes in cancer progression. Moreover, we carried out Weighted Gene Correlation Network Analysis (WGCNA) to investigate gene-related functions and we exploited potential correlations between rhomboid genes expression and immune cell infiltration in cancer tissues. Furthermore, we constructed gene-knockdown cancer cell lines to investigate rhomboid gene functions.

Results

We find that kidney renal clear cell carcinoma (KIRC) disease progression is affected by fluctuations in the expression of a number of the rhomboid family of genes and, more specifically, high levels of RHBDF2 gene expression are a good indicator of poor prognosis of the disease, as patients with high RHBDF2 expression levels exhibit less favorable survival rates compared to those with low RHBDF2 levels. Silencing of the RHBDF2 gene in KIRC cell lines leads to significantly diminished cell proliferation and migration; this is in good agreement with the identification of an enhanced presence of a number of cell growth and migration promoting signaling molecules in KIRC tumors. We found that, although high level of RHBDF2 correlated with increased infiltration of lymphocytes in cancer tissues, artificially overexpressed RHBDF2 led to an inhibition of the activity of the infiltrated immune cells through sustaining PD-L1 protein level. Furthermore, we show that RHBDF2 related cell migration and PD-L1 regulation were potentially mediated by EGFR signaling pathway.

Conclusions

RHBDF2 gene functions are correlated to facilitated renal clear cell carcinoma progression and may serve as a critical prognostic biomarker for the disease.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12935-021-02277-0.

Decreased expression of HADH is related to poor prognosis and immune infiltration in kidney renal clear cell carcinoma

Kidney renal clear cell carcinoma (KIRC) is the subtype pf kidney cancer having the highest mortality as well as the highest potential of invasion and metastasis. The expression of HADH, encoding a key enzyme in fatty acid β-oxidation, has rarely been reported to correlate with prognosis and immune infiltration in cancers. This study aimed to explore the prognostic value of HADH in patients with KIRC. Gene expression profiles and clinical data of KIRC patients were acquired from The Cancer Genome Atlas. We compared the expression of HADH between KIRC tissues and normal tissues. Then, the relationship between HADH expression and the clinicopathological characteristics (survival, age, gender, stage, and grade) of KIRC was explored. Data from several online databases and paraffin-embedded specimens from two cohorts were used for external validation (10 cases from Meizhou People's Hospital and another 75 cases from a tissue chip, with both cohorts including KIRC samples and paired normal tissues). We also predicted the fractions of tumor-infiltrating immune cells (TIICs) in various tissues using CIBERSORT. Next, we estimated the prognostic value of differences in TIIC proportions between the high and low HADH expression groups. Finally, gene set enrichment analysis (GSEA) was performed to explore the potential mechanisms by which HADH expression influences patient survival. The expression of HADH was significantly lower in KIRC tissue than in normal tissue. Decreased expression of HADH was significantly correlated with high histologic grade, advanced stage, and poor prognosis. The differential expression of HADH was validated at the protein level by immunohistochemistry. Multivariate Cox regression analysis indicated that HADH was an independent prognostic factor for KIRC. In addition, HADH expression was significantly associated with the accumulation of several TIICs, especially regulatory T cells. Finally, GSEA revealed that the transcriptome of the low HADH expression group was significantly enriched in genes involved in not only epithelial-mesenchymal transition and inflammatory response but also TNF-α, IL-6-JAK-STAT3, and interferon-γ signaling. In conclusion, our study demonstrated that decreased expression of HADH is related to poor prognosis and immune infiltration in KIRC; this finding may provide crucial information for the development of immunotherapies.

Downregulation of PPA2 expression correlates with poor prognosis of kidney renal clear cell carcinoma

Background

Kidney renal clear cell carcinoma (KIRC) is the most common subtype of kidney cancer. Inorganic pyrophosphatase (PPA2) is an enzyme that catalyzes the hydrolysis of pyrophosphate to inorganic phosphate; few studies have reported its significance in cancers. Therefore, we aimed to explore the prognostic value of PPA2 in KIRC.

Methods

PPA2 expression was detected via immunohistochemistry in a tissue chip containing specimens from 150 patients with KIRC. We evaluated the correlation between PPA2 expression, clinicopathological characteristics, and survival. Data from online databases and another cohort (paraffin-embedded specimens from 10 patients with KIRC) were used for external validation.

Results

PPA2 expression was significantly lower in KIRC tissues than in normal renal tissues (p < 0.0001). Low expression of PPA2 was significantly associated with a high histologic grade and poor prognosis. The differential expression of PPA2 was validated at the gene and protein levels. Multivariate Cox regression analysis showed that PPA2 expression was an independent prognostic factor in patients with KIRC. Gene set enrichment analysis suggested that decreased expression of PPA2 might be related to the epithelial-mesenchymal transition in KIRC.

Conclusions

Our study demonstrated that PPA2 is an important energy metabolism-associated biomarker correlated with a favorable prognosis in KIRC.

Up-regulation expression and prognostic significance of Syntaxin4 in kidney renal clear cell carcinoma

BACKGROUND

Syntaxin4 (STX4) gene encodes the protein STX4, a member of soluble N-ethylmaleimide-sensitive factor attachment protein receptors protein, playing a vital role in cell invadopodium formation and invasion, which is associated with the malignant progression of various human cancers. However, the expression and prognostic significance of STX4 in kidney renal clear cell carcinoma (KIRC) remain to be investigated.

METHODS

In this study, we collected the mRNA expression of STX4 in 535 KIRC patients from The Cancer Genome Atlasthrough the University of California Santa Cruz Xena database platform. Then we explored the expression of STX4 in KIRC, and the relationship with clinicopathological characteristics and prognostic value. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes function enrichment analyses were used to explore the potential mechanism of STX4 in KIRC. qRT-PCR analysis was performed toverify the above results with real world tissue specimens.

RESULTS

The results indicated that STX4 was up-expressed in KIRC, and were associated with higher histological grade, advanced stage, and poorer prognosis. Moreover, elevated STX4 expression is an independent risk factor for KIRC. qRT-PCR analysis showed that STX4 was significantly elevated in 10 paired of KIRC samples compared to normal samples. Functional enrichment analysis indicated that endo/exocytosis, autophagy, mTOR signaling pathway, and NOD-like receptor signaling pathway were enriched.

CONCLUSIONS

In summary, STX4 is constantly up-expressed in KIRC tissues, associated with a poor prognosis. We suggest that it can be an effective biomarker for the prognosis of KIRC and may be a novel therapeutic target in KIRC.

NFIB promotes the migration and progression of kidney renal clear cell carcinoma by regulating PINK1 transcription

Kidney renal clear cell carcinoma (KIRC) is the most common and aggressive type of renal cell carcinoma. Due to high mortality rate, high metastasis rate and chemical resistance, the prognosis of KIRC patients is poor. Therefore, it is necessary to study the mechanisms of KIRC development and to develop more effective prognostic molecular biomarkers to help clinical patients. In our study, we used The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases to investigate that the expression of nuclear factor I B (NFIB) is significantly higher in KIRC than in adjacent tissues. Moreover, NFIB expression levels are associated with multiple clinical pathological parameters of KIRC, and KIRC patients with high NFIB expression have poor prognosis, suggesting that NFIB may play vital roles in the malignant development of KIRC. Further studies demonstrated that NFIB could promote the progression and metastasis of KIRC and participate in the regulation of PTEN induced kinase 1 (PINK1). Furthermore, we used chromatin immunoprecipitation (ChIP) experiments to confirm that NFIB binds to the PINK1 promoter and regulates its expression at the transcriptional level. Further experiments also confirmed the important roles of PINK1 in promoting the development of tumors by NFIB. Hence, our data provide a new NFIB-mediated regulatory mechanism for the tumor progression of KIRC and suggest that NFIB can be applied as a new predictor and therapeutic target for KIRC.

Identification of mortality-risk-related missense variant for renal clear cell carcinoma using deep learning

Introduction:

Kidney renal clear cell carcinoma (KIRCC) is a highly heterogeneous and lethal cancer that can arise in patients with renal disease. DeepSurv combines a deep feed-forward neural network with a Cox proportional hazards function and could provide optimized survival results compared with convenient survival analysis.

Methods:

This study used an improved DeepSurv algorithm to identify the candidate genes to be targeted for treatment on the basis of the overall mortality status of KIRCC subjects. All the somatic mutation missense variants of KIRCC subjects were abstracted from TCGA-KIRC database.

Results:

The improved DeepSurv model (95.1%) achieved greater balanced accuracy compared with the DeepSurv model (75%), and identified 610 high-risk variants associated with overall mortality. The results of gene differential expression analysis also indicated nine KIRCC mortality-risk-related pathways, namely the tRNA charging pathway, the D-myo-inositol-5-phosphate metabolism pathway, the DNA double-strand break repair by nonhomologous end-joining pathway, the superpathway of inositol phosphate compounds, the 3-phosphoinositide degradation pathway, the production of nitric oxide and reactive oxygen species in macrophages pathway, the synaptic long-term depression pathway, the sperm motility pathway, and the role of JAK2 in hormone-like cytokine signaling pathway. The biological findings in this study indicate the KIRCC mortality-risk-related pathways were more likely to be associated with cancer cell growth, cancer cell differentiation, and immune response inhibition.

Conclusion:

The results proved that the improved DeepSurv model effectively classified mortality-related high-risk variants and identified the candidate genes. In the context of KIRCC overall mortality, the proposed model effectively recognized mortality-related high-risk variants for KIRCC.

An epithelial-mesenchymal transition-related long non-coding RNA signature to predict overall survival and immune microenvironment in kidney renal clear cell carcinoma

Kidney renal clear cell carcinoma (ccRCC) is a malignant tumor originating from renal tubular epithelium, lncRNAs can regulate the occurrence and development of EMT by targeting EMT transcription factors. We constructed a new survival signature based on EMT-related differentially expressed lncRNAs obtained from the Cancer Genome Atlas (TCGA-KIRC). We first determined 1377 EMT-related lncRNAs, lncRNA AL035661.1 with the largest correlation coefficient and the target gene was PFN2 (cor = 0.843; P= 1.37E-146). Meanwhile, we found an AUC of 0.758 in our signature and we predicted the AUC values of the patients’ 1, 2, 3-year survival rate as 0.768, 0.749, and 0.762 in TCGA cohort, respectively. Multivariate COX analysis was performed to determine if risk score was an independent prognostic predictor of OS. The results indicated that our risk score can be an independent predictor for OS (Univariate: HR = 1.350, 95% CI = 1.276–1.428, P< 0.001; Multivariate: HR = 1.295, 95% CI = 1.201–1.396, P< 0.001). We identified novel EMT-related lncRNAs markers for ccRCC prognosis. The underlying mechanism between EMT-related lncRNAs in ccRCC and tumor immunity is still unclear and requires further study.

A 14 immune-related gene signature predicts clinical outcomes of kidney renal clear cell carcinoma

Kidney renal clear cell carcinoma (KIRC) is the leading cause of kidney cancer-related deaths. Currently, there are no studies in tumor immunology investigating the use of signatures as a predictor of overall survival in KIRC patients. Our study attempts to establish an immune-related gene risk signature to predict clinical outcomes in KIRC. A total of 528 patients from The Cancer Genome Atlas (TCGA) database were included in our analysis and randomly divided into training (n = 315) and testing sets (n = 213). We collected 1,534 immune-related genes from the Immunology Database and Analysis Portal as candidates to construct our signature. LASSO-COX was used to find gene models with the highest predictive ability. We used survival and Cox analysis to test the model's independent prognostic ability. Univariate analysis identified 650 immune-related genes with prognostic abilities. After 1,000 iterations, we choose 14 of the most frequent and stable immune-related genes as our signature. We found that the signature was associated with M stage, T stage, and pathological staging. More importantly, the signature can independently predict clinical prognosis in KIRC patients. Gene Set Enrichment Analysis (GSEA) showed an association between our signature and critical metabolism pathways. Our research established a model based upon 14 immune-related genes that predicted the prognosis of KIRC patients based on tumor immune microenvironments.

A seven-gene signature model predicts overall survival in kidney renal clear cell carcinoma

Background

Kidney renal clear cell carcinoma (KIRC) is a potentially fatal urogenital disease. It is a major cause of renal cell carcinoma and is often associated with late diagnosis and poor treatment outcomes. More evidence is emerging that genetic models can be used to predict the prognosis of KIRC. This study aimed to develop a model for predicting the overall survival of KIRC patients.

Results

We identified 333 differentially expressed genes (DEGs) between KIRC and normal tissues from the Gene Expression Omnibus (GEO) database. We randomly divided 591 cases from The Cancer Genome Atlas (TCGA) into training and internal testing sets. In the training set, we used univariate Cox regression analysis to retrieve the survival-related DEGs and futher used multivariate Cox regression with the LASSO penalty to identify potential prognostic genes. A seven-gene signature was identified that included APOLD1, C9orf66, G6PC, PPP1R1A, CNN1G, TIMP1, and TUBB2B. The seven-gene signature was evaluated in the training set, internal testing set, and external validation using data from the ICGC database. The Kaplan-Meier analysis showed that the high risk group had a significantly shorter overall survival time than the low risk group in the training, testing, and ICGC datasets. ROC analysis showed that the model had a high performance with an AUC of 0.738 in the training set, 0.706 in the internal testing set, and 0.656 in the ICGC external validation set.

Conclusion

Our findings show that a seven-gene signature can serve as an independent biomarker for predicting prognosis in KIRC patients.

Abnormal expression and prognostic significance of EPB41L1 in kidney renal clear cell carcinoma based on data mining

Background

EPB41L1 gene (erythrocyte membrane protein band 4.1 like 1) encodes the protein 4.1N, a member of 4.1 family, playing a vital role in cell adhesion and migration, which is associated with the malignant progression of various human cancers. However, the expression and prognostic significance of EPB41L1 in kidney renal clear cell carcinoma (KIRC) remain to be investigated.

Methods

In this study, we collected the mRNA expression of EPB41L1 in KIRC through the Oncomine platform, and used the HPA database to perform the pathological tissue immunohistochemistry in patients. Then, the sub-groups and prognosis of KIRC were performed by UALCAN and GEPIA web-tool, respectively. Further, the mutation of EPB41L1 in KIRC was analyzed by c-Bioportal. The co-expression genes of EPB41L1 in KIRC were displayed from the LinkedOmics database, and function enrichment analysis was used by LinkFinder module in LinkedOmics. The function of EPB41L1 in cell adhesion and migration was confirmed by wound healing assay using 786-O cells in vitro. Co-expression gene network was constructed through the STRING database, and the MCODE plug-in of which was used to build the gene modules, both of them was visualized by Cytoscape software. Finally, the top modular genes in the same patient cohort were constructed through data mining in TCGA by using the UCSC Xena browser.

Results

The results indicated that EPB41L1 was down-expressed in KIRC, leading to a poor prognosis. Moreover, there is a mutation in the FERM domain of EPB41L1, but it has no significant effect on the prognosis of KIRC. The co-expressed genes of EPB41L1 were associated with cell adhesion and confirmed in vitro. Further analysis suggested that EPB41L1 and amyloid beta precursor protein (APP) were coordinated to regulated cancer cell adhesion, thereby increasing the incidence of cancer cell metastasis and tumor invasion.

Conclusions

In summary, EPB41L1 is constantly down-expressed in KIRC tissues, resulting a poor prognosis. Therefore, we suggest that it can be an effective biomarker for the diagnosis of KIRC.

Microenvironment-related gene TNFSF13B predicts poor prognosis in kidney renal clear cell carcinoma

Background

Kidney renal clear cell carcinoma (KIRC) affects the genitourinary system. Although treatment of KIRC in early stages can be highly successful, this type of cancer is difficult to detect until later stages of disease that are less easily treatable. Previous studies have focused on tumor cells, but have ignored the contributions of the tumor microenvironment.

Methods

We analyzed KIRC gene expression data from The Cancer Genome Atlas with the ESTIMATE algorithm to identify differentially expressed genes. Through protein-protein interaction network analysis, we identified clusters and picked genes from the clusters for further analysis. Differential expression, Kaplan-Meier, and univariate Cox analyses were used to select prognostic biomarkers. Gene Set Enrichment Analysis (GSEA) and Tumor Immune Estimation Resource (TIMER) analysis were used to explore the immune characteristics of these genes as biomarkers.

Results

Through the ESTIMATE algorithm and other system biology tools, TNFSF13B was identified as a prognostic biomarker. TNFSF13B is highly expressed in tumors, and high expression of TNFSF13B leads to poor prognosis. Further GSEA and TIMER analysis revealed that the expression of TNFSF13B was related to the immune signaling pathway and lymphocyte infiltration. Our findings strongly suggest that TNFSF13B may be a potential biomarker or target related to the tumor microenvironment for KIRC.

Comprehensive analysis of the HOXA gene family identifies HOXA13 as a novel oncogenic gene in kidney renal clear cell carcinoma

OBJECTIVES

Kidney renal clear cell carcinoma (KIRC) is one of the most common lethal cancers in the human urogenital system. As members of the Homeobox (HOX) family, Homeobox-A (HOXA) cluster genes have been reported to be involved in the development of many cancer types. However, the expression and clinical significance of HOXA genes in KIRC remain largely unknown.

MATERIALS AND METHODS

In this study, we comprehensively analyzed the mRNA expression and prognostic values of HOXA genes in KIRC using The Cancer Genome Atlas (TCGA) analysis databases online. Colony formation assay, flow cytometry and Western blot were used to detect cell proliferation, apoptosis, cell cycle, and protein level of the indicated gene.

RESULTS

We found that the HOXA genes were differentially expressed in KIRC tissues when compared with normal tissues. The expression of HOXA4 and HOXA13 were significantly up-regulated, while HOXA7 and HOXA11 were down-regulated in KIRC. High mRNA levels of HOXA2, HOXA3 and HOXA13, and low level of HOXA7 predicted poor overall survival (OS) of KIRC patients. High mRNA level of HOXA13 further indicated a poor disease-free survival (DFS) of KIRC patients. Functionally, knockdown of HOXA13 significantly suppressed cell proliferation of KIRC in vitro, increased the protein level of p53 and decreased the protein level of cyclin D1 in KIRC cells. Over-expression of HOXA13 had the opposite effects on KIRC cells.

CONCLUSION

Collectively, our findings suggest that HOXA13 functions as a novel oncogene in KIRC and may be a potential biomarker for this malignancy.

Construction and validation of a seven-gene signature for predicting overall survival in patients with kidney renal clear cell carcinoma via an integrated bioinformatics analysis

Kidney renal clear cell carcinoma (KIRC) remains a significant challenge worldwide because of its poor prognosis and high mortality rate, and accurate prognostic gene signatures are urgently required for individual therapy. This study aimed to construct and validate a seven-gene signature for predicting overall survival (OS) in patients with KIRC. The mRNA expression profile and clinical data of patients with KIRC were obtained from The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC). Prognosis-associated genes were identified, and a prognostic gene signature was constructed. Then, the prognostic efficiency of the gene signature was assessed. The results obtained using data from the TCGA were validated using those from the ICGC and other online databases. Gene set enrichment analyses (GSEA) were performed to explore potential molecular mechanisms. A seven-gene signature (PODXL, SLC16A12, ZIC2, ATP2B3, KRT75, C20orf141, and CHGA) was constructed, and it was found to be effective in classifying KIRC patients into high- and low-risk groups, with significantly different survival based on the TCGA and ICGC validation data set. Cox regression analysis revealed that the seven-gene signature had an independent prognostic value. Then, we established a nomogram, including the seven-gene signature, which had a significant clinical net benefit. Interestingly, the seven-gene signature had a good performance in distinguishing KIRC from normal tissues. GSEA revealed that several oncological signatures and GO terms were enriched. This study developed a novel seven-gene signature and nomogram for predicting the OS of patients with KIRC, which may be helpful for clinicians in establishing individualized treatments.

An effective seven-CpG-based signature to predict survival in renal clear cell carcinoma by integrating DNA methylation and gene expression

AIMS

Currently, using clinicopathological risk factors only is not far from effective to evaluate the risk of disease progression in renal clear cell carcinoma (KIRC) patients. Molecular biomarkers might improve risk stratification of KIRC. DNA methylation occurs the whole process of tumor development and transcriptional disorders are also one of the important characteristics of tumor. Hence, this study aims to develop an effective and independent prognostic signature for KIRC patients by Integrating DNA methylation and gene expression.

MAIN METHODS

Difference analysis was conducted on DNA methylation sites and gene expression data. The Spearman's rank correlation and univariate Cox regression analysis were used to screen out the CpG sites that related with RNAs' expression and KIRC patients' overall survival. Then, a five-CpG-based prognostic classifier was established using LASSO Cox regression method.

KEY FINDINGS

The seven-CpG-based classifier can successfully divide KIRC patients into high-risk from low-risk groups, even after adjustment for standard clinical prognostic factors, such as age, stage, gender and grade. Moreover, the seven-CpG-based signature was more effective as independent prognostic factors than the combined model of these clinical factors. Six differential mRNA genes corresponding to the seven CpG sites are all related to human cancers by functional exploration. The gene functional and pathway enrichment analysis found that genes in immune-related pathways were remarkably different in high and low-risk groups.

SIGNIFICANCE

The new seven-CpG-based signature could helpfully provide insights into the underlying mechanism of KIRC and may be a powerful independent biomarker for predicting of the survival of KIRC patients.

Reduced GRAMD1C expression correlates to poor prognosis and immune infiltrates in kidney renal clear cell carcinoma

There has been an increase in the mortality rate and morbidity of kidney cancer (KC) with kidney renal clear cell carcinoma (KIRC) being the most common subtype of KC. GRAMD1C (GRAM Domain Containing 1C) has not been reported to relate to prognosis and immunotherapy in any cancers. Using bioinformatics methods, we judged the prognostic value of GRAMD1C expression in KIRC and investigated the underlying mechanisms of GRAMD1C affecting the overall survival of KIRC based on data downloaded from The Cancer Genome Atlas (TCGA). The outcome revealed that reduced GRAMD1C expression could be a promising predicting factor of poor prognosis in kidney renal clear cell carcinoma. Meanwhile, GRAMDIC expression was significantly correlated to several tumor-infiltrating immune cells (TIICs), particularly the regulatory T cells (Tregs). Furthermore, GRAMD1C was most significantly associated with the mTOR signaling pathway, RNA degradation, WNT signaling pathway, toll pathway and AKT pathway in KIRC. Thus, GRAMD1C has the potential to become a novel predictor to evaluate prognosis and immune infiltration for KIRC patients.

LINC00997, a novel long noncoding RNA, contributes to metastasis via regulation of S100A11 in kidney renal clear cell carcinoma

Long noncoding RNAs (lncRNAs) play an essential role in cancer development. However, the contribution of the lncRNA LINC00997 to kidney renal clear cell carcinoma (KIRC) has not been thoroughly elucidated to date. In this study, we examined the expression and biological effect of LINC00997 in KIRC development. We also investigated the potential mechanism underlying the observed effects. We found that LINC00997 is highly expressed in multiple carcinomas, being highest in stage IV KIRC in our RNA-Seq datasets. In addition, our data demonstrated that in KIRC patients, higher levels of LINC00997 are correlated with lower overall survival (OS) and disease-free survival (DFS) rates. In 18 cases of KIRC, we found that LINC00997 expression was greater in cancer tissues and metastases than in normal tissues. These results revealed that S100A11 is positively associated with LINC00997 in KIRC, which is positively correlated with metastasis-associated molecules VIM, MMP2 and MMP7. Our in vitro wound healing assay and Transwell tests demonstrated that interfering with either LINC00997 or S100A11 expression reduced migration of 786-O cells by inhibiting VIM, MMP2 and MMP7 expression. Importantly, we verified LINC00997 and STAT3 binding by RIP and determined that both LINC00997 and STAT3 bind to the S100A11 promoter, as shown by dual-luciferase reporter gene assay. In addition, inhibiting LINC00997 or STAT3 expression attenuated S100A11 levels. Consequently, the LINC00997-STAT3-S100A11 axis may promote the development of KIRC, and LINC00997 may represent a potential prognostic biomarker and therapeutic target for KIRC patients.

NR1B2 suppress kidney renal clear cell carcinoma (KIRC) progression by regulation of LATS 1/2-YAP signaling

BACKGROUND

Kidney Renal Clear Cell Carcinoma (KIRC) accounts for 75% of all renal cancers. Previous study had conflict evidences regarding NR1B2 role in cancer, and its expression and biological role in KIRC remained unclear. Our aims were to characterize the role of NR1B2 in KIRC.

METHODS

NR1B2 expression in TCGA database were analyzed. Clinical KIRC samples were examined by RT-PCR, western blot and tissue microarray (TMA). The relationship between NR1B2 expression and the clinical characteristics were evaluated. KIRC cell line were stably overexpressed NR1B2 or with an NR1B2 knocked down using lentivirus system. The cells were analyzed by migration and invasion assay, then injected into nude mice to assess tumor growth and metastasis. EMT marker expression and LATS 1/2-YAP pathway demonstration were detected by the TCGA database and western blot.

RESULTS

The expression of NR1B2 in KIRC was significantly down-regulated in the TCGA database and our clinical samples. Moreover, NR1B2 expression negatively correlated with tumor stage and positively correlated with overall and disease-free survival rate. Univariate and multivariate analyses indicated the expression level of NR1B2 could be used as an independent factor for predicting the prognosis of KIRC. Overexpression NR1B2 significantly inhibited and knockdown NR1B2 markedly promoted KIRC cell invasion and metastasis both in vitro and in vivo. Mechanistic investigations revealed that NR1B2 might be a tumor suppressor to inhibit EMT through the LATS1/2-YAP pathway.

CONCLUSIONS

our results defined NR1B2 as a tumor suppressor in KIRC that restricted EMT by the LATS1/2-YAP pathway.

Comprehensive characterization of immune- and inflammation-associated biomarkers based on multi-omics integration in kidney renal clear cell carcinoma

Background

Kidney renal clear cell carcinoma (KIRC) is the most common type of kidney cancer in adults, and it is responsible for approximately 90–95% of cases. Although extensive evidence has suggested that many immune- and inflammation-related genes could serve as effective biomarkers in KIRC, the potential associations among immune-, inflammation- and KIRC-related genes has not been sufficiently understood.

Methods

Here, we integrated multiple levels of data to construct an immune-, inflammation- or KIRC-directed neighbour network (IIKDN network) and a KIRC-related gene-directed network (KIRCD network).

Results

Our analysis suggested that immune- and inflammation-related genes in the network have special topological characteristics and expression patterns related to KIRC. We further identified five core clusters that showed a tighter network structure and stronger correlation of expression from the KIRCD network. Specifically, multiple-level molecular characteristics were systematically portrayed, including somatic mutation, copy-number variant and DNA methylation for the genes in five core clusters. We discovered that the genes showed strong correlation with respect to the expression and methylation levels in these five core clusters. These five core clusters could become special prognostic biomarkers for KIRC, and functional analysis showed that they were associated with activation of the immune and inflammation systems and cancer progression.

Conclusions

Our findings highlighted the novel role of the immune and inflammation genes in KIRC.

Electronic supplementary material

The online version of this article (10.1186/s12967-019-1927-y) contains supplementary material, which is available to authorized users.