Prognostic Value of BIRC5 in Lung Adenocarcinoma Lacking EGFR, KRAS, and ALK Mutations by Integrated Bioinformatics Analysis

Therapeutic Efficacy of YM155 to Regulate an Epigenetic Enzyme in Major Subtypes of RCC

Renal cell carcinoma (RCC) is the most common type of kidney cancer and includes more than 10 subtypes. Compared to the intensively investigated clear cell RCC (ccRCC), the underlying mechanisms and treatment options of other subtypes, including papillary RCC (pRCC) and chromogenic RCC (chRCC), are limited. In this study, we analyzed the public databases for ccRCC, pRCC, and chRCC and found that BIRC5 was commonly overexpressed in a large cohort of pRCC and chRCC patients as well as ccRCC and was closely related to the progression of RCCs. We investigated the potential of BIRC5 as a therapeutic target for these three types of RCCs. Loss and gain of function studies showed the critical role of BIRC5 in cancer growth. YM155, a BIRC5 inhibitor, induced a potent tumor-suppressive effect in the three types of RCC cells and xenograft models. To determine the mechanism underlying the anti-tumor effects of YM155, we examined epigenetic modifications in the BIRC5 promoter and found that histone H3 lysine 27 acetylation (H3K27Ac) was highly enriched on the promoter region of BIRC5. Chromatin-immunoprecipitation analysis revealed that H3K27Ac enrichment was significantly decreased by YM155. Immunohistochemistry of xenografted tissue showed that overexpression of BIRC5 plays an important role in malignancy in RCC. Furthermore, high expression of P300 was significantly associated with the progression of RCC. Our findings demonstrate the P300-H3K27Ac-BIRC5 cascade in three types of RCC and provide a therapeutic path for future research on RCC.

(-)-Guaiol inhibit epithelial-mesenchymal transition in lung cancer via suppressing M2 macrophages mediated STAT3 signaling pathway

In the context of cancer expansion, epithelial-mesenchymal transition (EMT) plays an essential role in driving invasion and metastasis potential of cancer cells. Tumor-associated macrophages (TAMs)-derived factors involved in the initiation and progression of EMT. We assess the role of M2 macrophage in suppressing lung tumors of a natural compound (-)-Guaiol by using macrophage depleted model. Bone marrow-derived monocytes (BMDMs) were extracted and induced to M2-like phenotype in vitro. The co-culture of M2 macrophage and lung cancer cells was established to observe that inhibition of lung tumor growth by (-)-Guaiol requires presence of macrophages. This suppressed effect of (-)-Guaiol was alleviated when mice macrophage was depleted. The expression of M2-like macrophages was strongly reduced by (-)-Guaiol treated mice, but not the changes of M1-like macrophages. In vitro studies, we demonstrated that (-)-Guaiol suppressed M2 polarization of BMDMs, as well as migration, invasion, and EMT of lung cancer cells in co-culture. M2 macrophage-derived interleukin 10 (IL-10) was investigated as a critical signaling molecule between M2 macrophage and lung cancer cells. We have also verified that the mechanism of (-)-Guaiol inhibiting the EMT process of lung cancer is related to the activation of IL-10-mediated signal transducer and activator of transcription 3 (STAT3). These results suggested that the suppressive effect role of (-)-Guaiol in M2 macrophage promoting EMT of lung cancer, which was associated with inhibition of IL-10 mediated STAT3 signaling pathway.

Ginsenoside Rg3, a promising agent for NSCLC patients in the pandemic: a large-scale data mining and systemic biological analysis

Introduction

Non-small cell lung cancer (NSCLC) patients are particularly vulnerable to the Coronavirus Disease-2019 (COVID-19). Currently, no anti-NSCLC/COVID-19 treatment options are available. As ginsenoside Rg3 is beneficial to NSCLC patients and has been identified as an entry inhibitor of the virus, this study aims to explore underlying pharmacological mechanisms of ginsenoside Rg3 for the treatment of NSCLC patients with COVID-19.

Methods

Based on a large-scale data mining and systemic biological analysis, this study investigated target genes, biological processes, pharmacological mechanisms, and underlying immune implications of ginsenoside Rg3 for NSCLC patients with COVID-19.

Results

An important gene set containing 26 target genes was built. Target genes with significant prognostic value were identified, including baculoviral IAP repeat containing 5 (BIRC5), carbonic anhydrase 9 (CA9), endothelin receptor type B (EDNRB), glucagon receptor (GCGR), interleukin 2 (IL2), peptidyl arginine deiminase 4 (PADI4), and solute carrier organic anion transporter family member 1B1 (SLCO1B1). The expression of target genes was significantly correlated with the infiltration level of macrophages, eosinophils, natural killer cells, and T lymphocytes. Ginsenoside Rg3 may benefit NSCLC patients with COVID-19 by regulating signaling pathways primarily involved in anti-inflammation, immunomodulation, cell cycle, cell fate, carcinogenesis, and hemodynamics.

Conclusions

This study provided a comprehensive strategy for drug discovery in NSCLC and COVID-19 based on systemic biology approaches. Ginsenoside Rg3 may be a prospective drug for NSCLC patients with COVID-19. Future studies are needed to determine the value of ginsenoside Rg3 for NSCLC patients with COVID-19.

Identifying General Tumor and Specific Lung Cancer Biomarkers by Transcriptomic Analysis

The bioinformatic pipeline previously developed in our research laboratory is used to identify potential general and specific deregulated tumor genes and transcription factors related to the establishment and progression of tumoral diseases, now comparing lung cancer with other two types of cancer. Twenty microarray datasets were selected and analyzed separately to identify hub differentiated expressed genes and compared to identify all the deregulated genes and transcription factors in common between the three types of cancer and those unique to lung cancer. The winning DEGs analysis allowed to identify an important number of TFs deregulated in the majority of microarray datasets, which can become key biomarkers of general tumors and specific to lung cancer. A coexpression network was constructed for every dataset with all deregulated genes associated with lung cancer, according to DAVID’s tool enrichment analysis, and transcription factors capable of regulating them, according to oPOSSUM´s tool. Several genes and transcription factors are coexpressed in the networks, suggesting that they could be related to the establishment or progression of the tumoral pathology in any tissue and specifically in the lung. The comparison of the coexpression networks of lung cancer and other types of cancer allowed the identification of common connectivity patterns with deregulated genes and transcription factors correlated to important tumoral processes and signaling pathways that have not been studied yet to experimentally validate their role in lung cancer. The Kaplan–Meier estimator determined the association of thirteen deregulated top winning transcription factors with the survival of lung cancer patients. The coregulatory analysis identified two top winning transcription factors networks related to the regulatory control of gene expression in lung and breast cancer. Our transcriptomic analysis suggests that cancer has an important coregulatory network of transcription factors related to the acquisition of the hallmarks of cancer. Moreover, lung cancer has a group of genes and transcription factors unique to pulmonary tissue that are coexpressed during tumorigenesis and must be studied experimentally to fully understand their role in the pathogenesis within its very complex transcriptomic scenario. Therefore, the downstream bioinformatic analysis developed was able to identify a coregulatory metafirm of cancer in general and specific to lung cancer taking into account the great heterogeneity of the tumoral process at cellular and population levels.

Identification of potential circular RNA biomarkers in lung adenocarcinoma: A bioinformatics analysis and retrospective clinical study

Non-small cell lung cancer (NSCLC) is one of the leading causes of cancer-associated mortality. Lung adenocarcinoma (LAC) is the most prevalent pathological subtype of NSCLC and accounts for ~40% of all lung cancer mortalities. There remains an urgent demand for the identification of novel biomarkers for the diagnosis and development of therapeutic strategies for LAC. In the present study, the profiles of the differentially-expressed circular RNAs (circRNAs) in LAC tissues compared with those in their corresponding non-cancerous tissues were obtained after analyzing the circRNA microarray dataset GSE101586. The expression pattern of the indicated circRNAs in the LAC tissues were subsequently verified using reverse transcription-quantitative PCR (RT-qPCR). The potential prognostic significance of these circRNAs in patients with LAC were then analyzed in a retrospective clinical study. A circRNA-microRNA (miR or miRNA)-mRNA regulatory network in LAC was established by using Cytoscape. In addition, a protein-protein interaction (PPI) network was plotted using the Search Tool for the Retrieval of Interacting Genes/Proteins and visualized through Cytoscape. The prognostic value of the hub genes found was then analyzed based on the Gene Expression Profiling Interactive Analysis database. In total, four differentially-expressed circRNAs were obtained from the GSE101586 microarray dataset, three of which (hsa_circ_0006220, hsa_circ_0072088 and hsa_circ_0001666) were confirmed by RT-qPCR to be highly expressed in LAC tissues. This retrospective clinical study revealed that higher expression levels of these three circRNAs were associated with poorer prognoses in patients with LAC. In addition, siRNA-mediated knockdown of these circRNAs was found to inhibit cell proliferation, migration and invasion in LAC cells. Following analysis of the molecular mechanism underlying these circRNAs, eight miRNAs, namely miR-520f, miR-1261, miR-1270, miR-620, miR-188-3p, miR-516b, miR-940 and miR-661, were identified with potential binding sites for these three circRNAs. Subsequently, 232 overlapped genes from the 795 upregulated genes in the LAC samples from The Cancer Genome Atlas database and 7,829 predicted target genes of the list of eight aforementioned miRNAs were obtained. A circRNA-miRNA-mRNA network was then constructed. A PPI network was established, with six hub genes, namely kinesin family member (KIF) 2C, KIF18B, maternal embryonic leucine zipper kinase, baculoviral IAP repeat-containing 5, polo-like kinase 1 and cytoskeleton-associated protein 2-like, determined from this network. Higher expression levels of each of these hub genes were found to be associated with poorer prognoses of patients with LAC. To conclude, data from the present study suggested that circRNAs hsa_circ_0006220, hsa_circ_0072088 and hsa_circ_0001666 have the potential to be viable biomarkers and therapeutic targets for LAC.

BIRC5 promotes cancer progression and predicts prognosis in laryngeal squamous cell carcinoma

BACKGROUND

Laryngeal squamous cell carcinoma (LSCC) remains one of the most common respiratory tumors worldwide. Baculoviral inhibitor of apoptosis repeat containing 5 (BIRC5) is a member of the inhibitor-of-apoptosis protein family. BIRC5 plays an important role in various types of cell proliferation, differentiation, migration and invasion. However, the specific role of BIRC5 in LSCC remains unclear.

METHODS

To provide a prognostic biomarker for LSCC, we screened the prognostic genes of LSCC via bioinformatics. PPI network and KEGG pathways were used to select hub genes. Clinical prognoses were performed using a Kaplan-Meier plotter and Cox proportional-hazard analysis. BIRC5 expression in LSCC tissues and cell lines were detected by RT-PCR, Western blot and Immunohistochemistry (IHC). Cell proliferation, cell cycle and cell apoptosis were detected with Cell Counting Kit-8 (CCK-8) and Flow Cytometry assay, respectively.

RESULTS

Here, BIRC5 was strongly correlated with higher tumor grade and differentiation. BIRC5 was highly expressed in LSCC tissues when compared with normal tissues and increased expression of BIRC5 was associated with overall survival in LSCC patients. The suppression of BIRC5 induced cell apoptosis and cell cycle arrest, thereby inhibiting the proliferation of LSCC cells. The survival analysis confirmed that higher level of BIRC5 expression predicted poor prognosis of LSCC patients. BIRC5 may act as an oncogene of LSCC development and was suggested as a promising prognostic biomarker for LSCC.

Identification of a Novel Defined Immune-Autophagy-Related Gene Signature Associated With Clinical and Prognostic Features of Kidney Renal Clear Cell Carcinoma

Background: As a common cancer of the urinary system in adults, renal clear cell carcinoma is metastatic in 30% of patients, and 1-2 years after diagnosis, 60% of patients die. At present, the rapid development of tumor immunology and autophagy had brought new directions to the treatment of renal cancer. Therefore, it was extremely urgent to find potential targets and prognostic biomarkers for immunotherapy combined with autophagy. Methods: Through GSE168845, immune-related genes, autophagy-related genes, and immune-autophagy-related differentially expressed genes (IAR-DEGs) were identified. Independent prognostic value of IAR-DEGs was determined by differential expression analysis, prognostic analysis, and univariate and multivariate Cox regression analyses. Then, the lasso Cox regression model was established to evaluate the correlation of IAR-DEGs with the immune score, immune checkpoint, iron death, methylation, and one-class logistic regression (OCLR) score. Results: In this study, it was found that CANX, BID, NAMPT, and BIRC5 were immune-autophagy-related genes with independent prognostic value, and the risk prognostic model based on them was well constructed. Further analysis showed that CANX, BID, NAMPT, and BIRC5 were significantly correlated with the immune score, immune checkpoint, iron death, methylation, and OCLR score. Further experimental results were consistent with the bioinformatics analysis. Conclusion: CANX, BID, NAMPT, and BIRC5 were potential targets and effective prognostic biomarkers for immunotherapy combined with autophagy in kidney renal clear cell carcinoma.

A critical role of nuclear m6A reader YTHDC1 in leukemogenesis by regulating MCM complex-mediated DNA replication

YTHDC1 has distinct functions as a nuclear N6-methyladenosine (m6A) reader in regulating RNA metabolism. Here we show that YTHDC1 is overexpressed in acute myeloid leukemia (AML) and that it is required for the proliferation and survival of human AML cells. Genetic deletion of Ythdc1 markedly blocks AML development and maintenance as well as self-renewal of leukemia stem cells (LSCs) in vivo in mice. We found that Ythdc1 is also required for normal hematopoiesis and hematopoietic stem and progenitor cell (HSPC) maintenance in vivo. Notably, Ythdc1 haploinsufficiency reduces self-renewal of LSCs but not HSPCs in vivo. YTHDC1 knockdown has a strong inhibitory effect on proliferation of primary AML cells. Mechanistically, YTHDC1 regulates leukemogenesis through MCM4, which is a critical regulator of DNA replication. Our study provides compelling evidence that shows an oncogenic role and a distinct mechanism of YTHDC1 in AML.

The Bioinformatics-Based Analysis Identifies 7 Immune-Related Genes as Prognostic Biomarkers for Colon Cancer

Colon cancer poses a great threat to human health. Currently, there is no effective treatment for colon cancer due to its complex causative factors. Immunotherapy has now become a new method for tumor treatment. In this study, 487 DEGs were screened from The Cancer Genome Atlas (TCGA) database and ImmPort database, and GeneOntology (GO) functional enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis was performed. Hierarchical clustering of all samples revealed a significant correlation between colon cancer and immunity. The weighted gene co-expression network analysis (WGCNA) algorithm was used to identify key gene modules associated with immunity in colon cancer, here, module grey60 showed the highest correlation. A protein-protein interaction (PPI) network was constructed using the STRING database to screen hub genes, and subsequently, 7 immune-related genes the most closely associated with colon cancer were identified by differential expression in cancer and paracancer. Finally, a risk prediction model was developed using least absolute shrinkage and selection operator (LASSO) COX analysis, and the accuracy of the model was validated by GSE14333. This study determined that IRF4 and TNFRSF17 were immune-related genes in colon cancer, providing immune-related prognostic biomarkers for colon cancer.

Comprehensive Analysis of Inhibitor of Apoptosis Protein Expression and Prognostic Significance in Non-Small Cell Lung Cancer

Inhibitors of apoptosis proteins (IAPs) have been associated with tumor development and progression by affecting apoptosis through cell death signaling pathways. To date, eight IAPs (BIRC1-8) have been identified in mammalian cells. However, the role of IAPs in non-small cell lung cancer (NSCLC) development and progression has not been explored in depth. In this study, we used public datasets and bioinformatics tools to compare the expression, prognostic significance, and function of IAPs in NSCLC and its subtypes. Expression of IAPs in cancer and normal tissues and at different stages of NSCLC was compared with gene expression profiling interactive analysis, and their prognostic significance was analyzed with the Kaplan-Meier Plotter database. The correlations among IAPs were analyzed with the STRING database and SPSS19.0. Functional annotation of IAPs was analyzed by Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment on the basis of the DAVID tool. Among patients with lung adenocarcinoma (LUAD), the expression level of BIRC5 was higher than that in normal samples, and the expression of BIRC1 and BIRC5 significantly varied in different stages. Moreover, the BIRC1-3 and BIRC5 mRNA levels were associated with overall survival (OS), and the BIRC1-2 and BIRC5-6 mRNA levels were associated with progression-free survival (PFS). Among patients with lung squamous cell carcinoma (LUSC), the expression level of BIRC1 was lower and that of BIRC5 was higher than those in normal tissues, and BIRC5 expression significantly varied in different stages. BIRC1 expression was associated with OS, whereas BIRC2 and BIRC6 expression was associated with PFS. Enrichment analysis showed that most IAPs are associated with ubiquitin- and apoptosis-related pathways. Collectively, this study suggests BIRC5 as a potential diagnostic and staging marker, BIRC1 as a potential marker of OS, and BIRC2 and BIRC6 as potential PFS markers for patients with NSCLC. These highlight new targets for the early detection, treatment, and management of NSCLC.

A Prognostic Autophagy-Related Gene Pair Signature and Small-Molecule Drugs for Hepatocellular Carcinoma

Dysregulation of autophagy-related genes (ARGs) is related to the prognosis of cancers. However, the aberrant expression of ARGs signature in the prognosis of hepatocellular carcinoma (HCC) remain unclear. Using The Cancer Genome Atlas and the International Cancer Genome Consortium database, 188 common autophagy-related gene pairs (ARGPs) were identified. Through univariate, least absolute shrinkage and selection operator analysis, and multivariate Cox regression analysis, a prognostic signature of the training set was constructed on the basis of 6 ARGPs. Further analysis revealed that the ARGP based signature performed more accurately in overall survival (OS) prediction compared to other published gene signatures. In addition, a high risk of HCC was closely related to CTLA4 upregulation, LC3 downregulation, low-response to axitinib, rapamycin, temsirolimus, docetaxel, metformin, and high-response to bleomycin. Univariate Cox and multivariate Cox analysis revealed that the risk score was an independent prognostic factor for HCC. These results were internally validated in the test and TCGA sets and externally validated in the ICGC set. A nomogram, consisting of the risk score and the TNM stage, performed well when compared to an ideal nomogram. In conclusion, a 6-ARGP-based prognostic signature was identified and validated as an effective predictor of OS of patients with HCC. Furthermore, we recognized six small-molecule drugs, which may be potentially effective in treating HCC.

Fe3O4 magnetic nanoparticle-enhanced radiotherapy for lung adenocarcinoma via delivery of siBIRC5 and AS-ODN

Background

Radiotherapy is the mainstay treatment for lung adenocarcinoma, yet remains highly susceptible to resistance. Fe₃O₄ magnetic nanoparticles (MNPs) possess the ability to induce biological therapeutic effects. Herein, the current study set out to explore the effects of Fe₃O₄ MNPs on radiosensitivity of lung adenocarcinoma cells.

Methods

Fe₃O₄ MNPs loaded with both negatively-charged small interfering RNA against baculoviral IAP repeat containing 5 (siBIRC5) and oligodeoxynucleotide antisense (AS-ODN) to generate co-delivery NPs, followed by evaluation. Gel retardation assay was further performed to determine the binding ability of Fe₃O₄ MNPs to AS-ODN/siBIRC5. The radiosensitizing effect of NPs on lung adenocarcinoma cells was determined in the absence or the presence of NPs or radiotherapy. A549 and H460 tumor-bearing mice were established, where tumor tissues were subjected to immunohistochemistry.

Results

NPs were successfully prepared and characterized. BIRC5 expression levels were augmented in tissues of lung cancer patients. Fe₃O₄ MNPs enhanced the uptake of siBIRC5 and AS-ODN by lung adenocarcinoma cells. The presence of NPs under magnetic field reduced the BIRC5 expression and elevated the DR5 expression in lung adenocarcinoma cells. Lung adenocarcinoma cells treated with NPs exhibited inhibited tumor cell migration and increased DNA damage. After magnetic field treatment, tumors were better suppressed in the tumor-bearing mice treated with NPs, followed by radiotherapy.

Conclusion

Findings obtained in our study indicated that Fe₃O₄ MNPs-targeted delivery of siBIRC5 and AS-ODN enhances radiosensitivity, providing an innovative solution for the current clinically existing lung adenocarcinoma patients with radiotherapy resistance with a low risk of toxicity.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12967-021-02971-7.

The Early Diagnostic and Prognostic Value of BIRC5 in Clear-Cell Renal Cell Carcinoma Based on the Cancer Genome Atlas Data

PURPOSE

The aim of this study was to investigate the role of BIRC5 for early diagnosis and prognosis in clear-cell renal cell carcinoma (ccRCC) by studying the expression of BIRC5 and the correlation between BIRC5 expression and clinicopathological parameters and prognosis in ccRCC.

METHODS

The BIRC5 expression in ccRCC tissues and normal kidney tissues was measured using the Cancer Genome Atlas database and the Human Protein Atlas database. The correlation between BIRC5 expression and clinicopathological parameters and prognosis in ccRCC was analyzed using UALCAN, the Kaplan-Meier plotter, GEPIA, and SurvExpress. Thirteen-paired ccRCC plasma samples were used to verify the BIRC5 early diagnosis value of ccRCC.

RESULTS

The BIRC5 expression is significantly higher in ccRCC than in normal kidney tissues, and is correlated with the clinical stage and pathological grade of ccRCC (p < 0.05). The result of analyzing the relationship between BIRC5 expression and outcomes in ccRCC indicates that a high BIRC5 expression is an independent prognostic factor affecting the overall survival and disease-free survival of ccRCC (p < 0.05). Compared with normal kidney tissues, the immunohistochemical test shows that BIRC5 is significantly upregulated in ccRCC tissues. mRNA expression levels of BIRC5 were significantly higher in the ccRCC plasma than normal (p < 0.05).

CONCLUSIONS

The high expression of BIRC5 is an important indicator for the prognosis of ccRCC, which makes BIRC5 an effective biomarker for predicting the prognosis of patients in ccRCC. BIRC5 may be a great potential biomarker for early diagnosis of ccRCC.

A seven-gene prognostic signature predicts overall survival of patients with lung adenocarcinoma (LUAD)

Background

Lung adenocarcinoma (LUAD) is one of the most common types in the world with a high mortality rate. Despite advances in treatment strategies, the overall survival (OS) remains short. Our study aims to establish a reliable prognostic signature closely related to the survival of LUAD patients that can better predict prognosis and possibly help with individual monitoring of LUAD patients.

Methods

Raw RNA-sequencing data were obtained from Fudan University and used as a training group. Differentially expressed genes (DEGs) for the training group were screened. The univariate, least absolute shrinkage and selection operator (LASSO), and multivariate cox regression analysis were conducted to identify the candidate prognostic genes and construct the risk score model. Kaplan–Meier analysis, time-dependent receiver operating characteristic (ROC) curve were used to evaluate the prognostic power and performance of the signature. Moreover, The Cancer Genome Atlas (TCGA-LUAD) dataset was further used to validate the predictive ability of prognostic signature.

Results

A prognostic signature consisting of seven prognostic-related genes was constructed using the training group. The 7-gene prognostic signature significantly grouped patients in high and low-risk groups in terms of overall survival in the training cohort [hazard ratio, HR = 8.94, 95% confidence interval (95% CI)] [2.041–39.2]; P = 0.0004), and in the validation cohort (HR = 2.41, 95% CI [1.779–3.276]; P < 0.0001). Cox regression analysis (univariate and multivariate) demonstrated that the seven-gene signature is an independent prognostic biomarker for predicting the survival of LUAD patients. ROC curves revealed that the 7-gene prognostic signature achieved a good performance in training and validation groups (AUC = 0.91, AUC = 0.7 respectively) in predicting OS for LUAD patients. Furthermore, the stratified analysis of the signature showed another classification to predict the prognosis.

Conclusion

Our study suggested a new and reliable prognostic signature that has a significant implication in predicting overall survival for LUAD patients and may help with early diagnosis and making effective clinical decisions regarding potential individual treatment.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12935-021-01975-z.

Five-gene signature associating with Gleason score serve as novel biomarkers for identifying early recurring events and contributing to early diagnosis for Prostate Adenocarcinoma

Background: Compared to non-recurrent type, recurrent prostate adenocarcinoma (PCa) is highly fatal, and significantly shortens the survival time of affected patients. Early and accurate laboratory diagnosis is particularly important in identifying patients at high risk of recurrence, necessary for additional systemic intervention. We aimed to develop efficient and accurate diagnostic and prognostic biomarkers for new PCa following radical therapy. Methods: We identified differentially expressed genes (DEGs) and clinicopathological data of PCa patients from Gene Expression Omnibus (GEO) datasets and The Cancer Genome Atlas (TCGA) repositories. We then uncovered the most relevant clinical traits and genes modules associated with PCa prognosis using the Weighted gene correlation network analysis (WGCNA). Univariate Cox regression analysis and multivariate Cox proportional hazards (Cox-PH) models were performed to identify candidate gene signatures related to Disease-Free Interval (DFI). Data for internal and external cohorts were utilized to test and validate the accuracy and clinical utility of the prognostic models. Results: We constructed and validated an accurate and reliable model for predicting the prognosis of PCa using 5 Gleason score-associated gene signatures (ZNF695, CENPA, TROAP, BIRC5 and KIF20A). The ROC and Kaplan-Meier analysis revealed the model was highly accurate in diagnosing and predicting the recurrence and metastases of PCa. The accuracy of the model was validated using the calibration curves based on internal TCGA cohort and external GEO cohort. Using the model, patients could be prognostically stratified in to various groups including TNM classification and Gleason score. Multivariate analysis revealed the model could independently predict the prognosis of PCa patients and its utility was superior to that of clinicopathological characteristics. In addition, we fund the expression of the 5 gene signatures strongly and positively correlated with tumor purity but negatively correlated with infiltration CD8+ T cells to the tumor microenvironment. Conclusions: A 5 gene signatures can accurately be used in the diagnosis and prediction of PCa prognosis. Thus this can guide the treatment and management prostate adenocarcinoma.

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

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

CircANKRD52 Promotes the Tumorigenesis of Hepatocellular Carcinoma by Sponging miR-497-5p and Upregulating BIRC5 Expression

CircRNAs participate in the pathogenesis of a variety of cancers. Previous studies showed that baculoviral IAP repeat containing 5 (BIRC5) can promote tumor progression. But, the mechanisms by which circRNAs regulate BIRC5 expression in hepatocellular carcinoma (HCC) remain unknown. The clinical prognosis of BIRC5 or miR-497-5p expression in patients with HCC was assessed by TCGA RNA-seq dataset. hsa_circ_0026939 (circANKRD52) or BIRC5 was identified to bind with miR-497-5p by luciferase gene report, RIP and circRIP assays. MTT, colony formation, Transwell assays and a xenograft tumor model were used to estimate the role of miR-497-5p or circANKRD52 in HCC cells. As a result, we found that elevated expression of BIRC5 or decreased expression of miR-497-5p was linked to poor survival in HCC. Restored expression of miR-497-5p repressed cell proliferation, colony formation and invasiveness by targeting BIRC5, but its inhibitor showed the opposite results. Furthermore, circANKRD52 possessed a tumor-promoting effect by acting as a sponge of miR-497-5p and thereby upregulated BIRC5 in HCC cells. In conclusion, our findings demonstrated that circANKRD52 enhances the tumorigenesis of HCC by sponging miR-497-5p and upregulating BIRC5 expression.

Identification of prognostic significance of BIRC5 in breast cancer using integrative bioinformatics analysis

Aims: Baculoviral inhibitor of apoptosis repeat containing 5 (BIRC5) plays vital roles in carcinogenesis by influencing cell division and proliferation and by inhibiting apoptosis. However, the prognostic significance of BIRC5 remains unclear in breast cancer.

Methods:BIRC5 expression and methylation status were evaluated using the Oncomine and The Cancer Genome Atlas (TCGA) databases. The relevance between BIRC5 and different clinicopathological features as well as survival information was analyzed using the bc-GenExMiner database and Kaplan–Meier Plotter. BIRC5–drug interaction network was obtained using the Comparative Toxicogenomics Database.

Results: Based on the results from databases and own hospital data, BIRC5 was higher expressed in different breast cancer subtypes compared with the matched normal individuals. Hormone receptors were negatively correlated with BIRC5 expression, whereas the Scarff–Bloom–Richardson (SBR) grade, Nottingham Prognostic Index (NPI), human epidermal growth factor receptor-2 (HER-2) status, basal-like status, and triple-negative status were positively related to BIRC5 level in breast cancer samples with respect to normal tissues. High BIRC5 expression was responsible for shorter relapse-free survival, worse overall survival, reduced distant metastasis free survival, and increased risk of metastatic relapse event. BIRC5–drug interaction network indicated that several common drugs could modulate BIRC5 expression. Furthermore, a positive correlation between BIRC5 andcell-division cycle protein 20 (CDC20) gene was confirmed.

Conclusion:BIRC5 may be adopted as a promising predictive marker and potential therapeutic target in breast cancer. Further large-scale studies are needed to more precisely confirm the value of BIRC5 in treatment of breast cancer.

Identification and validation of an autophagy-related long non-coding RNA signature as a prognostic biomarker for patients with lung adenocarcinoma

Background

Lung adenocarcinoma (LUAD) is the most predominant pathological subtype of lung cancer, accounting for 40–70% of all lung cancer cases. Although significant improvements have been made in the screening, diagnosis, and precise management in recent years, the prognosis of LUAD remains bleak. This study aimed to investigate the prognostic significance of autophagy-related long non-coding RNAs (lncRNAs) and construct an autophagy-related lncRNA prognostic model in LUAD.

Methods

The gene expression data of LUAD patients were obtained from The Cancer Genome Atlas (TCGA) database. All autophagy-related genes were downloaded from the Human Autophagy Database (HADb). Spearman’s correlation test was exploited to identify potential autophagy-related lncRNAs. The multivariate Cox regression analysis was used to construct the prognostic signature, which divided LUAD patients into high-risk and low-risk groups. Subsequently, the receiver operating characteristic (ROC) curves were generated to assess the predictive ability of this prognostic model for overall survival (OS) in these individuals. Then, the Gene set enrichment analysis (GSEA) was conducted to execute pathway enrichment analysis. Finally, a multidimensional validation was exploited to verify our findings.

Results

A total of 1,144 autophagy-related lncRNAs were identified to construct the co-expression network via Spearman’s correlation test (|R²| >0.4 and P≤0.001). Ultimately, a 16 autophagy-related lncRNAs prognostic model was constructed, and the area under the ROC curve (AUC) was 0.775. The results of GSEA enrichment analysis showed that the genes in the high-risk group were mainly enriched in cell cycle and p53 signaling pathways. The results of the multidimensional database validation indicated that the expression level of BIRC5 was significantly correlated with the expression level of TMPO-AS1. Furthermore, both TMPO-AS1 and BIRC5 had a higher expression level in LUAD samples. LUAD patients with high expression levels of TMPO-AS1 and BIRC5 were correlated with advanced disease stage and poor OS.

Conclusions

In summary, our results suggested that the prognostic signature of the 16 autophagy-related lncRNAs has significant prognostic value for LUAD patients. Furthermore, TMPO-AS1 and BIRC5 are potential predictors and therapeutic targets in these individuals.

Immune signature-based risk stratification and prediction of immune checkpoint inhibitor's efficacy for lung adenocarcinoma

BACKGROUND

Lung adenocarcinoma (LUAD) is a common pulmonary malignant disease with a poor prognosis. There were limited studies investigating the influences of the tumor immune microenvironment on LUAD patients' survival and response to immune checkpoint inhibitors (ICIs).

METHODS

Based on TCGA-LUAD dataset, we constructed a prognostic immune signature and validated its predictive capability in the internal as well as total datasets. Then, we explored the differences of tumor-infiltrating lymphocytes, tumor mutation burden, and patients' response to ICI treatment between the high-risk score group and low-risk score group.

RESULTS

This immune signature consisted of 17 immune-related genes, which was an independent prognostic factor for LUAD patients. In the low-risk score group, patients had better overall survival. Although the differences were non-significant, patients with low-risk scores had more tumor-infiltrating follicular helper T cells and fewer macrophages (M0), which were closely related to clinical outcomes. Additionally, the total TMB was markedly decreased in the low-risk score group. Using immunophenoscore as a surrogate of ICI response, we found that patients with low-risk scores had significantly higher immunophenoscore.

CONCLUSION

The 17-immune-related genes signature may have prognostic and predictive relevance with ICI therapy but needs prospective validation.

Development and validation of a robust immune-related prognostic signature in early-stage lung adenocarcinoma

Background

The incidence of stage I and stage II lung adenocarcinoma (LUAD) is likely to increase with the introduction of annual screening programs for high-risk individuals. We aimed to identify a reliable prognostic signature with immune-related genes that can predict prognosis and help making individualized management for patients with early-stage LUAD.

Methods

The public LUAD cohorts were obtained from the large-scale databases including 4 microarray data sets from the Gene Expression Omnibus (GEO) and 1 RNA-seq data set from The Cancer Genome Atlas (TCGA) LUAD cohort. Only early-stage patients with clinical information were included. Cox proportional hazards regression model was performed to identify the candidate prognostic genes in GSE30219, GSE31210 and GSE50081 (training set). The prognostic signature was developed using the overlapped prognostic genes based on a risk score method. Kaplan–Meier curve with log-rank test and time-dependent receiver operating characteristic (ROC) curve were used to evaluate the prognostic value and performance of this signature, respectively. Furthermore, the robustness of this prognostic signature was further validated in TCGA-LUAD and GSE72094 cohorts.

Results

A prognostic immune signature consisting of 21 immune-related genes was constructed using the training set. The prognostic signature significantly stratified patients into high- and low-risk groups in terms of overall survival (OS) in training data set, including GSE30219 (HR = 4.31, 95% CI 2.29–8.11; P = 6.16E−06), GSE31210 (HR = 11.91, 95% CI 4.15–34.19; P = 4.10E−06), GSE50081 (HR = 3.63, 95% CI 1.90–6.95; P = 9.95E−05), the combined data set (HR = 3.15, 95% CI 1.98–5.02; P = 1.26E−06) and the validation data set, including TCGA-LUAD (HR = 2.16, 95% CI 1.49–3.13; P = 4.54E−05) and GSE72094 (HR = 2.95, 95% CI 1.86–4.70; P = 4.79E−06). Multivariate cox regression analysis demonstrated that the 21-gene signature could serve as an independent prognostic factor for OS after adjusting for other clinical factors. ROC curves revealed that the immune signature achieved good performance in predicting OS for early-stage LUAD. Several biological processes, including regulation of immune effector process, were enriched in the immune signature. Moreover, the combination of the signature with tumor stage showed more precise classification for prognosis prediction and treatment design.

Conclusions

Our study proposed a robust immune-related prognostic signature for estimating overall survival in early-stage LUAD, which may be contributed to make more accurate survival risk stratification and individualized clinical management for patients with early-stage LUAD.

Silencing of lncRNA LINC00857 Enhances BIRC5-Dependent Radio-Sensitivity of Lung Adenocarcinoma Cells by Recruiting NF-κB1

Lung adenocarcinoma (LUAD) is a predominant type of lung cancer in never-smoker patients. In this study, we identified a long noncoding RNA (lncRNA) LINC00857 that might regulate radio-sensitivity of LUAD cells. Expression of LINC00857 and baculoviral IAP repeat containing 5 (BIRC5) was determined to be upregulated in LUAD cells and tissues using qRT-PCR and western blot analysis. The correlation between LINC00857 and nuclear factor kappa B subunit 1 (NF-κB1) was verified using RNA immunoprecipitation and chromatin immunoprecipitation assays, while the binding relationship between NF-κB1 and BIRC5 was determined by dual-luciferase reporter assay. It was suggested that LINC00857 could recruit NF-κB1 in BIRC5 promoter region. BIRC5 promoter activity was repressed in response to small interfering-LINC00857 (si-LINC00857) in LUAD cells. Silencing LINC00857 or BIRC5 reduced proliferation and colony formation but enhanced apoptosis and radio-sensitivity of LUAD cells. The experiment in vivo verified the function of silencing LINC00857 on enhancing radio-sensitivity of LUAD cells. Our results reveal a functional regulatory LINC00857-NF-κB1-BIRC5 triplet in LUAD cells, suggesting LINC00857 as a potential target for LUAD treatment.

TRIP13 predicts poor prognosis in clear cell renal cell carcinoma

What is the leading molecular mechanism that causes broad resistance to systemic therapies remains a key question in renal cancer related research. We explored associations of TRIP13 expression with the clinical course using the tissue microarray (TMA). The TMA contained specimens from 87 patients diagnosed with clear cell renal cell carcinoma (ccRCC). We performed immunohistochemistry to investigate TRIP13 protein expression levels. The overall survival (OS) was analyzed using the Kaplan-Meier method and log-rank statistics. Univariate and multivariate analyses were conducted using Cox proportional hazard models. Median follow up for the TMA cohort was 7.0 years. Tissues from 28.74% of patients demonstrated high TRIP13 expression. Mean TRIP13 expression in TRIP13-rich tumors was significantly higher comparing to adjacent normal tissues (P < 0.05). TRIP13 expression did not significantly correlate with stage nor tumor grade (P > 0.05). Elevated expression of TRIP13 served as an independent unfavorable prognostic indicator of survival in ccRCC (P < 0.05). TRIP13 overexpression predicts poor prognosis in ccRCC. Together with the emerging reports, this observation raises a suspicion that TRIP13 is a substantial driver of resistance to systemic therapies against kidney cancer.

Seven immune-related genes prognostic power and correlation with tumor-infiltrating immune cells in hepatocellular carcinoma

Background

Given poor prognosis and the lack of efficient therapy for advanced hepatocellular carcinoma, immunotherapy has emerged as an increasingly important role. However, there were few reports on the correlation between immune‐related genes and HCC. The purpose of this study is to construct a novel immune‐related gene‐based prognostic signature for HCC and to explore the potential mechanisms.

Methods

We organized expression data of 374 HCC samples and 50 nontumor samples from TCGA database. A robust signature was constructed by Cox regression analysis based on the immune‐related genes, which were filtered by differential genes analysis and Cox regression analysis. Then, the correlation analysis between the signature and clinical characteristics was conducted. And the signature was validated in ICGC database. Furthermore, the relationships between immune cell infiltration and the signature were explored by bioinformatics analysis.

Results

Seven genes‐based model (Risk score = BIRC5 * 0.0238 + FOS * 0.0055 + DKK1 * 0.0085 + FGF13 * 0.3432 + IL11 * 0.0135 + IL17D * 0.0878 + SPP1 * 0.0003) was constructed eventually and it was proved to be an independent prognostic factor for HCC patients. The signature‐calculated risk scores were shown to be positively correlated with the infiltration of these five immune cells, including macrophages, neutrophils, CD8+T, dendritic, and B cells. And the results suggested that high amplication of BIRC5, FGF13, IL11, IL17D, and SPP1 were more likely correlated with immune cell infiltration. Finally, PPI network, TFs‐based regulatory network and gene enrichment plots were performed to show potential molecular mechanisms.

Conclusion

We construct a robust immune‐related gene‐based prognostic signature with seven genes and explore potential mechanisms about it, which may contribute to the immunotherapy research for HCC.

Unravelling the Role of miR-20b-5p, CCNB1, HMGA2 and E2F7 in Development and Progression of Non-Small Cell Lung Cancer (NSCLC)

Lung cancer is a prime cause of worldwide cancer deaths, with non-small cell lung cancer (NSCLC) as a frequent subtype. Surgical resection, chemotherapy are the currently used treatment methods. Delayed detection, poor prognosis, tumor heterogeneity, and chemoresistance make them relatively ineffective. Genomic medicine is a budding aspect of cancer therapeutics, where miRNAs are impressively involved. miRNAs are short ncRNAs that bind to 3′UTR of target mRNA, causing its degradation or translational repression to regulate gene expression. This study aims to identify important miRNA-mRNA-TF interactions in NSCLC using bioinformatics analysis. GEO datasets containing mRNA expression data of NSCLC were used to determine differentially expressed genes (DEGs), and identification of hub genes-BIRC5, CCNB1, KIF11, KIF20A, and KIF4A (all functionally enriched in cell cycle). The FFL network involved, comprised of miR-20b-5p, CCNB1, HMGA2, and E2F7. KM survival analysis determines that these components may be effective prognostic biomarkers and would be a new contemplation in NSCLC therapeutics as they target cell cycle and immunosurveillance mechanisms via HMGA2 and E2F7. They provide survival advantage and evasion of host immune response (via downregulation of cytokines-IL6, IL1R1 and upregulation of chemokines-CXCL13, CXCL14) to NSCLC. The study has provided innovative targets, but further validation is needed to confirm the proposed mechanism.

Identification of nine key genes by bioinformatics analysis for predicting poor prognosis in smoking-induced lung adenocarcinoma

Aim:

To screen and identify key genes related to the development of smoking-induced lung adenocarcinoma (LUAD).

Materials & methods:

We obtained data from the GEO chip dataset GSE31210. The differentially expressed genes were screened by GEO2R. The protein interaction network of differentially expressed genes was constructed by STRING and Cytoscape. Finally, core genes were screened. The overall survival time of patients with the core genes was analyzed by Kaplan–Meier method. Gene ontology and Kyoto encyclopedia of genes and genomes bioaccumulation was calculated by DAVID.

Results:

Functional enrichment analysis indicated that nine key genes were actively involved in the biological process of smoking-related LUAD.

Conclusion:

23 core genes and nine key genes among them were correlated with adverse prognosis of LUAD induced by smoking.

Upregulated expression of SAC3D1 is associated with progression in gastric cancer

SAC3 domain containing 1 (SAC3D1) has been reported to be involved in numerous types of cancer. However, the role of SAC3D1 in GC has not yet been elucidated. In the present study, the mRNA expression level of SAC3D1 between GC and normal tissues were assessed with a continuous variable meta-analysis based on multiple datasets from public databases. The protein expression level of SAC3D1 in GC and normal tissues was assessed by an in-house immunohistochem-istry (IHC). The association between SAC3D1 expression and some clinical parameters was assessed based on the TCGA and IHC data. Survival analysis was performed to assess the association between SAC3D1 expression and the survival of GC patients. The co-expressed genes of SAC3D1 were determined by integrating three online tools, and the enrichment analyses were performed to determine SAC3D1-related pathways and hub co-expressed genes. SAC3D1 was significantly upregulated in GC tumor tissues in comparison to normal tissues with the SMD being 0.45 (0.12, 0.79). The IHC results also indicated that SAC3D1 protein expression in GC tissues was markedly higher than in normal tissues. The SMD following the addition of the IHC data was 0.59 (0.11, 1.07). The protein levels of SAC3D1 were positively associated with the histological grade, T stage and N stage of GC (P<0.001). The TCGA data also revealed that the SAC3D1 mRNA level was significantly associated with the N stage (P<0.001). Moreover, prognosis analysis indicated that SAC3D1 was closely associated with the prognosis of patients with GC. Moreover, 410 co-expressed genes of SAC3D1 were determined, and these genes were mainly enriched in the cell cycle. In total, 4 genes (CDK1, CCNB1, CCNB2 and CDC20) were considered key co-expressed genes. On the whole, these findings demonstrate that SAC3D1 is highly expressed in GC and may be associated with the progression of GC.

Effects of autophagy-associated genes on the prognosis for lung adenocarcinoma

Background

Several studies show that autophagy plays an important part in the biological processes of lung adenocarcinoma. Therefore, this work aimed to establish one scoring system on the basis of the expression profiles of differentially expressed autophagy-related genes (DEARGs) in patients with lung adenocarcinoma.

Methods

The Cancer Genome Atlas (TCGA) was applied to retrieve lung adenocarcinoma data. The overall survival (OS)-associated DEARGs were selected for the DEARG scoring scale. Moreover, the online database Kaplan-Meier Plotter (www.Kmplot.com) was employed to verify the accuracy of our results.

Results

The expression patterns of DEARG were detected in lung adenocarcinoma as well as normal lung tissues. A gene set related to autophagy was identified, along with 9 genes that showed marked significance in predicting the lung adenocarcinoma prognosis. According to the cox regression results, DEARGs (including ITGB4, BIRC5, ERO1A, and NLRC4) were applied to calculate the DEARGs risk score. Patients with lower DEARGs risk scores were associated with better OS. Moreover, based on analysis with the receiver operating characteristic (ROC) curve, DEARGs accurately distinguished the healthy tissues from lung adenocarcinoma tissues [area under the curve (AUC) value of >0.6].

Conclusions

A scoring system is constructed based on the primary DEARGs, which accurately predicts the outcomes of lung adenocarcinoma.

Joint Transcriptomic Analysis of Lung Cancer and Other Lung Diseases

Background: Epidemiological and clinical evidence points cancer comorbidity with pulmonary chronic disease. The acquisition of some hallmarks of cancer by cells affected with lung pathologies as a cell adaptive mechanism to a shear stress, suggests that could be associated with the establishment of tumoral processes. Objective: To propose a bioinformatic pipeline for the identification of all deregulated genes and the transcriptional regulators (TFs) that are coexpressed during lung cancer establishment, and therefore could be important for the acquisition of the hallmarks of cancer. Methods: Ten microarray datasets (six of lung cancer, four of lung diseases) comparing normal and diseases-related lung tissue were selected to identify hub differentiated expressed genes (DEGs) in common between lung pathologies and lung cancer, along with transcriptional regulators through the utilization of specialized libraries from R language. DAVID bioinformatics tool for gene enrichment analyses was used to identify genes with experimental evidence associated to tumoral processes and signaling pathways. Coexpression networks of DEGs and TFs in lung cancer establishment were created with Coexnet library, and a survival analysis of the main hub genes was made. Results: Two hundred ten DEGs were identified in common between lung cancer and other lung diseases related to the acquisition of tumoral characteristics, which are coexpressed in a lung cancer network with TFs, suggesting that could be related to the establishment of the tumoral pathology in lung. The comparison of the coexpression networks of lung cancer and other lung diseases allowed the identification of common connectivity patterns (CCPs) with DEGs and TFs correlated to important tumoral processes and signaling pathways, that haven´t been studied to experimentally validate their role in the early stages of lung cancer. Some of the TFs identified showed a correlation between its expression levels and the survival of lung cancer patients. Conclusion: Our findings indicate that lung diseases share genes with lung cancer which are coexpressed in lung cancer, and might be able to explain the epidemiological observations that point to direct and inverse comorbid associations between some chronic lung diseases and lung cancer and represent a complex transcriptomic scenario.

Differentially expressed autophagy-related genes are potential prognostic and diagnostic biomarkers in clear-cell renal cell carcinoma

We examined the role of differentially expressed autophagy-related genes (DEARGs) in clear cell Renal Cell Carcinoma (ccRCC) using high-throughput RNA-seq data from The Cancer Genome Atlas (TCGA). Cox regression analyses showed that 5 DEARGs (PRKCQ, BID, BAG1, BIRC5, and ATG16L2) correlated with overall survival (OS) and 4 DEARGs (EIF4EBP1, BAG1, ATG9B, and BIRC5) correlated with disease-free survival (DFS) in ccRCC patients. Multivariate Cox regression analysis using the OS and DFS prognostic risk models showed that expression of the nine DEARGs accurately and independently predicted the risk of disease recurrence or progression in ccRCC patients (area under curve or AUC values > 0.70; all p < 0.05). Moreover, the DEARGs accurately distinguished healthy individuals from ccRCC patients based on receiver operated characteristic (ROC) analyses (area under curve or AUC values > 0.60), suggesting their potential as diagnostic biomarkers for ccRCC. The expression of DEARGs also correlated with the drug sensitivity of ccRCC cell lines. The ccRCC cell lines were significantly sensitive to Sepantronium bromide, a drug that targets BIRC5. This makes BIRC5 a potential therapeutic target for ccRCC. Our study thus demonstrates that DEARGs are potential diagnostic and prognostic biomarkers and therapeutic targets in ccRCC.