Potential prognostic biomarkers related to immunity in clear cell renal cell carcinoma using bioinformatic strategy

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

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

Establishment of a new prognostic risk model of GNG7 pathway-related molecules in clear cell renal cell carcinoma based on immunomodulators

Clear cell renal cell carcinoma (CCRCC) is a common tumor of the urological system for which surgery is the preferred treatment, but there is a lack of therapeutic options after surgery. This study aims to explore the biological role of GNG7 on CCRCC from a genetic perspective. Differences in mRNA expression and patient survival of GNG7 in patients with CCRCC and healthy patients were analyzed using the TCGA database. It was observed that GNG7 gene expression was downregulated in CCRCC tissue compared with healthy tissue, and high GNG7 predicted better prognosis for patients, and GNG7 also showed strong variability in clinical and TMN staging. The immune relevance of GNG7 and related genes was explored using renal cancer data from CCLE and TISIDB database. It was verified that the risk score constructed by 7 GNG7-related regulators might be used as an independent prognostic risk factor for CCRCC. A CCRCC prognostic model that involved 7 immune genes was further established to predict the survival probabilities of patients. At last, the GEO database and immunochemical tissue staining were used to validate GNG7 expression in CCRCC. Our study proposed a novel panel of genes to predict CCRCC OS based on GNG7-related immune genes, which may help to accurately predict the prognosis of CCRCC patients and make better clinical decisions for individual treatment.

Long non-coding RNAs enable precise diagnosis and prediction of early relapse after nephrectomy in patients with renal cell carcinoma

PURPOSE

Renal cell carcinoma belongs among the deadliest malignancies despite great progress in therapy and accessibility of primary care. One of the main unmet medical needs remains the possibility of early diagnosis before the tumor dissemination and prediction of early relapse and disease progression after a successful nephrectomy. In our study, we aimed to identify novel diagnostic and prognostic biomarkers using next-generation sequencing on a novel cohort of RCC patients.

METHODS

Global expression profiles have been obtained using next-generation sequencing of paired tumor and non-tumor tissue of 48 RCC patients. Twenty candidate lncRNA have been selected for further validation on an independent cohort of paired tumor and non-tumor tissue of 198 RCC patients.

RESULTS

Sequencing data analysis showed significant dysregulation of more than 2800 lncRNAs. Out of 20 candidate lncRNAs selected for validation, we confirmed that 14 of them are statistically significantly dysregulated. In order to yield better discriminatory results, we combined several best performing lncRNAs into diagnostic and prognostic models. A diagnostic model consisting of AZGP1P1, CDKN2B-AS1, COL18A1, and RMST achieved AUC 0.9808, sensitivity 95.96%, and specificity 90.4%. The model for prediction of early relapse after nephrectomy consists of COLCA1, RMST, SNHG3, and ZNF667-AS1 and achieved AUC 0.9241 with sensitivity 93.75% and specificity 71.07%. Notably, no combination has outperformed COLCA1 alone. Lastly, a model for stage consists of ZNF667-AS1, PVT1, RMST, LINC00955, and TCL6 and achieves AUC 0.812, sensitivity 85.71%, and specificity 69.41%.

CONCLUSION

In our work, we identified several lncRNAs as potential biomarkers and developed models for diagnosis and prognostication in relation to stage and early relapse after nephrectomy.

High expression of RPL27A predicts poor prognosis in patients with hepatocellular carcinoma

BACKGROUND

Hepatocellular carcinoma (HCC) is one of the most common cancers in the digestive system with rapid progression and poor prognosis. Recent studies have shown that RPL27A could be used as a biomarker for a variety of cancers, but its role in HCC is not clear.

METHOD

We analyzed the expression of RPL27A in the pan-cancer analysis and analyzed the relationship between the expression of RPL27A and the clinical features and prognosis of patients with HCC. We evaluated the expression difference of RPL27A in HCC tissues and paired normal adjacent tissues using immunohistochemistry. Furthermore, we analyzed the co-expression genes of RPL27A and used them to explore the possible mechanism of RPL27A and screen hub genes effecting HCC. In addition, we studied the role of RPL27A in immune infiltration and mutation.

RESULTS

We found that the expression level of RPL27A increased in a variety of cancers, including HCC. In HCC patients, the high expression of RPL27A was related to progression and poor prognosis as an independent predictor. We also constructed a protein interaction network through co-expression gene analysis of RPL27A and screened 9 hub genes. Enrichment analysis showed that co-expression genes were associated with ribosome pathway, viral replication, nuclear-transcribed mRNA catabolic process, and nonsense-mediated decay. We found that the expression level of RPL27A was closely related to TP53 mutation and immune infiltration in HCC.

CONCLUSION

RPL27A might become a biomarker in the diagnosis, treatment, and follow-up of patients with HCC.

Prediction of Prognosis and Chemotherapeutic Sensitivity Based on Cuproptosis-Associated lncRNAs in Cervical Squamous Cell Carcinoma and Endocervical Adenocarcinoma

Cervical cancer is the fourth most common cancer. The 5-year survival rate for metastatic cervical cancer is less than 10%. The survival time of patients with recurrent cervical cancer is approximately 13-17 months. Cuproptosis is a novel type of cell death related to mitochondrial respiration. Accumulative studies showed that long non-coding RNAs (lncRNAs) regulated cervical cancer progression. Compressive bioinformatic analysis showed that nine cuproptosis-related lncRNAs (CRLs), including C002128.2, AC002563.1, AC009237.14, AC048337.1, AC145423.1, AL117336.1, AP001542.3, ATP2A1-AS1, and LINC00426, were independently correlated with the overall survival (OS) of cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC) patients. The time-dependent area under curve value reached 0.716 at 1 year, 0.718 at 3 years, and 0.719 at 5 years. Notably, CESC patients in the low-risk group had increased immune cell infiltration and expression of several immune checkpoints, which indicated that they may benefit more from immune checkpoint blockade therapy. In addition, we also used the model for drug sensitivity analysis. Several drug sensitivities were more sensitive in high-risk patients and showed significant correlations with the risk models, such as Bortezomib_1191, Luminespib_1559, and Rapamycin_1084, suggesting that these drugs may be candidate clinical drugs for patients with a high risk of CESC. In summary, this study further explored the mechanism of CRLs in CESC and provided a more optimized prognostic model and some insights into chemotherapy of CESC.

A review on the role of LINC00472 in malignant and non-malignant disorders

Long intergenic non-protein coding RNA 472 (LINC00472) has been shown to regulate diverse cellular functions and contribute to the etiology of human disorders. LINC00472 gene is located on 6q13 and has different alternatively spliced transcripts. Expression pattern and function of LINC00472 have been evaluated in different types of cancers and some other disorders, including atherosclerosis, sepsis-induced acute hepatic injury, atrial fibrillation, neuropathic pain, primary biliary cholangitis and sepsis-induced cardiac dysfunction. This lincRNA can serve as a sponge for miR-24-3p, miR-196b-5p, miR-23a-3p, miR-93-5p, miR-4311, miR-455-3p and a number of other miRNAs. LINC00472 is able to regulate several pathways, including MEK/ERK, NF-kB, PTEN/PI3K/AKT, and STAT3 signaling pathways. This raises some concerning aspects that need to be investigated further and clarified in relation to diseases. Increasing our understanding of LINC00472's crucial roles will open new doors for creating effective therapeutic approaches against cancer and related diseases. The current study aims at providing an overview of functions of LINC00472 in malignant and non-malignant disorders.

LINC00426 is a potential immune phenotype-related biomarker and an overall survival predictor in PAM50 luminal B breast cancer

Background: Breast cancer (BRCA) represents the most frequent diagnosed malignancy in women worldwide. Despite treatment advances, BRCAs eventually develop resistance to targeted therapies, resulting in poor prognosis. The identification of new biomarkers, like immune-related long non-coding RNAs (lncRNAs), could contribute to the clinical management of BRCA patients. In this report, we evaluated the LINC00426 expression in PAM50 BRCA subtypes from two clinical independent cohorts (BRCA-TCGA and GEO-GSE96058 datasets). Methods and results: Using Cox regression models and Kaplan-Meier survival analyses, we identified that LINC00426 expression was a consistent overall survival (OS) predictor in luminal B (LB) BRCA patients. Subsequently, differential gene expression and gene set enrichment analyses identified that LINC00426 expression was associated with different immune-related and cancer-related pathways and processes in LB BRCA. Additionally, the LINC00426 expression was correlated with the infiltration level of diverse immune cell populations, alongside immune checkpoint and cytolytic activity-related gene expression. Conclusion: This evidence suggests that LINC00426 is a potential biomarker of immune phenotype and an OS predictor in PAM50 LB BRCA.

Accurate prognostic prediction for patients with clear cell renal cell carcinoma using a ferroptosis-related long non-coding RNA risk model

INTRODUCTION

Ferroptosis is a recently discovered type of programmed cell death that plays a crucial role in tumor occurrence and progression. However, no prognostic model has been established yet for clear cell renal cell carcinoma (ccRCC) using ferroptosis-related long non-coding RNAs (lncRNAs).

METHODS

In the present study, lncRNA expression profiles, sex, age, TMN stage, and other clinical data of ccRCC samples were extracted from The Cancer Genome Atlas database. In addition, ferroptosis-related lncRNAs were identified using co-expression analysis, and the risk model was established using Cox regression and least absolute shrinkage and selection operator regression analyses. Log-rank test and Kaplan-Meier analysis were performed to evaluate the predictive accuracy of the risk model for the overall survival (OS) of patients with ccRCC. Moreover, the functional enrichment of ferroptosis-related lncRNAs was performed and visualized using Gene Ontology and Kyoto Encyclopedia of Genes and Genomes.

RESULTS

Eight prognostic ferroptosis-related lncRNAs were identified, such as LINC01615, AC026401.3, LINC00944, AL590094.1, DLGAP1-AS2, AC016773.1, AC147651.1, and AP000439.2, making up the ferroptosis-related lncRNA risk model. The risk model effectively divided patients with ccRCC into high- and low-risk groups, and their survival time was calculated. The high-risk group showed significantly shorter OS compared to the low-risk group. The nomogram to predict the survival rate of the patients revealed that the risk score was the most critical factor affecting OS in patients with ccRCC. The ferroptosis-related lncRNA risk model was an independent predictor of prognostic risk assessment in patients with ccRCC.

CONCLUSION

The ferroptosis-related lncRNAs risk model and genomic clinicopathological nomogram have the potential to accurately predict the prognosis of patients with ccRCC and could serve as potential therapeutic targets in the future.

A prognostic cuproptosis-related lncRNA predictive signature for bladder cancer patients

Cuproptosis is a novel form of cell death in tumours. However, the clinical impact and mechanism of cuproptosis in bladder cancer (BC) remain unclear. This study aimed to explore the functions of long noncoding RNAs (lncRNAs) related to cuproptosis in BC and develop a prognostic predictive model. RNA sequencing and clinicopathological data were derived from The Cancer Genome Atlas and randomly divided into training and validation groups. Cuproptosis-related lncRNAs were identified by Cox regression analysis and least absolute shrinkage and selection operator, and the patients were divided into high- and low-risk groups according to the median value of the signature-based risk score. We established a signature of 17 cuproptosis-associated lncRNAs in the training set. In both sets, patients with higher signature-based risk scores had a notably higher probability of death (P ≤ 0.001) and a shorter survival duration. Cox regression analyses confirmed the risk score as an independent predictor of BC prognosis in the entire set. The area under the curve (AUC) values for 1-, 3-, and 5-year survival were 0.767, 0.734, and 0.764, respectively, confirming that the signature could determine the prognosis of BC. A signature-based nomogram was developed, and its prediction accuracy was validated using calibration curves. Several drugs, including Gemcitabine, Oxaliplatin, Mitoxantrone, Camptothecin, Cytarabine and Irinotecan may benefit low-risk BC patients more. Finally, in vitro experiments confirmed that the cuproptosis-related lncRNAs are highly expressed in bladder cancer cells after cuproptosis induced by exogenous copper ions. In conclusion, a cuproptosis-related lncRNA signature independently predicted prognosis in BC, indicating a possible mechanism and clinical treatment approach.

Prediction of Potential Biomarkers in Early-Stage Nasopharyngeal Carcinoma Based on Platelet RNA Sequencing

Early diagnosis is essential for the treatment and prevention of nasopharyngeal cancer. However, there is a lack of effective biological indicators for nasopharyngeal carcinoma (NPC). Therefore, we explored the potential biomarkers in tumour-educated blood platelet (TEP) RNA in early NPC. Platelets were isolated from blood plasma and their RNA was extracted. High-throughput sequenced data from a total of 33 plasma samples were analysed using DESeq2 to identify the differentially expressed genes (DEGs). Subsequently, the DEGs were subjected to principal component analysis (PCA), gene ontology (GO) analysis, and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis; and Cytoscape, TargetScan, and miRanda software were used for inferring the competing endogenous RNA network. We identified 19 long non-coding (lnc) RNAs (DElncRNAs) and 248 mRNAs (DEmRNAs) that were differentially expressed in the TEP RNA. In addition, SELP gene mRNA and lncRNAs AC092135.3, AC012358.2, AL021807.1, AP001972.5, and GPX1 were found to be down-regulated DEmRNA and DElncRNAs in the early stage of NPC. Bioinformatic analysis showed that these DEmRNAs and DElncRNAs may be involved in regulating the pathogenesis of NPC. Our research may provide new insights for exploring the biological mechanisms of NPC and early diagnosis using potential biomarkers.

Construction of cuproptosis-related lncRNAs/mRNAs model and prognostic prediction of hepatocellular carcinoma

Cuproptosis is a recently reported novel form of cell death, which is involved in the regulation of tumor progression. However, the specific role of cuproprosis in hepatocellular carcinoma (HCC) development remains unclear. In this study, we comprehensively analyzed the effect of cuproprosis-related lncRNAs/mRNAs on the prognosis of HCC patients based on the RNA-Seq transcriptome data and clinical data. We identified 6 cuproprosis-related signatures by Cox and Lasso regression analysis, including 3 mRNAs (FBXO30, RNF2, MPDZ) and 3 lncRNAs (PICSAR, LINC00426, AL590705.3). In addition, we constructed a prognostic prediction model for HCC. Risk analysis, RT-qPCR, and Kaplan-Meier analysis showed that the expression of FBXO30, RNF2, AL590705.3 and PICSAR was elevated in HCC, while the expression of MPDZ and LINC00426 was suppressed which was associated with better overall survival. Furthermore, immune response analysis suggested that HCC with high-risk score might respond favorably to immunotherapy. Moreover, the potential drugs that HCC might be sensitive to were screened by drug sensitivity profiling analysis. Taken together, our findings provided important information for the prediction of the prognosis of HCC patients and the development of personalized targeted therapy.

Functional deficiency of succinate dehydrogenase promotes tumorigenesis and development of clear cell renal cell carcinoma through weakening of ferroptosis

Clear cell renal cell carcinoma (ccRCC) is the most common subtype of renal carcinomas, with high mortality and poor prognoses worldwide. Succinate dehydrogenase (SDH) consists of four nuclear-encoded subunits and it is the only complex involved in both the tricarboxylic acid (TCA) cycle and oxidative phosphorylation (OXPHOS). Previous studies have shown decreased SDH activity in ccRCC. However, the role and underlying molecular mechanisms of SDH in ccRCC initiation and development remain unclear. In the present study, pan-cancer analysis of SDH gene expression was analyzed and the relationship between SDH gene expression and clinicopathological parameters was assessed using different databases. cBioPortal, UACLAN, and Tumor Immune Estimation Resource (TIMER) were subsequently utilized to analyze genetic alterations, methylation, and immune cell infiltration of SDH genes in ccRCC patients. We found SDHs were significantly downregulated in ccRCC tissues and correlated with ccRCC progression. Increased methylation and high SDH promoter mutation rates may be the cause of reduced expression of SDHs in ccRCC. Moreover, the interaction network showed that SDH genes were correlated with ferroptosis-related genes. We further demonstrated that SDH inhibition dampened oxidative phosphorylation, reduced ferroptotic events, and restored ferroptotic cell death, characterized by eliminated mitochondrial ROS levels, decreased cellular ROS and diminished peroxide accumulation. Collectively, this study provides new insights into the regulatory role of SDH in the carcinogenesis and progression of ccRCC, introducing a potential target for advanced antitumor therapy through ferroptosis.

Human circular RNA hsa_circRNA_101705 (circTXNDC11) regulates renal cancer progression by regulating MAPK/ERK pathway

Circular RNAs (circRNAs) play essential roles in the progression of human tumors, including renal cell carcinoma (RCC). The present study aimed to explore the functions and potential mechanisms of human circular RNA hsa_circRNA_101705 (circTXNDC11) in RCC. Quantitative real-time polymerase chain reaction (qRT-PCR) was applied to measure circTXNDC11 expression in RCC tissues and cell lines. RNase R and actinomycin D assays were conducted to analyze the characteristic of circTXNDC11. Cell Counting Kit-8 (CCK-8) assay, colony formation assay, and transwell invasion assay were performed to assess cell proliferation and invasion abilities. Western blotting was applied to assess the levels of MEK and ERK proteins in RCC cells. Murine xenograft model assay was conducted to deduce the role of circTXNDC11 in vivo. The current data showed that circTXNDC11 was overexpressed in RCC tissues and cells. The overexpression of circTXNDC11 is linked to advanced TNM stage and lymph node metastasis of renal cancer. Knocking down circTXNDC11 suppressed cell proliferation and invasion in vitro and reduced tumor growth in vivo. Mechanistically, circTXNDC11 promoted RCC growth and invasion by activating the MAPK/ERK pathway. Thus, the current findings identified circTXNDC11 as a novel regulator of RCC tumorigenesis through the regulation of the MAPK/ERK pathway, offering a potential therapeutic target for RCC treatment.

Constructing a new prognostic signature of gastric cancer based on multiple data sets

In order to explore new prediction methods and key genes for gastric cancer. Firstly, we downloaded the 6 original sequencing data of gastric cancer on the Illumina HumanHT-12 platform from Array Expression and Gene Expression Omnibus, and used bioinformatics methods to identify 109 up-regulated genes and 271 down-regulated genes. Further, we performed univariate Cox regression analysis of prognostic-related genes, then used Lasso regression to remove collinearity, and finally used multivariate Cox regression to analyze independent prognostic genes (MT1M, AKR1C2, HEYL, KLK11, EEF1A2, MMP7, THBS1, KRT17, RPESP, CMTM4, UGT2B17, CGNL1, TNFRSF17, REG1A). Based on these, we constructed a prognostic risk proportion signature, and found that patients with high-risk gastric cancer have a high degree of malignancy. Subsequently, we used the GSE15459 data set to verify the signature. By calculating the area under the recipient operator characteristic curve of 5-year survival rate, the test set and verification set are 0.739 and 0.681, respectively, suggesting that the prognostic signature has a moderate prognostic ability. The nomogram is used to visualize the prognostic sig-nature, and the calibration curve verification showed that the prediction accuracy is higher. Finally, we verified the expression and prognosis of the hub gene, and suggested that HEYL, MMP7, THBS1, and KRT17 may be potential prognostic biomarkers.

Characterization of Molecular Heterogeneity Associated With Tumor Microenvironment in Clear Cell Renal Cell Carcinoma to Aid Immunotherapy

Clear cell renal cell carcinoma (ccRCC) is the most common type of kidney cancer and has strong immunogenicity. A systematically investigation of the tumor microenvironment (TME) in ccRCC could contribute to help clinicians develop personalized treatment and facilitate clinical decision-making. In this study, we analyzed the immune-related subtype of ccRCC on the basis of immune-related gene expression data in The Cancer Genome Atlas (TCGA, N = 512) and E-MTAB-1980 (N = 101) dataset, respectively. As a result, two subtypes (C1 and C2) were identified by performing non-negative matrix factorization clustering. Subtype C1 was characterized by increased advance ccRCC cases and immune-related pathways. A higher immune score, stromal score, TMB value, Tumor Immune Dysfunction and Exclusion (TIDE) prediction score, and immune checkpoint genes expression level were also observed in C1. In addition, the C1 subtype might benefit from chemotherapy and immunotherapy. The patients in subtype C2 had more metabolism-related pathways, higher tumor purity, and a better prognosis. Moreover, some small molecular compounds for the treatment of ccRCC were identified between the two subtypes by using the Connectivity Map (CMap) database. Finally, we constructed and validated an immune-related (IR) score to evaluate immune modification individually. A high IR score corresponded to a favorable prognosis compared to a low IR score, while more advanced tumor stage and grade cases were enriched in the low IR score group. The two IR score groups also showed a distinct divergence among immune status, TME, and chemotherapy. The external validation dataset (E-MTAB-1980) and another immunotherapy cohort (IMvigor 210) demonstrated that patients in the high IR score group had a significantly prolonged survival time and clinical benefits compared to the low IR score group. Together, characterization of molecular heterogeneity and IR signature may help develop new insights into the TME of ccRCC and provide new strategies for personalized treatment.