Development of a novel six-long noncoding RNA signature predicting survival of patients with bladder urothelial carcinoma

Integration analysis of cis- and trans-regulatory long non-coding RNAs associated with immune-related pathways in non-small cell lung cancer

Background

Long non-coding RNAs (lncRNAs) are importantly involved in the initiation and progression of non-small cell lung cancer (NSCLC). However, the classification and mechanisms of lncRNAs remain largely elusive.

Aim

Hence, we addressed this through bioinformatics analysis.

Methods and results

We utilized microarray technology to analyze lncRNAs and mRNAs in twenty paired NSCLC tumor tissues and adjacent normal tissues. Gene set enrichment analysis, Kyoto Encyclopedia of Genes and Genomes, and Gene Ontology were conducted to discern the biological functions of identified differentially expressed transcripts. Additionally, networks of lncRNA-mRNA co-expression, including cis-regulation, lncRNA-transcription factor (TF)-mRNA, trans-regulation, and lncRNA-miRNA-mRNA interactions were explored. Furthermore, the study examined differentially expressed transcripts and their prognostic values in a large RNA-seq dataset of 1016 NSCLC tumors and normal tissues extracted from the Cancer Genome Atlas (TCGA). The analysis revealed 391 lncRNAs and 344 mRNAs with differential expression in NSCLC tumor tissues compared to adjacent normal tissues. Subsequently, 43,557 co-expressed lncRNA-mRNA pairs were identified, including 27 lncRNA-mRNA pairs in cis, 9 lncRNA-TF-mRNA networks, 34 lncRNA-mRNA pairs in trans, and 8701 lncRNA-miRNA-mRNA competing endogenous RNA (ceRNA) networks. Notably, these lncRNAs were found to be involved in immune-related pathways. Six significant transcripts, including NTF4, PTPRD-AS, ITGA11, HID1-AS1, RASGRF2-AS1, and TBX2-AS1, were identified within the ceRNA network and trans-regulation.

Conclusion

This study brings important insights into the regulatory roles of lncRNAs in NSCLC, providing a fresh perspective on lncRNA research in tumor biology.

Identification of telomere-related lncRNAs and immunological analysis in ovarian cancer

Background

Ovarian cancer (OC) is a global malignancy characterized by metastatic invasiveness and recurrence. Long non-coding RNAs (lncRNAs) and Telomeres are closely connected with several cancers, but their potential as practical prognostic markers in OC is less well-defined.

Methods

Relevant mRNA and clinical data for OC were sourced from The Cancer Genome Atlas (TCGA) database. The telomere-related lncRNAs (TRLs) prognostic model was established by univariate/LASSO/multivariate regression analyses. The effectiveness of the TRLs model was evaluated and measured via the nomogram. Additionally, immune infiltration, tumor mutational load (TMB), and drug sensitivity were evaluated. We validated the expression levels of prognostic genes. Subsequently, PTPRD-AS1 knockdown was utilized to perform the CCK8 assay, colony formation assay, transwell assay, and wound healing assay of CAOV3 cells.

Results

A six-TRLs prognostic model (PTPRD-AS1, SPAG5-AS1, CHRM3-AS2, AC074286.1, FAM27E3, and AC018647.3) was established, which can effectively predict patient survival rates and was successfully validated using external datasets. According to the nomogram, the model could effectively predict prognosis. Furthermore, we detected the levels of regulatory T cells and M2 macrophages were comparatively higher in the high-risk TRLs group, but the levels of activated CD8 T cells and monocytes were the opposite. Finally, the low-risk group was more sensitive to anti-cancer drugs. The mRNA levels of PTPRD-AS1, SPAG5-AS1, FAM27E3, and AC018647.3 were significantly over-expressed in OC cell lines (SKOV3, A2780, CAOV3) in comparison to normal IOSE-80 cells. AC074286.1 were over-expressed in A2780 and CAOV3 cells and CHRM3-AS2 only in A2780 cells. PTPRD-AS1 knockdown decreased the proliferation, cloning, and migration of CAOV3 cells.

Conclusion

Our study identified potential biomarkers for the six-TRLs model related to the prognosis of OC.

A pancancer analysis of the oncogenic role of cyclin B1 (CCNB1) in human tumors

Aberrant levels of the G2/M cyclin cyclin B1 (gene CCNB1) have been associated with multiple cancers; however, the literature lacks a focused and comprehensive analysis of the regulation of this important regulator of cell proliferation in cancer. Through this work, we performed a pancancer analysis of the levels of CCNB1 and dissected aspects of regulation and how this correlates with cancer prognosis. We comprehensively evaluated the expression and promoter methylation of CCNB1 across 38 cancers based on RNA sequencing data obtained from the Cancer Genome Atlas (TCGA). The correlation of CCNB1 with prognosis and the tumor microenvironment was explored. Using lung adenocarcinoma data, we studied the potential upstream noncoding RNAs involved in the regulation of CCNB1 and validated the protein levels and prognostic value of CCNB1 for this disease site. CCNB1 was highly expressed, and promoter methylation was reduced in most cancers. Gene expression of CCNB1 correlated positively with poor prognosis of tumor patients, and these results were confirmed at the protein level using lung adenocarcinoma. CCNB1 expression was associated with the infiltration of T helper cells, and this further correlated with poor prognosis for certain cancers, including renal clear cell carcinoma and lung adenocarcinoma. Subsequently, we identified a specific upstream noncoding RNA contributing to CCNB1 overexpression in lung adenocarcinoma through correlation analysis, expression analysis and survival analysis. This study provides a comprehensive analysis of the expression and methylation status of CCNB1 across several forms of cancer and provides further insight into the mechanistic pathways regulating Cyclin B1 in the tumorigenesis process.

A novel cuproptosis-related lncRNAs signature predicts prognostic and immune of bladder urothelial carcinoma

Bladder Urothelial Carcinoma (BLCA) remains the most common urinary system tumor, and its prognosis is poor. Cuproptosis is a recently discovered novel cell death involved in the development of tumor cells. However, the use of cuproptosis to predict the prognosis and immunity of Bladder Urothelial Carcinoma remains largely unclear, and this study was designed to verify cuproptosis-related long non-coding RNAs (lncRNAs) to estimate the prognosis and immunity of Bladder Urothelial Carcinoma. In our study, we first defined the expression of cuproptosis-related genes (CRGs) in BLCA, and 10 CRGs were up- or downregulated. We then constructed a co-expression network of cuproptosis-related mRNA and long non-coding RNAs using RNA sequence data from The Cancer Genome Atlas Bladder Urothelial Carcinoma (TCGA-BLCA), clinical features and mutation data from BLCA patients to obtain long non-coding RNAs by Pearson analysis. Afterward, univariate and multivariate COX analysis identified 21 long non-coding RNAs as independent prognostic factors and used these long non-coding RNAs to construct a prognostic model. Then, survival analysis, principal component analysis (PCA), immunoassay, and comparison of tumor mutation frequencies were performed to verify the accuracy of the constructed model, and GO and KEGG functional enrichment analysis was used to verify further whether cuproptosis-related long non-coding RNAs were associated with biological pathways. The results showed that the model constructed with cuproptosis-related long non-coding RNAs could effectively evaluate the prognosis of BLCA, and these long non-coding RNAs were involved in numerous biological pathways. Finally, we performed immune infiltration, immune checkpoint and drug sensitivity analyses on four genes (TTN, ARID1A, KDM6A, RB1) that were highly mutated in the high-risk group to evaluate the immune association of risk genes with BLCA. In conclusion, the cuproptosis-related lncRNA markers constructed in this study have evaluation value for prognosis and immunity in BLCA, which can provide a certain reference for the treatment and immunity of BLCA.

LINC01468 drives NAFLD-HCC progression through CUL4A-linked degradation of SHIP2

Accumulating evidence suggests that long noncoding RNAs (lncRNAs) are deregulated in hepatocellular carcinoma (HCC) and play a role in the pathogenesis of non-alcoholic fatty liver disease (NAFLD). However, the current understanding of the role of lncRNAs in NAFLD-associated HCC is limited. In this study, transcriptomic profiling analysis of three paired human liver samples from patients with NAFLD-driven HCC and adjacent samples showed that LINC01468 expression was significantly upregulated. In vitro and in vivo gain- and loss-of-function experiments showed that LINC01468 promotes the proliferation of HCC cells through lipogenesis. Mechanistically, LINC01468 binds SHIP2 and promotes cullin 4 A (CUL4A)-linked ubiquitin degradation, thereby activating the PI3K/AKT/mTOR signaling pathway, resulting in the promotion of de novo lipid biosynthesis and HCC progression. Importantly, the SHIP2 inhibitor reversed the sorafenib resistance induced by LINC01468 overexpression. Moreover, ALKBH5-mediated N6-methyladenosine (m6A) modification led to stabilization and upregulation of LINC01468 RNA. Taken together, the findings indicated a novel mechanism by which LINC01468-mediated lipogenesis promotes HCC progression through CUL4A-linked degradation of SHIP2. LINC01468 acts as a driver of HCC progression from NAFLD, highlights the potential of the LINC01468-SHIP2 axis as a therapeutic target for HCC.

Emerging role of lncRNAs in drug resistance mechanisms in head and neck squamous cell carcinoma

Head and neck squamous cell carcinoma (HNSCC) originates in the squamous cell lining the mucosal surfaces of the head and neck region, including the oral cavity, nasopharynx, tonsils, oropharynx, larynx, and hypopharynx. The heterogeneity, anatomical, and functional characteristics of the patient make the HNSCC a complex and difficult-to-treat disease, leading to a poor survival rate and a decreased quality of life due to the loss of important physiologic functions and aggressive surgical injury. Alteration of driver-oncogenic and tumor-suppressing lncRNAs has recently been recently in HNSCC to obtain possible biomarkers for diagnostic, prognostic, and therapeutic approaches. This review provides current knowledge about the implication of lncRNAs in drug resistance mechanisms in HNSCC. Chemotherapy resistance is a major therapeutic challenge in HNSCC in which lncRNAs are implicated. Lately, it has been shown that lncRNAs involved in autophagy induced by chemotherapy and epithelial-mesenchymal transition (EMT) can act as mechanisms of resistance to anticancer drugs. Conversely, lncRNAs involved in mesenchymal-epithelial transition (MET) are related to chemosensitivity and inhibition of invasiveness of drug-resistant cells. In this regard, long non-coding RNAs (lncRNAs) play a pivotal role in both processes and are important for cancer detection, progression, diagnosis, therapy response, and prognostic values. As the involvement of more lncRNAs is elucidated in chemoresistance mechanisms, an improvement in diagnostic and prognostic tools could promote an advance in targeted and specific therapies in precision oncology.

Genome-wide Exploration of a Pyroptosis-Related Long Non-Coding RNA Signature Associated With the Prognosis and Immune Response in Patients With Bladder Cancer

Background: Bladder cancer (BLCA) is a malignant tumor with a complex molecular mechanism and high recurrence rate in the urinary system. Studies have shown that pyroptosis regulates tumor cell proliferation and metastasis and affects the prognosis of cancer patients. However, the role of pyroptosis-related (PR) genes or long non-coding RNAs (lncRNAs) in BLCA development is not fully understood.

Methods: We comprehensively analyzed the molecular biological characteristics of PR genes in BLCA, including copy number variation, mutations, expression and prognostic value based on TCGA database. We then identified PR lncRNAs with prognostic value based on the expression of PR genes and performed a consistent clustering analysis of 407 BLCA patients according to the expression of prognosis-related PR lncRNAs and identified two clusters. The least absolute shrinkage and selection operator (LASSO) regression was used to establish a PR lncRNA signature and calculate the risk score associated with the prognosis of patients with BLCA. Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Set Enrichment Analysis (GSEA) were used to evaluate the possible functions of PR lncRNA signature. We also evaluated the relationship between the risk score and tumor immune microenvironment (TIME).

Results: A total of 33 PR genes were obtained in our study and 194 prognosis-related PR lncRNAs were identified. We also constructed a signature consisting of eight-PR-lncRNAs and divided patients into high- and low-risk groups. The overall survival rate of patients with a high risk was significantly lower than patients with a low risk. The risk score was significantly correlated with the degree of infiltration of multiple immune cell subtypes and positively correlated with multiple immune checkpoint genes expression in BLCA. Enrichment analyses showed that these lncRNAs are involved in human immune regulatory functions and immune-related pathways.

Conclusion: Our study comprehensively studied the molecular biological characteristics of PR genes BLCA, and the eight-PR-lncRNA signature we identified might play a crucial role in tumor immunity and may be able to predict the prognosis of BLCA patients, providing a theoretical basis for an in-depth study of the relationship between the prognosis and TIME.

Analysis of lncRNA sequences: FAM3D-AS1, LINC01230, LINC01315 and LINC01468 in endometrial cancer

Background

The analysis of long non-coding RNA (lncRNA) in endometrial cancer is a novel field of science. Although numerous lncRNA sequences have been identified until today, their correlation with endometrial cancer is still undetermined. The aim of this study was to analyze the expression of four lncRNA sequences: FAM3D-AS1, LINC01230, LINC01315 and LINC01468 and to investigate their significance in endometrial cancer.

Methods

LncRNA sequences were investigated in paraffin blocks (tumor tissue and non-malignant endometrial tissue in archival postoperative specimens) in endometrial cancer patients (Cases, n = 120) and in cancer-free controls (n = 80) using real-time PCR assay.

Results

This study revealed a lower expression of LINC01468 in endometrial cancer patients than in controls. Both LINC01468 and FAM3D-AS1 were positively correlated with Body Mass Index (BMI) in cancer-free controls.

Conclusions

LncRNA LINC01468 may be a protective factor in development of endometrial cancer.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-022-09426-2.

Identifying a Novel Defined Pyroptosis-Associated Long Noncoding RNA Signature Contributes to Predicting Prognosis and Tumor Microenvironment of Bladder Cancer

Background

Bladder cancer (BLCA) is a common malignant tumor of the urinary tract, which is the sixth most common cancer among men. Numerous studies suggested that pyroptosis and long noncoding RNAs (lncRNAs) played an essential role in the development of cancers. However, the role of pyroptosis-related lncRNAs in BLCA and their prognostic value are still unclear.

Methods

In this study, we constructed a signature model through least absolute shrinkage and selection operator (LASSO) Cox regression analysis and Cox univariate analysis based on The Cancer Genome Atlas (TCGA) database. The expression of 12 pyroptosis-related lncRNAs was also confirmed by qRT-PCR in BLCA cell lines. TIMER, XCELL, QUANTISEQ, MCPCOUNTER, EPIC, and CIBERSORT R script were applied to quantify the relative proportions of infiltrating immune cells. Correlation coefficients were computed by Spearman analyses. The Kaplan–Meier method, Cox regression model, and log-rank tests were used to evaluate the prognostic value. The R package of pRRophetic was used to predict IC50 of common chemotherapeutic agents.

Results

A total of 12 pyroptosis-related lncRNAs with great prognosis value were identified. The expression was investigated by qRT-PCR in four BLCA cell lines. Then, 126 cases were identified as high-risk group, and 277 cases were identified as low-risk group based on the cutoff point. Patients in the low-risk group showed a significant survival advantage. Furthermore, we found that clinical features were significantly related to the risk score. As well, based on the C-index values, a nomogram was constructed. The gene set enrichment analysis (GSEA) results showed that mitogen-activated protein kinase (MAPK) signaling, transforming growth factor (TGF)-β signaling, and WNT signaling were with important significance in the high-risk group. Moreover, we found that riskscore was positively correlated with M0 macrophages and M2 macrophages.

Conclusions

In conclusion, our study indicated that pyroptosis is closely connected to BLCA. The riskscore generated from the expression of 12 pyroptosis-related lncRNAs was evaluated by various clinical features including survival status, tumor microenvironment, clinicopathological characteristic, and chemotherapy. It may offer a significant basis for future studies.

Multi-Omics analysis identifies a lncRNA-related prognostic signature to predict bladder cancer recurrence

Bladder cancer (BLCA) is one of the most common cancers worldwide with high recurrence rate. Hence, we intended to establish a recurrence-related long non-coding RNA (lncRNA) model of BLCA as a potential biomarker based on multi-omics analysis. Multi-omics data including copy number variation (CNV) data, mutation annotation files, RNA expression profiles and clinical data of The Cancer Genome Atlas (TCGA) BLCA cohort (303 cases) and GSE31684 (93 cases) were downloaded from public database. With multi-omics analysis, twenty lncRNAs were identified as the candidates related with BLCA recurrence, CNVs and mutations in training set. Ten-lncRNA signature were established using least absolute shrinkage and selection operation (LASSO) and Cox regression. Then, various survival analysis was used to assess the power of lncRNA model in predicting BLCA recurrence. The results showed that the recurrence-free survival time of high-risk group was significantly shorter than that of low-risk group in training and testing sets, and the predictive value of ten-lncRNA signature was robust and independent of other clinical variables. Gene Set Enrichment Analysis (GSEA) showed this signature were associated with immune disorders, indicating this signature may be involved in tumor immunology. After compared with the other reported lncRNA signatures, ten-lncRNA signature was validated as a superior prognostic model in predicting the recurrence of BLCA. The effectiveness of the model was also evaluated in bladder cancer samples via qRT-PCR. Thus, the novel ten-lncRNA signature, constructed based on multi-omics data, had robust prognostic power in predicting the recurrence of BLCA and potential clinical implications as biomarkers.

Identification of DNA methylation biomarkers for risk of liver metastasis in early-stage colorectal cancer

Background

Liver metastases can occur even in CRC patients who underwent curative surgery. While evidence suggested that adjuvant chemotherapy can help to reduce the occurrence of liver metastases for certain patients, it is not a recommended routine as the side effects outweigh the potential benefits, especially in Stage II CRC patients. This study aims to construct a model for predicting liver metastasis risk using differential methylation signals in primary CRC tumors, which can facilitate the decision for adjuvant chemotherapy.

Methods

Fifty-nine stage I/II and IV CRC patients were enrolled. Primary tumor, adjacent normal tissue, and metastatic tumor tissues were subject to targeted bisulfite sequencing for DNA methylation. The Least Absolute Shrinkage and Selection Operator (LASSO) algorithm was used to identify potential DMRs for predicting liver metastasis of CRC.

Results

We identified a total of 241,573 DMRs by comparing the DNA methylation profile of primary tumors of stage II patients who developed metastasis to those who were metastasis-free during the follow up period. 213 DMRs were associated with poor prognosis, among which 182 DMRS were found to be hypermethylated in the primary tumor of patients with metastases. Furthermore, by using the LASSO regression model, we identified 23 DMRs that contributed to a high probability of liver metastasis of CRC. The leave-one-out cross validation (LOOCV) was used to evaluate model predictive performance at an AUC of 0.701. In particular, 7 out of those 23 DMRs were found to be in the promoter region of genes that were previously reported prognostic biomarkers in diverse tumor types, including TNNI2, PAX8, GUF1, KLF4, EVI2B, CEP112, and long non-coding RNA AC011298. In addition, the model was also able to distinguish metastases of different sites (liver or lung) at an AUC of 0.933.

Conclusion

We have identified DNA methylation biomarkers associated with the risk of cancer liver metastasis in early-stage CRC patients. A risk prediction model based on those epigenetic markers was proposed for outcome assessment.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13148-021-01108-3.

Identification of a Genome Instability-Associated LncRNA Signature for Prognosis Prediction in Colon Cancer

Long non-coding RNAs (lncRNAs) were reported to have the potential in maintaining genome instability, but the identification of lncRNAs related to genome instability and their prognostic value have not been largely explored in colon cancer. In this study, we obtained 155 genome instability-associated lncRNAs based on somatic mutation profiles in colon cancer from The Cancer Genome Atlas (TCGA) database. Functional enrichment analysis revealed the possible roles of genes co-expressed with those lncRNAs involved in some cancer, genome instability and immune related biological processes. Combined with overall survival data, a seven-lncRNA signature was established for prognosis prediction. According to the risk score calculated by this signature, high-risk patients characterized by high somatic mutation count, high microsatellite instability, significantly poorer clinical outcomes and specific tumor immune infiltration status compared with low-risk patients. The lncRNA signature was validated to be an independent prognostic indicator with good predictive performance in TCGA cohort. Furthermore, the prognostic value of the ZNF503-AS1 in lncRNA signature was confirmed in another independent dataset from Gene Expression Omnibus database. In summary, the genome instability-associated lncRNA signature in this study could be a promising tool for effectively predicting survival outcomes in colon cancer.

Aberrant methylation modifications reflect specific drug responses in small cell lung cancer

In the study, Methylated DNA immunoprecipitation sequencing, RNA sequencing, and whole-exome sequencing were employed to clinical small cell lung cancer (SCLC) patients. Then, we verified the therapeutic predictive effects of differentially methylated genes (DMGs) in 62 SCLC cell lines. Of 4552 DMGs between chemo-sensitive and chemo-insensitive group, coding genes constituted the largest percentage (85.08%), followed by lncRNAs (10.52%) and miRNAs (3.56%). Both two groups demonstrated two methylation peaks near transcription start site and transcription end site. Two lncRNA-miRNA-mRNA networks suggested the extensive genome connection between chemotherapy efficacy-related non-coding RNAs (ncRNAs) and mRNAs. Combing miRNAs and lncRNAs could effectively predict chemotherapy response in SCLC. In addition, we also verified the predictive values of mutated genes in SCLC cell lines. This study was the first to evaluate multiple drugs efficacy-related ncRNAs and mRNAs which were modified by methylation in SCLC. DMGs identified in our research might serve as promising therapeutic targets to reverse drugs-insensitivity by complex lncRNA-miRNA-mRNA mechanisms in SCLC.

Identification of immune-related LncRNA for predicting prognosis and immunotherapeutic response in bladder cancer

Long noncoding RNAs (lncRNAs) have multiple functions in the cancer immunity response and the tumor microenvironment. To investigate the immune-related lncRNA (IRlncRNA) signature for predicting prognosis and immunotherapeutic response in bladder cancer (BLCA), we extracted BLCA data from The Cancer Genome Atlas (TCGA) database. Finally, a total of 405 cases were enrolled and 8 prognostic IRlncRNAs (MIR181A2HG, AC114730.3, LINC00892, PTPRD-AS1, LINC01013, MRPL23-AS1,LINC01395, AC002454.1) were identified in the training set. Risk scores were calculated to divide patients into high-risk and low-risk groups, and the high-risk patients tended to have a poor overall survival (OS). Multivariate Cox regression analysis confirmed that the IRlncRNA signature could be an independent prognostic factor. The results were subsequently confirmed in the validating set. Additionally, this 8-IRlncRNA classifier was related to recurrence free survival (RFS) of BLCA. Functional characterization revealed this signature mediated immune-related phenotype. This signature was also associated with immune cell infiltration (i.e., macrophages M0, M2, Tregs, CD8 T cells, and neutrophils) and immune checkpoint inhibitors (ICIs) immunotherapy-related biomarkers [mismatch repair (MMR) genes, tumor mutation burden (TMB) and immune checkpoint genes]. The present study highlighted the value of the 8-IRlncRNA signature as a predictor of prognosis and immunotherapeutic response in BLCA.

Comprehensive Analysis of LincRNAs in Classical and Basal-Like Subtypes of Pancreatic Cancer

Pancreatic ductal adenocarcinomas (PDAC) belong to the deadliest malignancies in the western world. Mutations in TP53 and KRAS genes along with some other frequent polymorphisms occur almost universally and are major drivers of tumour initiation. However, these mutations cannot explain the heterogeneity in therapeutic responses and differences in overall survival observed in PDAC patients. Thus, recent classifications of PDAC tumour samples have leveraged transcriptome-wide gene expression data to account for epigenetic, transcriptional and post-transcriptional mechanisms that may contribute to this deadly disease. Intriguingly, long intervening RNAs (lincRNAs) are a special class of long non-coding RNAs (lncRNAs) that can control gene expression programs on multiple levels thereby contributing to cancer progression. However, their subtype-specific expression and function as well as molecular interactions in PDAC are not fully understood yet. In this study, we systematically investigated the expression of lincRNAs in pancreatic cancer and its molecular subtypes using publicly available data from large-scale studies. We identified 27 deregulated lincRNAs that showed a significant different expression pattern in PDAC subtypes suggesting context-dependent roles. We further analyzed these lincRNAs regarding their common expression patterns. Moreover, we inferred clues on their functions based on correlation analyses and predicted interactions with RNA-binding proteins, microRNAs, and mRNAs. In summary, we identified several PDAC-associated lincRNAs of prognostic relevance and potential context-dependent functions and molecular interactions. Hence, our study provides a valuable resource for future investigations to decipher the role of lincRNAs in pancreatic cancer.

Identification of an immune-related long non-coding RNA signature and nomogram as prognostic target for muscle-invasive bladder cancer

To identify an immune-related prognostic signature based on long non-coding RNAs (lncRNAs) and find immunotherapeutic targets for bladder urothelial carcinoma, we downloaded RNA-sequencing data from The Cancer Genome Atlas (TCGA) dataset. Functional enrichment analysis demonstrated bladder urothelial carcinoma was related to immune-related functions. We obtained 332 immune-related genes and 262 lncRNAs targeting immune-related genes. We constructed a signature based on eight lncRNAs in training cohort. Patients were classified as high-risk and low-risk according to signature risk score. High-risk patients had poor overall survival compared with low-risk patients (P < 0.001). Multivariate Cox regression suggested the signature was an independent prognostic indicator. The findings were further validated in testing, entire TCGA and external validation cohorts. Gene set enrichment analysis indicated significant enrichment of immune-related phenotype in high-risk group. Immunohistochemistry and online analyses validated the functions of 4 key immune-related genes (LIG1, TBX1, CTSG and CXCL12) in bladder urothelial carcinoma. Nomogram proved to be a good classifier for muscle-invasive bladder cancer through combining the signature. In conclusion, our immune-related prognostic signature and nomogram provided prognostic indicators and potential immunotherapeutic targets for muscle-invasive bladder cancer.

LNCAROD is stabilized by m6A methylation and promotes cancer progression via forming a ternary complex with HSPA1A and YBX1 in head and neck squamous cell carcinoma

Head and neck squamous cell carcinoma (HNSCC) constitute approximately 4% of all cancers worldwide. In this study, we analyzed the expression profile of the long noncoding RNA (lncRNA) of 502 HNSCC patients from The Cancer Genome Atlas database. Among the differentially expressed lncRNAs between HNSCC and normal samples, LNCAROD is overexpressed in HNSCC and associated with advanced T stage and shortened overall survival. The N6‐methyladenosine (m6A) modification mediated by METTL3 and METTL14 enhanced the stability of LNCAROD in HNSCC cells. Depletion of LNCAROD attenuated cell proliferation, mobility in vitro, and tumorigenicity in vivo, whereas overexpression of LNCAROD exerted opposite effects. LNCAROD is mainly distributed in nucleus and binds with YBX1 and HSPA1A proteins. Silencing either YBX1 or HSPA1A did not affect the level of LNCAROD. However, loss of LNCAROD led to shortened half‐life of YBX1 protein. Mechanistically, LNCAROD protected YBX1 from proteasomal degradation by facilitating YBX1‐HSPA1A protein–protein interaction. Depletion of HSPA1A in LNCAROD‐overexpressing cells resulted in accelerated proteasomal degradation of YBX1 protein. Moreover, re‐expression of Flag‐YBX1 in LNCAROD‐silenced cells rescued malignant behavior of HNSCC cells. Our study indicates that LNCAROD is an oncogenic lncRNA and dysregulation of m6A modification might account for aberrant expression of LNCAROD in HNSCC. LNCAROD acts as a scaffold for the interaction between YBX1 and HSPA1A, preventing proteasomal degradation of YBX1 in HNSCC cells.

Screening of characteristic biomolecules related to bladder cancer based on construction of ceRNA regulation network

OBJECTIVES

The purpose of this study is to screen bladder cancer-associated biomarkers by combining lncRNA, miRNA, and mRNA expression profile of bladder cancer, and to explore bladder cancer-associated tumor markers by constructing a ceRNA regulation network.

METHODS

Bladder cancer mRNA and miRNA samples were downloaded from the TCGA database; the lncRNA and mRNA detected in the RNA-seq expression profile were identified using the HUGO Gene Nomenclature Committee database.

RESULTS

Screening for significant differentially expressed RNA resulted in 1693 mRNAs, 66 lncRNAs, and 130 miRNAs. Then, the significant differently expressed RNAs from the screening were subjected to annotation analysis of GO functional nodes and KEGG signaling pathways. A ceRNA regulation network consisting of lncRNA-miRNA-mRNA was constructed by synthesizing lncRNA-miRNA and miRNA-mRNA. Finally, a ceRNA regulation network consisting of two lncRNAs, one miRNA, and three mRNAs was obtained. KM remodeling curve analysis was performed for each factor.

CONCLUSIONS

In bladder cancer tumor samples, samples down-regulated by LINC01198, PPTRD-AS1, has-miR-216a, SEMA3D, EPHA5, and DCLK1 had a good overall survival prognosis, indicating that these several characteristic target molecules were found to be high-risk factors for bladder cancer tumors.

Identification and Validation of an Individualized Prognostic Signature of Bladder Cancer Based on Seven Immune Related Genes

BACKGROUND

There has been no report of prognostic signature based on immune-related genes (IRGs). This study aimed to develop an IRG-based prognostic signature that could stratify patients with bladder cancer (BLCA).

METHODS

RNA-seq data along with clinical information on BLCA were retrieved from the Cancer Genome Atlas (TCGA) and gene expression omnibus (GEO). Based on TCGA dataset, differentially expressed IRGs were identified via Wilcoxon test. Among these genes, prognostic IRGs were identified using univariate Cox regression analysis. Subsequently, we split TCGA dataset into the training (n = 284) and test datasets (n = 119). Based on the training dataset, we built a least absolute shrinkage and selection operator (LASSO) penalized Cox proportional hazards regression model with multiple prognostic IRGs. It was validated in the training dataset, test dataset, and external dataset GSE13507 (n = 165). Additionally, we accessed the six types of tumor-infiltrating immune cells from Tumor Immune Estimation Resource (TIMER) website and analyzed the difference between risk groups. Further, we constructed and validated a nomogram to tailor treatment for patients with BLCA.

RESULTS

A set of 47 prognostic IRGs was identified. LASSO regression and identified seven BLCA-specific prognostic IRGs, i.e., RBP7, PDGFRA, AHNAK, OAS1, RAC3, EDNRA, and SH3BP2. We developed an IRG-based prognostic signature that stratify BLCA patients into two subgroups with statistically different survival outcomes [hazard ratio (HR) = 10, 95% confidence interval (CI) = 5.6-19, P < 0.001]. The ROC curve analysis showed acceptable discrimination with AUCs of 0.711, 0.754, and 0.772 at 1-, 3-, and 5-year follow-up respectively. The predictive performance was validated in the train set, test set, and external dataset GSE13507. Besides, the increased infiltration of CD4+ T cells, CD8+ T cells, macrophage, neutrophil, and dendritic cells in the high-risk group (as defined by the signature) indicated chronic inflammation may reduce the survival chances of BLCA patients. The nomogram demonstrated to be clinically-relevant and effective with accurate prediction and positive net benefit.

CONCLUSION

The present immune-related signature can effectively classify BLCA patients into high-risk and low-risk groups in terms of survival rate, which may help select high-risk BLCA patients for more intensive treatment.