Identification of a prognostic long noncoding RNA signature in lung squamous cell carcinoma: a population-based study with a mean follow-up of 3.5 years

Identification of hub genes in calcific aortic valve disease

Calcific aortic valve disease (CAVD) is a heart valve disorder characterized primarily by calcification of the aortic valve, resulting in stiffness and dysfunction of the valve. CAVD is prevalent among aging populations and is linked to factors such as hypertension, dyslipidemia, tobacco use, and genetic predisposition, and can result in becoming a growing economic and health burden. Once aortic valve calcification occurs, it will inevitably progress to aortic stenosis. At present, there are no medications available that have demonstrated effectiveness in managing or delaying the progression of the disease. In this study, we mined four publicly available microarray datasets (GSE12644 GSE51472, GSE77287, GSE233819) associated with CAVD from the GEO database with the aim of identifying hub genes associated with the occurrence of CAVD and searching for possible biological targets for the early prevention and diagnosis of CAVD. This study provides preliminary evidence for therapeutic and preventive targets for CAVD and may provide a solid foundation for subsequent biological studies.

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

BACKGROUND

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

RESULTS

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

CONCLUSIONS

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

Upregulation of OTX2-AS1 is Associated With Immune Infiltration and Predicts Prognosis of Gastric Cancer

BACKGROUND

It is unclear whether the long non-coding RNA (lncRNA) OTX2 antisense RNA 1 (OTX2-AS1) plays a pivotal role in gastric cancer (GC). An analysis of The Cancer Genome Atlas (TCGA) database data and bioinformatics was used to explore the relationship between OTX2-AS1 and GC in the current study.

METHODS

We evaluated the relationship between clinical features and OTX2-AS1 expression, prognostic factors, and the significant involvement of OTX2-AS1 in function using various statistical methods, such as Kaplan-Meier method, Cox regression analysis, Gene Set Enrichment Analysis (GSEA), and immune infiltration analysis. GC cell lines were tested for OTX2-AS1 expression using qRT-PCR.

RESULTS

A high level of OTX2-AS1 expression was significantly and negatively associated with Helicobacter pylori (H pylori) infection in GC patients (P = .006) and predicted a poorer overall survival (OS) (HR: 1.54; 95% CI: 1.10-2.14; P = .011), progression-free interval (PFI) (HR: 1.75; 95% CI: 1.22-2.51; P = .002) and disease-specific survival (DSS) (HR: 1.85; 95% CI: 1.21-2.85; P = .005) in GC patients. There was an independent correlation between OTX2-AS1 expression (HR: 1.771; 95% CI: 1.164-2.696; P = .008) and OS in patients with GC. There were differential enrichments for the OTX2-AS1 high expression phenotype in the olfactory transduction, G alpha (s) signaling events, keratinization, olfactory signaling pathway, and preimplantation embryo. OTX2-AS1 expression may be related to certain immune-infiltrating cells. Compared to gastric epithelial cells (GES-1), GC cell lines showed a significant increase in OTX2-AS1 expression.

CONCLUSION

There was a significant association between OTX2-AS1 expression in GC patients and poor survival, suggesting that it may be a useful biomarker for prognosis and immunotherapy outcome of stomach adenocarcinoma (STAD) in GC.

Prognostic value and immunological characteristics of a novel cuproptosis-related long noncoding RNAs risk signature in kidney renal clear cell carcinoma

Background: Cuproptosis has been found as a novel cell death mode significantly associated with mitochondrial metabolism, which may be significantly associated with the occurrence and growth of tumors. LncRNAs take on critical significance in regulating the development of kidney renal clear cell carcinoma (KIRC), whereas the correlation between cuproptosis-related LncRNAs (CRLs) and KIRC is not clear at present. Therefore, this study built a prognosis signature based on CRLs, which can achieve accurate prediction of the outcome of KIRC patients. Methods: The TCGA database provided the expression profile information and relevant clinical information of KIRC patients. Univariate Cox, Lasso, and multivariate Cox were employed for building a risk signature based on CRLs. Kaplan-Meier (K-M) survival analysis and time-dependent receiver operating characteristic (ROC) curve were employed for the verification and evaluation of the reliability and accuracy of risk signature. Then, qRT-PCR analysis of risk LncRNAs was conducted. Finally, the possible effect of the developed risk signature on the microenvironment for tumor immunization was speculated in accordance with ssGSEA and ESTIMATE algorithms. Results: A prognosis signature composed of APCDD1L-DT, MINCR, AL161782.1, and AC026401.3 was built based on CRLs. As revealed by the results of the K-M survival study, the OS rate and progression-free survival rate of highrisk KIRC patients were lower than those of lowrisk KIRC patients, and the areas under ROC curves of 1, 3, and 5 years were 0.828, 0.780, and 0.794, separately. The results of the immune analysis showed that there were significant differences in the status of immunization and the microenvironment of tumor between groups at low-risk and at high-risk. The qRT-PCR results showed that the relative expression level of MINCR and APCDD1L-DT were higher in 786-O and 769-P tumor cells than in HK-2 cells, which were normal renal tubular epithelial cells. Conclusion: The developed risk signature takes on critical significance in the prediction of the prognosis of patients with KIRC, and it can bring a novel direction for immunotherapy and clinical drug treatment of KIRC. In addition, 4 identified risk LncRNAs (especially APCDD1L-DT and MINCR) can be novel targets for immunotherapy of KIRC patients.

Identification of pyroptosis-related long non-coding RNAs with prognosis and therapy in lung squamous cell carcinoma

Pyroptosis is a type of programmed cell death with an intense inflammatory response. Previous studies have shown that pyroptosis plays an important role in the pathogenesis and progression of lung cancer. However, the prognostic value and drug targets of pyroptosis-related lncRNAs in lung squamous cell carcinoma (LSCC) have never been studied. In the present study, we identified 1468 pyroptosis-related lncRNAs in LSCC by performing Pearson correlation analysis between the pyroptosis-related genes and the lncRNAs from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) database. The whole set was divided into a training and a test set with a 1:1 ratio. Univariate Cox regression and least absolute shrinkage and selection operator (LASSO) analyses were conducted to establish an 11 multilncRNA signature in the three sets. The signature divided LSCC patients into the low-risk and the high-risk groups. Kaplan–Meier analysis and receiver operating characteristic (ROC) indicated that the prognostic signature had a promising predictive capability for LSCC patients. Besides, the association of microenvironment and immunotherapy response with signature was also analyzed. Moreover, 28 potential compounds targeting signature were screened as possible drugs to treat LSCC. Finally, a nomogram model was constructed to offer the quantitative prediction and net benefit for the prognosis of LSCC patients. In conclusion, the 11 pyroptosis-related lncRNAs and their signature may be promising prognostic factors and therapeutic targets for patients with LSCC.

A novel pyroptosis-related lncRNA prognostic signature associated with the immune microenvironment in lung squamous cell carcinoma

Background

A growing body of evidence suggests that pyroptosis-related lncRNAs (PRncRNAs) are associated with the prognoses of tumor patients and their tumor immune microenvironments. However, the function of PRlncRNAs in lung squamous cell carcinoma (LUSC) remains unclear.

Methods

We downloaded the transcriptome and clinical information of 551 LUSC samples from the The Cancer Genome Atlas (TCGA) database and randomly separated patients with complete information into two cohorts. Based on the training cohort, we developed a pyroptosis-related signature. We then examined the signature in the test cohort and all retained patients. We also clustered two risk groups in each cohort according to the signature and performed survival analysis, functional analysis, tumor immune microenvironment analysis and drug sensitivity analysis.

Results

A prognostic signature containing five PRlncRNAs (AP001189.1, PICART1, LINC02555, AC010422.4, and AL606469.1) was developed. A principal component analysis (PCA) indicated better differentiation between patients with different risk scores. Kaplan–Meier (K–M) analysis demonstrated poorer survival among patients with higher risk scores (P < 0.001). A receiver operating characteristic (ROC) curve analysis provided evidence confirming the accuracy of the signature, and univariate (p = 0.005) and multivariate (p = 0.008) Cox regression analyses confirmed the independent value of the risk score in prognoses. Clinical subgroup validation indicated that the signature was more suitable for patients with early-stage LUSC. We also created a nomogram to increase the accuracy of the prediction. Moreover, functional analysis revealed that pathways related to tumor development and pyroptosis were enriched in the high-risk group. Furthermore, the prognostic signature was proven to be a predictor of sensitivity to immunotherapy and chemotherapy.

Conclusions

We developed a novel pyroptosis-associated signature with independent value for the prognosis of LUSC patients. PRlncRNAs are closely associated with the tumor immune microenvironment in LUSC and might offer new directions for immunotherapy.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-022-09790-z.

Pan-Cancer Methylated Dysregulation of Long Non-coding RNAs Reveals Epigenetic Biomarkers

Different cancer types not only have common characteristics but also have their own characteristics respectively. The mechanism of these specific and common characteristics is still unclear. Pan-cancer analysis can help understand the similarities and differences among cancer types by systematically describing different patterns in cancers and identifying cancer-specific and cancer-common molecular biomarkers. While long non-coding RNAs (lncRNAs) are key cancer modulators, there is still a lack of pan-cancer analysis for lncRNA methylation dysregulation. In this study, we integrated lncRNA methylation, lncRNA expression and mRNA expression data to illuminate specific and common lncRNA methylation patterns in 23 cancer types. Then, we screened aberrantly methylated lncRNAs that negatively regulated lncRNA expression and mapped them to the ceRNA relationship for further validation. 29 lncRNAs were identified as diagnostic biomarkers for their corresponding cancer types, with lncRNA AC027601 was identified as a new KIRC-associated biomarker, and lncRNA ACTA2-AS1 was regarded as a carcinogenic factor of KIRP. Two lncRNAs HOXA-AS2 and AC007228 were identified as pan-cancer biomarkers. In general, the cancer-specific and cancer-common lncRNA biomarkers identified in this study may aid in cancer diagnosis and treatment.

A Signature of 14 Long Non-Coding RNAs (lncRNAs) as a Step towards Precision Diagnosis for NSCLC

LncRNAs have arisen as new players in the world of non-coding RNA. Disrupted expression of these molecules can be tightly linked to the onset, promotion and progression of cancer. The present study estimated the usefulness of 14 lncRNAs (HAGLR, ADAMTS9-AS2, LINC00261, MCM3AP-AS1, TP53TG1, C14orf132, LINC00968, LINC00312, TP73-AS1, LOC344887, LINC00673, SOX2-OT, AFAP1-AS1, LOC730101) for early detection of non-small-cell lung cancer (NSCLC). The total RNA was isolated from paired fresh-frozen cancerous and noncancerous lung tissue from 92 NSCLC patients diagnosed with either adenocarcinoma (LUAD) or lung squamous cell carcinoma (LUSC). The expression level of lncRNAs was evaluated by a quantitative real-time PCR (qPCR). Based on Ct and delta Ct values, logistic regression and gradient boosting decision tree classifiers were built. The latter is a novel, advanced machine learning algorithm with great potential in medical science. The established predictive models showed that a set of 14 lncRNAs accurately discriminates cancerous from noncancerous lung tissues (AUC value of 0.98 ± 0.01) and NSCLC subtypes (AUC value of 0.84 ± 0.09), although the expression of a few molecules was statistically insignificant (SOX2-OT, AFAP1-AS1 and LOC730101 for tumor vs. normal tissue; and TP53TG1, C14orf132, LINC00968 and LOC730101 for LUAD vs. LUSC). However for subtypes discrimination, the simplified logistic regression model based on the four variables (delta Ct AFAP1-AS1, Ct SOX2-OT, Ct LINC00261, and delta Ct LINC00673) had even stronger diagnostic potential than the original one (AUC value of 0.88 ± 0.07). Our results demonstrate that the 14 lncRNA signature can be an auxiliary tool to endorse and complement the histological diagnosis of non-small-cell lung cancer.