lncRNA Profiles Enable Prognosis Prediction and Subtyping for Esophageal Squamous Cell Carcinoma

Identification of necroptosis-related lncRNAs for prognosis prediction and screening of potential drugs in patients with colorectal cancer

BACKGROUND

Tumor recurrence and metastasis lead to a poor prognosis in colorectal cancer (CRC). Necroptosis is closely related to the tumor microenvironment (TME) and affects tumor recurrence and metastasis. We aimed to stratify CRC patients according to necroptosis-related long noncoding RNAs (lncRNAs), which can be used to not only evaluate prognosis and improve precision medicine in clinical practice but also screen potential immunotherapy drugs.

AIM

To stratify CRC patients according to necroptosis-related lncRNAs (NRLs), which can be used to not only evaluate prognosis and improve precision medicine in clinical practice but also screen potential immunotherapy drugs.

METHODS

LncRNA expression profiles were collected from The Cancer Genome Atlas. NRLs were identified by coexpression analysis. Cox regression analysis identified a NRL signature. Then, the value of this signature was comprehensively and multidimensionally evaluated, and its reliability for CRC prognosis prediction was assessed with clinical CRC data and compared with that of six other lncRNA signatures. Gene set enrichment analysis, TME analysis and half-maximal inhibitory concentration (IC₅₀) prediction were also performed according to the risk score (RS) of the signature.

RESULTS

An 8-lncRNA signature significantly associated with overall survival (OS) was constructed, and its reliability was validated with clinical CRC data. Most of the areas under the receiver operating characteristic curves (AUCs) values for 1-, 3- and 5-year OS for this signature were higher than those for the other six lncRNA signatures. OS, disease-specific survival and the progression-free interval were all significantly poorer in the high-risk group. The RS of the signature showed good concordance with the predicted prognosis, with AUCs for 1-, 3- and 5-year OS of 0.79, 0.81 and 0.77, respectively. Additionally, the calibration plots for this signature combined with clinical factors showed that this combination could effectively improve the ability to predict OS. The RS was correlated with tumor stage, lymph node metastasis and distant metastasis. Most of the enriched Kyoto Encyclopedia of Genes and Genomes and Gene Ontology terms were tumor metastasis-related pathways in the high-risk group; these patients showed greater infiltration of immunosuppressive cells, such as cancer-associated fibroblasts, hematopoietic stem cells and M2 macrophages, but less infiltration of infiltrating antitumor effector immune cells, such as cluster of differentiation 8⁺ T cells and regulatory T cells (Tregs). We explored additional potential immune checkpoint genes and potential immunotherapeutic and chemotherapeutic drugs with relatively low IC₅₀ values.

CONCLUSION

We identified an NRL signature with strong fidelity that could stably predict prognosis and might be an indicator of the TME of CRC. Furthermore, additional potential immunotherapeutic and chemotherapeutic drugs were explored.

Mechanisms of Chinese Medicine in Gastroesophageal Reflux Disease Treatment: Data Mining and Systematic Pharmacology Study

OBJECTIVE

To identify specific Chinese medicines (CMs) that may benefit patients with gastroesophageal reflux disease (GERD), and explore the action mechanism.

METHODS

Domestic and foreign literature on the treatment of GERD with CMs was searched and selected from China National Knowledge Infrastructure, China Science and Technology Journal Database, Wanfang Database, and PubMed from October 1, 2011 to October 1, 2021. Data from all eligible articles were extracted to establish the database of CMs for GERD. Apriori algorithm of data mining techniques was used to analyze the rules of herbs selection and core Chinese medicine formulas were identified. A system pharmacology approach was used to explore the action mechanism of these medicines.

RESULTS

A total of 278 prescriptions for GERD were analyzed, including 192 CMs. Results of Apriori algorithm indicated that Evodiae Fructus and Coptidis Rhizoma were the highest confidence combination. A total of 32 active ingredients and 66 targets were screened for the treatment of GERD. Enrichment analysis showed that the mechanisms of action mainly involved pathways in cancer, fluid shear stress and atherosclerosis, advanced glycation end product (AGE), the receptor for AGE signaling pathway in diabetic complications, bladder cancer, and rheumatoid arthritis.

CONCLUSION

Evodiae Fructus and Coptidis Rhizoma are the core drugs in the treatment of GERD and the potential mechanism of action of these medicines includes potential target and pathways.

Identification of m6A-related lncRNAs as prognostic signature within colon tumor immune microenvironment

BACKGROUND

The current study probed prognosis-related potential for m6A-related lncRNAs signatures within colon tumor immune microenvironment (TIM).

METHODS

After downloading transcriptomic datasets for colon cancer (CC) patients from The Cancer Genome Atlas (TCGA), they were divided, in a 1:1 ratio, within training or test datasets. m6A-related lncRNAs were then scrutinized across such dataset using Pearson correlation assessment before generating a m6A-related lncRNAs prognosis-related model using the training dataset. The latter was then validated with the test and the whole dataset. In addition, we compared the differences of TIM and the estimated IC50 of drug response between the high- and low-risk groups.

RESULTS

Overall survival (OS) resulted as linked with 11 m6A-related lncRNAs, while within the developed prognosis-related model, areas-under-curves were as follows: within training dataset, values at 3-, 4-, and 5-years were 0.777, 0.819, and 0.805, accordingly, and for test one, they were 0.697, 0.682, and 0.706, respectively. Finally, the values for the whole dataset were 0.675 (3-year), 0.682 (4-years), and 0.679 (5-years), accordingly. Moreover, CC cases categorized within low-risk cohort demonstrated enhanced OS (p < .0001), lower metastasis (p = 2e-06) and lower T stage (p = .0067), more instability for microsatellite status (p = .012), and downregulation for PD-L1, PD-1, CTLA-4, LAG3, and HAVCR2 (p < .05). In addition, risk scorings were significantly linked to the degree of infiltrative intensity for CD8 and CD4 (memory resting) T-cells, T-regulatory (Tregs), and Mast cells triggering (p < .05). Patients with low infiltrative propensity for CD4 T-cells also had better OS (p = .016). Moreover, six representative drugs were found to be sensitive for treating CC patients.

CONCLUSION

A robust m6A-related prognostic model with great performances was developed before exploring the TIM characteristics and its potential therapeutic drugs, which might improve the prognosis and therapeutic efficacy.

Bioinformatics Analysis of the Inflammation-Associated lncRNA-mRNA Coexpression Network in Type 2 Diabetes

Introduction

Diabetes is a chronic inflammatory state, and a key role of lncRNAs in diabetes complications is a new area of research.

Methods

In this study, key lncRNAs related to diabetes inflammation were identified by RNA-chip mining and lncRNA-mRNA coexpression network construction and finally verified by RT-qPCR.

Results

We ultimately obtained 12 genes, including A1BG-AS1, AC084125.4, RAMP2-AS1, FTX, DBH-AS1, LOXL1-AS1, LINC00893, LINC00894, PVT1, RUSC1-AS1, HCG25, and ATP1B3-AS1. RT-qPCR assays verified that LOXL1-AS1, A1BG-AS1, FTX, PVT1, and HCG25 were upregulated in the HG+LPS-induced THP-1 cells, and LINC00893, LINC00894, RUSC1-AS1, DBH-AS1, and RAMP2-AS1 were downregulated in the HG+LPS-induced THP-1 cells.

Conclusions

lncRNAs and mRNAs are extensively linked and form a coexpression network, and lncRNAs may influence the development of type 2 diabetes by regulating the corresponding mRNAs. The ten key genes obtained may become biomarkers of inflammation in type 2 diabetes in the future.

m7G-related lncRNAs are potential biomarkers for predicting prognosis and immune responses in patients with oral squamous cell carcinoma

Among head and neck cancers, oral squamous cell carcinoma (OSCC) is the most common malignant tumor. N-7-methylguanosine (m7G) and lncRNAs are both related to the development and progression of tumors. Therefore, this study aims to explore and establish the prognostic signal of OSCC based on m7G-related lncRNAs. In this study, RNA sequencing transcriptome data of OSCC patients were downloaded from The Cancer Genome Atlas (TCGA) database. Therefore, m7G-related lncRNAs were identified as differentially expressed in OSCC. Then, univariate Cox regression analysis and LASSO regression analysis were conducted to evaluate the prognostic significance of differentially expressed lncRNAs. Consequently, the abovementioned lncRNAs were assigned five OSCC patient risk scores, with high-risk and low-risk patients assigned to each group. Different signaling pathways were significantly enriched between the two groups as determined by set enrichment analysis (GSEA). Multivariate Cox regression analysis confirmed the factors used to construct the nomogram model. Then, the prognosis of the nomogram model was evaluated. Consequently, high-risk individuals had higher immune infiltration levels. According to the results of a study that evaluated the sensitivity of different risk subgroups to antitumour drugs, the high-risk group had a high sensitivity to doxorubicin. By performing real-time polymerase chain reaction (RT‒PCR), we verified the expression of these five m7G lncRNAs. Therefore, the model based on five m7G-related lncRNAs was able to predict the overall survival rates of OSCC patients and guide their treatment. It can also spur new ideas about how to prevent and treat OSCC.

LncRNA SNHG3 promoted cell proliferation, migration, and metastasis of esophageal squamous cell carcinoma via regulating miR-151a-3p/PFN2 axis

Esophageal squamous cell carcinoma (ESCC) is an aggressive malignant tumor with a poor prognosis. The dysregulation of long non-coding RNAs (lncRNAs) is closely related to the tumorigenesis and progression of ESCC. However, the effects of lncRNA small nucleolar RNA host gene 3 (lncRNA SNHG3) in ESCC are still unclear. Therefore, a series of experiments methods, such as quantitative real-time polymerase chain reaction, function gain/loss experiments, western blots, and animal xenograft tumor model, were employed to explore the biological function and molecular mechanism of SNHG3 in ESCC. As results, we first reported that SNHG3 was significantly up-regulated in ESCC tissues and cells. SNHG3 knockdown obviously inhibited cell proliferation, migration, invasion, and promoted apoptosis. Mechanism analysis revealed that SNHG3 sponged miR-151a-3p to regulate PFN2. Inhibition of miR-151a-3p and overexpression of PFN2 attenuated the positive effect of SNHG3 knockdown on suppressing tumor progression. Furthermore, the anti-tumor effects of SNHG3 knockdown were also observed in vivo. In summary, our results indicated that SNHG3 knockdown suppressed tumor development via the miR-151a-3p/PFN2 axis, and targeting SNHG3 may provide a new opportunity for ESCC patients.

A Genomic Instability-Related Long Noncoding RNA Signature for Predicting Hepatocellular Carcinoma Prognosis

Background. Long noncoding RNAs (lncRNAs) are found to be novel biomarkers for hepatocellular carcinoma (HCC) and play an important role in tumor progression. We established a genomic instability-related long noncoding RNA signature (GIlncSig) as an independent prognosis factor and also investigated its impact on prognosis significance. Method. Somatic mutation profiles, clinical characteristics, and RNA sequencing data were obtained from The Cancer Genome Atlas (TCGA) database. Lasso regression was used to construct GIlncSig. KEGG was used to identify the possible biological pathways. ESTIMATE and CIBERSORT algorithms were used to calculate the immune microenvironment scores and proportion of immune cells in HCC patients. The expression of LINC00501 was conducted by qRT-PCR. Cell proliferation was measured by EdU, CCK-8, and colony formation assay, and cell migration and invasion ability were measured by wound healing and transwell assay. Results. 135 genomic instability-related lncRNAs were identified, and GIlncSig was constructed using 13 independent lncRNAs with significant prognosis values. Based on the GIlncSig, high-risk group had worse clinical outcomes than low-risk group, while high-risk group also had higher UBQLN4, KRAS, ARID1A, and PIK3CA expression. Moreover, the efficiency of GIlncSig combining single-gene mutation was higher than single-gene mutation alone such as TP53. The results of CIBERSORT and ESTIMATE showed that GS group and GU group had significantly different immune infiltration. In addition, LINC00501 was identified as a potential biomarker in HCC with strong relationship with clinical characteristics. In vitro assays validated that LINC00501 promoted proliferation and migration of HCC cell lines. Conclusion. Our results showed that GIlncSig serves as a potential independent prognosis factor to predict HCC patients’ prognosis for exploring potential mechanism and therapy strategy. Besides, LINC00501 plays an important role in the progression of HCC, which may be a potential therapy target.

Prognosis Risk Model Based on Pyroptosis-Related lncRNAs for Bladder Cancer

Objective. Bladder cancer (BC) is the most common malignancy in the urinary system and is prone to recurrence and metastasis. Pyroptosis is a kind of cell necrosis that is triggered by the gasdermin protein family. lncRNAs are noncoding RNAs that are more than 200 nucleotides long. Both pyroptosis and lncRNAs are associated with tumor development and progression. This study is aimed at exploring and establishing a prognostic signature of BC based on pyroptosis-related lncRNAs. Methods. In this study, The Cancer Genome Atlas (TCGA) database provided us with the RNA sequencing transcriptome data of bladder cancer patients, and we identified differentially expressed pyroptosis-related lncRNAs in bladder cancer. Then, the prognostic significance of these lncRNAs was assessed using univariate Cox regression analysis and LASSO regression analysis. Subsequently, 4 pyroptosis-related lncRNAs, namely, AL121652.1, AL161729.4, AC007128.1, and AC124312.3, were identified by multivariate Cox regression analysis, thus constructing the prognostic risk model. Then, we compared the levels of immune infiltration, differences in cell function, immune checkpoints, and m6A-related gene expression levels between the high- and low-risk groups. Result. Patients were divided into low-risk or high-risk groups based on the median risk score. Kaplan–Meier survival analysis indicated that the overall survival of bladder cancer patients in the low-risk group was substantially superior to that in the high-risk group ( $p<0.001$ ). The receiver operating characteristic (ROC) curve further confirmed the credibility of our model. Moreover, gene set enrichment analysis (GSEA) indicated that these were different signal pathways significantly enriched between the two groups. Immune infiltration, immune checkpoint, and N6-methyladenosine-related gene analysis also reflected that there were notable differences between the two groups. Conclusion. Therefore, this prognostic risk model is based on the level of pyroptotic lncRNAs, which is conducive to individualized assessment of the risk of patients and provides a reference for clinical treatment. This will also help provide insights into the prognosis and treatment of bladder cancer.

RAP1/TERF2IP-A Multifunctional Player in Cancer Development

Simple Summary

RAP1 (TERF2IP) is a member of the shelterin complex that protects telomeric DNA and plays a critical role in maintaining chromosome stability. However, mammalian RAP1 was recently found to have additional functions apart from telomeres, acting as a regulator of the NF-κB pathway and transcription factor, and has been suggested that they have putative roles in cancer development. Here, we focus on the main roles of RAP1 in different mechanisms of oncogenesis, progression, and chemoresistance, and consider the clinical significance of findings about its regulation and biological functions.

Abstract

Mammalian RAP1 (TERF2IP), the most conserved shelterin component, plays a pleiotropic role in the regulation of a variety of cellular processes, including cell metabolism, DNA damage response, and NF-κB signaling, beyond its canonical telomeric role. Moreover, it has been demonstrated to be involved in oncogenesis, progression, and chemoresistance in human cancers. Several mutations and different expression patterns of RAP1 in cancers have been reported. However, the functions and mechanisms of RAP1 in various cancers have not been extensively studied, suggesting the necessity of further investigations. In this review, we summarize the main roles of RAP1 in different mechanisms of cancer development and chemoresistance, with special emphasis on the contribution of RAP1 mutations, expression patterns, and regulation by non-coding RNA, and briefly discuss telomeric and non-telomeric functions.