The Role of lncRNA PCAT6 in Cancers

Identification and functional prediction of long non-coding RNAs related to oxidative stress in the jejunum of piglets

OBJECTIVE

Oxidative stress (OS) is a pathological process arising from the excessive production of free radicals in the body. It has the potential to alter animal gene expression and cause damage to the jejunum. However, there have been few reports of changes in the expression of long noncoding RNAs (lncRNAs) in the jejunum in piglets under OS. The purpose of this research was to examine how lncRNAs in piglet jejunum change under OS.

METHODS

The abdominal cavities of piglets were injected with diquat (DQ) to produce OS. Raw reads were downloaded from the SRA database. RNA-seq was utilized to study the expression of lncRNAs in piglets under OS. Additionally, six randomly selected lncRNAs were verified using quantitative real-time polymerase chain reaction (qRT‒PCR) to examine the mechanism of oxidative damage.

RESULTS

A total of 79 lncRNAs were differentially expressed (DE) in the treatment group compared to the negative control group. The target genes of DE lncRNAs were enriched in gene ontology (GO) terms and Kyoto encyclopedia of genes and genomes (KEGG) signaling pathways. Chemical carcinogenesis-reactive oxygen species, the Foxo signaling pathway, colorectal cancer, and the AMPK signaling pathway were all linked to OS.

CONCLUSION

Our results demonstrated that DQ-induced OS causes differential expression of lncRNAs, laying the groundwork for future research into the processes involved in the jejunum's response to OS.

DARS-AS1: A Vital Oncogenic LncRNA Regulator with Potential for Cancer Prognosis and Therapy

DARS-AS1, short for Aspartyl-tRNA synthetase antisense RNA 1, has emerged as a pivotal player in cancers. Upregulation of this lncRNA is a recurrent phenomenon observed across various cancer types, where it predominantly assumes oncogenic roles, exerting influence on multiple facets of tumor cell biology. This aberrant expression of DARS-AS1 has triggered extensive research investigations, aiming to unravel its roles and clinical values in cancer. In this review, we elucidate the significant correlation between dysregulated DARS-AS1 expression and adverse survival prognoses in cancer patients, drawing from existing literature and pan-cancer analyses from The Cancer Genome Atlas (TCGA). Additionally, we provide comprehensive insights into the diverse functions of DARS-AS1 in various cancers. Our review encompasses the elucidation of the molecular mechanisms, ceRNA networks, functional mediators, and signaling pathways, as well as its involvement in therapy resistance, coupled with the latest advancements in DARS-AS1-related cancer research. These recent updates enrich our comprehensive comprehension of the pivotal role played by DARS-AS1 in cancer, thereby paving the way for future applications of DARS-AS1-targeted strategies in tumor prognosis evaluation and therapeutic interventions. This review furnishes valuable insights to advance the ongoing efforts in combating cancer effectively.

Developing a RiskScore Model based on Angiogenesis-related lncRNAs for Colon Adenocarcinoma Prognostic Prediction

AIM

We screened key angiogenesis-related lncRNAs based on colon adenocarcinoma (COAD) to construct a RiskScore model for predicting COAD prognosis and help reveal the pathogenesis of the COAD as well as optimize clinical treatment.

BACKGROUND

Regulatory roles of lncRNAs in tumor progression and prognosis have been confirmed, but few studies have probed into the role of angiogenesis-related lncRNAs in COAD.

OBJECTIVE

To identify key angiogenesis-related lncRNAs and build a RiskScore model to predict the survival probability of COAD patients and help optimize clinical treatment.

METHODS

Sample data were collected from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) database. The HALLMARK pathway score in the samples was calculated using the single sample gene set enrichment analysis (ssGSEA) method. LncRNAs associated with angiogenesis were filtered by an integrated pipeline algorithm. LncRNA-based subtypes were classified by ConsensusClusterPlus and then compared with other established subtypes. A RiskScore model was created based on univariate Cox, least absolute shrinkage and selection operator (LASSO) regression and stepwise regression analysis. The Kaplan-Meier curve was drawn by applying R package survival. The time-dependent ROC curves were drawn by the timeROC package. Finally, immunotherapy benefits and drug sensitivity were analyzed using tumor immune dysfunction and exclusion (TIDE) software and pRRophetic package.

RESULTS

Pathway analysis showed that the angiogenesis pathway was a risk factor affecting the prognosis of COAD patients. A total of 66 lncRNAs associated with angiogenesis were screened, and three molecular subtypes (S1, S2, S3) were obtained. The prognosis of S1 and S2 was better than that of S3. Compared with the existing subtypes, the S3 subtype was significantly different from the other two subtypes. Immunoassay showed that immune cell scores of the S2 subtype were lower than those of the S1 and S3 subtypes, which also had the highest TIDE scores. We recruited 8 key lncRNAs to develop a RiskScore model. The high RiskScore group with inferior survival and higher TIDE scores was predicted to benefit limitedly from immunotherapy, but it may be more sensitive to chemotherapeutics. A nomogram designed by RiskScore signature and other clinicopathological characteristics shed light on rational predictive power for COAD treatment.

CONCLUSION

We constructed a RiskScore model based on angiogenesis-related lncRNAs, which could serve as potential prognostic predictors for COAD patients and may offer clues for the intervention of anti-angiogenic application. Our results may help evaluate the prognosis of COAD and provide better treatment strategies.

Evaluation of Long Non-coding RNA (LncRNA) in the Pathogenesis of Chemotherapy Resistance in Cervical Cancer: Diagnostic and Prognostic Approach

Cervical cancer (CC), caused by human papillomavirus (HPV), is a leading cause of female malignancies worldwide. Therefore, understanding the underlying mechanisms of CC development and identifying novel therapeutic targets are significantly important. Cisplatin resistance is a significant challenge in the management of CC. Recent studies highlighted the critical role of long non-coding RNAs (lncRNAs) in modulation of cisplatin resistance. This comprehensive review aims to collect the current understanding roles of lncRNAs and their involvement in cisplatin resistance in CC by highlighting key processes of cancer progression, including apoptosis, proliferation, angiogenesis and epithelial-to-mesenchymal transition (EMT). We discussed the role of lncRNA in CC resistance to cisplatin through molecular pathways and examined gene expression changes. We also discussed treatment strategies and factors that reduce CC resistance to cisplatin by targeting them.

Creation of a Prognostic Model Using Cuproptosis-Associated Long Noncoding RNAs in Hepatocellular Carcinoma

Cuproptosis is an unusual form of cell death caused by copper accumulation in mitochondria. Cuproptosis is associated with hepatocellular carcinoma (HCC). Long noncoding RNAs (LncRNAs) have been shown to be effective prognostic biomarkers, yet the link between lncRNAs and cuproptosis remains unclear. We aimed to build a prognostic model of lncRNA risk and explore potential biomarkers of cuproptosis in HCC. Pearson correlations were used to derive lncRNAs co-expressed in cuproptosis. The model was constructed using Cox, Lasso, and multivariate Cox regressions. Kaplan-Meier survival analysis, principal components analysis, receiver operating characteristic curve, and nomogram analyses were carried out for validation. Seven lncRNAs were identified as prognostic factors. A risk model was an independent prognostic predictor. Among these seven lncRNAs, prostate cancer associated transcript 6 (PCAT6) is highly expressed in different types of cancer, activating Wnt, PI3K/Akt/mTOR, and other pathways; therefore, we performed further functional validation of PCAT6 in HCC. Reverse transcription-polymerase chain reaction results showed that PCAT6 was aberrantly highly expressed in HCC cell lines (HepG2 and Hep3B) compared to LO2 (normal hepatocytes). When its expression was knocked down, cells proliferated and migrated less. PCAT6 might be a potential biomarker for predicting prognosis in HCC.

Pan-cancer analysis of PCAT6 and its effect on oesophageal squamous cell carcinoma cell proliferation and migration

Bioinformatics methods were used to analyze the role of PCAT6 in a variety of tumors and verify its role in oesophageal squamous cell carcinoma (ESCC) EC109 cells. The pan-cancer dataset was downloaded from the University of California Santa Cruz (UCSC) database to analyze the expression of PCAT6 in pan-cancer and its relationship with prognosis, clinical features, and immune infiltration. The expression and prognosis of PCAT6 in ESCC were verified by Gene Expression Omnibus (GEO) and Kaplan-Meier database. CCK8, colony formation, wound healing, Transwell cell invasion (CI), and cell migration (CM) assays were used to detect the effect of PCAT6 knockdown on the ability of ESCC cell proliferation (CP), CI and CM. Gene Set Enrichment Analysis was used to analyze the signaling pathways involved in the regulation of PCAT6. Quantitative real-time PCR and western blotting were used to examine the expression of cancer stem cell-related markers and the activation of JAK/STAT pathway in ESCC after PCAT6 knockdown. PCAT6 is significantly up-regulated in a variety of tumor tissues, and its expression is closely related to prognosis, clinical features and immune infiltration. High expression of PCAT6 leads to poor prognosis in ESCC patients. In ESCC EC109 cells, PCAT6 knockdown inhibited the ability of CP, CI, CM, and stemness, and inhibited the activation of JAK/STAT signaling pathway. PCAT6 expression is elevated in a variety of tumors. PCAT6 plays an oncogene role in ESCC by activating the JAK/STAT signaling pathway.

Bioinformatics analysis of lncRNAs in the occurrence and development of osteosarcoma

BACKGROUND

Osteosarcoma (OS) is a disease with high mortality in children and adolescents, and metastasis is one of its important clinical features. However, the molecular mechanism of OS occurrence is not completely clear. Thus, we screened potential biomarkers of OS and analyze their prognostic value.

METHODS

The Cancer Genome Atlas (TCGA) datasets were used to analyze the differential lncRNAs in patients with OS of different immune score and the lncRNAs expressed by immune cells. Cox regression was used to develop the prognosis prediction model and specify the prognosis outcomes. Risk-proportional regression model was constructed, and the samples were divided into high and low groups based on the risk scores for the survival analysis. The areas under the receiver operating characteristic (ROC) curve were calculated and the risk-score model was verified. Finally, using 4 gene sets (comprising chemokines, immune checkpoint blockades, immune activity-related genes, and immune cells), and 4 analysis tools (CIBERSORT, TIMER, XCELL and MCP) to evaluated tumor immune infiltration.

RESULTS

Twenty-nine long non-coding ribonucleic acids (lncRNAs) were obtained from the intersection of the screened lncRNAs. Caspase recruitment domain-containing protein 8-antisense RNA 1 (CARD8-AS1), lncRNA five prime to Xist (FTX), KAT8 regulatory NSL complex unit 1-antisense RNA 1 (KANSL1-AS1), Neuroplastin Intronic Transcript 1 (NPTN-IT1), oligodendrocyte maturation-associated long intervening non-coding RNA (OLMALINC) and RPARP Antisense RNA 1 (RPARP-AS1) were found to be correlated with survival. Univariate and multivariate regression analysis showed risk score [HR (hazard ratio) 3.5, P value 0.0043; HR 3.7, P value 0.0033] and metastasis (HR 4.7, P value 6.60E-05; HR 4.8, P value 8.36E-05) were the key factors of patients with OS. The areas under curves (AUCs) of the 1-, 3-, and 5-year ROC curves of the prognostic model were 0.715, 0.729, and 0.771. The low-risk patients tended to have a high abundance of immune cells.

CONCLUSIONS

This study showed that a risk score based on 6 lncRNAs has potential value in the prognosis of OS, and patients with low-risk scores have high immune cell infiltration and good prognosis. This study may enrich understandings of underlying mechanisms related to the occurrence and development of OS.

Knockdown of lncRNA PCAT6 suppresses the growth of non-small cell lung cancer cells by inhibiting macrophages M2 polarization via miR-326/KLF1 axis

Non-small cell lung cancer (NSCLC) is the most common malignant tumor of lung, which seriously threatens the life of people. It has been reported that lncRNA prostate cancer-associated transcript 6 (PCAT6) could facilitate the metastasis of NSCLC cells. However, whether lncRNA PCAT6 in NSCLC cells could affect the tumor microenvironment (TME) remains unclear. In the present study, the level of PCAT6 in NSCLC cells was detected using RT-qPCR. The effects of PCAT6 knockdown on the viability and apoptosis in NSCLC cells were detected with CCK-8 and flow cytometry assay. NSCLC cell-derived exosomes were isolated with ultracentrifugation. Next, transwell assay was conducted to assess the migration and invasion of NSCLC cells. Dual-luciferase reporter assay was performed to verify the relationship among PCAT6, miR-326, and KLF1 in A549 cells. In addition, nanoparticle tracking analysis (NTA) was applied to detect the particle size of isolated exosomes. Moreover, ELISA assay was performed to detect the levels of IL-1β and IL-10 in the supernatant of macrophage. We found knockdown of PCAT6 significantly inhibited the viability, migration, and invasion of NSCLC cells. In addition, dual-luciferase reporter assay illustrated that miR-326 was the target of PCAT6 and KLF1 was the target of miR-326 in NSCLC cells. Moreover, NSCLC cells-derived exosomes could promote macrophages M2 polarization by transporting PCAT6. Meanwhile, macrophages M2 polarization was able to promote the metastasis and epithelial-mesenchymal transition (EMT) process of NSCLC cells via regulating PCAT6/miR-326/KLF1 axis. Taken together, knockdown of lncRNA PCAT6 suppressed the growth of NSCLC cells by inhibiting macrophages M2 polarization via miR-326/KLF1 axis.