LINC02257, an Enhancer RNA of Prognostic Value in Colon Adenocarcinoma, Correlates With Multi-Omics Immunotherapy-Related Analysis in 33 Cancers

Prognostic cellular senescence-related lncRNAs patterns to predict clinical outcome and immune response in colon cancer

Background

Cellular senescence (CS) is believed to be a major factor in the evolution of cancer. However, CS-related lncRNAs (CSRLs) involved in colon cancer regulation are not fully understood. Our goal was to create a novel CSRLs prognostic model for predicting prognosis and immunotherapy and exploring its potential molecular function in colon cancer.

Methods

The mRNA sequencing data and relevant clinical information of GDC TCGA Colon Cancer (TCGA-COAD) were obtained from UCSC Xena platform, and CS-associated genes was acquired from the CellAge website. Pearson correlation analysis was used to identify CSRLs. Then we used Kaplan-Meier survival curve analysis and univariate Cox analysis to acquire prognostic CSRL. Next, we created a CSRLs prognostic model using LASSO and multivariate Cox analysis, and evaluated its prognostic power by Kaplan-Meier and ROC curve analysis. Besides, we explored the difference in tumor microenvironment, somatic mutation, immunotherapy, and drug sensitivity between high-risk and low-risk groups. Finally, we verified the functions of MYOSLID in cell experiments.

Results

Three CSRLs (AC025165.1, LINC02257 and MYOSLID) were identified as prognostic CSRLs. The prognostic model exhibited a powerful predictive ability for overall survival and clinicopathological features in colon cancer. Moreover, there was a significant difference in the proportion of immune cells and the expression of immunosuppressive point biomarkers between the different groups. The high-risk group benefited from the chemotherapy drugs, such as Teniposide and Mitoxantrone. Finally, cell proliferation and CS were suppressed after MYOSLID knockdown.

Conclusion

CSRLs are promising biomarkers to forecast survival and therapeutic responses in colon cancer patients. Furthermore, MYOSLID, one of 3-CSRLs in the prognostic model, could dramatically regulate the proliferation and CS of colon cancer.

A cuproptosis-related lncRNAs signature predicts prognosis and reveals pivotal interactions between immune cells in colon cancer

Copper-mediated cell death presents distinct pathways from established apoptosis processes, suggesting alternative therapeutic approaches for colon cancer. Our research aims to develop a predictive framework utilizing long-noncoding RNAs (lncRNAs) related to cuproptosis to predict colon cancer outcomes while examining immune interactions and intercellular signaling. We obtained colon cancer-related human mRNA expression profiles and clinical information from the Cancer Genome Atlas repository. To isolate lncRNAs involved in cuproptosis, we applied Cox proportional hazards modeling alongside the least absolute shrinkage and selection operator technique. We elucidated the underlying mechanisms by examining the tumor mutational burden, the extent of immune cell penetration, and intercellular communication dynamics. Based on the model, drugs were predicted and validated with cytological experiments. A 13 lncRNA-cuproptosis-associated risk model was constructed. Two colon cancer cell lines were used to validate the predicted representative mRNAs with high correlation coefficients with copper-induced cell death. Survival enhancement in the low-risk cohort was evidenced by the trends in Kaplan-Meier survival estimates. Analysis of immune cell infiltration suggested that survival was induced by the increased infiltration of naïve CD4+ T cells and a reduction of M2 macrophages within the low-risk faction. Decreased infiltration of naïve B cells, resting NK cells, and M0 macrophages was significantly associated with better overall survival. Combined single-cell analysis suggested that CCL5-ACKR1, CCL2-ACKR1, and CCL5-CCR1 pathways play key roles in mediating intercellular dialogues among immune constituents within the neoplastic microhabitat. We identified three drugs with a high sensitivity in the high-risk group. In summary, this discovery establishes the possibility of using 13 cuproptosis-associated lncRNAs as a risk model to assess the prognosis, unravel the immune mechanisms and cell communication, and improve treatment options, which may provide a new idea for treating colon cancer.

LINC02257 regulates colorectal cancer liver metastases through JNK pathway

Background

Long noncoding RNAs (lncRNAs) have emerged as critical regulators of colorectal cancer (CRC) progression, but their roles and underlying mechanisms in colorectal cancer liver metastases (CRLMs) remain poorly understood.

Methods

To explore the expression patterns and functions of lncRNAs in CRLMs, we analyzed the expression profiles of lncRNAs in CRC tissues using the TCGA database and examined the expression patterns of lncRNAs in matched normal, CRC, and CRLM tissues using clinical samples. We further investigated the biological roles of LINC02257 in CRLM using in vitro and in vivo assays, and verified its therapeutic potential in a mouse model of CRLM.

Results

Our findings showed that LINC02257 was highly expressed in metastatic CRC tissues and its expression was negatively associated with overall survival. Functionally, LINC02257 promoted CRC cell growth, migration, metastasis, and inhibited cell apoptosis in vitro, and enhanced liver metastasis in vivo. Mechanistically, LINC02257 up-regulated phosphorylated c-Jun N-terminal kinase (JNK) to promote CRLM.

Conclusions

Our study revealed that LINC02257 played a key role in the proliferation and metastasis of CRC cells through the LINC02257/JNK axis. Targeting this axis may represent a promising therapeutic strategy for the treatment of liver metastases in patients with CRC.

Non-coding RNAs in Precursor Lesions of Colorectal Cancer: Their Role in Cancer Initiation and Formation

Colorectal cancer (CRC) is one of the world's most common types of malignancy. The proliferation of precancerous lesions causes this type of cancer. Two distinct pathways for CRC carcinogenesis have been identified: the conventional adenoma-carcinoma pathway and the serrated neoplasia pathway. Recently, evidence has demonstrated the regulatory roles of noncoding RNAs (ncRNAs) in the initiation and progression of precancerous lesions, especially in the adenoma-carcinoma pathway and serrated neoplasia pathway. By expanding the science of molecular genetics and bioinformatics, several studies have identified dysregulated ncRNAs that function as oncogenes or tumor suppressors in cancer initiation and formation by diverse mechanisms via intracellular signaling pathways known to act on tumor cells. However, many of their roles are still unclear. This review summarizes the functions and mechanisms of ncRNAs (such as long non-coding RNAs, microRNAs, long intergenic non-coding RNAs, small interfering RNAs, and circRNAs) in the initiation and formation of precancerous lesions.

Development and validation of cuproptosis-related lncRNA signatures for prognosis prediction in colorectal cancer

BACKGROUND

Cuproptosis, a novel form of programmed cell death, plays an essential role in various cancers. However, studies of the function of cuproptosis lncRNAs (CRLs) in colorectal cancer (CRC) remain limited. Thus, this study aims to identify the cuprotosis-related lncRNAs (CRLs) in CRC and to construct the potential prognostic CRLs signature model in CRC.

METHODS

First, we downloaded RNA-Seq data and clinical information of CRC patients from TCGA database and obtained the prognostic CRLs based on typical expression analysis of cuproptosis-related genes (CRGs) and univariate Cox regression. Then, we constructed a prognostic model using the Least Absolute Shrinkage and Selection Operator algorithm combined with multiple Cox regression methods (Lasso-Cox). Next, we generated Kaplan-Meier survival and receiver operating characteristic curves to estimate the performance of the prognostic model. In addition, we also analysed the relationships between risk signatures and immune infiltration, mutation, and drug sensitivity. Finally, we performed quantitative reverse transcription polymerase chain reaction (qRT -PCR) to verify the prognostic model.

RESULT

Lasso-Cox analysis revealed that four CRLs, SNHG16, LENG8-AS1, LINC0225, and RPARP-AS1, were related to CRC prognosis. Receiver operating characteristic (ROC) and Kaplan-Meier analysis curves indicated that this model performs well in prognostic predictions of CRC patients. The DCA results also showed that the model included four gene signatures was better than the traditional model. In addition, GO and KEGG analyses revealed that DE-CRLs are enriched in critical signalling pathway, such as chemical carcinogenesis-DNA adducts and basal cell carcinoma. Immune infiltration analysis revealed significant differences in immune infiltration cells between the high-risk and low-risk groups. Furthermore, significant differences in somatic mutations were noted between the high-risk and low-risk groups. Finally, we also validated the expression of four CRLs in FHCs cell lines and CRC cell lines using qRT-PCR.

CONCLUSION

The signature composed of SNHG16, LENG8-AS1, LINC0225, and RPARP-AS1, which has better performance in predicting colorectal cancer prognosis and are promising biomarkers for prognosis prediction of CRC.

Construction and Validation of a Novel Prognosis Model in Colon Cancer Based on Cuproptosis-Related Long Non-Coding RNAs

Colon cancer (CC) is one of the most common (6%) malignancies and leading cause of cancer-associated death (more than 0.5 million) worldwide, which demands reliable prognostic biomarkers. Cuproptosis is a novel modality of regulated cell death triggered by the accumulation of intracellular copper. LncRNAs have been reported as prognostic signatures in different types of tumors. However, the correlation between cuproptosis-related lncRNAs (CRLs) and CC remains unclear. Data of CC patients were downloaded from public databases. The prognosis-associated CRLs were identified by co-expression analysis and univariate Cox. Least absolute shrinkage and selection operator were utilized to construct the CRLs-based prognostic signature in silico for CC patients. CRLs level was validated in human CC cell lines and patient tissues. ROC curve and Kaplan-Meier curve results revealed that high CRLs-risk score was associated with poor prognosis in CC patients. Moreover, the nomogram revealed that this model possessed a steady prognostic prediction capability with C-index as 0.68. More importantly, CC patients with high CRLs-risk score were more sensitive to eight targeted therapy drugs. The prognostic prediction power of the CRLs-risk score was further confirmed by cell lines, tissues and two independent CC cohorts. This study constructed a novel ten-CRLs-based prognosis model for CC patients. The CRLs-risk score is expected to serve as a promising prognostic biomarker and predict targeted therapy response in CC patients.

Emerging Role of Enhancer RNAs as Potential Diagnostic and Prognostic Biomarkers in Cancer

Enhancers are distal cis-acting elements that are commonly recognized to regulate gene expression via cooperation with promoters. Along with regulating gene expression, enhancers can be transcribed and generate a class of non-coding RNAs called enhancer RNAs (eRNAs). The current discovery of abundant tissue-specific transcription of enhancers in various diseases such as cancers raises questions about the potential role of eRNAs in disease diagnosis and therapy. This review aimed to demonstrate the current understanding of eRNAs in cancer research with a focus on the potential roles of eRNAs as prognostic and diagnostic biomarkers in cancers.

The Prediction of Necroptosis-Related lncRNAs in Prognosis and Anticancer Therapy of Colorectal Cancer

Background

Colorectal cancer is one of the most common gastrointestinal malignancies globally. Necroptosis has been proved to play a role in the occurrence and development of the tumor, which makes it a new target for molecular therapy. However, the role of necroptosis in colorectal cancer remains unknown yet. Our study aims to build a prognostic signature of necroptosis-related lncRNAs (nrlncRNAs) to predict the outcomes of patients with colorectal cancer and facilitate in anticancer therapy.

Method

We obtained RNA-seq and clinical data of colorectal adenocarcinoma from the TCGA database and got prognosis-related nrlncRNAs by univariate regression analysis. Then, we carried out the LASSO regression and multivariate regression analysis to build the prognostic signature, whose predictive ability was tested by the Kaplan-Meier as well as ROC curves and verified by the internal cohort. Moreover, we divided the cohort into 2 groups based on median of risk scores: high- and low-risk groups. By analyzing the difference in the tumor microenvironment, microsatellite instability, and tumor mutation burden between the two groups, we explored the potential chemotherapy and immunotherapy drugs.

Results

We screened out 9 nrlncRNAs and built a prognostic signature based on them. With its good prognostic ability, the risk scores can act as an independent prognostic factor for patients with colorectal cancer. The overall survival rate of patients in high-risk group was significantly higher than the low-risk one. Furthermore, risk scores can also give us hints about the tumor microenvironment and facilitate in predicting the response to the CTLA-4 blocker treatment and other chemotherapeutic agents with potential efficacy such as cisplatin and staurosporine.

Conclusions

In conclusion, our prognostic signature of necroptosis-related lncRNAs can facilitate in predicting the prognosis and response to the anticancer therapy of colorectal cancer patients.

A Hypoxia-Related lncRNA Signature Correlates with Survival and Tumor Microenvironment in Colorectal Cancer

The hypoxic tumor microenvironment and long noncoding RNAs (lncRNAs) are pivotal in cancer progression and correlate with the survival outcome of patients. However, the role of hypoxia-related lncRNAs (HRLs) in colorectal cancer (CRC) development remains largely unknown. Herein, we developed a hypoxia-related lncRNA signature to predict patients' survival and immune infiltration. The RNA-sequencing data of 500 CRC patients were obtained from The Cancer Genome Atlas (TCGA) dataset, and HRLs were selected using Pearson's analysis. Next, the Cox regression analysis was applied to construct a risk signature consisting of 9 HRLs. This signature could predict the overall survival (OS) of CRC patients with high accuracy in training, validation, and entire cohort. This signature was an independent risk factor and exerted predictive ability in different subgroups. Functional analysis revealed different molecular features between high- and low-risk groups. A series of drugs including cisplatin showed different sensitivities between the two groups. The expression pattern of immune checkpoints was also distinct between the two clusters in this model. Furthermore, the high-risk group had higher immune, stromal, and ESTIMATE score and a more repressive immune microenvironment than the low-risk group. Moreover, MYOSLID, one of the lncRNAs in this signature, could significantly regulate the proliferation, invasion, and metastasis of CRC.

Expression characteristics of long non-coding RNA in colon adenocarcinoma and its potential value for judging the survival and prognosis of patients: bioinformatics analysis based on The Cancer Genome Atlas database

Background

To investigate the expression characteristics of long non-coding RNA (lncRNA) in colon adenocarcinoma (COAD) and its potential value in predicting the prognosis of patient survival.

Methods

We downloaded COAD-related RNA sequencing (RNA-seq) data and patient survival data from The Cancer Genome Atlas (TCGA). The data were analyzed for lncRNA expression differences, subjected to Cox regression analysis for survival rate, and Kaplan-Meier (KM) survival curves were plotted to analyze the role of the key genes related to prognostic survival by pathway enrichment analysis.

Results

The data of 494 COAD clinical samples from TCGA were analyzed; 204 lncRNAs were differentially expressed, 156 were up-regulated, and 48 were down-regulated. The 10 genes with the most significant expression differences were Linc02418, Blacat1, ELFN1-AS1, CRNDE, AC002384.1, AL353801.1, LINC01645, AC073283.2, AC087379.1, and LINC00484. Cox regression analysis of 204 lncRNA genes showed that 23 lncRNA genes with significant effects on the prognosis and survival rate of COAD patients were obtained when P<0.05 was used as the threshold. With P≤0.001 as the threshold, the KM curves of 4 genes (Linc02257, Linc02474, Ac010789.1, Ac083967.1) were statistically significant (P<0.05). The gene Linc02257 was selected for Gene Ontology (GO) function and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis, and it was revealed that the inheritance of Linc02257-regulated gene expression was closely related to tumor development, such as collagen-containing extracellular matrix, organogenesis, activity of membrane protein receptors, and ion channel activity. The signaling pathways regulated by Linc02257 were also closely related to tumors, such as neuroactive ligand-receptor interaction, the PI3K-AKT signaling pathway, calcium signaling pathway, and protein digestion and absorption.

Conclusions

In COAD, lncRNA is differentially expressed and plays an important role in the disease regulation. It has potential application value in the diagnosis, targeted therapy, and prognosis of COAD patients.

The enhancer RNA ADCY10P1 is associated with the progression of ovarian cancer

BACKGROUND

Emerging evidence identifies enhancer RNAs (eRNAs) as a class of regulatory ncRNAs that can contribute to the transcription of target genes. In this study, we used an integrated data analysis method to identify the important role of eRNAs in ovarian cancer (OC).

METHODS

Gene expression profiles and clinical information from The Cancer Genome Atlas (TCGA) database were used for this study. Based on expression analysis using GEPIA2 gene and Kaplan-Meier survival was performed to ensure the significance of the selected enhancer RNA ADCY10P1 in OC. Next, we explored the correlation and clinical significance between ADCY10P1 and target gene NFYA. Furthermore, we evaluated the effects of overexpression of ADCY10P1 on the proliferation, migration, invasion and epithelial-mesenchymal transformation (EMT) of OC cell lines. We also investigated the biological function enrichment score of ADCY10P1 and verified it with OC cell lines. Finally, external validation was conducted, and the prognostic value of the ADCY10P1 in different tumors was demonstrated.

RESULTS

We selected the eRNA ADCY10P1 associated with OC prognosis, with NFYA as its predicted target gene. Low ADCY10P1 expression was found to be associated with poor overall survival, high histological grade, and advanced stage of OC. Additionally, overexpression of ADCY10P1 inhibited the proliferation, migration, invasion and EMT phenotype of OC cell lines. Furthermore, ADCY10P1 was observed to inhibit glycolysis and fatty acid metabolism, thereby affecting OC progression. Meanwhile, OC tissue samples were externally validated. In addition, the pan-cancer analysis revealed that ADCY10P1 had prognostic value in other cancers.

CONCLUSIONS

This study showed that ADCY10P1 plays a key role in OC progression and may facilitate prognosis prediction.

Identification of Enhancer RNA CDK6-AS1 as a Potential Novel Prognostic Biomarker in Gastric Cancer

Background: This study aimed to confirm the role of enhancer RNAs (eRNAs) in gastric cancer and their clinical utility.

Methods: We used Cox survival and relevance analysis to identify the candidate eRNAs in gastric cancer and performed Gene Ontology and Reactome pathway enrichment to determine the potential functions of eRNAs. Correlation between eRNA, tumor-infiltrating immune cells, and drug sensitivity was then analyzed.

Results:CDK6-AS1, a long non-coding RNA cyclin-dependent kinase 6, may serve as a poor potential prognostic biomarker candidate in gastric cancer with a positive correlation with its target gene CDK6. The low CDK6-AS1 expression group showed more frequent mutated driver genes than the high expression group. Moreover, CDK6-AS1 is involved in a key oncogenic pathway of the cell cycle and RNA transcription. CDK6-AS1 also shows dysregulations and associations with prognosis at the pan-cancer level. This eRNA may also be associated with immune cell infiltration and drug sensitivity.

Conclusion:CDK6-AS1 may be a potential prognostic biomarker and chemotherapeutic drug sensitivity predictor in gastric cancer.

Inflammatory Immune-Associated eRNA: Mechanisms, Functions and Therapeutic Prospects

The rapid development of multiple high-throughput sequencing technologies has made it possible to explore the critical roles and mechanisms of functional enhancers and enhancer RNAs (eRNAs). The inflammatory immune response, as a fundamental pathological process in infectious diseases, cancers and immune disorders, coordinates the balance between the internal and external environment of the organism. It has been shown that both active enhancers and intranuclear eRNAs are preferentially expressed over inflammation-related genes in response to inflammatory stimuli, suggesting that enhancer transcription events and their products influence the expression and function of inflammatory genes. Therefore, in this review, we summarize and discuss the relevant inflammatory roles and regulatory mechanisms of eRNAs in inflammatory immune cells, non-inflammatory immune cells, inflammatory immune diseases and tumors, and explore the potential therapeutic effects of enhancer inhibitors affecting eRNA production for diseases with inflammatory immune responses.

Enhancer RNAs (eRNAs) in Cancer: The Jacks of All Trades

Simple Summary

This review focuses on eRNAs and the several mechanisms by which they can regulate gene expression. In particular we describe here the most recent examples of eRNAs dysregulated in cancer or involved in the immune escape of tumor cells.

Abstract

Enhancer RNAs (eRNAs) are non-coding RNAs (ncRNAs) transcribed in enhancer regions. They play an important role in transcriptional regulation, mainly during cellular differentiation. eRNAs are tightly tissue- and cell-type specific and are induced by specific stimuli, activating promoters of target genes in turn. eRNAs usually have a very short half-life but in some cases, once activated, they can be stably expressed and acquire additional functions. Due to their critical role, eRNAs are often dysregulated in cancer and growing number of interactions with chromatin modifiers, transcription factors, and splicing machinery have been described. Enhancer activation and eRNA transcription have particular relevance also in inflammatory response, placing the eRNAs at the interplay between cancer and immune cells. Here, we summarize all the possible molecular mechanisms recently reported in association with eRNAs activity.

DCP1A is an unfavorable prognostic-related enhancer RNA in hepatocellular carcinoma

Long non-coding RNAs (lncRNAs) are associated with occurrence and development of tumors. Enhancer RNA (eRNA) is a special type of lncRNAs produced from transcription of enhancer elements. The function of eRNAs in tumors have elicited significant attention recently. However, the clinical significance and role of eRNAs in hepatocellular carcinoma (HCC) has not been fully explored. The current study sought to explore the expression level and prognostic value of key eRNAs in HCC. Bioinformatics analyses were used to explore expression levels of key prognostic eRNAs in HCC and their correlation with target genes. A total of 1580 enhancer RNAs (eRNAs) and 1791 target genes were initially retrieved from TCGA-LIHC gene expression database. Further analysis through survival and correlation analysis led to identification of 12 eRNAs and 13 target genes. The findings showed that DCP1A was the most prognosis-related eRNA. This eRNA showed the highest correlation with the target gene, PRKCD. Analysis showed that poor overall survival (OS) in HCC patients was correlated with high expression level of DCP1A (eRNA) and PRKCD (target gene). The up-regulation of DCP1A was associated with advanced tumor stage, larger tumor size and higher histological grade. The results of pan-cancer analysis showed that the expression of DCP1A was differentially expressed in 13 other types of tumor tissues and their corresponding normal tissues. This eRNA was highly expressed in digestive system tumors. Functional analysis showed that high expression level of DCP1A was implicated in multiple tumor-related signaling pathways. The findings of the current study indicated DCP1A is a novel biomarker that can be used as a potential therapeutic target for HCC patients.