Comprehensive analyses of correlation and survival reveal informative lncRNA prognostic signatures in colon cancer

Expression profile of long noncoding RNAs and comprehensive analysis of lncRNA-cisTF-DGE regulation in condyloma acuminatum

OBJECTIVE

To identify differentially expressed long noncoding RNAs (lncRNAs) in condyloma acuminatum (CA) and to explore their probable regulatory mechanisms by establishing coexpression networks.

METHODS

High-throughput RNA sequencing was performed to assess genome-wide lncRNA expression in CA and paired adjacent mucosal tissue. The expression of candidate lncRNAs and their target genes in larger CA specimens was validated using real-time quantitative reverse transcriptase polymerase chain reaction (RT‒qPCR). Furthermore, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were used for the functional enrichment analysis of these candidate lncRNAs and differential mRNAs. The coexpressed mRNAs of the candidate lncRNAs, calculated by Pearson's correlation coefficient, were also analysed using GO and KEGG analysis. In addition, the interactions among differentially expressed lncRNAs (DElncRNAs)-cis-regulatory transcription factors (cisTFs)-differentially expressed genes (DEGs) were analysed and their network was constructed.

RESULTS

A total of 546 lncRNAs and 2553 mRNAs were found to be differentially expressed in CA compared to the paired control. Functional enrichment analysis revealed that the DEGs coexpressed with DElncRNAs were enriched in the terms of cell adhesion and keratinocyte differentiation, and the pathways of ECM-receptor interaction, local adhesion, PI3K/AKT and TGF-ß signaling. We further constructed the network among DElncRNAs-cisTFs-DEGs and found that these 95 DEGs were mainly enriched in GO terms of epithelial development, regulation of transcription or gene expression. Furthermore, the expression of 3 pairs of DElncRNAs and cisTFs, EVX1-AS and HOXA13, HOXA11-AS and EVX1, and DLX6-AS and DLX5, was validated with a larger number of specimens using RT‒qPCR.

CONCLUSION

CA has a specific lncRNA profile, and the differentially expressed lncRNAs play regulatory roles in mRNA expression through cis-acting TFs, which provides insight into their regulatory networks. It will be useful to understand the pathogenesis of CA to provide new directions for the prevention, clinical treatment and efficacy evaluation of CA.

LncRNA ZNF667-AS1 Targets miR-523-3p/KIF5C Axis to Hinder Colon Cancer Progression

LncRNA ZNF667-AS1 plays an important role in the carcinogenesis and progression of various cancers. However, their role in colon cancer (CC) remains unclear. The expression of ZNF667-AS1, KIF5C, and miR-523-3p in CC cells and tissues was analyzed using RT-qPCR and western blotting. CCK-8 scratch-wound assay, western blotting, and flow cytometry were conducted to investigate the malignant activity of CC in vitro. Luciferase reporter, RNA pull-down, and Ago2 immunoprecipitation (RIP) experiments were conducted to ascertain the association of miR-523-3p with ZNF667-AS1 and KIF5C 3'UTR. Xenograft tumor experiments were also performed. CC cells and tissues showed low expression of NF667-AS1 and KIF5C and elevated expression of miR-523-3p. ZNF667-AS1 overexpression attenuates proliferation and migration of CC cells, restores inactivated apoptosis in vitro, and inhibits tumor growth in vivo. MiR-523-3p targets both ZNF667-AS1 and the KIF5C 3'UTR. ZNF667-AS1 overexpression in SW480 and SW620 cells attenuated the oncogenic effect of miR-523-3p in CC. However, this attenuating effect was counteracted by KIF5C overexpression. ZNF667-AS1 sequestered miR-523-3, reducing miR-523-3p-mediated inhibition of KIF5C expression, thereby repressing colon carcinogenesis in vitro. Our findings shed light on a novel anticancer strategy that could potentially combat CC.

Lymphovascular invasion in colorectal cancers: can we predict it preoperatively?

PURPOSE

This study aimed to investigate preoperative predictors of lymphovascular invasion (LVI), which is a poor prognostic factor usually detected postoperatively in patients with colorectal cancer.

METHODS

Results for all patients operated on for colorectal cancer between January 1, 2006, and December 31, 2021, were retrospectively analyzed. Potential preoperative factors and postoperative pathology results were recorded. The patients were categorized as those with LVI and those without LVI. Potential factors that may be associated with LVI were compared between the 2 groups.

RESULTS

The study included 335 patients. The incidence of LVI was 3.11 times higher in patients with ascending colon tumors (odds ratio [OR], 3.11; 95% confidence interval [CI], 1.34-7.23; P=0.008) and 4.28 times higher in those with metastatic tumors (OR, 4.28; 95% CI, 2.18-8.39; P<0.001). Diabetes mellitus was inversely related to LVI in colorectal cancer patients; specifically, LVI was 56% less common in colorectal cancer patients with diabetes mellitus, irrespective of its duration (OR, 0.44; 95% CI, 0.25-0.76; P<0.001).

CONCOUSION

The presence of preoperative LVI in colorectal cancer patients is difficult to predict. In particular, the effect of the effect of factors such as chronic disease accompanied by microvascular pathologies on LVI is still unclear. Advances in the neoadjuvant treatment of colorectal cancer patients, who are becoming more widespread every day, will encourage the investigation of different methods of preoperatively predicting LVI as a poor prognostic factor in these patients.

Identification of associations between lncRNA and drug resistance based on deep learning and attention mechanism

Introduction

Abnormal lncRNA expression can lead to the resistance of tumor cells to anticancer drugs, which is a crucial factor leading to high cancer mortality. Studying the relationship between lncRNA and drug resistance becomes necessary. Recently, deep learning has achieved promising results in predicting biomolecular associations. However, to our knowledge, deep learning-based lncRNA-drug resistance associations prediction has yet to be studied.

Methods

Here, we proposed a new computational model, DeepLDA, which used deep neural networks and graph attention mechanisms to learn lncRNA and drug embeddings for predicting potential relationships between lncRNAs and drug resistance. DeepLDA first constructed similarity networks for lncRNAs and drugs using known association information. Subsequently, deep graph neural networks were utilized to automatically extract features from multiple attributes of lncRNAs and drugs. These features were fed into graph attention networks to learn lncRNA and drug embeddings. Finally, the embeddings were used to predict potential associations between lncRNAs and drug resistance.

Results

Experimental results on the given datasets show that DeepLDA outperforms other machine learning-related prediction methods, and the deep neural network and attention mechanism can improve model performance.

Dicsussion

In summary, this study proposes a powerful deep-learning model that can effectively predict lncRNA-drug resistance associations and facilitate the development of lncRNA-targeted drugs. DeepLDA is available at https://github.com/meihonggao/DeepLDA.

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.

The Role of NcRNAs to Regulate Immune Checkpoints in Cancer

At present, the incidence of cancer is becoming more and more common, but its treatment has always been a problem. Although a small number of cancers can be treated, the recurrence rates are generally high and cannot be completely cured. At present, conventional cancer therapies mainly include chemotherapy and radiotherapy, which are the first-line therapies for most cancer patients, but there are palliatives. Approaches to cancer treatment are not as fast as cancer development. The current cancer treatments have not been effective in stopping the development of cancer, and cancer treatment needs to be imported into new strategies. Non-coding RNAs (ncRNAs) is a hot research topic at present. NcRNAs, which include microRNAs (miRNAs), circular RNAs (circRNAs), and long non-coding RNAs (lncRNAs), participate in all aspects of cancer biology. They are involved in the progression of tumors into a new form, including B-cell lymphoma, glioma, or the parenchymal tumors such as gastric cancer and colon cancer, among others. NcRNAs target various immune checkpoints to affect tumor proliferation, differentiation, and development. This might represent a new strategy for cancer treatment.

Establishment and validation of a prognostic model based on HRR-related lncRNAs in colon adenocarcinoma

BACKGROUND

Colon cancer (CRC) is the second leading cause of cancer-related death, and its 5-year survival rate is very low. Homologous recombination repair (HRR) is deficient in most colon cancer. Some long non-coding RNAs (lncRNAs) participate in tumorigenesis of colon cancer through the HRR pathway. We aim to establish a prognostic model based on the HRR-related lncRNAs, expecting to provide a new strategy for precision treatment development in colon cancer.

METHODS

Pearson's correlation was used to identify the HRR-related prognostic lncRNAs in the TCGA-COAD cohort. The TCGA-COAD cohort was randomized into the training set and the testing set. LASSO Cox regression was used to establish the model which was analyzed in the training set and validated in the testing set and the entire TCGA-COAD cohort. Finally, we explored the potential biological function of our model.

RESULTS

A prognostic model was established based on nineteen HRR-related lncRNAs in the training set. COAD patients were scored by the uniform formula and divided into high-risk and low-risk groups based on the median risk score. Patients with high-risk scores indicated poor prognosis in the training set, and the result was confirmed in the testing set and the entire TCGA-COAD cohort (all p < 0.01). Multivariable analysis suggested that our model was an independent factor for overall survival in COAD. The area under the curve (AUC) and C-index indicated that our model had better predictive efficiency than other indicators in the TCGA-COAD cohort. Functional enrichment analysis suggested that our model was associated with the MAPK pathway in COAD. Besides, our model was positively correlated with the HRD scores.

CONCLUSION

A new prognostic model was established based on nineteen HRR-related lncRNAs which had excellent predictive efficiency on the prognosis of COAD. This prognostic model may provide a new strategy for prognostic prediction of COAD patients.

ImReLnc: Identifying Immune-Related LncRNA Characteristics in Human Cancers Based on Heuristic Correlation Optimization

Long non-coding RNAs (lncRNAs) play critical roles in cancer through gene expression and immune regulation. Identifying immune-related lncRNA (irlncRNA) characteristics would contribute to dissecting the mechanism of cancer pathogenesis. Some computational methods have been proposed to identify irlncRNA characteristics in human cancers, but most of them are aimed at identifying irlncRNA characteristics in specific cancer. Here, we proposed a new method, ImReLnc, to recognize irlncRNA characteristics for 33 human cancers and predict the pathogenicity levels of these irlncRNAs across cancer types. We first calculated the heuristic correlation coefficient between lncRNAs and mRNAs for immune-related enrichment analysis. Especially, we analyzed the relationship between lncRNAs and 17 immune-related pathways in 33 cancers to recognize the irlncRNA characteristics of each cancer. Then, we calculated the Pscore of the irlncRNA characteristics to evaluate their pathogenicity levels. The results showed that highly pathogenic irlncRNAs appeared in a higher proportion of known disease databases and had a significant prognostic effect on cancer. In addition, it was found that the expression of irlncRNAs in immune cells was higher than that of non-irlncRNAs, and the proportion of irlncRNAs related to the levels of immune infiltration was much higher than that of non-irlncRNAs. Overall, ImReLnc accurately identified the irlncRNA characteristics in multiple cancers based on the heuristic correlation coefficient. More importantly, ImReLnc effectively evaluated the pathogenicity levels of irlncRNAs across cancer types. ImReLnc is freely available at https://github.com/meihonggao/ImReLnc.

Circ_0026416 downregulation blocks the development of colorectal cancer through depleting MYO6 expression by enriching miR-545-3p

Background

Emerging evidence reveals that the initiation and development of human cancers, including colorectal cancer (CRC), are associated with the deregulation of circular RNAs (circRNAs). Our study intended to disclose the role of circ_0026416 in the malignant behaviors of CRC.

Methods

The detection for circ_0026416 expression, miR-545-3p expression, and myosin VI (MYO6) mRNA expression was performed using quantitative real-time PCR (qPCR). CCK-8 assay, colony formation assay, transwell assay, and flow cytometry assay were applied for functional analysis to monitor cell proliferation, migration, invasion, and apoptosis. The protein levels of MYO6 and epithelial mesenchymal-transition (EMT) markers were detected by western blot. Mouse models were used to determine the role of circ_0026416 in vivo. The potential relationship between miR-545-3p and circ_0026416 or MYO6 was verified by dual-luciferase reporter assay and RIP assay.

Results

The expression of circ_0026416 was increased in CRC tumor tissues and cell lines. Circ_0026416 downregulation inhibited CRC cell proliferation, colony formation, migration, invasion, and EMT but induced cell apoptosis in vitro, and circ_0026416 knockdown also blocked tumor growth in vivo. MiR-545-3p was a target of circ_0026416, and rescue experiments indicated that circ_0026416 knockdown blocked CRC development by enriching miR-545-3p. In addition, miR-545-3p targeted MYO6 and inhibited MYO6 expression. MiR-545-3p enrichment suppressed CRC cell malignant behaviors by sequestering MYO6. Importantly, circ_0026416 knockdown depleted MYO6 expression by enriching miR-545-3p.

Conclusion

Circ_0026416 downregulation blocked the development of CRC through depleting MYO6 expression by enriching miR-545-3p.

Highlights

Circ_0026416 downregulation inhibits CRC development in vitro and in vivo.

Circ_0026416 regulates the expression of MYO6 by targeting miR-545-3p.

Circ_0026416 governs the miR-545-3p/MYO6 axis to regulate CRC progression.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12957-021-02407-y.

LINC01224 promotes colorectal cancer progression through targeting miR-485-5p/MYO6 axis

Background

Long noncoding RNAs (lncRNAs) are related to colorectal cancer (CRC) development. However, the role and mechanism of lncRNA LINC01224 in CRC development are largely unknown.

Methods

LINC01224, Yin Yang 1 (YY1), microRNA (miR)-485-5p, and myosins of class VI (MYO6) levels were examined using quantitative reverse transcription polymerase chain reaction and western blotting. Functional analyses were processed through CCK-8, colony formation, flow cytometry, transwell, and xenograft analyses. Dual-luciferase reporter, chromatin immunoprecipitation (ChIP), RNA immunoprecipitation, and pull-down assays were conducted to analyze the binding interaction.

Results

LINC01224 abundance was elevated in CRC tissue samples and cell lines. Elevated LINC01224 might indicate the lower 5-year overall survival in 52 CRC patients. LINC01224 was upregulated via the transcription factor YY1. LINC01224 knockdown restrained CRC cell proliferation, migration, and invasion and increased apoptosis. MiR-485-5p was sponged by LINC01224, and miR-485-5p downregulation relieved the influence of LINC01224 interference on CRC progression. MYO6 was targeted via miR-485-5p and regulated via LINC01224/miR-485-5p axis. MiR-485-5p overexpression suppressed CRC cell proliferation, migration, and invasion and facilitated apoptosis. MYO6 upregulation mitigated the role of miR-485-5p. LINC01224 knockdown decreased xenograft tumor growth.

Conclusion

YY1-induced LINC01224 regulates CRC development via modulating miR-485-5p/MYO6 axis.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12957-021-02389-x.

Importance of Circ0009910 in colorectal cancer pathogenesis as a possible regulator of miR-145 and PEAK1

Introduction

Colorectal cancer (CRC) is one of the most frequent neoplasms in the world. Based on the emerging role of noncoding RNAs, particularly circular RNAs in pathogenesis of cancers, we designed this study to inspect the expression levels of a circ0009910-mediated regulatory pathway in colorectal cancer.

Methods

After bioinformatics analyses and construction of putative circ0009910/ miR-145-5p/PEAK1 pathway, the expression levels of these components were evaluated in 50 CRC tissues and adjacent specimens by quantitative real-time PCR. Moreover, we appraised the correlation coefficients between these transcripts and calculated the correlation between circ0009910 expression levels with clinicopathological features of patients.

Results

Circ0009910 and PEAK1 were significantly upregulated, while miR-145-5p was decreased in CRC samples compared with adjacent tissues (p < 0.05). Moreover, statistically significant correlations were observed between expression levels of circ0009910, miR-145-5p, and PEAK1. We also reported considerable correlations between circ0009910 expression and clinicopathological parameters including sex and perineural invasion. Finally, ROC curve analysis showed circ0009910 level as a discriminative biomarker for CRC.

Conclusion

For the first time, we could introduce circ0009910 as an important biomarker in CRC. Collectively, this investigation helped us to identify a newly diagnosed pathway in CRC that can be a potential axis for designing effective drugs for treatment of CRC patients.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12957-021-02378-0.

Effects of LncRNA MEG3 on immunity and autophagy of non-small cell lung carcinoma through IDO signaling pathway

Background

The study was done to investigate the effect of LncRNA MEG3 on the immunity and autophagy of non-small cell lung carcinoma through the IDO signaling pathway.

Methods

A total of 78 cases of early NSCLC patients (research group; RG) and 69 cases of health controls (control group; CG) during the same time were included. The contents of LncRNA MEG3 and miR-543 in peripheral blood and tissues and their diagnostic values for NSCLC were detected. The relationship between LncRNA MEG3 and miR-543 and their posttreatment contents and influence on the prognosis of NSCLC patients were tested. The expression of LncRNA MEG3, miR-543, and IDO (IDO1, IDO2, and TDO proteins) in the lung tissue of rats and the immune function in the CG and the RG were detected. The effects of LncRNA MEG3 and miR-543 on the biological behavior of NSCLC cells were determined. The role of LncRNA MEG3, miR-543, and IDO in NSCLC was verified.

Results

LncRNA MEG3 was low in peripheral blood and tissues, while miR-543 was high (P < 0.05); both had good diagnostic values for NSCLC (P < 0.05). LncRNA MEG3 had a negative correlation with miR-543 (P < 0.05) and influenced the prognosis of NSCLC patients (P < 0.05). LncRNA MEG3 in the lung tissue of rats using IDO inhibitor was elevated compared with that of lung carcinoma model rats (P < 0.05). The level of miR-543 was declined compared with that of lung carcinoma model rats (P < 0.05). The levels of IDO1, IDO2, and TDO proteins were evidently declined compared with those of lung carcinoma model rats (P < 0.05). Compared with lung carcinoma model rats, CD3⁺, CD4⁺, and CD4⁺/CD8⁺ of IDO inhibitor rats were elevated, while CD8⁺ was declined (P < 0.05). Cell proliferation and invasion ability and IDO1, IDO2, TDO, Beclin-1, and LC3-II proteins were declined in the sh-LncRNA MEG3 group (P < 0.05), while those in the mimics-miR-543 group were evidently elevated (P < 0.05). However, the double luciferase activity detection and RIP experiment confirmed that there was targeted regulation among them (P < 0.05).

Conclusion

MEG3 has low expression in NSCLC and affects the immunity and autophagy of NSCLC cells via regulating the miR-543/IDO signaling pathway, which is effective for the treatment of NSCLC.

The downregulation of NCXs is positively correlated with the prognosis of stage II-IV colon cancer

Purpose

Colon cancer (CC) is a very common gastrointestinal tumor that is prone to invasion and metastasis in the late stage. This study aims to observe the expression of Na⁺/Ca²⁺ exchangers (NCXs) and analyze the correlation between NCXs and the prognosis of CC.

Methods

Specimens of 111 stage II–IV CC patients were collected. We used western blotting, qPCR, and immunohistochemical staining to observe the distributions and expression levels of NCX isoforms (NCX1, NCX2, and NCX3) in CC and distal normal tissues. Cox proportional hazards models were used to assess prognostic factors for patients.

Results

The expression of NCXs in most tumor specimens was lower than that in normal tissues. The NCX expression levels in tumor tissues from the primary tumor, local lymph node metastasis sites, and distant liver metastasis sites were increasingly significantly lower than those in normal tissues. The results of the Kaplan-Meier survival curves showed that the downregulation of any NCX isoform was closely related to the worse prognosis of advanced CC.

Conclusion

NCXs can be used as independent prognostic factors for CC. Our research results are expected to provide new targets for the treatment of CC.