Immune-Related Gene Expression Analysis Revealed Three lncRNAs as Prognostic Factors for Colon Cancer

Identification of ASMTL-AS1 and LINC02604 lncRNAs as novel biomarkers for diagnosis of colorectal cancer

PURPOSE

Colorectal cancer is one of the major leading causes of death worldwide, and available treatments for advanced colorectal cancer are not successful. Therefore, early detection of colorectal cancer is essential to improve patient survival, and biomarkers are potential tools to achieve this goal. Considering the key role of lncRNAs in cancers, the aim of this study is to identify lncRNAs involved in colorectal cancer as new potential prognosis biomarkers for CRC.

METHODS

In this observational study, gene expression data obtained from the TCGA database were analyzed, Identification of differentially expressed mRNAs, miRNAs, and lncRNAs was performed, and ceRNA network was drawn. Also, survival analysis of patients was performed in order to identify potential biomarkers related to the diagnosis and prognosis of colon cancer. After confirming the results using the GSE39582 dataset, the expression of target lncRNAs in colorectal tumor tissues was also investigated to confirm the bioinformatic data.

RESULTS

Analysis of the TCGA data showed that the expression of three lncRNAs-SNHG7, ASMTL-AS1, and LINC02604-that had the highest interaction with other miRNAs and mRNAs identified based on the ceRNA network was increased in colorectal cancer. Also, based on the ceRNA network, three microRNAs, hsa-let-7d-5p, hsa-mir-92a-3p, and hsa-mir-423-5p, and eight mRNAs, including CPA4, MSI2, RRM2, IGF2BP1, ONECUT2, HMGA1, SOX4, and SRM, were associated with all three mentioned lncRNAs, the expression of microRNAs was decreased and the expression of mRNAs was increased. By enrichment analysis, it was found that the target lncRNAs are involved in the processes of cell proliferation, apoptosis, and metastasis, indicating their importance in the development and malignancy of colorectal cancer. Furthermore, Kaplan-Meier analysis showed a significant increase in mortality in patients with higher expression levels of these lncRNAs. Analysis of the GSE39582 dataset, and real-time RT-PCR analysis, confirmed our bioinformatic results. Also, ROC analysis showed that SNHG7 was a relatively good promising biomarker (AUC = 0.73, p value = 0.02), while ASMTL-AS1 (AUC = 0.92, p value < 0.0001) and LINC02604 (AUC = 1.00, p value < 0.0001) emerged as excellent diagnostic biomarkers in colorectal cancer.

CONCLUSION

It seems that increased expression of lncRNAs ASMTL-AS1 and LINC02604 can serve as molecular biomarkers for CRC, possibly through the sponge hsa-let-7d-5p, hsa-mir-92a-3p, and hsa-mir-423 5p, which increases target mRNAs, which are effective in the carcinogenesis process.

Biological Roles and Pathogenic Mechanisms of LncRNA MIR4435-2HG in Cancer: A Comprehensive Review

The long non-coding RNA MIR4435-2HG has been confirmed to play a crucial regulatory role in various types of tumors. As a novel type of non-coding RNA, MIR4435-2HG plays a key role in regulating the expression of tumor-related genes, interfering with cellular signaling pathways, and affecting tumor immune evasion. Its unique structure allows it to regulate the expression of various tumor-related genes through different pathways, participating in the regulation of tumor signaling pathways, such as regulating the expression of oncogenes and tumor suppressor genes, influencing the biological behaviors of proliferation, metastasis, and apoptosis in tumors. Numerous studies have found a high expression of MIR4435-2HG in various tumor tissues, closely related to the clinical pathological characteristics of tumors, such as staging, lymph node metastasis and prognosis. Some studies have discovered that MIR4435-2HG can regulate the sensitivity of tumor cells to chemotherapy drugs, affecting tumor cell drug resistance. This provides new insights into overcoming tumor drug resistance by regulating MIR4435-2HG. Therefore, studying its molecular mechanisms, expression regulation, and its relationship with the clinical features of tumors is of great significance for revealing the mechanisms of tumor occurrence and developing new therapeutic targets.

Construction of a novel MPT-driven necrosis-related lncRNAs signature for prognosis prediction in laryngeal squamous cell carcinoma

Mitochondrial permeability transition (MPT)-driven necrosis, a type of programmed cell death, has recently gained much attention in a variety of tumor types. Few studies have been performed to explore the role of MPT-driven necrosis-related lncRNAs (MPTDNRlncRNAs) in laryngeal squamous cell carcinoma (LSCC). The purpose of our study is to screen MPTDNRlncRNAs with prognostic value and to explore their potential roles in LSCC. The RNA-sequencing data and the corresponding clinical data of LSCC patients were obtained from the TCGA database, and those MPT-driven necrosis-related genes were extracted from the Gene Set Enrichment Analysis (GSEA) database. We identified MPTDNRlncRNAs differentially expressed in LSCC. Also, we gained MPT-driven necrosis-related prognostic lncRNAs by univariate cox regression analysis. A novel MPTDNRlncRNAs signature was constructed by LASSO-COX. The accuracy and utility of the MPTDNRlncRNAs signature were evaluated via a variety of statistical methods. Multiple bioinformatics tools were used to explore the underlying difference in biological functions and signaling pathways between the different risk groups. The expressions levels of MPTDNRlncRNAs were analyzed using RT-qPCR in LSCC cell line. Finally, we identified A 5 MPTDNRlncRNAs signature in LSCC. Our prognostic model demonstrated an efficient ability to predict outcomes. The proportion difference of immune cells in the subgroups were significant, such as M0 macrophage and T follicular helper cells. The in vitro experiments suggested that our MPTDNRlncRNAs were significantly different. This 5 MPTDNRlncRNAs signature is a prognostic biomarker for LSCC. More importantly, the novel biologic prognostic model can be utilized for personalized immunotherapy in LSCC patients.

Development and validation of ferroptosis-related lncRNA signature and immune-related gene signature for predicting the prognosis of cutaneous melanoma patients

Ferroptosis, a form of cell death caused by iron-dependent peroxidation of lipids, plays an important role in cancer. Recent studies have shown that long noncoding RNAs (lncRNAs) are involved in the regulation of ferroptosis in tumor cells and are also closely related to tumor immunity. Immune cell infiltration in the tumor microenvironment affects the prognosis and clinical outcome of immunotherapy in melanoma patients, and immune cell classification may be able to accurately predict the prognosis of melanoma patients. However, the prognostic value of ferroptosis-related lncRNAs (FRLs) in melanoma has not been thoroughly explored, and it is difficult to define the immune characteristics of melanoma. We used The Cancer Genome Atlas (TCGA), the Genotype-Tissue Expression (GTEx) database, and the FerrDb database to identify FRLs. FRLs with prognostic value were evaluated in an experimental cohort utilizing univariate, LASSO (least absolute shrinkage and selection operator) and multivariate Cox regression, followed by in vitro assays evaluating the expression levels and the biological functions of three candidate FRLs. Kaplan-Meier (K-M) and receiver operating characteristic (ROC) curve analyses were used to assess the validity of the risk model, and the drug sensitivity of FRLs was examined by drug sensitivity analysis. The differentially expressed genes between the high- and low-risk groups in the risk model were enriched in the immune pathway, and we further found immune gene signatures (IRGs) that could predict the prognosis of melanoma patients through a series of methods including single-sample Gene Set Enrichment Analysis (ssGSEA). Finally, two GEO cohorts were used to validate the predictive accuracy and reliability of these two signature models. Our findings suggest that FRLs and IRGs have the potential to predict the prognosis of patients with cutaneous melanoma.

Prognosis Signature of Cuprotosis-Related lncRNAs Associated with Kidney Renal Clear Cell Carcinoma

Cuprotosis is a novel cell death mechanism that can be explored to treat various tumors. A few studies on the role of cuprotosis-related long noncoding RNA (lncRNA) in the development and prognosis of kidney renal clear cell carcinoma (KIRC) have been reported. We aimed to study the relationship between the prognosis of patients suffering from KIRC and lncRNAs associated with cuprotosis. The Cancer Genome Atlas (TCGA) database was analyzed, and the transcriptome data and clinical information on the patients with KIRC were obtained. The cuprotosis-related lncRNAs were identified by using Pearson correlation analysis, and the significant changes in the lncRNAs associated with KIRC were studied by conducting the T-test. The cuprotosis-related lncRNAs with KIRC prognostic values were identified by using the univariate Cox analysis, least absolute shrinkage and selection operator (LASSO), and support vector machine (SVM) methods. A prognostic marker composed of three cuprotosis-related lncRNAs was identified following the multivariate regression analysis method. Patients with KIRC were divided into two groups based on the expression characteristics of three cuprotosis-related lncRNAs by using the K nearest neighbor (KNN) cluster analysis method. Significant differences in survival were observed between the two groups. In addition, the results obtained following the independent prognostic analysis of the risk score (RS) and clinical correlation revealed that the three cuprotosis-related lncRNA prognostic markers could accurately predict the prognosis of patients with KIRC. The results reported herein provide new insights into the pathogenesis of KIRC and the contribution of lncRNAs associated with cuprotosis. The results also helped identify a prognostic indicator that could potentially provide information for KIRC treatment.

The m7G-Related Long Noncoding RNA Signature Predicts Prognosis and Indicates Tumour Immune Infiltration in Colon Cancer

With high morbidity and mortality, colon cancer (CC) is considered as one of the most often diagnosed cancers around the world. M7G-related lncRNA may provide a regulatory function in the formation of CC, but the principle of regulation is still unclear. The purpose of this research was to establish a novel signature that may be used to predict survival and tumour immunity in CC patients. Data about CC in TCGA was collected for analysis, coexpression analysis and univariate Cox analysis were used to screen prognostic m7G-related lncRNAs. A consensus clustering analysis based on prognostic m7G-related lncRNAs was applied, and a prognosis model based on least absolute shrinkage and selection operator (LASSO) regression analysis was established. Independent prognostic analysis, nomogram, PCA, clinicopathological correlation analysis, TMB, survival analysis, immune correlation analysis, qRT–PCR and clinical therapeutic compound prediction were also applied. 90 prognostic m7G-related lncRNAs were found, GO and KEGG analysis showed that prognostic m7G-related lncRNAs were mainly related to cell transcription and translation. The results of the consensus clustering analysis revealed substantial disparities in survival prognosis and tumour immune infiltration between two clusters. We built a risk model with 21 signature m7G-related lncRNAs, patients in the high-risk group had a considerably poorer prognosis than those in the low-risk group. Independent prognostic analysis confirmed that patients’ prognosis was linked to their tumour stage and risk score. PCA, subgroups with distinct clinicopathological characteristics were studied for survival, multi-index ROC curve, c-index curve, the survival analysis of TMB, and model comparison tested the reliability of risk model. A tumour immunoassay revealed a substantial difference in immune infiltration between high-risk and low-risk individuals. Five chemicals were eliminated, and qRT–PCR indicated that the four lncRNAs were expressed differently. Overall, m7G-related lncRNA is closely related to colon cancer and the 21 signature lncRNAs risk model can efficiently evaluate the prognosis of CC patients, which has a possible positive consequence for the future diagnosis and therapy of CC.

MIR4435-2HG：A tumor-associated long non-coding RNA

BACKGROUND

It is well known that the changes in the expression level of LncRNA can affect the progression of tumors, which has caused a great upsurge of research in recent years. More and more LncRNA has been proved to take effect on a series of cancers and can promote tumor growth, migration and invasion. In this review, we aim to clarify the pathophysiological functions of LncRNA -MIR4435-2 HG in multiple tumors can be elucidated.

METHODS

By consulting the literature through PubMed, this paper summarizes the relationship between MIR4435-2HG and tumor and its role in the occurrence and development of cancer, and also expounds the specific molecular mechanism of the effect of MIR4435-2HG on cancer.

RESULTS

MIR4435-2HG can function as an oncogene in a variety of cancers. The expression level was abnormally elevated in a series of cancers, consisting of melanoma gastric cancer, head and neck squamous cell carcinoma, oral squamous cell carcinoma, lung cancer, cervical cancer, prostate carcinoma, ovarian cancer, breast cancer, hepatocellular Carcinoma, clear cell renal cell carcinoma malignant, glioma and colorectal cancer. Moreover, MIR4435-2HG is related to the poor prognosis of a variety of cancers. MIR4435-2HG can also affect tumor proliferation, invasion and apoptosis. In addition, MIR4435-2HG can also enhance the metabolic function of myeloid dendritic cells of elite HIV-1 controllers.

CONCLUSION

MIR4435-2HG affects the development of a variety of cancers. It can act as a clinical marker for early tumor diagnosis and takes effects to tumor targeted therapy.

Comprehensive Analysis of Necroptosis-Related Long Noncoding RNA Immune Infiltration and Prediction of Prognosis in Patients With Colon Cancer

Colon cancer (CC) is one of the most frequent malignancies in the world, with a high rate of morbidity and death. In CC, necroptosis and long noncoding RNA (lncRNAs) are crucial, but the mechanism is not completely clear. The goal of this study was to create a new signature that might predict patient survival and tumor immunity in patients with CC. Expression profiles of necroptosis-related lncRNAs in 473 patients with CC were retrieved from the TCGA database. A consensus clustering analysis based on differentially expressed (DE) genes and a prognostic model based on least absolute shrinkage and selection operator (LASSO) regression analysis were conducted. Clinicopathological correlation analysis, expression difference analysis, PCA, TMB, GO analysis, KEGG enrichment analysis, survival analysis, immune correlation analysis, prediction of clinical therapeutic compounds, and qRT–PCR were also conducted. Fifty-six necroptosis-related lncRNAs were found to be linked to the prognosis, and consensus clustering analysis was performed. There were substantial variations in survival, immune checkpoint expression, clinicopathological correlations, and tumor immunity among the different subgroups. Six lncRNAs were discovered, and patients were split into high-risk and low-risk groups based on a risk score generated using these six lncRNAs. The survival time of low-risk patients was considerably longer than that of high-risk patients, indicating that these lncRNAs are directly associated with survival. The risk score was associated with the tumor stage, infiltration depth, lymph node metastasis, and distant metastasis. After univariate and multivariate Cox regression analysis, the risk score and tumor stage remained significant. Cancer- and metabolism-related pathways were enriched by KEGG analyses. Immune infiltration was shown to differ significantly between high- and low-risk patients in a tumor immunoassay. Eight compounds were screened out, and qRT–PCR confirmed the differential expression of the six lncRNAs. Overall, in CC, necroptosis-related lncRNAs have an important function, and the prognosis of patients with CC can be predicted by these six necroptosis-related lncRNAs. They may be useful in the future for customized cancer therapy.