The lncRNA ALMS1-IT1 may promote malignant progression of lung adenocarcinoma via AVL9-mediated activation of the cyclin-dependent kinase pathway

Identification of novel disulfidptosis-related lncRNA signatures to predict the prognosis and immune microenvironment of skin cutaneous melanoma patients

BACKGROUND

Skin cutaneous melanoma (SKCM) is an aggressive form of malignant melanoma with poor prognosis and high mortality rates. Disulfidptosis is a newly discovered cell death regulatory mechanism caused by the abnormal accumulation of disulfides. This unique pathway is guiding significant new research to understand cancer progression for targeted treatment. However, the correlation between disulfidptosis with long non-coding RNAs (lncRNAs) in SKCM remains unknown at present.

METHODS

The Cancer Genome Atlas database furnished lncRNA expression data and clinical information for SKCM patients. Pearson correlation and Cox regression analyses identified disulfidptosis-related lncRNAs associated with SKCM prognosis. ROC curves and a nomogram validated the model. TME, immune infiltration, GSEA analysis, immune checkpoint gene expression profiling, and drug sensitivity were assessed in high and low-risk groups. Consistent clustering categorized SKCM patients for personalized clinical treatment guidance.

RESULTS

A total of twelve disulfidptosis-related lncRNAs were identified for the development of prognosis prediction models. The area under the curve (AUC) values of the ROC curve and the nomogram provided reliable discrimination to evaluate the prognostic potential for SKCM patients. The TME played a crucial role in tumorigenesis, progression and prognosis, and the risk scores were closely related to immune cell infiltration. Meanwhile, the combination of chemotherapy, targeted therapy, and immunotherapy was recommended for low-risk patients based on drug sensitivity and immune efficacy analyses.

CONCLUSION

We identified a risk model of twelve disulfidptosis-related lncRNAs that could be used to predict the prognosis of SKCM patients and help guide immunotherapy and chemotherapy for personalized treatment plans.

lncRNAs and cyclin-dependent kinases: Unveiling their critical roles in cancer progression

Long non-coding RNAs (lncRNAs) are a diverse class of RNA molecules that do not code for proteins but play critical roles in gene regulation. One such role involves the modulation of cell cycle progression and proliferation through interactions with cyclin-dependent kinases (CDKs), key regulators of cell division. Dysregulation of CDK activity is a hallmark of cancer, contributing to uncontrolled cell growth and tumor formation. These lncRNA-CDK interactions are part of a complex network of molecular mechanisms underlying cancer pathogenesis, involving various signaling pathways and regulatory circuits. Understanding the interplay between lncRNAs, CDKs, and cancer biology holds promise for developing novel therapeutic strategies targeting these molecular targets for more effective cancer treatment. Furthermore, targeting CDKs, key cell cycle progression and proliferation regulators, offers another avenue for disrupting cancer pathways and overcoming drug resistance. This can open new possibilities for individualized treatment plans and focused therapeutic interventions.

Predictive significance of glycolysis-associated lncRNA profiles in colorectal cancer progression

BACKGROUND

The Warburg effect is a hallmark characteristic of colorectal cancer (CRC). Despite extensive research, the role of long non-coding RNAs (lncRNAs) in influencing the Warburg effect remains incompletely understood. Our study aims to identify lncRNAs that may modulate the Warburg effect by functioning as competing endogenous RNAs (ceRNAs).

METHODS

Utilizing bioinformatics approaches, we extracted glycolysis-associated gene data from the Kyoto Encyclopedia of Genes and Genomes (KEGG) and identified 101 glycolysis-related lncRNAs in CRC. We employed Univariable Cox regression, Least Absolute Shrinkage and Selection Operator (LASSO) regression analysis, and Multivariable Cox regression to develop a prognostic model comprising four glycolysis-linked lncRNAs. We then constructed a prognostic nomogram integrating this lncRNA model with other relevant clinical parameters.

RESULTS

The prognostic efficacy of our four-lncRNA signature and its associated nomogram was validated in both training and validation cohorts. Functional assays demonstrated significant glycolysis and hexokinase II (HK2) inhibition following the silencing of RUNDC3A - AS1, a key lncRNA in our prognostic signature, highlighting its regulatory importance in the Warburg effect.

CONCLUSIONS

Our research illuminates the critical role of glycolysis-centric lncRNAs in CRC. The developed prognostic model and nomogram underscore the pivotal prognostic and regulatory significance of the lncRNA RUNDC3A - AS1 in the Warburg effect in colorectal cancer.

Genotype-phenotype associations in Alström syndrome: a systematic review and meta-analysis

BACKGROUND

Alström syndrome (ALMS; #203800) is an ultrarare monogenic recessive disease. This syndrome is associated with variants in the ALMS1 gene, which encodes a centrosome-associated protein involved in the regulation of several ciliary and extraciliary processes, such as centrosome cohesion, apoptosis, cell cycle control and receptor trafficking. The type of variant associated with ALMS is mostly complete loss-of-function variants (97%) and they are mainly located in exons 8, 10 and 16 of the gene. Other studies in the literature have tried to establish a genotype-phenotype correlation in this syndrome with limited success. The difficulty in recruiting a large cohort in rare diseases is the main barrier to conducting this type of study.

METHODS

In this study we collected all cases of ALMS published to date. We created a database of patients who had a genetic diagnosis and an individualised clinical history. Lastly, we attempted to establish a genotype-phenotype correlation using the truncation site of the patient's longest allele as a grouping criteria.

RESULTS

We collected a total of 357 patients, of whom 227 had complete clinical information, complete genetic diagnosis and meta-information on sex and age. We have seen that there are five variants with high frequency, with p.(Arg2722Ter) being the most common variant, with 28 alleles. No gender differences in disease progression were detected. Finally, truncating variants in exon 10 seem to be correlated with a higher prevalence of liver disorders in patients with ALMS.

CONCLUSION

Pathogenic variants in exon 10 of the ALMS1 gene were associated with a higher prevalence of liver disease. However, the location of the variant in the ALMS1 gene does not have a major impact on the phenotype developed by the patient.

Circular RNA in Non-small Cell Lung Carcinoma: Identification of Targets and New Treatment Modalities

Despite availability of several treatment options for non-small cell lung cancer (NSCLC), such as surgery, chemotherapy, radiation, targeted therapy and immunotherapy, the survival rate of patients for five years is in the range of 22%. Therefore, identification of new targets and treatment modalities for this disease is an important issue. In this context, we screened the PubMed database for up-regulated circular RNAs (circRNAs) which promote growth of NSCLC in preclinical models in vitro as well as in vivo xenograft models in immuno-compromised mice. This approach led to potential targets for further validation and inhibition with small molecules or antibody-derived entities. In case of preclinical validation, the corresponding circRNAs can be inhibited with small interfering RNAs (siRNA) or short hairpin RNAs (shRNA). The identified circRNAs act by sponging microRNAs (miRs) preventing cleavage of the mRNA of the corresponding targets. We identified nine circRNAs up-regulating transmembrane receptors, five circRNAs increasing expression of secreted proteins, nine circRNAs promoting expression of components of signaling pathways, six circRNAs involved in regulation of splicing and RNA processing, six circRNAs up-regulating actin-related and RNA processing components, seven circRNAs increasing the steady-state levels of transcription factors, two circRNAs increasing high-mobility group proteins, four circRNAs increasing components of the epigenetic modification system and three circRNAs up-regulating protein components of additional systems.

Construction and validation of stemness-related lncRNA pair signature for predicting prognosis in colorectal cancer

PURPOSE

The purpose of this study was to identify a prognostic signature based on stemness-related differentially expressed lncRNAs in colorectal cancer (CRC) and to investigate their potential as biomarkers for diagnosis, prognosis, and therapeutic targets.

METHODS

Stemness-related genes were collected from the TCGA cohort, and 13 differently expressed stemness-related lncRNAs were identified as prognostic factors for CRC using Kaplan-Meier analysis. A risk model was constructed based on the calculated risk score as a novel independent prognostic factor for CRC patients. The study also investigated the association between the risk model and immune checkpoints and m6A differentiation gene expression. qRT-PCR analysis was performed to validate the expression of differentially expressed stemness-related lncRNAs in CRC cell lines compared to normal colon mucosal cell line.

RESULTS

The low-risk lncRNAs were associated with higher survival in CRC patients (Kaplan-Meier analysis, P < 0.001). The risk model was a significant independent prognostic factor for CRC patients. Type I INF response was statistically significant between low- and high-risk groups. CD44, CD70, PVR, TNFSF4, BTNL2, CD40, these immune checkpoints were expressed differently between two risk groups. There was a significant difference between m6A differentiation gene expression such as METTL3, METTL14, WTAP, RBM15, ZC3H13, YTHDC2, YTHDF2, ALKBH5. qRT-PCR analysis validated that there were five up-regulated and eight down-regulated differently expressed stemness-related lncRNAs in CRC cell lines compared to the normal colon mucosal cell line.

CONCLUSION

This study suggests that the 13 CRC stemness-related lncRNA signature could become a promising and reliable prognostic factor for colorectal cancer. The risk model based on the calculated risk score may have implications for personalized medicine and targeted therapies for CRC patients. The study also suggests that immune checkpoints and m6A differentiation genes may play important roles in the development and progression of CRC.

5-Methylcytosine-related lncRNAs: predicting prognosis and identifying hot and cold tumor subtypes in head and neck squamous cell carcinoma

BACKGROUND

5-Methylcytosine (m⁵C) methylation is recognized as an mRNA modification that participates in biological progression by regulating related lncRNAs. In this research, we explored the relationship between m⁵C-related lncRNAs (mrlncRNAs) and head and neck squamous cell carcinoma (HNSCC) to establish a predictive model.

METHODS

RNA sequencing and related information were obtained from the TCGA database, and patients were divided into two sets to establish and verify the risk model while identifying prognostic mrlncRNAs. Areas under the ROC curves were assessed to evaluate the predictive effectiveness, and a predictive nomogram was constructed for further prediction. Subsequently, the tumor mutation burden (TMB), stemness, functional enrichment analysis, tumor microenvironment, and immunotherapeutic and chemotherapeutic responses were also assessed based on this novel risk model. Moreover, patients were regrouped into subtypes according to the expression of model mrlncRNAs.

RESULTS

Assessed by the predictive risk model, patients were distinguished into the low-MLRS and high-MLRS groups, showing satisfactory predictive effects with AUCs of 0.673, 0.712, and 0.681 for the ROCs, respectively. Patients in the low-MLRS groups exhibited better survival status, lower mutated frequency, and lower stemness but were more sensitive to immunotherapeutic response, whereas the high-MLRS group appeared to have higher sensitivity to chemotherapy. Subsequently, patients were regrouped into two clusters: cluster 1 displayed immunosuppressive status, but cluster 2 behaved as a hot tumor with a better immunotherapeutic response.

CONCLUSIONS

Referring to the above results, we established a m⁵C-related lncRNA model to evaluate the prognosis, TME, TMB, and clinical treatments for HNSCC patients. This novel assessment system is able to precisely predict the patients' prognosis and identify hot and cold tumor subtypes clearly for HNSCC patients, providing ideas for clinical treatment.

Regulation of the Cell Cycle by ncRNAs Affects the Efficiency of CDK4/6 Inhibition

Cyclin-dependent kinases (CDKs) regulate cell division at multiple levels. Aberrant proliferation induced by abnormal cell cycle is a hallmark of cancer. Over the past few decades, several drugs that inhibit CDK activity have been created to stop the development of cancer cells. The third generation of selective CDK4/6 inhibition has proceeded into clinical trials for a range of cancers and is quickly becoming the backbone of contemporary cancer therapy. Non-coding RNAs, or ncRNAs, do not encode proteins. Many studies have demonstrated the involvement of ncRNAs in the regulation of the cell cycle and their abnormal expression in cancer. By interacting with important cell cycle regulators, preclinical studies have demonstrated that ncRNAs may decrease or increase the treatment outcome of CDK4/6 inhibition. As a result, cell cycle-associated ncRNAs may act as predictors of CDK4/6 inhibition efficacy and perhaps present novel candidates for tumor therapy and diagnosis.

LncRNA ALMS1-IT1 is a novel prognostic biomarker and correlated with immune infiltrates in colon adenocarcinoma

Colon adenocarcinoma (COAD) is one of the most serious cancers. It is important to accurately predict prognosis and provide individualized treatment. Evidence suggests that clinicopathological features and immune status of the body are related to the occurrence and development of cancer. Expression of long non-coding RNA (LncRNA) ALMS1 intronic transcript 1 (ALMS1-IT1) is observed in some cancer types, and we believe that it may have the potential to serve as a marker of COAD. Therefore, we used the data obtained from the cancer genome atlas (TCGA) database to prove the relationship between ALMS1-IT1 and COAD. Wilcoxon rank sum test, Chi-square test, Fisher exact test and logistic regression were used to evaluate relationships between clinical-pathologic features and ALMS1-IT1 expression. Receiver operating characteristic curves were used to describe binary classifier value of ALMS1-IT1 using area under curve score. Kaplan-Meier method and Cox regression analysis were used to evaluate factors contributing to prognosis. Gene oncology (GO) and (Kyoto Encyclopedia of Genes and Genomes) KEGG enrichment analysis were used to predict the function of differentially expressed genes associated with ALMS1-IT1. Gene set enrichment analysis (GSEA) was used to predict canonical pathways associated with ALMS1-IT1.Immune infiltration analysis was performed to identify the significantly involved functions of ALMS1-IT1. Starbase database was used to predict miRNAs and RNA binding proteins (RBPs) that may interact with ALMS1-IT1. Increased ALMS1-IT1 expression in COAD was associated with N stage (P < .001), M stage (P = .003), Pathologic stage (P = .002), and Primary therapy outcome (P = .009). Receiver operating characteristic curve suggested the significant diagnostic and prognostic ability of ALMS1-IT1 (area under curve = 0.857). High ALMS1-IT1 expression predicted a poorer overall-survival (P = .005) and poorer progression-free interval (PFI) (P = .012), and ALMS1-IT1 expression was independently correlated with PFI in COAD patients (hazard ratio (HR) :1.468; 95% CI: 1.029-2.093; P =.034) (HR: 1.468; 95% CI: 1.029-2.093; P = .034). GO, KEGG, GSEA, and immune infiltration analysis showed that ALMS1-IT1 expression was correlated with regulating the function of DNA and some types of immune infiltrating cells. ALMS1-IT1 expression was significantly correlated with poor survival and immune infiltrations in COAD, and it may be a promising prognostic biomarker in COAD.

Identification of Nine M6A-Related Long Noncoding RNAs as Prognostic Signatures Associated with Oxidative Stress in Oral Cancer Based on Data from The Cancer Genome Atlas

Objective

Although the expression of long noncoding RNAs (lncRNAs) and N6-methyladenosine (M6A) is correlated with different tumors, it remains unclear how M6A-related lncRNA functioning affects the initiation and progression of oral squamous cell carcinoma (OSCC).

Materials and Methods

Gene expression and clinical data were retrieved from The Cancer Genome Atlas. The prognostic value of M6A-related lncRNAs was determined using univariate Cox regression analyses. Gene set enrichment analysis of OSCC patient clusters revealed the pathways that elucidate the mechanism. Furthermore, a risk-based model was established. The difference in the overall survival (OS) between groups, including low-/high-risk groups, was determined by Kaplan-Meier analysis. Relationships among immune cells, clusters, clinicopathological characteristics, and risk scores were explored.

Results

Among 1,080 M6A-related lncRNAs, 36 were prognosis-related. Patients with OSCC were divided into two clusters. T stage and the pathological grade were noticeably lower in cluster 2 than in cluster 1. Epithelial-mesenchymal transition showed greater enrichment in cluster 1. Nine hub M6A-related lncRNAs were identified for the model of risk score for predicting OSCC prognosis. The OS was longer in patients with a low-risk score than in patients with a high-risk score. The risk score was an independent prognostic factor of OSCC and was associated with the infiltration of different immune cells. T stages and the American Joint Committee on Cancer (AJCC) stages were more advanced in the high-risk score group than in the low-risk score group. Finally, expression correlation analysis showed that the risk score is associated with the expression of oxidative stress markers.

Conclusion

M6A-related lncRNAs play an important role in OSCC progression. Immune cell infiltration was related to the risk score model in OSCC and could accurately predict OSCC prognosis.

Establishment of a Cell Necroptosis Index to Predict Prognosis and Drug Sensitivity for Patients With Triple-Negative Breast Cancer

Background: Necroptosis has been an alternatively identified mechanism of programmed cancer cell death, which plays a significant role in cancer. However, research about necroptosis-related long noncoding RNAs (lncRNAs) in cancer are still few. Moreover, the potentially prognostic value of necroptosis-related lncRNAs and their correlation with the immune microenvironment remains unclear. The present study aimed to explore the potential prognostic value of necroptosis-related lncRNAs and their relationship to immune microenvironment in triple-negative breast cancer (TNBC).

Methods: The RNA expression matrix of patients with TNBC was obtained from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) databases. Finally, 107 patients of GSE58812, 159 patients of TCGA, and 143 patients of GSE96058 were included. Necroptosis-related lncRNAs were screened by Cox regression and Pearson correlation analysis with necroptosis-related genes. By LASSO regression analysis, nine necroptosis-related lncRNAs were employed, and a cell necroptosis index (CNI) was established; then, we evaluated its prognostic value, clinical significance, pathways, immune infiltration, and chemotherapeutics efficacy.

Results: Based on the CNI value, the TNBC patients were divided into high- and low-CNI groups, and the patients with high CNI had worse prognosis, more lymph node metastasis, and larger tumor (p < 0.05). The receiver operating characteristic (ROC) analysis showed that the signature performed well. The result of the infiltration proportion of different immune cell infiltration further explained that TNBC patients with high CNI had low immunogenicity, leading to poor therapeutic outcomes. Moreover, we found significant differences of the IC50 values of various chemotherapeutic drugs in the two CNI groups, which might provide a reference to make a personalized chemotherapy for them.

Conclusion: The novel prognostic marker CNI could not only precisely predict the survival probability of patients with TNBC but also demonstrate a potential role in antitumor immunity and drug sensitivity.

Identification of RNA Methylation-Related lncRNAs Signature for Predicting Hot and Cold Tumors and Prognosis in Colon Cancer

N6-methyladenosine (m6A), N1-methyladenosine (m1A), 5-methylcytosine (m5C), and 7-methylguanosine (m7G) are the major forms of RNA methylation modifications, which are closely associated with the development of many tumors. However, the prognostic value of RNA methylation-related long non-coding RNAs (lncRNAs) in colon cancer (CC) has not been defined. This study summarised 50 m6A/m1A/m5C/m7G-related genes and downloaded 41 normal and 471 CC tumor samples with RNA-seq data and clinicopathological information from The Cancer Genome Atlas (TCGA) database. A total of 1057 RNA methylation-related lncRNAs (RMlncRNAs) were identified with Pearson correlation analysis. Twenty-three RMlncRNAs with prognostic values were screened using univariate Cox regression analysis. By consensus clustering analysis, CC patients were classified into two molecular subtypes (Cluster 1 and Cluster 2) with different clinical outcomes and immune microenvironmental infiltration characteristics. Cluster 2 was considered to be the “hot tumor” with a better prognosis, while cluster 1 was regarded as the “cold tumor” with a poorer prognosis. Subsequently, we constructed a seven-lncRNA prognostic signature using the least absolute shrinkage and selection operator (LASSO) Cox regression. In combination with other clinical traits, we found that the RNA methylation-related lncRNA prognostic signature (called the “RMlnc-score”) was an independent prognostic factor for patients with colon cancer. In addition, immune infiltration, immunotherapy response analysis, and half-maximum inhibitory concentration (IC50) showed that the low RMlnc-score group was more sensitive to immunotherapy, while the high RMlnc-score group was sensitive to more chemotherapeutic agents. In summary, the RMlnc-score we developed could be used to predict the prognosis, immunotherapy response, and drug sensitivity of CC patients, guiding more accurate, and personalized treatment regimens.

Cross-Talk Between m6A- and m5C-Related lncRNAs to Construct a Novel Signature and Predict the Immune Landscape of Colorectal Cancer Patients

Background

N6-methyladenosine (m⁶A) and 5-methylcytosine (m⁵C) can modify long non-coding RNAs (lncRNAs), thereby affecting tumorigenesis and tumor progression. However, there is a lack of knowledge regarding the potential roles and cross-talk of m⁶A- and m⁵C-related lncRNAs in the tumor microenvironment (TME) and their effect on prognosis.

Methods

We systematically evaluated the expression patterns of m⁶A- and m⁵C-related lncRNAs in 1358 colorectal cancer (CRC) samples from four datasets. Consensus clustering was conducted to identify molecular subtypes of CRC, and the clinical significance, TME, tumor-infiltrating immune cells (TIICs), and immune checkpoints in the different molecular subtypes were analyzed. Finally, we established a m⁶A- and m⁵C-related lncRNA signature and a prognostic nomogram.

Results

We identified 141 m⁶A- and m⁵C-related lncRNAs by co-expression analysis, among which 23 lncRNAs were significantly associated with the overall survival (OS) of CRC patients. Two distinct molecular subtypes (cluster A and cluster B) were identified, and these two distinct molecular subtypes could predict clinicopathological features, prognosis, TME stromal activity, TIICs, immune checkpoints. Next, a m⁶A- and m⁵C-related lncRNA signature for predicting OS was constructed, and its predictive capability in CRC patients was validated. We then constructed a highly accurate nomogram for improving the clinical applicability of the signature. Analyses of clinicopathological features, prognosis, TIICs, cancer stem cell (CSC), and drug response revealed significant differences between two risk groups. In addition, we found that patients with a low-risk score exhibited enhanced response to anti-PD-1/L1 immunotherapy. Functional enrichment analysis showed that these lncRNAs related to the high-risk group were involved in the development and progression of CRC.

Conclusions

We conducted a comprehensive analysis of m⁶A- and m⁵C-related lncRNAs in CRC and revealed their potential functions in predicting tumor-immune-stromal microenvironment, clinicopathological features, and prognosis, and determined their role in immunotherapy. These findings may improve our understanding of the cross-talk between m⁶A- and m⁵C-related lncRNAs in CRC and pave a new road for prognosis assessment and more effective immunotherapy strategies.

Identification and Validation of an Endoplasmic Reticulum Stress-Related lncRNA Signature for Colon Adenocarcinoma Patients

Purpose

Methods

Results

Conclusion

Development and Validation of a Ferroptosis-Related lncRNAs Prognosis Model in Oral Squamous Cell Carcinoma

Objectives: Ferroptosis is an iron-dependent form of programmed cell death, which affects the prognosis of many cancers. Some long non-coding RNA (lncRNA) can affect the prognosis of cancer by regulating the process of ferroptosis. However, the role of ferroptosis-related lncRNA (frlncRNA) in oral squamous cell carcinoma (OSCC) is not yet clear.

Materials and Methods: The data of OSCC patients were downed from The Cancer Genome Atlas (TCGA). After univariate and multivariate Cox regression analysis, the prognosis-related ferroptosis-related lncRNAs were obtained to construct a prognostic model. Calculated the risk score to divide patients into high and low risk groups, and evaluated the predictive ability of the model and the differential expression of immunity in the high and low risk groups.

Results: The prognostic model for OSCC was constructed based on 8 prognostic-related frlncRNAs which co-expressed with 25 mRNAs. Kaplan-Meier analyses displayed that the risk score is inversely proportional to patient survival. Receiver operating characteristic (ROC) and decision curve analysis (DCA) indicated that the risk score is superior to other clinical characteristics, and independent prognostic analysis demonstated that risk score is independent factor for the overall survival (OS) rate. The results of immunological analysis showed differences in immune cells, functions, immune checkpoints, and m6A expression between high and low risk groups.

Conclusion: We constructed an OSCC patients prognosis model based on 8 frlncRNAs, which can provide prognostic evaluation and immune analysis for OSCC patients, and provided new direction for OSCC targeted therapy.

Comprehensive Analysis of N6-Methyladenosine-Related lncRNA Signature for Predicting Prognosis and Immune Cell Infiltration in Patients with Colorectal Cancer

Background

Colorectal cancer (CRC) is the third most common tumor worldwide. Aberrant N6-methyladenosine (m6A) modification can influence the progress of the CRC. Additionally, long noncoding RNA (lncRNA) plays a critical role in CRC and has a close relationship with m6A modification. However, the prognostic potential of m6A-related lncRNAs in CRC patients still remains to be clarified.

Methods

We use “limma” R package, “glmnet” R package, and “survival” R package to screen m6A-related-lncRNAs with prognostic potential. Then, we comprehensively analysed and integrated the related lncRNAs in different TNM stages from TCGA database using the LASSO Cox regression. Meanwhile, the relationship between functional enrichment of m6A-related lncRNAs and immune microenvironment in CRC was also investigated using the TCGA database. A prognostic model was constructed and validated to determine the association between m6A-related lncRNAs in different TNM stages and the prognosis of CRC.

Result

We demonstrated that three related m6A lncRNAs in different TNM stages were associated with the prognosis of CRC patients. Patients from the TCGA database were classified into the low-risk and the high-risk groups based on the expression of these lncRNAs. The patients in the low-risk group had longer overall survival than the patients in the high-risk group (P < 0.001). We further constructed and validated a prognostic nomogram based on these genes with a C-index of 0.80. The receiver operating characteristic curves confirmed the predictive capacity of the model. Meanwhile, we also found that the low-risk group has the correlation with the dendritic cell (DC). Finally, we discovered the relationship between the m6A regulators and the three lncRNAs.

Conclusion

The prognostic model based on three m6A-related lncRNAs exhibits superior predictive performance, providing a novel prognostic model for the clinical evaluation of CRC patients.

Diagnostic and prognostic value of microRNA-2355-3p and contribution to the progression in lung adenocarcinoma

The aim of this study was to delve into the clinical significance and biological function of miR-2355-3p in LUAD. Tissues and blood samples from 116 LUAD patients and blood samples of 90 healthy volunteers were collected. The relative expression of miR-2355-3p was evaluated by quantitative real-time polymerase chain reaction (qRT-PCR). The receiver operating curve (ROC) was plotted for diagnostic value estimation. Kaplan–Meier survival curves were constructed, and multivariate survival analyses were performed for prognostic value estimation. A luciferase reporter assay was carried out to confirm the interaction of miR-2355-3p and ZCCHC14. The CCK-8 and transwell assays were conducted to explore the function of miR-2355-3p on LUAD cells. Rescue experiments were performed to verify the interaction. miR-2355-3p showed an upregulated expression in the samples of LUAD patients. For diagnostic value estimation, the AUC was 0.905 with a sensitivity was 84.5% and specificity of 83.3%. For the estimation of prognostic value, the P-value of log-rank test on K-M curves was 0.002 and 0.006 for overall survival and progression survival, respectively. Based on multivariate Cox regression analysis, miR-2355-3p was a powerful prognostic tool with a P-value of 0.027. ZCCHC14 has binding sites with miR-2355-3p, an expression level, and luciferase activity negatively correlated with miR-2355-3p expression. Knockdown of miR-2355-3p inhibited proliferation, migration, and invasion of LUAD cells, but ZCCHC14 can rescue this inhibition. miR-2355-3p has the potential to be a diagnostic marker and prognostic marker for LUAD. Inhibition of miR-2355-3p in LUAD cells can suppress the progression of LUAD at least partly by direct targeting ZCCHC14.