Identification of m6A-Related Biomarkers Associated with Prognosis of Colorectal Cancer

White Adipocyte Stem Cell Expansion Through Infant Formula Feeding: New Insights into Epigenetic Programming Explaining the Early Protein Hypothesis of Obesity

Prolonged breastfeeding (BF), as opposed to artificial infant formula feeding (FF), has been shown to prevent the development of obesity later in life. The aim of our narrative review is to investigate the missing molecular link between postnatal protein overfeeding-often referred to as the "early protein hypothesis"-and the subsequent transcriptional and epigenetic changes that accelerate the expansion of adipocyte stem cells (ASCs) in the adipose vascular niche during postnatal white adipose tissue (WAT) development. To achieve this, we conducted a search on the Web of Science, Google Scholar, and PubMed databases from 2000 to 2025 and reviewed 750 papers. Our findings revealed that the overactivation of mechanistic target of rapamycin complex 1 (mTORC1) and S6 kinase 1 (S6K1), which inhibits wingless (Wnt) signaling due to protein overfeeding, serves as the primary pathway promoting ASC commitment and increasing preadipocyte numbers. Moreover, excessive protein intake, combined with the upregulation of the fat mass and obesity-associated gene (FTO) and a deficiency of breast milk-derived microRNAs from lactation, disrupts the proper regulation of FTO and Wnt pathway components. This disruption enhances ASC expansion in WAT while inhibiting brown adipose tissue development. While BF has been shown to have protective effects against obesity, the postnatal transcriptional and epigenetic changes induced by excessive protein intake from FF may predispose infants to early and excessive ASC commitment in WAT, thereby increasing the risk of obesity later in life.

The diverse landscape of RNA modifications in cancer development and progression

BACKGROUND

RNA modifications, a central aspect of epitranscriptomics, add a regulatory layer to gene expression by modifying RNA function without altering nucleotide sequences. These modifications play vital roles across RNA species, influencing RNA stability, translation, and interaction dynamics, and are regulated by specific enzymes that add, remove, and interpret these chemical marks.

OBJECTIVE

This review examines the role of aberrant RNA modifications in cancer progression, exploring their potential as diagnostic and prognostic biomarkers and as therapeutic targets. We focus on how altered RNA modification patterns impact oncogenes, tumor suppressor genes, and overall tumor behavior.

METHODS

We performed an in-depth analysis of recent studies and advances in RNA modification research, highlighting key types and functions of RNA modifications and their roles in cancer biology. Studies involving preclinical models targeting RNA-modifying enzymes were reviewed to assess therapeutic efficacy and potential clinical applications.

RESULTS

Aberrant RNA modifications were found to significantly influence cancer initiation, growth, and metastasis. Dysregulation of RNA-modifying enzymes led to altered gene expression profiles in oncogenes and tumor suppressors, correlating with tumor aggressiveness, patient outcomes, and response to immunotherapy. Notably, inhibitors of these enzymes demonstrated potential in preclinical models by reducing tumor growth and enhancing the efficacy of existing cancer treatments.

CONCLUSIONS

RNA modifications present promising avenues for cancer diagnosis, prognosis, and therapy. Understanding the mechanisms of RNA modification dysregulation is essential for developing targeted treatments that improve patient outcomes. Further research will deepen insights into these pathways and support the clinical translation of RNA modification-targeted therapies.

Elucidating the role of FBXW4 in osteoporosis: integrating bioinformatics and machine learning for advanced insight

BACKGROUND

Osteoporosis (OP), often termed the "silent epidemic," poses a substantial public health burden. Emerging insights into the molecular functions of FBXW4 have spurred interest in its potential roles across various diseases.

METHODS

This study explored FBXW4 by integrating DEGs from GEO datasets GSE2208, GSE7158, GSE56815, and GSE35956 with immune-related gene compilations from the ImmPort repository. Gene selection was refined using advanced approaches, including LASSO regression and SVM-RFE. Functional enrichment of FBXW4-associated genes was assessed via GSEA and GSVA, identifying significant immune pathway involvement. Immune-related biological processes linked to FBXW4 expression were further evaluated using CIBERSORT and ESTIMATE algorithms. Validation of FBXW4 expression was performed using GSE35956.

RESULTS

A total of 13 hub genes were selected through LASSO and SVM-RFE analyses. Functional assays implicated FBXW4 in antiviral defense, cytokine production, and immune response modulation. Notably, FBXW4 expression correlated positively with several immune cell subsets, including memory B cells, activated memory CD4+ T cells, naive B cells, gamma delta T cells, M0 macrophages, follicular helper T cells, and naive CD4+ T cells, while showing a negative association with neutrophils.

CONCLUSIONS

This study uncovers a complex interplay between FBXW4 and immune processes in osteoporosis, suggesting its potential utility as a biomarker for OP diagnosis and monitoring. These findings lay the groundwork for future investigations into the therapeutic and diagnostic potential of FBXW4 in OP.

High WTAP expression level as a promising biomarker for poor prognosis in colorectal cancer: a pilot study

Colorectal cancer (CRC) is a major public health concern and identifying prognostic molecular biomarkers can help stratify patients based on risk profiles, thus enabling personalized medicine. Epitranscriptomic modifications play a relevant role in controlling gene expression, N6-methyladenosine (m6A) regulators play crucial roles in cancer progression, but their clinical significance in CRC cancer has thus far not been elucidated. Thus, we aimed to examine by immunohistochemical techniques and RT-qPCR, protein levels and RNAs expression of m6A writers (METTL3, WTAP) and eraser (FTO) in a cohort of 10 patients affected by CRC. The patients were followed for 5 years and values of METTL3, WTAP and FTO RNAs in alive vs dead patients were compared. Proteins expression and RNAs expression had a different trend, METTL3, WTAP and FTO proteins' expression showed an increasing trend from non-cancerous adjacent (N) tissue vs carcinoma (CA) tissue G1 stage, and then a decreasing trend from G1 to G2 and G3 stages. The most marked increase was observed in WTAP that, from a 40% of protein expression positivity in N tissue raised to the 81% of positivity in G1 stage K tissue. RNAs expression of METTL3, WTAP and FTO genes in N tissue vs G1 stage CA tissue was significantly different, the analysis and comparison of RNAs values in patient alive after 5 years (0.58±0.04) vs patients dead after 5 years (1.69±0.29) showed that only WTAP values resulted significantly high in dead patients. The fact that WTAP protein expression levels lower while WTAP RNA expression remains high, lets us hypothesize a sort of inhibition of protein expression, but further studies are needed to clarify the mechanism. Although the results suggest a relationship between biological meaning and prognostic utility of WTAP, this prognostic utility must be confirmed by further studies on a larger sample.

Mechanisms and clinical landscape of N6-methyladenosine (m6A) RNA modification in gastrointestinal tract cancers

Epigenetics encompasses reversible and heritable chemical modifications of non-nuclear DNA sequences, including DNA and RNA methylation, histone modifications, non-coding RNA modifications, and chromatin rearrangements. In addition to well-studied DNA and histone methylation, RNA methylation has emerged as a hot topic in biological sciences over the past decade. N6-methyladenosine (m6A) is the most common and abundant modification in eukaryotic mRNA, affecting all RNA stages, including transcription, translation, and degradation. Advances in high-throughput sequencing technologies made it feasible to identify the chemical basis and biological functions of m6A RNA. Dysregulation of m6A levels and associated modifying proteins can both inhibit and promote cancer, highlighting the importance of the tumor microenvironment in diverse biological processes. Gastrointestinal tract cancers, including gastric, colorectal, and pancreatic cancers, are among the most common and deadly malignancies in humans. Growing evidence suggests a close association between m6A levels and the progression of gastrointestinal tumors. Global m6A modification levels are substantially modified in gastrointestinal tumor tissues and cell lines compared to healthy tissues and cells, possibly influencing various biological behaviors such as tumor cell proliferation, invasion, metastasis, and drug resistance. Exploring the diagnostic and therapeutic potential of m6A-related proteins is critical from a clinical standpoint. Developing more specific and effective m6A modulators offers new options for treating these tumors and deeper insights into gastrointestinal tract cancers.

Molecular subtype identification and prognosis stratification by a immunogenic cell death-related gene expression signature in colorectal cancer

OBJECTIVES

This study intended to develop a new immunogenic cell death (ICD)-related prognostic signature for colorectal cancer (CRC) patients.

RESEARCH DESIGN AND METHODS

The Non-Negative Matrix Factorization (NMF) algorithm was adopted to cluster tumor samples based on ICD gene expression to obtain ICD-related subtypes. Survival analysis and immune microenvironment analysis were conducted among different subtypes. Regression analysis was used to construct the model. Based on riskscore median, cancer patients were classified into high and low risk groups, and independent prognostic ability of the model was analyzed. The CIBERSORT algorithm was adopted to determine the immune infiltration level of both groups.

RESULTS

We analyzed the differential genes between cluster 4 and cluster 1-3 and obtained 12 genes with the best prognostic features finally (NLGN1, SLC30A3, C3orf20, ADAD2, ATOH1, ATP6V1B1, KCNQ2, MUCL3, RGCC, CLEC17A, COL6A5, and INSL4). In addition, patients with lower risk had higher levels of infiltration of most immune cells, lower Tumor Immune Dysfunction and Exclusion (TIDE) level and higher immunophenscore (IPS) level than those with higher risk.

CONCLUSIONS

This study constructed and validated the ICD feature signature predicting CRC prognosis and provide a reference criteria for guiding the prognosis and immunotherapy of CRC cancer patients.

Deregulated expression of autophagy genes; PIK3C3 and RAB7A in COVID-19 patients

BACKGROUND

The role of autophagy in coronaviruses infection and replication has a lot of debate. Autophagy involves the catalytic breakdown of intracellular components to be subsequently recycled by the lysosome. The aim of the study was to evaluate autophagy genes; PIK3C3 and RAB7A expressions in COVID-19 patients, and identify if PIK3C3 and RAB7A can be used as markers for monitoring COVID-19 patients.

METHODS

A case-control study was carried out on 50 patients and 50 healthy controls. Genes expression was performed using quantitative real-time polymerase chain reaction.

RESULTS

Compared to controls, PIK3C3 and RAB7A gene expression levels were significantly lower in patients (p < 0.001) with approximately with 9.4 and 2.3 decreased fold in PIK3C3 and RAB7A respectively. The ROC curve of PIK3C3 and RAB7A expressions showed sensitivity of 84 % and 74 % and specificity of 98 % and 78 % respectively. There was a positive correlation between PIK3C3 expression and WBCs, absolute neutrophil count, interleukin-6, D-dimer, and ALT among patients and between RAB7A expression and WBCs, CRP, IL-6, D-dimer and ALT in patients.

CONCLUSIONS

The study showed reduction of PIK3C3 and RAB7A expressions in COVID-19 patients. However, further studies are recommended to clarify their roles in the disease pathogenies as autophagy genes.

An immune-related gene prognostic prediction risk model for neoadjuvant chemoradiotherapy in rectal cancer using artificial intelligence

Background

This study aimed to establish and validate a prognostic model based on immune-related genes (IRGPM) for predicting disease-free survival (DFS) in patients with locally advanced rectal cancer (LARC) undergoing neoadjuvant chemoradiotherapy, and to elucidate the immune profiles associated with different prognostic outcomes.

Methods

Transcriptomic and clinical data were sourced from the Gene Expression Omnibus (GEO) database and the West China Hospital database. We focused on genes from the RNA immune-oncology panel. The elastic net approach was employed to pinpoint immune-related genes significantly impacting DFS. We developed the IRGPM for rectal cancer using the random forest technique. Based on the IRGPM, we calculated prognostic risk scores to categorize patients into high-risk and low-risk groups. Comparative analysis of immune characteristics between these groups was conducted.

Results

In this study, 407 LARC samples were analyzed. The elastic net identified a signature of 20 immune-related genes, forming the basis of the IRGPM. Kaplan-Meier survival analysis revealed a lower 5-year DFS in the high-risk group compared to the low-risk group. The receiver operating characteristic (ROC) curve affirmed the model's robust predictive capability. Validation of the model was performed in the GSE190826 cohort and our institution's cohort. Gene expression differences between high-risk and low-risk groups predominantly related to cytokine-cytokine receptor interactions. Notably, the low-risk group exhibited higher immune scores. Further analysis indicated a greater presence of activated B cells, activated CD8 T cells, central memory CD8 T cells, macrophages, T follicular helper cells, and type 2 helper cells in the low-risk group. Additionally, immune checkpoint analysis revealed elevated PDCD1 expression in the low-risk group.

Conclusions

The IRGPM, developed through random forest and elastic net methodologies, demonstrates potential in distinguishing DFS among LARC patients receiving standard treatment. Notably, the low-risk group, as defined by the IRGPM, showed enhanced activation of adaptive immune responses within the tumor microenvironment.

KIF18A promotes cervical squamous cell carcinoma progression by activating the PI3K/AKT pathway through upregulation of CENPE

BACKGROUND

Cervical cancer is a prevalent malignancy that significantly contributes to morbidity and mortality rates among women in developing nations. Although the association of KIF18A with various cancers has been established, its role in cervical squamous cell carcinoma (CESC) remains elusive.

METHODS

The KIF18A impact on the progression of CESC and its underlying mechanism were investigated through comprehensive bioinformatics analysis utilizing publicly available datasets. The levels of KIF18A and CENPE were assessed in clinical CESC samples through western blotting and qRT-PCR. To discover the role and molecular pathways of KIF18A in CESC, a combination of experimental approaches, including wound-healing, flow cytometry, CCK-8, and Transwell assay, were employed.

RESULTS

Our results demonstrate a significant KIF18A expression upregulation in CESC tissues in contrast to healthy tissues. In vitro, KIF18A upregulation was found to enhance cell growth, migration, and invasion and activate the PI3K/AKT signaling pathway while concurrently suppressing apoptosis. Conversely, downregulating KIF18A exhibited contrasting effects. Mechanistically, we observed a positive significant connection between KIF18A and CENPE in CESC cells.

CONCLUSION

KIF18A promotes tumor growth in CESC by modulating the PI3K/AKT signaling pathway through regulation of CENPE, making it a potential biomarker for diagnosis and prognosis as well as a therapeutic target.

Abnormal genetic and epigenetic patterns of m6A regulators associated with tumor microenvironment in colorectal cancer

Background

N6-methyladenosine (m6A) has a critical role in the development and progression of cancer. However, the genetic and epigenetic patterns, as well as tumor microenvironment (TME) infiltration characteristics of m6A regulators in colorectal cancer (CRC) remain largely unknown.

Methods

Molecular patterns of m6A modifications of 24 m6A regulators in CRC samples were evaluated using data from The Cancer Genome Atlas (TCGA). Mutations, copy number variations (CNVs), DNA methylation, and chromatin accessibility were examined to investigate the underlying mechanisms of the aberrant expression of m6A regulators. Correlations between m6A-related genes and TME cell-infiltrating characteristics were evaluated using Tumor Immune Estimation Resource (TIMER).

Results

The m6A regulators were frequently dysregulated in CRC, with two downregulated and 16 upregulated. All the m6A regulators had mutations (frequency ranging from 0.9% to 7%), with active mutations tending to occur in RBM15 and inactive mutations in ZC3H13. Only five m6A regulators had CNV frequency greater than 1%: YTHDC2 (2.4%), YTHDF1 (7.0%), YTHDF3 (1.9%), VIRMA (1.7%), and ZC3H13 (3.0%). The copy numbers of these five genes were positively correlated with their expression levels. The m6A regulators frequently showed imbalanced methylation in CRC, with hypomethylation of YTHDF2, IGF2BP3, FTO, and hypermethylation of HNRNPC, METTL3, and WTAP. Most m6A regulators had high chromatin accessibility, which was positively correlated with their gene expression. IGF2BP1 was identified as an independent prognostic factor for overall survival. Moreover, the expression of most m6A regulators was positively correlated with the infiltration of B cells, CD8+ T cells, CD4+ T cells, macrophages, neutrophils, and dendritic cells.

Conclusions

Aberrant expression of m6A regulators is associated with mutation, CNV, and chromatin accessibility, owing to both genetic and epigenetic modifications. The TME infiltration characterization of m6A regulators could guide the development of more effective immunotherapy strategies in CRC.

Primary microcephaly gene CENPE is a novel biomarker and potential therapeutic target for non-WNT/non-SHH medulloblastoma

Background

Non-WNT/non-SHH medulloblastoma (MB) is one of the subtypes with the highest genetic heterogeneity in MB, and its current treatment strategies have unsatisfactory results and significant side effects. As a member of the centromere protein (CENP) family, centromeric protein E (CENPE) is a microtubule plus-end-directed kinetochore protein. Heterozygous mutations in CENPE can leads to primary microcephaly syndrome. It has been reported that CENPE is upregulated in MB, but its role in MB development is still unknown.

Methods

We downloaded the relevant RNA seq data and matched clinical information from the GEO database. Bioinformatics analysis includes differential gene expression analysis, Kaplan-Meier survival analysis, nomogram analysis, ROC curve analysis, immune cell infiltration analysis, and gene function enrichment analysis. Moreover, the effects of CENPE expression on cell proliferation, cell cycle, and p53 signaling pathway of non-WNT/non-SHH MB were validated using CENPE specific siRNA in vitro experiments.

Results

Compared with normal tissues, CENPE was highly expressed in MB tissues and served as an independent prognostic factor for survival in non-WNT/non-SHH MB patients. The nomogram analysis and ROC curve further confirmed these findings. At the same time, immune cell infiltration analysis showed that CENPE may participate in the immune response and tumor microenvironment (TME) of non-WNT/non-SHH MB. In addition, gene enrichment analysis showed that CENPE was closely related to the cell cycle and p53 pathway in non-WNT/non-SHH MB. In vitro experimental validation showed that knockdown of CENPE inhibited cell proliferation by activating the p53 signaling pathway and blocking the cell cycle.

Conclusion

The expression of CENPE in non-WNT/non-SHH MB was positively correlated with poor prognosis. CENPE may affect tumor progression by regulating cell cycle, p53 pathway, and immune infiltration. Hence, CENPE is highly likely a novel biomarker and potential therapeutic target for non-WNT/non-SHH MB.

A novel long noncoding RNA AC125257.1 facilitates colorectal cancer progression by targeting miR-133a-3p/CASC5 axis

Colorectal cancer (CRC) is a common malignant gastrointestinal tumor. Long noncoding RNAs (lncRNAs) are revealed to be critically involved in CRC progression, providing new direction for exploring the pathogenesis of CRC. This study aimed to explore the biological functions and regulatory mechanisms of lncRNA AC125257.1 in CRC. Western blotting and reverse-transcription quantitative polymerase chain reaction were used for the measurement of gene expression. Cell counting kit-8 assay and flow cytometry analysis were used to explore the effects of AC125257.1 on CRC cell viability and apoptosis. RNA pull-down and immunoprecipitation assays were performed for validating the binding between AC125257.1 and its potential downstream microRNA. Results showed that lncRNA AC125257.1 expression was upregulated in CRC cells and tumor tissues. AC125257.1 enhanced cell viability and suppressed apoptosis of CRC cells. Moreover, the knockdown of AC125257.1 suppressed CRC progression in vitro and inhibited tumor growth in vivo. miR-133a-3p was revealed to bind with AC125257.1 in CRC cells. CASC5 was proved to be targeted by miR-133a-3p. Moreover, rescue assays indicated that the knockdown of AC125257.1 suppressed the pathogenic overexpression of CASC5. To conclude, AC125257.1 aggravates CRC development via miR-873-5p/CASC5 axis. Our findings might suggest a novel perspective that AC125257.1 may become the target for CRC treatment.

N6-methyladenosine related gene expression signatures for predicting the overall survival and immune responses of patients with colorectal cancer

N6-methyladenosine (m6A) modification has been demonstrated to exhibit a crucial prognostic effect on colorectal cancer (CRC). Nonetheless, potential mechanism of m6A in survival rate and immunotherapeutic response remains unknown. Here we investigated the genes associated with m6A regulators and developed a risk score for predicting the overall survival (OS) of CRC patients. RNA-seq transcriptomic profiling data of COAD/READ samples were obtained from The Cancer Genome Atlas (TCGA) database. Absolute Shrinkage and Selection Operator (LASSO)- Cox regression analysis was conducted to identify the m6A-related gene expression signatures and the selected genes were inputted into stepwise regression to develop a prognostic risk score in TCGA, and its predictive performance of CRC survival was further validated in Gene Expression Omnibus (GEO) datasets. According to our results, the risk score comprising 18 m6A-related mRNAs was significantly associated with CRC survival in both TCGA and GEO datasets. And the stratified analysis also confirmed that high-risk score acted as a poor factor in different age, sex, T stage, and tumour, node, metastasis (TNM) stages. The m6A-related prognostic score in combination with clinical characteristics yielded time-dependent area under the receiver operating characteristic curve (AUCs) of 0.85 (95%CI: 0.79-0.91), 0.84 (95%CI: 0.79-0.90) and 0.80 (95%CI: 0.71-0.88) for the prediction of the 1-, 3-, 5-year OS of CRC in TCGA cohort. Furthermore, mutation of oncogenes occurred more frequently in the high-risk group and the composition of immune cells in tumour microenvironment (TME) was significantly distinct between the low- and high-risk groups. The low-risk group had a lower microsatellite instability (MSI) score, T-cell exclusion score and dysfunction score, implying that low-risk patients may have a better immunotherapy response than high-risk patients. In summary, a prognostic risk score derived from m6A-related gene expression signatures could serve as a potential prognostic predictor for CRC survival and indicator for predicting immunotherapy response in CRC patients.

Identification of Diagnostic Markers for Breast Cancer Based on Differential Gene Expression and Pathway Network

Background: Breast cancer is the second largest cancer in the world, the incidence of breast cancer continues to rise worldwide, and women's health is seriously threatened. Therefore, it is very important to explore the characteristic changes of breast cancer from the gene level, including the screening of differentially expressed genes and the identification of diagnostic markers. Methods: The gene expression profiles of breast cancer were obtained from the TCGA database. The edgeR R software package was used to screen the differentially expressed genes between breast cancer patients and normal samples. The function and pathway enrichment analysis of these genes revealed significant enrichment of functions and pathways. Next, download these pathways from KEGG website, extract the gene interaction relations, construct the KEGG pathway gene interaction network. The potential diagnostic markers of breast cancer were obtained by combining the differentially expressed genes with the key genes in the network. Finally, these markers were used to construct the diagnostic prediction model of breast cancer, and the predictive ability of the model and the diagnostic ability of the markers were verified by internal and external data. Results: 1060 differentially expressed genes were identified between breast cancer patients and normal controls. Enrichment analysis revealed 28 significantly enriched pathways (p < 0.05). They were downloaded from KEGG website, and the gene interaction relations were extracted to construct the gene interaction network of KEGG pathway, which contained 1277 nodes and 7345 edges. The key nodes with a degree greater than 30 were extracted from the network, containing 154 genes. These 154 key genes shared 23 genes with differentially expressed genes, which serve as potential diagnostic markers for breast cancer. The 23 genes were used as features to construct the SVM classification model, and the model had good predictive ability in both the training dataset and the validation dataset (AUC = 0.960 and 0.907, respectively). Conclusion: This study showed that the difference of gene expression level is important for the diagnosis of breast cancer, and identified 23 breast cancer diagnostic markers, which provides valuable information for clinical diagnosis and basic treatment experiments.

Prospero homeobox 1 promotes proliferation, migration, and invasion of osteosarcoma cells and its clinical significance

Osteosarcoma (OS) is the most common primary malignant bone tumor. Prospero homeobox 1 (PROX1) is a key transcription factor involved in some cancers, but the role of PROX1 in OS is unclear. This study aimed to explore the clinical and biology significance of PROX1 in OS. Fifty-four OS tissues and matched nontumor tissues were collected to explore the relationship between PROX1 expression and clinical characteristics and prognosis. qRT-PCR and immunohistochemistry were used to investigate the expression patterns of PROX1 in OS tissues and cells. CCK-8, wound healing, and transwell assays were used to detect the effects of PROX1 on the proliferation, migration, and invasion of OS cells. Transcriptome sequencing, bioinformatics analysis and qRT-PCR were used to explore the regulatory network of PROX1. PROX1 was significantly higher in OS tissues and cells compared to normal tissues and cell lines. In OS patients, high expression of PROX1 was associated with Enneking stage (P < 0.001) and M classification (P < 0.001). High PROX1 expression predicted a poorer overall survival (P = 0.0047). Compared with untreated cells, OS cells overexpressing PROX1 showed higher proliferation, migration, and invasion abilities, while knockdown of PROX1 suppressed these abilities. The results of Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis revealed that the down regulated genes were mainly enriched in TNF signaling pathway, MAPK signaling pathway, and neuroactive ligand-receptor interaction. High PROX1 expression was significantly associated with poor overall survival in OS patients. PROX1 may be a promising prognostic marker and therapeutic target for OS patients.

Potential Prognostic Value of a Seven m6A-Related LncRNAs Signature and the Correlative Immune Infiltration in Colon Adenocarcinoma

Long non-coding RNAs (lncRNAs) and their N6-methyladenosine (m6A) modifications play an essential role in tumorigenesis and cancer progression. This study was designed to explore the value of m6A-related lncRNAs in prognosis and therapeutic applications of immune infiltration of colon adenocarcinoma (COAD). We downloaded the COAD gene expression and clinical data from The Cancer Genome Atlas project. By co-expression analysis, Lasso Cox regression analysis, and univariate and multivariate Cox regression, we constructed an independent prognostic signature of seven m6A-related lncRNAs. The prognostic lncRNAs were divided into two clusters by consistent clustering analysis, as well as into two groups of low–high risk based on the signature. Then we identified the relationship between the different groups with clinical features and immune cell infiltration. Cluster 2 had a higher risk score with a lower survival rate. The risk score was higher in groups with advanced clinical features, such as stage III–IV, N1-3, and M1. The expression of AC156455.1 was increased in tumor tissues and cluster 2, and the lncRNA ZEB1−AS1 was notably higher in the high-risk group. Five types of immune cells showed differences in two clusters, and most were upregulated in type 2. The expression of memory B cells was positively correlated with the risk score. The prognostic model was verified by the Gene Expression Omnibus (GEO) dataset. Besides, we found that the expression of these seven lncRNAs in tumor tissues was significantly higher than that in normal tissues, which verified the feasibility of the model. Thus, the signature of seven m6A-related lncRNAs can independently predict the prognosis of COAD. This signature is also closely associated with immune cell infiltration, and new therapeutic targets can be explored from this field.