Pan-Cancer Prognostic, Immunity, Stemness, and Anticancer Drug Sensitivity Characterization of N6-Methyladenosine RNA Modification Regulators in Human Cancers

MDFI promotes the proliferation and tolerance to chemotherapy of colorectal cancer cells by binding ITGB4/LAMB3 to activate the AKT signaling pathway

Colorectal cancer (CRC) is one of the most lethal cancers. Single-cell RNA sequencing (scRNA-seq) and protein-protein interactions (PPIs) have enabled the systematic study of CRC. In our research, the activation of the AKT pathway in CRC was analyzed by KEGG using single-cell sequencing data from the GSE144735 dataset. The correlation and PPIs of MDFI and ITGB4/LAMB3 were examined. The results were verified in the TCGA and CCLE and further tested by coimmunoprecipitation experiments. The effect of MDFI on the AKT pathway via ITGB4/LAMB3 was validated by knockdown and lentiviral overexpression experiments. The effect of MDFI on oxaliplatin/fluorouracil sensitivity was probed by colony formation assay and CCK8 assay. We discovered that MDFI was positively associated with ITGB4/LAMB3. In addition, MDFI was negatively associated with oxaliplatin/fluorouracil sensitivity. MDFI upregulated the AKT pathway by directly interacting with LAMB3 and ITGB4 in CRC cells, and enhanced the proliferation of CRC cells via the AKT pathway. Finally, MDFI reduced the sensitivity of CRC cells to oxaliplatin and fluorouracil. In conclusion, MDFI promotes the proliferation and tolerance to chemotherapy of colorectal cancer cells, partially through the activation of the AKT signaling pathway by the binding to ITGB4/LAMB3. Our findings provide a possible molecular target for CRC therapy.

WTAP enhances the instability of SYTL1 mRNA caused by YTHDF2 in bladder cancer

BACKGROUND

Bladder cancer (BCa) is the most frequent type of cancer in humans. The association between m6A modification and the anti-tumor effects of natural killer (NK) cells has been described in BCa. This study intended to investigate the implications of m6A regulators in modulating SYTL1 expression in BCa and the association with the anti-tumor effects of NK cells.

METHODS

The prognostic role of SYTL1 in BCa was investigated using bioinformatics analysis, and the correlation between SYTL1 expression and NK cells was analyzed. The effects of SYTL1 on the anti-tumor response of NK-92 cells were examined by RT-qPCR, cytotoxicity, western blot, and ELISA assays. The relationships among WTAP, YTHDF2, and SYTL1 were investigated by RT-qPCR, RIP-qPCR, ELISA, and actinomycin D treatment. Finally, the effects of WTAP and SYTL1 on BCa tumor growth and the anti-tumor response of NK cells were verified in vivo.

RESULTS

SYTL1 was reduced in BCa tissues and had a prognostic significance, which was related to NK cell-mediated anti-tumor responses. NK-92 cells produced toxicity to BCa cells, which was further enhanced by SYTL1 overexpression in BCa cells through prompting LDH, NKG2D, NKp30, and NKp44 and IFN-γ levels. WTAP enhanced the degradation of the SYTL1 mRNA by YTHDF2. WTAP and YTHDF2 impaired the anti-tumor response of NK cells in BCa. SYTL1 inhibited the BCa progression in mice while enhancing the anti-tumor response of NK cells.

CONCLUSIONS

WTAP inhibited the anti-tumor response of NK cells to BCa cells by promoting the degradation of SYTL1 mRNA through YTHDF2-mediated m6A methylation.

Fludarabine Enhances Radiosensitivity by Promoting Ferroptosis in B-Cell Lymphoma

The objective of this study is to investigate the impact of fludarabine, a signal transducer and activator of transcription-1 (STAT1) inhibitor, on the radiosensitivity of B-cell lymphoma (BCL) and to explore the underlying mechanisms. Radiotherapy is one of the primary treatments for BCL, and STAT1 plays a critical role in the transcription of cell proliferation-related genes, which are associated with radiotherapy and ferroptosis. This study aims to determine whether fludarabine can enhance the radiosensitivity of BCL and to elucidate the molecular pathways involved. Various in vitro methodologies, including CCK-8 assays, clonogenic formation assays, immunohistochemistry, immunofluorescence, flow cytometry, qRT-PCR, and Western blot analyses, were employed in B-cell lymphoma cell models to thoroughly investigate the effects of fludarabine on radiosensitivity. Subsequently, the obtained results were further validated through in vivo animal models and by examining human diffuse large B-cell lymphoma (DLBCL) cancer samples. Our findings demonstrate that the combination of fludarabine and irradiation synergistically inhibits cell viability and colony formation, while inducing apoptosis and ferroptosis in B-cell lymphoma cell lines Raji and Su-DHL-10. Moreover, fludarabine was found to enhance the ferroptosis induced by radiation, thereby synergistically impeding the growth of BCL. In vivo experiments confirmed these findings, revealing that the intraperitoneal injection of fludarabine significantly enhanced the inhibitory effects of radiation on Raji cell xenograft models, leading to an increased percentage of ferroptosis compared to models without fludarabine. Additionally, the administration of liproxstatin-1, a ferroptosis inhibitor, attenuated the inhibition of xenograft growth caused by the combination of fludarabine and irradiation. Furthermore, our analysis of clinical data revealed that increased co-expression of STAT1 and GPX4 is associated with poor overall survival in patients with diffuse large B-cell lymphoma. These results highlight the potential of fludarabine to enhance radiosensitivity and ferroptosis induction as a promising therapeutic strategy for BCL. Our results demonstrated that fludarabine promoted radiation-induced BCL death through the ferroptosis pathway. We have identified a previously unrecognized mechanism in the fludarabine and radiation combination, indicating that it is necessary to conduct prospective clinical trials to verify this new treatment regimen in BCL.

Subtype recognition and identification of a prognosis model characterized by antibody-dependent cell phagocytosis-related genes in breast cancer

BACKGROUND

Breast cancer (BC) is a heterogeneous tumor with a variety of etiology and clinical features. Antibody-dependent cell phagocytosis (ADCP) is the last step of immune checkpoint inhibition (ICI), and macrophages detect and recognize tumor cells, then destroy and engulf tumor cells. Despite the large number, negative regulators that inhibit phagocytic activity are still a key obstacle to the full efficacy of ICI.

PATIENTS AND METHODS

An ADCP-related risk score prognostic model for risk stratification as well as prognosis prediction was established in the Cancer Genome Atlas (TCGA) cohort. The predictive value of ADCP risk score in prognosis and immunotherapy was also further validated in the TCGA along with International Cancer Genome Consortium cohorts. To promote the clinical application of the risk score, a nomogram was established, with its effectiveness verified by different methods.

RESULTS

In this study, the genes collected from previous studies were defined as ADCP-related genes. In BC patients, two ADCP-related subtypes were identified. The immune characteristics and prognostic stratification were significant different between them.

CONCLUSIONS

We identified two subtypes associated with ADCP gene expression in breast cancer. They have significant differences in immune cells, molecular functions, HLA family genes, immune scores, stromal scores, and inflammatory gene expression, which have important guiding significance for the selection of clinical treatment methods. At the same time, we constructed a risk model based on ADCP, and the risk score can be used as a good indicator of prognosis, providing potential therapeutic advantages for chemotherapy and immunotherapy, thus helping the clinical decision-making of BC patients.

Characterization of m6A methylation modifications in gastric cancer

Widely recognized as an essential epitranscriptomic modification, RNA N6-methyladenosine (m6A) is involved in both physiological and pathological processes. Here, we want to investigate m6A modification's potential roles in gastric cancer. Gastric cancer samples were selected from TCGA-STAD and GEO (GSE84426, GSE84433) datasets. Based on 18 regulators of m6A, m6A modification patterns were thoroughly evaluated in gastric cancer samples. Principal component analysis algorithms were used to construct the m6Ascore, using which, m6A modification features in tumor somatic mutations and immune checkpoint blockade therapy were analyzed. 34 gastric cancer samples were collected to verify the effectiveness of the m6Ascore. Here, we determined three different m6A modification patterns. m6Acluster-C modification pattern presented immune activation-associated enrichment pathways and have significant survival advantages. Then, in gastric cancer, m6Ascore could act as an independent prognostic biomarker. A significant survival benefit was exhibited in patients with high m6Ascore. Moreover, the modification signature of m6A uncovered in this study would help to predict immune checkpoint blockade therapy's responses. In conclusion, our discoveries all pointed to the fact that modification patterns of m6A were linked to the TME. Moreover, evaluation of individual tumor's m6A modification pattern will help to guide immunotherapy strategies that shows more therapeutic effects.

A new prognostic model for glioblastoma multiforme based on coagulation-related genes

Background

Glioblastoma multiforme (GBM) is the most aggressive, common, and lethal type of primary brain tumor. Multiple cancers have been associated with abnormalities in the coagulation system that facilitate tumor invasion and metastasis. In GBM, the prognostic value and underlying mechanism of coagulation-related genes (CRGs) have not been explored.

Methods

RNA sequencing (RNA-seq) and clinical information on GBM were obtained from The Cancer Genome Atlas (TCGA) and Chinese Glioma Genome Atlas (CGGA), respectively. Following the identification of differentially expressed CRGs (DECRGs) between GBM and control samples, the survival-related DECRGs were selected via univariate and multivariate Cox regression analyses to establish a prognostic signature. The prognostic performance and clinical utility of the prognostic signature were assessed by the Kaplan-Meier (KM) analysis and receiver operating characteristic (ROC) curve analysis, and a nomogram was constructed. The signature genes-related underlying mechanisms were analyzed according to gene set enrichment analysis (GSEA), Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and single-cell analysis. Finally, the difference in immune cell infiltration, stromal score, immune score, and Estimation of Stromal and Immune cells in Malignant Tumor tissues using Expression data (ESTIMATE) score were compared between different risk groups.

Results

A 5-gene prognostic signature (PLAUR, GP6, C5AR1, SERPINA5, F2RL2) was established for overall survival (OS) prediction of GBM patients. The predicted efficiency of the prognostic signature was confirmed in TGGA-GBM dataset and validated in the CGGA-GBM dataset, revealing that it could differentiate GBM patients from controls well, and high risk score was accompanied with poor prognosis. Moreover, biological process (BP) and signaling pathway analyses showed that signature genes were mainly enriched in the functions of blood coagulation and tumor invasion and metastasis. Moreover, high-risk patients exhibited higher levels of immune cell infiltration, stromal score, immune score, and ESTIMATE score than that of low-risk patients.

Conclusions

An analysis of coagulation-related prognostic signatures was conducted in this study, as well as how signature genes may affect GBM progress, providing information that might provide new ideas for the development of GBM-related molecular targeted therapies.

M6A regulator methylation patterns and characteristics of immunity in acute ST-segment elevation myocardial infarction

M6A methylation is the most prevalent and abundant RNA modification in mammals. Although there are many studies on the regulatory role of m6A methylation in the immune response, the m6A regulators in the pathogenesis of acute ST-segment elevation myocardial infarction (STEMI) remain unclear. We comprehensively analysed the role of m6A regulators in STEMI and built a predictive model, revealing the relationship between m6A methylations and the immune microenvironment. Differential analysis revealed that 18 of 24 m6A regulators were significantly differentially expressed, and there were substantial interactions between the m6A regulator. Then, we established a classifier and nomogram model based on 6 m6A regulators, which can easily distinguish the STEMI and control samples. Finally, two distinct m6A subtypes were obtained and significantly differentially expressed in terms of infiltrating immunocyte abundance, immune reaction activity and human leukocyte antigen genes. Three hub m6A phenotype related genes (RAC2, RELA, and WAS) in the midnightblue module were identified by weighted gene coexpression network analysis, and were associated with immunity. These findings suggest that m6A modification and the immune microenvironment play a key role in the pathogenesis of STEMI.

Pan-cancer analysis and experimental validation revealed the m6A methyltransferase KIAA1429 as a potential biomarker for diagnosis, prognosis, and immunotherapy

BACKGROUND

KIAA1429, also known as VIRMA (vir-like m6A methyltransferase associated), plays a crucial role in tumorigenesis by modulating the level of m6A methylation. Previous studies have reported the prevalent overexpression of KIAA1429 in multiple cancers, related to a poor prognosis. Nevertheless, the precise role of KIAA1429 in tumor progression and its impact on the immune response remains unclear.

METHODS

A differential analysis of KIAA1429 expression was performed across cancers using data from the Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx) databases. We evaluated the role of KIAA1429 in the diagnosis, prognosis, and immunotherapy of tumor patients using bioinformatics methods. In addition, we also analyzed the associations between KIAA1429 and DNA methylation, immunotherapy. RT-qPCR was used to study the expression levels of KIAA1429 mRNA in 11 cell lines.

RESULTS

KIAA1429 is found to be overexpressed in 28 cancer types, but its expression is relatively low in patients with acute myeloid leukemia (LAML) and ovarian serous cystadenocarcinoma (OV). Moreover, KIAA1429 demonstrates a positive correlation with advanced stages of multiple cancers. Kaplan-Meier (KM) analysis suggested that patients with elevated KIAA1429 expression had shorter survival. Furthermore, KIAA1429 shows strong associations with DNA methylation, tumor-infiltrating immune cells (TIICs), and the tumor microenvironment (TME). RT-qPCR results indicated significantly higher expression of KIAA1429 in tumor cells compared to matched-normal cells.

CONCLUSIONS

In summary, our work illustrates that KIAA1429 expression is positively connected with poor prognosis in multiple cancers. Moreover, KIAA1429 could serve as a diagnostic factor and a predictor of immune response for specific tumor types.

METTL3 regulates N6-methyladenosine modification of ANGPTL3 mRNA and potentiates malignant progression of stomach adenocarcinoma

BACKGROUND

N6-methyladenosine (m6A) is associated with mammalian mRNA biogenesis, decay, translation and metabolism, and also contributes greatly to gastrointestinal tumor formation and development. Therefore, the specific mechanisms and signaling pathways mediated by methyltransferase-like 3 (METTL3), which catalyzes the formation of m6A chemical labeling in stomach adenocarcinoma (STAD), are still worth exploring.

METHODS

Quantitative real-time PCR (qRT-PCR) was constructed to detect the expression of METTL3 in gastric cancer cell lines and patient tissues. The biological function of METTL3 was investigated in vitro/in vivo by Cell Counting Kit-8, colony formation assay, Transwell assay and nude mouse tumorigenesis assay. Based on the LinkedOmics database, the genes co-expressed with METTL3 in the TCGA STAD cohort were analyzed to clarify the downstream targets of METTL3. Methylated RNA immunoprecipitation-qPCR (MeRIP-qPCR) and RNA stability analysis were employed to explore the mechanism of METTL3 in gastric cancer progression.

RESULTS

We analyzed TCGA data and found that METTL3 was frequently elevated in STAD, and demonstrated that METTL3 was present at high levels in clinical STAD tissues and cells. High METTL3 expression was more likely to have advanced TNM tumors and distant metastasis. On the other hand, METTL3 silencing effectively impeded the higher oncogenic capacity of AGS and HGC27 cells in vivo and in vitro, as reflected by slowed cell growth and diminished migration and invasion capacities. Continued mining of the TCGA dataset identified the co-expression of angiopoietin-like 3 (ANGPTL3) and METTL3 in STAD. Lower level of ANGPTL3 was related to increased level of METTL3 in STAD samples and shorter survival times in STAD patients. ANGPTL3 enrichment limited the growth and metastasis of STAD cells. Besides, ANGPTL3 mRNA levels could be decreased by METTL3-dominated m6A modifications, a result derived from a combination of MeRIP-qPCR and RNA half-life experiments. Importantly, the inhibitory effect of METTL3 silencing on cancer could be reversed to some extent by ANGPTL3 inhibition.

CONCLUSIONS

Overall, our findings suggested that METTL3 functioned an oncogenic role in STAD by reducing ANGPTL3 expression in an m6A-dependent manner. The discovery of the METTL3-ANGPTL3 axis and its effect on STAD tumor growth will contribute to further studies on the mechanisms of gastric adenocarcinoma development.

Construction and validation of a prognostic model for lung adenocarcinoma based on endoplasmic reticulum stress-related genes

Lung adenocarcinoma (LUAD) is one of the most universal types of cancer all over the world and its morbidity continues to rise year by year. Growing evidence has demonstrated that endoplasmic reticulum stress is highly activated in cancer cells and plays a key role in regulating the fate of cancer cells. However, the role and mechanism of endoplasmic reticulum stress in lung adenocarcinoma genesis and development remains unclear. In this research, we developed a prognostic model to predict the overall survival of patients with LUAD utilizing endoplasmic reticulum stress-related genes and screened out potential small molecular compounds, which could assist the clinician in making accurate decisions and better treat LUAD patients. Firstly, we downloaded 419 endoplasmic reticulum stress-related genes (ERSRGs) from Molecular Signatures Database (MSigDB). Secondly, we obtained information about the transcriptome profiling and corresponding clinical data of 59 normal samples and 535 lung adenocarcinoma samples from The Cancer Genome Atlas (TCGA) database. Next, we used the DESeq2 package to identify differentially expressed genes related to endoplasmic reticulum stress. We performed univariate Cox, least absolute shrinkage and selection operator (LASSO), and multivariate Cox regression analysis to establish a prognostic model for LUAD patients based on ERSRGs. Then, we carried out univariate and multivariate independent prognostic analysis of endoplasmic reticulum stress-related gene (ERSRG) score and some clinical traits of lung adenocarcinoma. Additionally, we developed a clinically applicable nomogram for predicting survival for LUAD patients over one, three, and five years. Moreover, we carried out a drug sensitivity analysis to identify novel small molecule compounds for LUAD treatment. Finally, we examined the tumor microenvironment (TME) and immune cell infiltrating analysis to explore the interactions between immune and cancer cells. 142 differentially expressed ERSRGs were identified by using the DESeq2 package. A prognostic model was built based on 7 differentially expressed ERSRGs after performing univariate Cox regression, LASSO regression, and multivariate Cox regression analysis. According to the results of univariate and multivariate independent prognostic analysis, we found ERSRG score can be used as an independent prognostic maker. Using the Kaplan-Meier curves, we found low-risk patients had higher survival probability than high-risk patients in both training set and test set. A nomogram was drawn to predict 1-, 3-, and 5-year survival probability. The calibration curves explained good performance of the model for the prediction of survival. Phenformin, OSU-03012, GSK-650394 and KIN001-135 were identified as the drugs most likely to provide important information to clinicians about the treatment of LUAD patients. A prognostic prediction model was established based on 7 differentially expressed ERSRGs (PDX1, IGFBP1, DDIT4, PPP1R3G, CFTR, DERL3 and NUPR1), which could effectively predict the prognosis of LUAD patients and give a reference for clinical doctors to help LUAD patients to make better treatment tactics. Based on the 4 small molecule compounds (Phenformin, OSU-03012, GSK-650394 and KIN001-135) we discovered, targeting endoplasmic reticulum stress-related genes may also be a therapeutic approach for LUAD patients.

Comprehensive pan-cancer analysis of N7-methylguanosine regulators: Expression features and potential implications in prognosis and immunotherapy

Although immunotherapy has made great strides in cancer therapy, its effectiveness varies widely among individual patients as well as tumor types, and there is an urgent need to develop biomarkers for effectively assessing immunotherapy response. In recent years, RNA methylation regulators have demonstrated to be novel potential biomarkers for prognosis as well as immunotherapy of cancers, such as N6-methyladenine (m6A) and 5-methylcytosine (m5C). N7-methylguanosine (m7G) is a prevalent RNA modification in eukaryotes, but the relationship between m7G regulators and prognosis as well as tumor immune microenvironment is still unclear. In this study, a pan-cancer analysis of 26 m7G regulators across 17 cancer types was conducted based on the bioinformatics approach. On the one hand, a comprehensive analysis of expression features, genetic variations and epigenetic regulation of m7G regulators was carried out, and we found that the expression tendency of m7G regulators were different among tumors and their aberrant expression in cancers could be affected by single nucleotide variation (SNV), copy number variation (CNV), DNA methylation and microRNA (miRNA) separately or simultaneously. On the other hand, the m7Gscore was modeled based on single sample gene set enrichment analysis (ssGSEA) for evaluating the relationships between m7G regulators and cancer clinical features, hallmark pathways, tumor immune microenvironment, immunotherapy response as well as pharmacotherapy sensitivity, and we illustrated that the m7Gscore exhibited tight correlations with prognosis, several immune features, immunotherapy response and drug sensitivity in most cancers. In conclusion, our pan-cancer analysis revealed that m7G regulators may exert critical roles in the tumor progression and immune microenvironment, and have the potential as biomarkers for predicting prognosis, immunotherapy response as well as candidate drug compounds for cancer patients.

Integrative pan-cancer analysis and clinical characterization of the N7-methylguanosine (m7G) RNA modification regulators in human cancers

Background: RNA modification is one of the epigenetic mechanisms that regulates post-transcriptional gene expression, and abnormal RNA modifications have been reported to play important roles in tumorigenesis. N7-methylguanosine (m7G) is an essential modification at the 5′ cap of human mRNA. However, a systematic and pan-cancer analysis of the clinical relevance of m7G related regulatory genes is still lacking.

Methods: We used univariate Cox model and Kaplan-Meier analysis to generate the forest plot of OS, PFI, DSS and identified the correlation between the altered expression of m7G regulators and patient survival in 33 cancer types from the TCGA and GTEx databases. Then, the “estimate” R-package, ssGSEA and CIBERSORT were used to depict the pan-cancer immune landscape. Through Spearman’s correlation test, we analyzed the correlation between m7G regulators and the tumor microenvironment (TME), immune subtype, and drug sensitivity of the tumors, which was further validated in NSCLC. We also assessed the changes in the expression of m7G related regulatory genes in NSCLC with regards to the genetic and transcriptional aspects and evaluated the correlation of METTL1 and WDR4 expression with TMB, MSI and immunotherapy in pan-cancer.

Results: High expression of most of the m7G regulators was significantly associated with worse prognosis. Correlation analyses revealed that the expression of majority of the m7G regulators was correlated with tumor immune infiltration and tumor stem cell scores. Drug sensitivity analysis showed that the expression of CYFP1,2 was closely related to drug sensitivity for various anticancer agents (p < 0.001). Analysis of the pan-cancer immune subtype revealed significant differences in the expression of m7G regulators between different immune subtypes (p < 0.001). Additionally, the types and proportions of mutations in METTL1 and WDR4 and their relevance to immunotherapy were further described.

Conclusion: Our study is the first to evaluate the correlation between the altered expression of m7G regulators and patient survival, the degree of immune infiltration, TME and drug sensitivity in pan-cancer datasets.

Integrated Analyses of m6A Regulator-Mediated Methylation Modification Patterns and Tumor Microenvironment Infiltration Characterization in Pan-Cancer

The invasion of immune cells in the tumor microenvironment (TME) is closely related to cancer development. Studies have demonstrated that N6-methyladenosine (m⁶A) can affect the invasion of immune cells in TME as well as cancer development. We comprehensively analyzed the RNA-seq data of 16 different cancer types based on 20 m⁶A regulators and identified two distinct m⁶A modification patterns, which were closely associated with TME cell infiltration and overall patient survival. Then, we used principal component analysis (PCA) to construct m6Ascore based on the expression of m⁶A-related prognostic genes, which can successfully predict patient survival. The low-m6Ascore subtype is characterized by more immune cell infiltration, good prognosis and lower TNM stages, while the high-m6Ascore subtype is characterized by low immune infiltration, stromal activation, and poor prognosis. m6Ascore was also closely associated with immunotherapy response and was significantly higher in complete response/partial response (CR/PR) patients than in stable disease/progressive disease (SD/PD) patients in both immunotherapy cohorts. Therefore, our study indicates that m⁶A modification plays an important role in the prognosis of pan-cancer and the formation of complex TME in pan-cancer. Our research helps to improve the cognition of m⁶A modifications at pan-cancer levels and identify more effective strategies for immunotherapy.

m7G-Associated subtypes, tumor microenvironment, and validation of prognostic signature in lung adenocarcinoma

Background: 7-Methylguanosine (m7G) is an important posttranscriptional modification that regulates gene expression and is involved in tumorigenesis and development. Tumor microenvironment has been proven to be highly involved in tumor progression and prognosis. However, how m7G-associated genes affect the tumor microenvironment of patients with lung adenocarcinoma (LUAD) remains to be further clarified.

Methods: The genetic alterations of m7G-associated genes and their associations with the prognosis and tumor microenvironment in LUAD patients were systemically analyzed. An m7G-Riskscore was established and analyzed for its performance in disease prognosis and association with patient response to immunotherapy. Expression of the model genes at the protein level was investigated through ex vivo experiments. A nomogram was finally obtained based on the m7G-Riskscore and several significant clinical pathological features.

Results: m7G-Associated genes were obtained from five LUAD datasets from The Cancer Genome Atlas and Gene Expression Omnibus databases, and their expression pattern was determined. Based on the m7G-associated genes, three LUAD clusters were defined. The differentially expressed genes from the three clusters were screened and used to further divide the LUAD patients into two gene clusters. It was demonstrated that the alterations of m7G-associated genes were associated with the clinical pathological features, prognosis, and tumor immune infiltration in LUAD patients. An m7G-Riskscore including CAND1, RRM2, and SLC2A1 was obtained with robust and accurate prognostic performance. WB and cell immunofluorescence also showed significant dysregulation of CAND1, RRM2, and SLC2A1 in LUAD. In addition, a nomogram was established to improve the clinical feasibility of the m7G-Riskscore. Correlation analysis revealed that patients with a lower m7G-Riskscore had higher immune and stromal scores, responded well to chemotherapeutics and multiple targeted drugs, and survived longer. Patients with a higher m7G-Riskscore tended to suffer from a higher tumor mutation burden. Furthermore, the m7G-Riskscore exhibited significant associations with immune cell infiltration and cancer stemness.

Conclusion: This study systemically analyzed m7G-associated genes and identified their potential role in tumor microenvironment and prognosis in patients with LUAD. The findings of the present study may help better understand LUAD from the m7G perspective and also provide a new thought toward the prognosis and treatment of LUAD.

A signature constructed with mitophagy-related genes to predict the prognosis and therapy response for breast cancer

Over the past decades, the incidence and mortality rates of breast cancer (BC) have increased rapidly; however, molecular biomarkers that can reliably detect BC are yet to be discovered. Our study aimed to identify a novel signature that can predict the prognosis of patients with BC. Data from the TCGA-BRCA cohort were analyzed using univariate Cox regression analysis, and least absolute shrinkage and selection operator (LASSO) analysis was performed to build a stable prognostic model. Subsequently, Kaplan–Meier (K–M) and receiver operating characteristic (ROC) analyses were performed to demonstrate the predictive power of our gene signature. Each patient was assigned to either a low- or high-risk group. Patients with high-risk BC had poorer survival than those with low-risk BC. Cox regression analysis suggested that our signature was an independent prognostic factor. Additionally, decision curve analysis and calibration accurately predicted the capacity of our nomogram. Thus, based on the differentially expressed genes (DEGs) of mitophagy-related tumor classification, we established a 13-gene signature and robust nomogram for predicting BC prognosis, which can be beneficial for the diagnosis and treatment of BC.

Analysis and prognostic significance of tumour immune infiltrates and immune microenvironment of m6A-related lncRNAs in patients with gastric cancer

BACKGROUND

Studies have shown that long noncoding RNAs and N6-methyladenosine play important roles in gastric cancer. The purpose of this study was to determine the correlation and prognostic value of m6A-related lncRNAs and immune infiltration in gastric cancer.

METHODS

We downloaded the clinically related information and RNA-Seq transcriptome data of gastric cancer patients from the TCGA database. Univariate Cox regression analysis and Pearson analysis were used to screen out m6A-related lncRNAs. Consensus cluster analysis was used to divide the sample into two clusters, and LASSO analysis and Cox regression analysis were used to construct a risk scoring model.

RESULTS

A total of 25 lncRNA expression profiles were screened, and gastric cancer patients were divided into different subtypes. Cluster 2 had a better prognosis, but its stromal score, ESTIMATE score and immune score were low. Cluster 1 was rich in resting memory CD4 T cells, regulatory T cells, monocytes, and resting mast cells, and Cluster 2 was rich in activated memory CD4 T cells and follicular helper T cells. Thirteen lncRNAs were selected to construct a risk model, and the prognosis of gastric cancer patients in the high-risk group was poor. The expression of PD-L1 in tumours is significantly higher than that in normal tissues. Univariate and multivariate Cox regression analysis results showed that the overall survival rate was significantly related to stage and the risk score, which can be used as an independent prognostic factor. The results of the heatmap and scatter plot showed that clusters (P = 0.0045) and grade (G1-2, G3, P = 0.0037) were significantly related to prognosis. The relationship between the risk score and immune cell infiltration showed that memory B cells, resting dendritic cells, M0 macrophages, and M2 macrophages were positively correlated with the risk score, while resting mast cells, monocytes, activated NK cells, and follicular helper T cells were negatively correlated with the risk score.

CONCLUSION

The results of this study indicate that m6A-related lncRNAs may play an important role in the prognosis of gastric cancer patients and the tumour immune microenvironment and may provide help for the treatment of gastric cancer patients.

Comprehensive Analysis and Reinforcement Learning of Hypoxic Genes Based on Four Machine Learning Algorithms for Estimating the Immune Landscape, Clinical Outcomes, and Therapeutic Implications in Patients With Lung Adenocarcinoma

Background

Patients with lung adenocarcinoma (LUAD) exhibit significant heterogeneity in therapeutic responses and overall survival (OS). In recent years, accumulating research has uncovered the critical roles of hypoxia in a variety of solid tumors, but its role in LUAD is not currently fully elucidated. This study aims to discover novel insights into the mechanistic and therapeutic implications of the hypoxia genes in LUAD cancers by exploring the potential association between hypoxia and LUAD.

Methods

Four machine learning approaches were implemented to screen out potential hypoxia-related genes for the prognosis of LUAD based on gene expression profile of LUAD samples obtained from The Cancer Genome Atlas (TCGA), then validated by six cohorts of validation datasets. The risk score derived from the hypoxia-related genes was proven to be an independent factor by using the univariate and multivariate Cox regression analyses and Kaplan-Meier survival analyses. Hypoxia-related mechanisms based on tumor mutational burden (TMB), the immune activity, and therapeutic value were also performed to adequately dig deeper into the clinical value of hypoxia-related genes. Finally, the expression level of hypoxia genes was validated at protein level and clinical samples from LUAD patients at transcript levels.

Results

All patients in TCGA and GEO-LUAD group were distinctly stratified into low- and high-risk groups based on the risk score. Survival analyses demonstrated that our risk score could serve as a powerful and independent risk factor for OS, and the nomogram also exhibited high accuracy. LUAD patients in high-risk group presented worse OS, lower TMB, and lower immune activity. We found that the model is highly sensitive to immune features. Moreover, we revealed that the hypoxia-related genes had potential therapeutic value for LUAD patients based on the drug sensitivity and chemotherapeutic response prediction. The protein and gene expression levels of 10 selected hypoxia gene also showed significant difference between LUAD tumors tissues and normal tissues. The validation experiment showed that the gene transcript levels of most of their genes were consistent with the levels of their translated proteins.

Conclusions

Our study might contribute to the optimization of risk stratification for survival and personalized management of LUAD patients by using the hypoxia genes, which will provide a valuable resource that will guide both mechanistic and therapeutic implications of the hypoxia genes in LUAD cancers.

Development and Validation of a Novel Gene Signature for Predicting the Prognosis of Idiopathic Pulmonary Fibrosis Based on Three Epithelial-Mesenchymal Transition and Immune-Related Genes

Background: Increasing evidence has revealed that epithelial–mesenchymal transition (EMT) and immunity play key roles in idiopathic pulmonary fibrosis (IPF). However, correlation between EMT and immune response and the prognostic significance of EMT in IPF remains unclear.

Methods: Two microarray expression profiling datasets (GSE70866 and GSE28221) were downloaded from the Gene Expression Omnibus (GEO) database. EMT- and immune-related genes were identified by gene set variation analysis (GSVA) and the Estimation of STromal and Immune cells in MAlignant Tumors using Expression data (ESTIMATE) algorithm. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed to investigate the functions of these EMT- and immune-related genes. Cox and least absolute shrinkage and selection operator (LASSO) regression analyses were used to screen prognostic genes and establish a gene signature. Gene Set Enrichment Analysis (GSEA) and Cell-type Identification By Estimating Relative Subsets Of RNA Transcripts (CIBERSORT) were used to investigate the function of the EMT- and immune-related signatures and correlation between the EMT- and immune-related signatures and immune cell infiltration. Quantitative real-time polymerase chain reaction (qRT-PCR) was performed to investigate the mRNA expression of genes in the EMT- and immune-related signatures.

Results: Functional enrichment analysis suggested that these genes were mainly involved in immune response. Moreover, the EMT- and immune-related signatures were constructed based on three EMT- and immune-related genes (IL1R2, S100A12, and CCL8), and the K–M and ROC curves presented that the signature could affect the prognosis of IPF patients and could predict the 1-, 2-, and 3-year survival well. Furthermore, a nomogram was developed based on the expression of IL1R2, S100A12, and CCL8, and the calibration curve showed that the nomogram could visually and accurately predict the 1-, 2-, 3-year survival of IPF patients. Finally, we further found that immune-related pathways were activated in the high-risk group of patients, and the EMT- and immune-related signatures were associated with NK cells activated, macrophages M0, dendritic cells resting, mast cells resting, and mast cells activated. qRT-PCR suggested that the mRNA expression of IL1R2, S100A12, and CCL8 was upregulated in whole blood of IPF patients compared with normal samples.

Conclusion: IL1R2, S100A12, and CCL8 might play key roles in IPF by regulating immune response and could be used as prognostic biomarkers of IPF.

A Two-eRNA-Based Signature Can Impact the Immune Status and Predict the Prognosis and Drug Sensitivity of Lung Adenocarcinoma

Enhancer RNAs (eRNAs) are intergenic long noncoding RNAs (lncRNAs) participating in the development of malignant cancers via targeting cancer-associated genes and immune checkpoints. Immune infiltration of the tumor microenvironment was positively associated with overall survival (OS) in lung adenocarcinoma (LUAD). In this study, we aimed to explore the clinical significance of PCBP1-AS1 in LUAD and developed a novel prognostic signature based on two eRNAs. Our team discovered that the expression of PCBP1-AS1 was distinctly downregulated in LUAD specimens compared with nontumor specimens. Lower PCBP1-AS1 expression was related to advanced clinical stages and poor prognosis. KEGG analysis unveiled that the coexpression genes of PCBP1-AS1 were involved in the regulation of several tumor-related pathways. In addition, remarkable associations were observed between the expression of PCBP1-AS1 and the levels of several immune cells. Then, we used PCBP1-AS1 and TBX5-AS1 to develop a prognostic model. Survival assays unveiled that patients with higher risk scores exhibited a shorter OS in contrast to patients with lower risk scores. In addition, multivariable Cox regressive analysis indicated that the risk score was an independent prediction factor in LUAD sufferers. The anticancer drug sensitivity analysis indicated that risk score had a positive relationship with several anticancer drugs. Taken together, our findings indicated PCBP1-AS1 as a function modulator in LUAD development. In addition, we constructed a robust immune-related eRNA signature which might be a clinical prognosis factor for LUAD patients.

The Mechanism of Insulin-Like Growth Factor II mRNA-Binging Protein 3 Induce Decidualization and Maternal-Fetal Interface Cross Talk by TGF-β1 in Recurrent Spontaneous Abortion

Recurrent spontaneous abortion (RSA) is defined as the loss of two or more consecutive intrauterine pregnancies that are clinically established early in pregnancy. To date, the etiology and underlying mechanisms of RSA remain unclear. It is widely thought that the impairment of decidualization is inclined to induce subsequent pregnancy failure and leads to the dysregulation of extra-villous trophoblast invasion and proliferation through maternal–fetal cross talk. However, the mechanism of decidualization in RSA has yet to be understood. In our study, we demonstrate that decidual samples from RSA patients have significantly higher insulin-like growth factor 2 mRNA-binding protein 3 (IGF2BP3) and lower TGF-β1 levels compared to healthy controls. In addition, the overexpression of IGF2BP3 in human endometrial stromal cells (hESCs) can lead to the impairment of decidualization in vitro-induced model and the abnormal cell cycle regulation. Furthermore, TGF-β1 and MMP9 levels were greatly increased after decidualization, whereas IGF2BP3 overexpression inhibited endometrial mesenchymal decidualization by downregulating TGF-β1, impeding maternal–fetal interface cytokine cross talk, and limiting the ability of trophoblast invasion. In conclusion, our investigation first demonstrates that abnormal elevation of IGF2BP3 in the pregnant endometrium leads to the impairment of decidualization and abnormal trophoblast invasion, thereby predisposing individuals to RSA.

ZC3H13-mediated N6-methyladenosine modification of PHF10 is impaired by fisetin which inhibits the DNA damage response in pancreatic cancer

DNA damage repair is a major barrier for chemotherapy efficacy of pancreatic ductal adenocarcinoma (PDAC), including the efficacy of platinum-based and gemcitabine/nab-paclitaxel treatments. N6-methyladenosine modifications (m6A) have recently been reported to play a role in homologous recombination (HR) repair of DNA double strand breaks (DSBs); however, the mechanism of action remains unknown. Our previous work indicated that fisetin may be a promising anti-tumour agent that induces DNA damage. In this study, we reported that fisetin induced DSBs and suppressed HR repair through m6A modification in PDAC cells. The m6A writer ZC3H13 and PHF10, which is a subunit of the PBAF chromatin remodelling complex, were identified as the main molecules affected by fisetin treatment. To our knowledge, it's the first time that PHF10 was found and involved in the DNA damage response. PHF10 loss-of-function resulted in elevated recruitment of γH2AX, RAD51, and 53BP1 to DSB sites and decreased HR repair efficiency. Moreover, ZC3H13 knockdown downregulated the m6A methylation of PHF10 and decreased PHF10 translation in a YTHDF1-dependent manner. In conclusion, our study demonstrates that fisetin enhanced DSBs via ZC3Hl3-mediated m6A modification of PHF10, which may provide insight into novel therapeutic approaches for PDAC.

RNA modification writers influence tumor microenvironment in gastric cancer and prospects of targeted drug therapy

Background: RNA adenosine modifications are crucial for regulating RNA levels. N6-methyladenosine (m6A), N1-methyladenosine (m1A), adenosine-to-inosine RNA editing, and alternative polyadenylation (APA) are four major RNA modification types. Methods: We evaluated the altered mRNA expression profiles of 27 RNA modification enzymes and compared the differences in tumor microenvironment (TME) and clinical prognosis between two RNA modification patterns using unsupervised clustering. Then, we constructed a scoring system, WM_score, and quantified the RNA modifications in patients of gastric cancer (GC), associating WM_score with TME, clinical outcomes, and effectiveness of targeted therapies. Results: RNA adenosine modifications strongly correlated with TME and could predict the degree of TME cell infiltration, genetic variation, and clinical prognosis. Two modification patterns were identified according to high and low WM_scores. Tumors in the WM_score-high subgroup were closely linked with survival advantage, CD4[Formula: see text] T-cell infiltration, high tumor mutation burden, and cell cycle signaling pathways, whereas those in the WM_score-low subgroup showed strong infiltration of inflammatory cells and poor survival. Regarding the immunotherapy response, a high WM_score showed a significant correlation with PD-L1 expression, predicting the effect of PD-L1 blockade therapy. Conclusion: The WM_scoring system could facilitate scoring and prediction of GC prognosis.

N6-Methyladenosine Regulator-Mediated Immue Patterns and Tumor Microenvironment Infiltration Characterization in Glioblastoma

Background

Epigenetic modifications, according to emerging evidence, perform a critical role for cellular immune response and tumorigenesis. Nonetheless, the role of N6-methyladenosine modification in shaping of the glioblastoma tumor microenvironment is unknown.

Methods

N6-methyladenosine(m6A) methylation patterns in GBM patients were evaluated via multiple omics analysis of 15 m6A regulators and systematically correlated with tumor immune features. For quantification of N6-methyladenosine methylation patterns of individual patients, GM-score was developed and correlated with clinical and immunological characteristics.

Results

Glioblastoma has two different m6A methylation patterns that are strongly associated with TME characteristics, tumor subtype, immunotherapy response, and patient prognosis. High-GM-score is associated with an immune tolerance phenotype dominated by the IDH1 wild molecular subtype and the Mesenchymal tissue subtype, as well as a high infiltration of immune cells and stromal cells and a poor prognosis. Furthermore, despite higher immune checkpoint expression, individuals with a high-GM-score have a poorer response to anti-CTLA4 immunotherapy regimens due to T-cells dysfunctional. Low-GM-score individuals had an immunodeficient phenotype dominated by IDH mutant molecular subtypes and Proneural tissue subtypes, with less immune cell infiltration and a better prognosis. Furthermore, patients with low-GM-scores had higher microsatellite instability (MSI) and t-cell exclusion scores, as well as a better response to anti-CTLA4 immunotherapy regimens.

Conclusion

This study demonstrated that m6A modification patterns play an important role in the shaping of TME complexity and diversity. The GM-score could identify m6A modification patterns in individual patients, resulting in a more personalization and efficacious anti-tumor immunotherapy strategy.

MYC-activated RNA N6-methyladenosine reader IGF2BP3 promotes cell proliferation and metastasis in nasopharyngeal carcinoma

N6-Methyladenosine (m6A) modification is the most abundant RNA modification in eukaryotic cells. IGF2BP3, a well-known m6A reader, is deregulated in many cancers, but its role in nasopharyngeal carcinoma (NPC) remains unclear. In this work, IGF2BP3 was upregulated in NPC tissues and cells. The high level of IGF2BP3 was positively related to late clinical stages, node metastasis, and poor outcomes. Moreover, IGF2BP3 accelerated NPC cell tumor progression and metastasis in vitro and vivo. Upstream mechanism analyses indicated that the high expression of IGF2BP3 in head and neck tumors was mainly due to mRNA level amplification. Luciferase assay and chromatin immunoprecipitation assay (CHIP) depicted that MYC was effectively bound to the promoter of IGF2BP3, thereby improving its transcriptional activity. Results also showed that IGF2BP3 was not only positively correlated with KPNA2 expression but also modulated the expression of KPNA2. m6A RNA immunoprecipitation (MeRIP) and RNA stability experiments verified that silencing IGF2BP3 significantly inhibited the m6A modification level of KPNA2, thereby stabilizing the mRNA stability of KPNA2. Rescue experiments proved that the effect of inhibiting or overexpressing IGF2BP3 on NPC cells was partly reversed by KPNA2. Collectively, MYC-activated IGF2BP3 promoted NPC cell proliferation and metastasis by influencing the stability of m6A-modified KPNA2. Our findings offer new insights that IGF2BP3 may serve as a new molecular marker and potential therapeutic target for NPC treatment.

Construction and Clinical Translation of Causal Pan-Cancer Gene Score Across Cancer Types

Pan-cancer strategy, an integrative analysis of different cancer types, can be used to explain oncogenesis and identify biomarkers using a larger statistical power and robustness. Fine-mapping defines the casual loci, whereas genome-wide association studies (GWASs) typically identify thousands of cancer-related loci and not necessarily have a fine-mapping component. In this study, we develop a novel strategy to identify the causal loci using a pan-cancer and fine-mapping assumption, constructing the CAusal Pan-cancER gene (CAPER) score and validating its performance using internal and external validation on 1,287 individuals and 985 cell lines. Summary statistics of 15 cancer types were used to define 54 causal loci in 15 potential genes. Using the Cancer Genome Atlas (TCGA) training set, we constructed the CAPER score and divided cancer patients into two groups. Using the three validation sets, we found that 19 cancer-related variables were statistically significant between the two CAPER score groups and that 81 drugs had significantly different drug sensitivity between the two CAPER score groups. We hope that our strategies for selecting causal genes and for constructing CAPER score would provide valuable clues for guiding the management of different types of cancers.