m6A-immune-related lncRNA prognostic signature for predicting immune landscape and prognosis of bladder cancer

The RNA N6-methyladenosine demethylase FTO regulates ATG5 to inhibit malignant progression of uveal melanoma

PURPOSE

This research aimed to identify the function of fat mass- and obesity-associated protein (FTO), an eraser of N6-methyladenosine (m6A), and explore its possible mechanisms in uveal melanoma (UVM).

METHODS

We performed quantitative real-time PCR (qPCR), Western blotting and gene correlation analysis with GEPIA2 to assess FTO expression and identify its potential targets in UVM. CCK-8, colony formation, cell cycle, cell apoptosis, wound healing and Transwell invasion assays were utilized to assess cell viability, cell cycle distribution, apoptosis, migration and invasion. Western blotting, qPCR and methylated RNA immunoprecipitation-qPCR (MeRIP-qPCR) were carried out to explore the underlying mechanism of FTO in 2 UVM cell lines.

RESULTS

FTO, a key m6A demethylase, was found to be upregulated in human UVM tissues compared with normal choroid tissues. Knockdown of FTO in Mel270 and OMM2.3 cells significantly promoted proliferation and migration and suppressed apoptosis. Mechanistically, knockdown of FTO decreased the expression of ATG5, an autophagy-related gene, leading to attenuation of autophagosome formation, thereby inhibiting autophagy. Upon FTO knockdown, increased levels of methylated ATG5 and decreased ATG5 stability were detected. Furthermore, ATG5 dramatically alleviated FTO downregulation-induced tumor growth and metastasis.

CONCLUSIONS

Our research highlights the importance of the m6A demethylase FTO in UVM by demonstrating that it direct regulates ATG5-induced autophagy in an m6A-dependent manner. These findings suggest that FTO may serve as a potential therapeutic target for UVM.

RNA N6-methyladenosine modifications in urological cancers: from mechanism to application

The N6-methyladenosine (m6A) modification is the most common modification of messenger RNAs in eukaryotes and has crucial roles in multiple cancers, including in urological malignancies such as renal cell carcinoma, bladder cancer and prostate cancer. The m6A RNA modification is controlled by three types of regulators, including methyltransferases (writers), demethylases (erasers) and RNA-binding proteins (readers), which are responsible for gene regulation at the post-transcriptional level. This Review summarizes the current evidence indicating that aberrant or dysregulated m6A modification is associated with urological cancer development, progression and prognosis. The complex and context-dependent effects of dysregulated m6A modifications in urological cancers are described, along with the potential for aberrantly expressed m6A regulators to provide valuable diagnostic and prognostic biomarkers as well as new therapeutic targets.

FTO promotes the progression of bladder cancer via demethylating m6A modifications in PTPN6 mRNA

Bladder cancer (BC), a highly prevalent malignancy of the urinary system, necessitates further investigation into its progression mechanisms. N6-methyladenosine (m6A) RNA methylation, a prevalent modification in cellular RNA, has been implicated in the tumorigenesis and metastasis of various cancers. In this study, the upregulation of FTO in human BC samples and its association with poor prognosis were demonstrated using immunohistochemistry (IHC) on tissue sections collected from BC patients. The functional role of FTO in promoting the proliferation and metastasis abilities of BC cells was determined using a combination of in vitro and in vivo assays. In vitro, we conducted cell proliferation assays, such as the Cell Counting Kit-8 (CCK-8) assay, and metastasis assays, including the wound healing assay and transwell invasion assay. In vivo, we employed xenograft models to assess tumor growth and metastasis. Furthermore, our investigation into potential FTO targets in BC cells revealed that FTO modifies PTPN6 mRNA, leading to increased stability and expression of PTPN6, thereby enhancing proliferation and metastasis abilities. In conclusion, our findings indicate that FTO serves as an oncogenic factor in BC, suggesting its potential utility as a diagnostic or prognostic biomarker for bladder cancer.

Identifying subtypes and developing prognostic models based on N6-methyladenosine and immune microenvironment related genes in breast cancer

Breast cancer (BC) is the most prevalent cancer in women globally. The tumor microenvironment (TME), comprising epithelial tumor cells and stromal elements, is vital for breast tumor development. N6-methyladenosine (m6A) modification plays a key role in RNA metabolism, influencing its various aspects such as stability and translation. There is a notable link between m6A methylation and immune cells in the TME, although this relationship is complex and not fully deciphered. In this research, BC expression and clinicopathological data from TCGA were scrutinized to assess expression profiles, mutations, and CNVs of 31 m6A genes and immune microenvironment-related genes, examining their correlations, functions, and prognostic impacts. Lasso and Cox regression identified prognostic genes for constructing a nomogram. Single-cell analyses mapped the distribution and patterns of these genes in BC cell development. We investigated associations between gene-derived risk scores and factors like immune infiltration, TME, checkpoints, TMB, CSC indices, and drug response. As a complement to computational analyses, in vitro experiments were conducted to confirm these expression patterns. We included 31 m6A regulatory genes and discovered a correlation between these genes and the extent of immune cell infiltration. Subsequently, a 7-gene risk score was generated, encompassing HSPA2, TAP1, ULBP2, CXCL1, RBP1, STC2, and FLT3. It was observed that the low-risk group exhibited better overall survival (OS) in BC, with higher immune scores but lower tumor mutational burden (TMB) and cancer stem cell (CSC) indices, as well as lower IC50 values for commonly used drugs. To enhance clinical applicability, age and stage were incorporated into the risk score, and a more comprehensive nomogram was constructed to predict OS. This nomogram was validated and demonstrated good predictive performance, with area under the curve (AUC) values for 1-year, 3-year, and 5-year OS being 0.848, 0.807, and 0.759, respectively. Our findings highlight the profound impact of prognostic-related genes on BC immune response and prognostic outcomes, suggesting that modulation of the m6A-immune pathway could offer new avenues for personalized BC treatment and potentially improve clinical outcomes.

N6-methyladenosine modified lncRNAs signature for stratification of biochemical recurrence in prostate cancer

Nonmutational epigenetic reprogramming is a crucial mechanism contributing to the pronounced heterogeneity of prostate cancer (PCa). Among these mechanisms, N6-methyladenosine (m6A)-modified long non-coding RNAs (lncRNAs) have emerged as key players. However, the precise roles of m6A-modified lncRNAs in PCa remain to be elucidated. In this study, methylated RNA immunoprecipitation sequencing (MeRIP-seq) was conducted on primary and metastatic PCa samples, leading to the identification of 21 lncRNAs exhibiting differential methylation and expression patterns. We further established a PCa prognostic signature, named m6A-modified lncRNA score (mLs), based on 9 differential methylated lncRNAs in 4 multicenter cohorts. The high mLs score cohort exhibited a tendency for earlier biochemical recurrence (BCR) compared to the low mLs score cohort. Remarkably, the predictive performance of the mLs score surpassed that of five previously reported lncRNA-based signatures. Functional enrichment analysis underscored a negative correlation between the mLs score and lipid metabolism. Additionally, through MeRIP-qPCR, we pinpointed a hub gene, MIR210HG, which was validated through in vitro and in vivo experiments. These findings collectively illuminate the landscape of m6A-methylated lncRNAs in PCa tissue via MeRIP-seq and harness this information to prognosticate PCa outcomes using the mLs score. Furthermore, our study validates, both experimentally and mechanistically, the facilitative role of MIR210HG in driving PCa progression.

Overview of the interplay between m6A methylation modification and non-coding RNA and their impact on tumor cells

N6-methyladenosine (m6A) is one of the most common internal modifications in eukaryotic RNA. The presence of m6A on transcripts can affect a series of fundamental cellular processes, including mRNA splicing, nuclear transportation, stability, and translation. The m6A modification is introduced by m6A methyltransferases (writers), removed by demethylases (erasers), and recognized by m6A-binding proteins (readers). Current research has demonstrated that m6A methylation is involved in the regulation of malignant phenotypes in tumors by controlling the expression of cancer-related genes. Non-coding RNAs (ncRNAs) are a diverse group of RNA molecules that do not encode proteins and are widely present in the human genome. This group includes microRNAs (miRNAs), long non-coding RNAs (lncRNAs), circular RNAs (circRNAs), and PIWI interaction RNAs (piRNAs). They function as oncogenes or tumor suppressors through various mechanisms, regulating the initiation and progression of cancer. Previous studies on m6A primarily focused on coding RNAs, but recent discoveries have revealed the significant regulatory role of m6A in ncRNAs. Simultaneously, ncRNAs also exert their influence by modulating the stability, splicing, translation, and other biological processes of m6A-related enzymes. The interplay between m6A and ncRNAs collectively contributes to the occurrence and progression of malignant tumors in humans. This review provides an overview of the interactions between m6A regulatory factors and ncRNAs and their impact on tumors.

Effects and mechanisms of N6-methyladenosine RNA methylation in environmental pollutant-induced carcinogenesis

Environmental pollution, including air pollution, plastic contamination, and heavy metal exposure, is a pressing global issue. This crisis contributes significantly to pollution-related diseases and is a critical risk factor for chronic health conditions, including cancer. Mounting evidence underscores the pivotal role of N6-methyladenosine (m6A) as a crucial regulatory mechanism in pathological processes and cancer progression. Governed by m6A writers, erasers, and readers, m6A orchestrates alterations in target gene expression, consequently playing a vital role in a spectrum of RNA processes, covering mRNA processing, translation, degradation, splicing, nuclear export, and folding. Thus, there is a growing need to pinpoint specific m6A-regulated targets in environmental pollutant-induced carcinogenesis, an emerging area of research in cancer prevention. This review consolidates the understanding of m6A modification in environmental pollutant-induced tumorigenesis, explicitly examining its implications in lung, skin, and bladder cancer. We also investigate the biological mechanisms that underlie carcinogenesis originating from pollution. Specific m6A methylation pathways, such as the HIF1A/METTL3/IGF2BP3/BIRC5 network, METTL3/YTHDF1-mediated m6A modification of IL 24, METTL3/YTHDF2 dynamically catalyzed m6A modification of AKT1, METTL3-mediated m6A-modified oxidative stress, METTL16-mediated m6A modification, site-specific ATG13 methylation-mediated autophagy, and the role of m6A in up-regulating ribosome biogenesis, all come into play in this intricate process. Furthermore, we discuss the direction regarding the interplay between pollutants and RNA metabolism, particularly in immune response, providing new information on RNA modifications for future exploration.

The identification of a N6-methyladenosin-modifed immune pattern to predict immunotherapy response and survival in urothelial carcinoma

BACKGROUND

Dysregulation of the immune system and N6-methyladenosine (m6A) contribute to immune therapy resistance and cancer progression in urothelial carcinoma (UC). This study aims to identify immune-related molecules, that are m6A-modified, and that are associated with tumor progression, poor prognosis, and immunotherapy response.

METHODS

We identified prognostic immune genes (PIGs) using Cox analysis and random survival forest variable hunting algorithm (RSF-VH) on immune genes retrieved from the Immunology Database and Analysis Portal database (ImmPort). The RM2Target database and MeRIP-seq analysis, combined with a hypergeometric test, assessed m6A methylation in these PIGs. We analyzed the correlation between the immune pattern and prognosis, as well as their association with clinical factors in multiple datasets. Moreover, we explored the interplay between immune patterns, tumor immune cell infiltration, and m6A regulators.

RESULTS

28 PIGs were identified, of which the 10 most significant were termed methylated prognostic immune genes (MPIGs). These MPIGs were used to create an immune pattern score. Kaplan-Meier and Cox analyses indicated this pattern as an independent risk factor for UC. We observed significant associations between the immune pattern, tumor progression, and immune cell infiltration. Differential expression analysis showed correlations with m6A regulators expression. This immune pattern proved effective in predicting immunotherapy response in UC in real-world settings.

CONCLUSION

The study identified a m6A-modified immune pattern in UC, offering prognostic and therapeutic response predictions. This emphasizes that immune genes may influence tumor immune status and progression through m6A modifications.

Disulfidptosis-related lncRNA signature reveals immune microenvironment and novel molecular subtyping of stomach adenocarcinoma

The main challenge in treating stomach adenocarcinoma (STAD) is chemotherapy resistance, which is characterized by changes in the immune microenvironment. Disulfidptosis, a novel form of programmed cell death, is involved in STAD but its mechanism is not fully understood. Long non-coding RNAs (LncRNAs) may play a role in regulating disulfidptosis and influencing the immune microenvironment and chemotherapy resistance in STAD. This study aims to establish disulfidptosis-related lncRNA (DRL) features and explore their significance in the immune microenvironment and chemotherapy resistance in STAD patients. By analyzing RNA sequencing and clinical data from STAD patients and extracting disulfidptosis-related genes, we identified DRLs through co-expression, single-factor and multi-factor Cox regression, and Lasso regression analyses. We also investigated differences in the immune microenvironment, immune function, immune checkpoint gene expression, and chemotherapy resistance between different risk groups using various algorithms. A prognostic risk model consisting of 2 DRLs was constructed, with a strong predictive value for patient survival, outperforming other clinical-pathological factors in predicting 3-year and 5-year survival. Immune-related analysis revealed a strong positive correlation between T cell CD4+ cells and risk score across all algorithms, and higher expression of immune checkpoint genes in the high-risk group. In addition, high-risk patients showed better sensitivity to Erlotinib, Oxaliplatin, and Gefitinib. Furthermore, three novel molecular subtypes of STAD were identified based on the 2-DRLs features, with evaluation of the immune microenvironment and chemotherapy drug sensitivity for each subgroup, which holds significant implications for achieving precise treatment in STAD. Overall, our 2-DRLs prognostic model demonstrates high predictive value for patient survival in STAD, potentially providing new targets for individualized immune and chemical therapy.

The potential of DEirlncRNAs: A novel approach to predict glioblastoma prognosis

Background

Despite tremendous evolution in therapies, the prognosis of glioblastoma (GBM) remains grim, which calls for innovative approaches to optimize chemotherapy efficacy and predict risk.

Methods

The transcriptome and clinical data of GBM were acquired from the Cancer Genome Atlas (TCGA), followed by the identification of differentially expressed immune-related long noncoding RNAs (DEirlncRNAs) with Pearson correlation and limma packet analyses. Survival-related DEirlncRNA pairs were screened with univariate Cox proportional hazard regression. Prognostic markers were obtained, and risk scores were calculated with Lasso regression and multivariate Cox risk regression analyses. The association of the prognostic risk model with immune cell infiltration was evaluated by comprehensively analyzing tumor-infiltrating immune cells with TIMER, XCELL, CIBERSORT, QUANTISEQ, and EPIC. Differences in half-maximal inhibitory concentration (IC50) values between the high- and low-risk groups were assessed with the Wilcoxon signed-rank test.

Results

A total of 276 DEirlncRNAs were identified, followed by the visualization of their expression patterns. Two prognosis-related DEirlncRNA pairs were screened, with high accuracy and reliability. The constructed prognostic risk model effectively distinguished between high- and low-risk patients, and significant differences were observed in survival outcomes between the high- and low-risk groups. Furthermore, risk scores were associated with tumor-infiltrating immune cells and DEirlncRNA expression. Additionally, the risk model had a correlation with the effectiveness of commonly used chemotherapeutic agents, providing clues into potential treatment responses.

Conclusions

In our study, a novel signature was constructed with paired DEirlncRNAs (regardless of their expression), which holds significant clinical predictive value and is a potential breakthrough for personalized management of GBM.

Independent prognostic value of CLDN6 in bladder cancer based on M2 macrophages related signature

M2 macrophages are associated with the prognosis of bladder cancer. CLDN6 has been linked to immune infiltration and is crucial for predicting the prognosis in multi-tumor. The effect of CLDN6 on M2 macrophages in bladder cancer remains elusive. Here, we compared a total of 40 machine learning algorithms, then selected optimal algorithm to develop M2 macrophages-related signature (MMRS) based on the identified M2 macrophages related module. MMRS predicted the prognosis better than other models and associated to immunotherapy response. CLDN6, as an important variable in MMRS, was an independent factor for poor prognosis. We found that CLDN6 was highly expressed and affected immune infiltration, immunotherapy response, and M2 macrophages polarization. Meanwhile, CLDN6 promoted the growth of bladder cancer and enhanced the carcinogenic effect by inducing polarization of M2 macrophages. In total, CLDN6 is an independent risk factor in MMRS to predict the prognosis of bladder cancer.

METTL3 and METTL14-mediated N6-methyladenosine modification of SREBF2-AS1 facilitates hepatocellular carcinoma progression and sorafenib resistance through DNA demethylation of SREBF2

As the most prevalent epitranscriptomic modification, N6-methyladenosine (m6A) shows important roles in a variety of diseases through regulating the processing, stability and translation of target RNAs. However, the potential contributions of m6A to RNA functions are unclear. Here, we identified a functional and prognosis-related m6A-modified RNA SREBF2-AS1 in hepatocellular carcinoma (HCC). The expression of SREBF2-AS1 and SREBF2 in HCC tissues and cells was measured by RT-qPCR. m6A modification level of SREBF2-AS1 was measured by methylated RNA immunoprecipitation assay. The roles of SREBF2-AS1 in HCC progression and sorafenib resistance were investigated by proliferation, apoptosis, migration, and cell viability assays. The regulatory mechanisms of SREBF2-AS1 on SREBF2 were investigated by Chromatin isolation by RNA purification, RNA immunoprecipitation, CUT&RUN, and bisulfite DNA sequencing assays. Our findings showed that the expression of SREBF2-AS1 was increased in HCC tissues and cells, and positively correlated with poor survival of HCC patients. m6A modification level of SREBF2-AS1 was also increased in HCC and positively correlated with poor prognosis of HCC patients. METTL3 and METTL14-induced m6A modification upregulated SREBF2-AS1 expression through increasing SREBF2-AS1 transcript stability. Functional assays showed that only m6A-modified, but not non-modified SREBF2-AS1 promoted HCC progression and sorafenib resistance. Mechanistic investigations revealed that m6A-modified SREBF2-AS1 bound and recruited m6A reader FXR1 and DNA 5-methylcytosine dioxygenase TET1 to SREBF2 promoter, leading to DNA demethylation at SREBF2 promoter and the upregulation of SREBF2 transcription. Functional rescue assays showed that SREBF2 was the critical mediator of the oncogenic roles of SREBF2-AS1 in HCC. Together, this study showed that m6A-modified SREBF2-AS1 exerted oncogenic roles in HCC through inducing DNA demethylation and transcriptional activation of SREBF2, and suggested m6A-modified SREBF2-AS1 as a prognostic biomarker and therapeutic target for HCC.

A pan-cancer analysis of the oncogenic and immunological roles of transglutaminase 1 (TGM1) in human cancer

BACKGROUND

There is currently a limited number of studies on transglutaminase type 1 (TGM1) in tumors. The objective of this study is to perform a comprehensive analysis across various types of cancer to determine the prognostic significance of TGM1 in tumors and investigate its role in the immune environment.

METHOD

Pan-cancer and mutational data were retrieved from the TCGA database and analyzed using R (version 3.6.4) and its associated software package. The expression difference and prognosis of TGM1 were examined, along with its correlation with tumor heterogeneity, stemness, mutation landscape, and RNA modification. Additionally, the relationship between TGM1 expression and tumor immunity was investigated using the TIMER method.

RESULTS

TGM1 is expressed differently in various tumors and normal samples and is associated with the overall survival and progression-free time of KIRC, ACC, SKCM, LIHC, and STES. In LICH, we found a negative correlation between TGM1 expression and 6 indicators of tumor stemness. The mutation frequencies of BLCA, LIHC, and KIRC were 1.7%, 0.3%, and 0.3% respectively. In BLCA and BRCA, there was a significant correlation between TGM1 expression and the infiltration of CD4 + T cells, CD8 + T cells, neutrophils, and dendritic cells.

CONCLUSION

TGM1 has the potential to serve as both a prognostic marker and a drug target.

Knowledge mapping and current trends of m6A methylation in the field of cancer

Background

Cancer is a serious threat to people's lives and health, killing millions of people every year. Here, we performed a bibliometric analysis of tumor N6-methyladenosine methylation data between 2001 and 2022 to understand research trends and potential future directions.

Methods

A total of 890 papers published in the Web of Science core collection database between January 1, 2001 and December 31, 2022 were analyzed. Bibliometric analysis was performed using VOSviewer software to explore citations, co-authorship, co-citations, and co-occurrence.

Results

Although few papers were published before 2018, there was a rapid increase in publications after 2018. The People's Republic of China published 810 papers with 16,957 citations, both ranking first in the word. Sun Yat Sen University had the highest number of citations and published articles (67 published papers and 2702 citations), indicative of its active collaborative research status. Wang Xiao was the most co-cited author with 546 co-citations. Huang Yufei and Meng Jia ranked first with a link strength of 22, making them the most active collaborative authors. Frontiers in Oncology and Nature were the most active and co-cited journals, with 57 papers and 1953 co-citations, respectively. Studies of tumor N6-methyladenosine methylation can be divided into three categories: "tumor metabolism", "tumor bioinformatics and immunity", and "tumor progression".

Conclusions

This study systematically summarized the research on tumor N6-methyladenosine methylation during the past 20 years and suggested potential ways to explore its biomarkers and immunotherapy in the future.

The prognostic significance and clinical relevance of stem cell characteristic in bladder cancer

Background

Bladder cancer (BLCA) is a common malignant tumor of urinary system and prognostic biomarkers are needed for better clinical decision-making and patient management. Cancer stem cells (CSCs) are involved in carcinogenesis, development, metastasis and recurrence of BLCA. This study explored the prognostic and predictive value of CSCs-related genes and laid the groundwork for precision treatment development in BLCA.

Methods

The mRNA data and corresponding clinical information obtained from TCGA-BLCA cohort was used to discover biomarkers and develop CSCs-related prognostic model, which was further validated in GSE32548 and GSE32894 datasets. In addition, the association between CSCs-related risk score and therapeutic efficacy was analyzed to explore the potential predictive value of the prognostic model.

Results

We identified four CSCs-related subtypes and 900 differentially expressed genes (DEGs) among subtypes. Then the CSCs-related prognostic model was built based on 16 CSCs-related DEGs with the most significant prognostic value. Patients in the low-risk group had better overall survival than those in high-risk group (P < 0.001; HR, 0.42; 95 %CI, 0.31-0.57). Multivariable Cox analysis in training and test sets confirmed the independence of CSCs-related risk score as a prognostic factor (P < 0.05). The difference of survival between two risk groups were probably due to the significantly varied immune microenvironment based on the analysis of infiltrated immune cells. Additionally, the risk score was significantly associated with chemotherapy sensitivity and the response to anti-PD-L1 therapy (P < 0.05) which suggested a potential predictive value of CSCs-related risk model.

Conclusion

We established a risk classifier based on 16 CSCs-related genes for predicting survival in patients with BLCA. The CSCs-related risk model has both prognostic value and potential predictive value for therapeutic efficacy, which brings us closer to understanding the important role of CSCs in BLCA and may provide guidance for clinical treatment decision-making and patient management. The clinical utility of the CSCs-related risk classifier warrants further studies.

Characterization and verification of CAF-relevant prognostic gene signature to aid therapy in bladder cancer

Cancer-associated fibroblasts (CAFs) are significantly involved in determining the patient's prognosis and response to bladder cancer (BLCA) therapy. CAFs can induce epithelial-mesenchymal transformation (EMT) as well as complex interaction with immune cells. Hence, it is imperative to identify potential markers for enhancing our understanding of CAFs in BLCA progression and immune regulation. A variety of algorithms and analyses were employed in the study, leading to the development of a novel prognostic feature for CAFs-Stromal-EMT (CSE)-prognostic feature. This feature was constructed based on the genes MFAP5, PCOLCE2, and JUN. Furthermore, we revealed that patients with higher CSE risk scores responded to immunotherapy better compared to those with lower. Finally, we verified two CSE-related genes using in vitro experiments. Our results suggested that the CSE-prognostic feature could predict the prognosis and evaluate the response of patients to immune and chemotherapies. This would aid clinicians in designing treatment strategies for patients with BLCA.

TFRC, associated with hypoxia and immune, is a prognostic factor and potential therapeutic target for bladder cancer

BACKGROUND

Bladder cancer is a common malignancy of the urinary system, and the survival rate and recurrence rate of patients with muscular aggressive (MIBC) bladder cancer are not ideal. Hypoxia is a pathological process in which cells acquire special characteristics to adapt to anoxic environment, which can directly affect the proliferation, invasion and immune response of bladder cancer cells. Understanding the exact effects of hypoxia and immune-related genes in BLCA is helpful for early assessment of the prognosis of BLCA. However, the prognostic model of BLCA based on hypoxia and immune-related genes has not been reported.

PURPOSE

Hypoxia and immune cell have important role in the prognosis of bladder cancer (BLCA). The aim of this study was to investigate whether hypoxia and immune related genes could be a novel tools to predict the overall survival and immunotherapy of BLCA patients.

METHODS

First, we downloaded transcriptomic data and clinical information of BLCA patients from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. A combined hypoxia and immune signature was then constructed on the basis of the training cohort via least absolute shrinkage and selection operator (LASSO) analysis and validated in test cohort. Afterwards, Kaplan-Meier curves, univariate and multivariate Cox and subgroup analysis were employed to assess the accuracy of our signature. Immune cell infiltration, checkpoint and the Tumor Immune Dysfunction and Exclusion (TIDE) algorithm were used to investigate the immune environment and immunotherapy of BLCA patients. Furthermore, we confirmed the role of TFRC in bladder cancer cell lines T24 and UMUC-3 through cell experiments.

RESULTS

A combined hypoxia and immune signature containing 8 genes were successfully established. High-risk group in both training and test cohorts had significantly poorer OS than low-risk group. Univariate and multivariate Cox analysis indicated our signature could be regarded as an independent prognostic factor. Different checkpoint was differently expressed between two groups, including CTLA4, HAVCR2, LAG3, PD-L1 and PDCD1. TIDE analysis indicated high-risk patients had poor response to immunotherapy and easier to have immune escape. The drug sensitivity analysis showed that high-risk group patients were more potentially sensitive to many drugs. Meanwhile, TFRC could inhibit the proliferation and invasion ability of T24 and UMUC-3 cells.

CONCLUSION

A combined hypoxia and immune-related gene could be a novel predictive model for OS and immunotherapy estimation of BLCA patients and TFRC could be used as a potential therapeutic target in the future.

Identification of a novel m6A-related lncRNAs signature and immunotherapeutic drug sensitivity in pancreatic adenocarcinoma

BACKGROUND

Pancreatic adenocarcinoma (PDAC) ranks as the fourth leading cause for cancer-related deaths worldwide. N6-methyladenosine (m6A) and long non-coding RNAs (lncRNAs) are closely related with poor prognosis and immunotherapeutic effect in PDAC. The aim of this study is to construct and validate a m6A-related lncRNAs signature and assess immunotherapeutic drug sensitivity in PDAC.

METHODS

RNA-seq data for 178 cases of PDAC patients and 167 cases of normal pancreatic tissue were obtained from TCGA and GTEx databases, respectively. A set of 21 m6A-related genes were downloaded based on the previous report. Co-expression network was conducted to identify m6A-related lncRNAs in PDAC. Cox analyses and least absolute shrinkage and selection operator (Lasso) regression model were used to construct a risk prognosis model. The relationship between signature genes and immune function was explored by single-sample GSEA (ssGSEA). The tumor immune dysfunction and exclusion (TIDE) score and tumor mutation burden (TMB) were utilized to evaluate the response to immunotherapy. Furthermore, the expression levels of 4 m6A-related lncRNAs on PDAC cell lines were measured by the quantitative real-time PCR (qPCR). The drug sensitivity between the high- and low-risk groups was validated using PDAC cell lines by Cell-Counting Kit 8 (CCK8).

RESULTS

The risk prognosis model was successfully constructed based on 4 m6A-related lncRNAs, and PDAC patients were divided into the high- and low-risk groups. The overall survival (OS) of the high-risk groups was more unfavorable compared with the low-risk groups. Receiver operating characteristic (ROC) curves demonstrated that the risk prognosis model reasonably predicted the 2-, 3- and 5-year OS of PDAC patients. qPCR analysis confirmed the decreased expression levels of 4 m6A-related lncRNAs in PDAC cells compared to the normal pancreatic cells. Furthermore, CCK8 assay revealed that Phenformin exhibited higher sensitivity in the high-risk groups, while Pyrimethamine exhibited higher sensitivity in the low-risk groups.

CONCLUSION

The prognosis of patients with PDAC were well predicted in the risk prognosis model based on m6A-related lncRNAs, and selected immunotherapy drugs have potential values for the treatment of pancreatic cancer.

Molecular subgroup establishment and signature creation of lncRNAs associated with acetylation in lung adenocarcinoma

BACKGROUND

The significance of long non-coding RNAs (lncRNAs) as pivotal mediators of histone acetylation and their influential role in predicting the prognosis of lung adenocarcinoma (LUAD) has been increasingly recognized. However, there remains uncertainty regarding the potential utility of acetylation-related lncRNAs (ARLs) in prognosticating the overall survival (OS) of LUAD specimens.

METHODS

The RNA-Seq and clinical information were downloaded from The Cancer Genome Atlas (TCGA). Through the differential analysis, weighted correlation network analysis (WGCNA), Pearson correlation test and univariate Cox regression, we found out the prognosis associated ARLs and divided LUAD specimens into two molecular subclasses. The ARLs were employed to construct a unique signature through the implementation of the Least Absolute Shrinkage and Selection Operator (LASSO) algorithm. Subsequently, the predictive performance was evaluated using ROC analysis and Kaplan-Meier survival curve analysis. Finally, ARL expression in LUAD was confirmed by quantitative real-time PCR (qRT-PCR).

RESULTS

We triumphantly built a ARLs prognostic model with excellent predictive accuracy for LUAD. Univariate and multivariate Cox analysis illustrated that risk model served as an independent predictor for influencing the overall survival OS of LUAD. Furthermore, a nomogram exhibited strong prognostic validity. Additionally, variations were observed among subgroups in the field of immunity, biological functions, drug sensitivity and gene mutations within the field.

CONCLUSIONS

Nine ARLs were identified as promising indicators of personalized prognosis and drug selection for people suffering with LUAD.

Establishment of a prognostic risk prediction model incorporating disulfidptosis-related lncRNA for patients with prostate cancer

PURPOSE

Prostate cancer (PCa) is one of the major tumor diseases that threaten men's health globally, and biochemical recurrence significantly impacts its prognosis. Disulfidptosis, a recently discovered cell death mechanism triggered by intracellular disulfide accumulation leading to membrane rupture, is a new area of research in the context of PCa. Currently, its impact on PCa remains largely unexplored. This study aims to investigate the correlation between long non-coding RNAs (lncRNAs) associated with disulfidptosis and the prognosis of PCa, seeking potential connections between the two.

METHODS

Transcriptomic data for a PCa cohort were obtained from the Cancer Genome Atlas database. Disulfidptosis-related lncRNAs (DDRLs) were identified through differential expression and Pearson correlation analysis. DDRLs associated with biochemical recurrence-free survival (BRFS) were precisely identified using univariate Cox and LASSO regression, resulting in the development of a risk score model. Clinical factors linked to BRFS were determined through both univariate and multivariate Cox analyses. A prognostic nomogram combined the risk score with key clinical variables. Model performance was assessed using Receiver Operating Characteristic (ROC) curves, Decision Curve Analysis (DCA), and calibration curves. The functional impact of a critical DDRL was substantiated through assays involving CCK8, invasion, migration, and cell cloning. Additionally, immunohistochemical (IHC) staining for the disulfidptosis-related protein SLC7A11 was conducted.

RESULTS

The prognostic signature included AC026401.3, SNHG4, SNHG25, and U73166.1 as key components. The derived risk score from these signatures stood as one of the independent prognostic factor for PCa patients, correlating with poorer BRFS in the high-risk group. By combining the risk score with clinical variables, a practical nomogram was created, accurately predicting BRFS of PCa patients. Notably, silencing AC026401.3 significantly hindered PCa cell proliferation, invasion, migration, and colony formation. IHC staining revealed elevated expression of the dithiosulfatide-related protein SLC7A11 in tumor tissue.

CONCLUSIONS

A novel prognostic signature for PCa DDRLs, possessing commendable predictive power, has been constructed, simultaneously providing potential therapeutic targets associated with disulfidptosis, among which AC026401.3 has been validated in vitro and demonstrated inhibition of PCa tumorigenesis after its silencing.

Biological role of long non-coding RNA KCNQ1OT1 in cancer progression

Long non-coding RNAs (lncRNAs) are a type of RNAs that are more than 200 nucleotides without protein-coding potential. In recent years, more and more attention has been paid to the role of lncRNAs in cancer pathogenesis. LncRNA KCNQ1 overlapping transcript 1 (KCNQ1OT1) is located on chromosome 11p15.5 with a total length of 91 kb and is highly expressed in various malignancies, which is closely related to tumor growth, lymph node metastasis, survival cycle and recurrence rate. In addition, KCNQ1OT1 is involved in the regulation of PI3K/AKT and Wnt/β-catenin signaling pathways. In this review, the mechanism and related progress of KCNQ1OT1 in different cancers were reviewed. It was found that KCNQ1OT1 can stabilize mRNA expression through sponging miRNA, which not only induced tumor cell proliferation, migration, invasion, drug resistance, epithelial-mesenchymal transition (EMT) and inhibited cell apoptosis in vitro, but also promoted tumor growth and metastasis in vivo. Therefore, as a new biomarker and therapeutic target, KCNQ1OT1 has broad prospects for the diagnosis and treatment of different cancers.

m6A-mediated lncRNA NEAT1 plays an oncogenic role in non-small cell lung cancer by upregulating the HMGA1 expression through binding miR-361-3p

BACKGROUND

Lung cancer is the most common primary malignant tumor of the lung, and 85% of lung cancer is non-small cell lung cancer (NSCLC). The N6-methyladenosine (m6A) and long noncoding RNAs (lncRNAs) have been widely reported to participate in the development of non-small cell lung cancer.

OBJECTIVE

However, the potential molecular mechanisms of m6A-regulated lncRNAs in NSCLC still need further investigation.

METHODS

The expression levels and the role of lncRNA NEAT1 in NSCLC tissues or cells were measured by RT-qPCR, Western blot, cell counting kit 8 (CCK-8), flow cytometry assay. RNA immunoprecipitation (RIP) was used to measure the levels of m6A modification of NEAT1. Bioinformatics analysis and dual-luciferase reporter gene assay were detected the relationship between miR-361-3p and NEAT1/HMGA1. Mouse xenograft tumor models were established to confirm the effects of lncRNA NEAT1 in vivo.

RESULTS

In this study, we verified whether m6A-modified lncRNA nuclear enriched abundant transcript 1 (NEAT1) is involved in NSCLC progression via miR-361-3p/HMGA1 axis. Firstly, we found that lncRNA NEAT1 was upregulated in NSCLC, and was associated with a poor survival in NSCLC patients. Methyltransferase like 3 (METTL3)-mediated m6A modification stabilized and upregulated NEAT1 expression. Next, function experiment indicated that depletion of METTL3 and NEAT1 induced cell apoptosis and inhibited cell proliferation, epithelial-mesenchymal transition (EMT). Likewise, in vivo experiments further supported the oncogenic role of NEAT1 in NSCLC. In addition, the molecular mechanism was uncovered in our study, and we found that lncRNA NEAT1 promoted the expression of high-mobility group AT-hook 1 (HMGA1) by sponging miR-361-3p and then promoted tumorigenesis of NSCLC.

CONCLUSION

In conclusion, our findings demonstrated that METTL3-mediated m6A modification accelerated NSCLC progression by regulating the NEAT1/miR-361-3p/HMGA1 axis, which provides important targets for the treatment of NSCLC.

miRNA/epithelial-mesenchymal axis (EMT) axis as a key player in cancer progression and metastasis: A focus on gastric and bladder cancers

The metastasis a major hallmark of tumors that its significant is not only related to the basic research, but clinical investigations have revealed that majority of cancer deaths are due to the metastasis. The metastasis of tumor cells is significantly increased due to EMT mechanism and therefore, inhibition of EMT can reduce biological behaviors of tumor cells and improve the survival rate of patients. One of the gaps related to cancer metastasis is lack of specific focus on the EMT regulation in certain types of tumor cells. The gastric and bladder cancers are considered as two main reasons of death among patients in clinical level. Herein, the role of EMT in regulation of their progression is evaluated with a focus on the function of miRNAs. The inhibition/induction of EMT in these cancers and their ability in modulation of EMT-related factors including ZEB1/2 proteins, TGF-β, Snail and cadherin proteins are discussed. Moreover, lncRNAs and circRNAs in crosstalk of miRNA/EMT regulation in these tumors are discussed and final impact on cancer metastasis and response of tumor cells to the chemotherapy is evaluated. Moreover, the impact of miRNAs transferred by exosomes in regulation of EMT in these cancers are discussed.

Construction of an m6A- and neutrophil extracellular traps-related lncRNA model to predict hepatocellular carcinoma prognosis and immune landscape

Purpose

To investigate the impact of N6-methyladenosine- (m6A) and neutrophil extracellular traps- (NETs) related lncRNAs (MNlncRNAs) on the prognosis of hepatocellular carcinoma (HCC).

Methods

We collected m6A and NETs-related genes from published studies. We identified the MNlncRNAs by correlation analysis. Cox regression and the least absolute selection operator (LASSO) method were used to select predictive MNlncRNAs. The expressions of predictive MNlncRNAs were detected by cell and tissue experiments. Survival, medication sensitivity, and immunological microenvironment evaluations were used to assess the model's prognostic utility. Finally, we performed cellular experiments to further validate the model's prognostic reliability.

Results

We obtained a total of 209 MNlncRNAs. 7 MNlncRNAs comprised the prognostic model, which successfully stratifies HCC patients, with the area under the curve (AUC) ranging from 0.7 to 0.8. In vitro tests confirmed that higher risk patients had worse prognosis. Risk score, immunological microenvironment, and immune checkpoint gene expression were all significantly correlated with each other in HCC. In the group at high risk, immunotherapy could be more successful. Cellular assays confirmed that HCC cells with high risk scores have a higher proliferation and invasive capacity.

Conclusion

The MNlncRNAs-related prognostic model aided in determining HCC prognosis, revealing novel therapeutic options, notably immunotherapy.

Construction of an efferocytosis-related long non-coding ribonucleic acid scoring system to predict clinical outcome and immunotherapy response in pancreatic adenocarcinoma

Background

Efferocytosis suppresses antitumour immune responses by inducing the release and secretion of cytokines. Long non-coding ribonucleic acids (lncRNAs) have various functions in different forms of programmed cell death and in immune regulation. This study aims to explore the potential role of efferocytosis-related lncRNAs as biomarkers in pancreatic adenocarcinoma (PAAD).

Methods

Transcriptome profiles, simple nucleotide variations and clinical data of patients with PAAD were extracted from The Cancer Genome Atlas (TCGA) database. Co-expression algorithms identified efferocytosis-related lncRNAs. The efferocytosis-related lncRNA scoring system (ERLncSys) was established using Cox regression and the Least Absolute Shrinkage and Selection Operator algorithm. Additionally, Kaplan-Meier (K-M) curves, Cox regression, receiver operating characteristic (ROC) curves and clinical parameter stratification analyses were used to evaluate ERlncSys. Moreover, ERlncSys was explored through Gene Set Variation Analysis, Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses. Furthermore, the TIMER platform, ESTIMATE algorithm, single sample Gene Set Enrichment Analysis and immune checkpoint analysis were utilised to explore the predictive power of ERlncSys for the tumour immune microenvironment (TIME). Finally, a consensus clustering algorithm identified distinct molecular profiles among patients with PAAD, aiding in the identification of potential beneficiaries for immunotherapy.

Results

K-M, Cox regression and ROC analyses confirmed the robust prognostic efficacy of ERlncSys. Clinical stratification analysis indicated the broad applicability of ERlncSys in PAAD. Additionally, mmunological analyses indicated that ERlncSys can determine immune cell infiltration status in the TIME. Furthermore, consensus clustering analysis based on ERlncSys divided the TCGA-PAAD cohort into two clusters. Cluster 1 exhibited characteristics consistent with an immune 'hot tumour' compared to cluster 2, suggesting cluster 1 is a more suitable population for immune checkpoint inhibitor therapy.

Conclusion

The established ErlncSys aids in predicting the prognosis and understanding the TIME landscape of patients with PAAD. In turn, it facilitates the identification of optimal candidates for immunotherapy. This study introduces novel insights into the potential value of efferocytosis-related lncRNAs as biomarkers in PAAD.

Bulk and single-cell RNA-sequencing analyses along with abundant machine learning methods identify a novel monocyte signature in SKCM

Background

Global patterns of immune cell communications in the immune microenvironment of skin cutaneous melanoma (SKCM) haven't been well understood. Here we recognized signaling roles of immune cell populations and main contributive signals. We explored how multiple immune cells and signal paths coordinate with each other and established a prognosis signature based on the key specific biomarkers with cellular communication.

Methods

The single-cell RNA sequencing (scRNA-seq) dataset was downloaded from the Gene Expression Omnibus (GEO) database, in which various immune cells were extracted and re-annotated according to cell markers defined in the original study to identify their specific signs. We computed immune-cell communication networks by calculating the linking number or summarizing the communication probability to visualize the cross-talk tendency in different immune cells. Combining abundant analyses of communication networks and identifications of communication modes, all networks were quantitatively characterized and compared. Based on the bulk RNA sequencing data, we trained specific markers of hub communication cells through integration programs of machine learning to develop new immune-related prognostic combinations.

Results

An eight-gene monocyte-related signature (MRS) has been built, confirmed as an independent risk factor for disease-specific survival (DSS). MRS has great predictive values in progression free survival (PFS) and possesses better accuracy than traditional clinical variables and molecular features. The low-risk group has better immune functions, infiltrated with more lymphocytes and M1 macrophages, with higher expressions of HLA, immune checkpoints, chemokines and costimulatory molecules. The pathway analysis based on seven databases confirms the biological uniqueness of the two risk groups. Additionally, the regulon activity profiles of 18 transcription factors highlight possible differential regulatory patterns between the two risk groups, suggesting epigenetic event-driven transcriptional networks may be an important distinction. MRS has been identified as a powerful tool to benefit SKCM patients. Moreover, the IFITM3 gene has been identified as the key gene, validated to express highly at the protein level via the immunohistochemical assay in SKCM.

Conclusion

MRS is accurate and specific in evaluating SKCM patients' clinical outcomes. IFITM3 is a potential biomarker. Moreover, they are promising to improve the prognosis of SKCM patients.

ZBTB7C m6A modification incurred by METTL3 aberration promotes osteosarcoma progression

Aberrant N6-methyladenosine (m6A) modification of mRNAs contributes significantly to the epigenetic tumorigenesis, however, its precise role and the key targets in osteosarcoma (OS) are not defined. Here we reported that selective METTL3 (methyltransferase like 3) elevation and the consequential increase of m6A modification causally affect OS progression. The fast-growing OS cells displayed preferential upregulation of METTL3 and increased m6A modification. Conversely, m6A inhibition by 3-deazaadenosine, siRNA-mediated METTL3 knockdown or a METTL3-selective inhibitor by STM2457 effectively inhibits OS cell growth and induced OS cell apoptosis. Further investigation revealed that an oncogenic protein ZBTB7C was likely a critical m6A target that mediated the oncogenic effects. ZBTB7C mRNA contains a typical m6A motif of high confidence and its mRNA and protein were enriched with increased m6A modification in OS samples/cells. In an OS xenograft model, STM2457 or siRNA-mediated METTL3 knockdown effectively lowed ZBTB7C abundance. More importantly, the anti-OS effects of STM2457 were significantly reduced when ZBTB7C was overexpressed by lentivirus. Together, our results demonstrate that the METTL3 aberration and the resultant ZBTB7C m6A modification form an important epigenetic regulatory loop that promotes OS progression, and targeting the METTL3/ZBTB7C axis may provide novel insights into the potential strategies for OS therapy.

A prognostic model based on necroptosis-related genes for prognosis and therapy in bladder cancer

Bladder cancer, one of the most prevalent malignant cancers, has high rate of recurrence and metastasis. Owing to genomic instability and high-level heterogeneity of bladder cancer, chemotherapy and immunotherapy drugs sensitivity and lack of prognostic markers, the prognosis of bladder cancer is unclear. Necroptosis is a programmed modality of necrotic cell death in a caspase-independent form. Despite the fact that necroptosis plays a critical role in tumor growth, cancer metastasis, and cancer patient prognosis, necroptosis-related gene sets have rarely been studied in bladder cancer. As a result, the development of new necroptosis-related prognostic indicators for bladder cancer patients is critical. Herein, we assessed the necroptosis landscape of bladder cancer patients from The Cancer Genome Atlas database and classified them into two unique necroptosis-related patterns, using the consensus clustering. Then, using five prognosis-related genes, we constructed a prognostic model (risk score), which contained 5 genes (ANXA1, DOK7, FKBP10, MAP1B and SPOCD1). And a nomogram model was also developed to offer the clinic with a more useful prognostic indicator. We found that risk score was significantly associated with clinicopathological characteristics, TIME, and tumor mutation burden in patients with bladder cancer. Moreover, risk score was a valid guide for immunotherapy, chemotherapy, and targeted drugs. In our study, DOK7 was chosen to further verify our prognosis model, and functional assays indicated that knockdown the expression of DOK7 could prompt bladder cancer proliferation and migration. Our work demonstrated the potential role of prognostic model based on necroptosis genes in the prognosis, immune landscape and response efficacy of immunotherapy of bladder cancer.