Effects of RNA methylation N6-methyladenosine regulators on malignant progression and prognosis of melanoma.
TL;DR: In this paper, the authors identify genetic markers and assess prognostic performance of N6-methyladenosine (m6A) regulators in melanoma and construct a three-gene risk signature with distinct prognostic value.
Abstract: Background Melanoma is an extremely aggressive type of skin cancer and experiencing a expeditiously rising mortality in a current year. Exploring new potential prognostic biomarkers and therapeutic targets of melanoma are urgently needed. The ambition of this research was to identify genetic markers and assess prognostic performance of N6-methyladenosine (m6A) regulators in melanoma. Methods Gene expression data and corresponding clinical informations of melanoma patients as well as sequence data of normal controls are collected from The Cancer Genome Atlas (TCGA) and the Genotype-Tissue Expression (GTEx) databases. Quantitative real-time PCR (qRT-PCR) analysis was carried out to detect the RNA expression of IGF2BP3 in A375 cell line, melanoma tissues, and normal tissues. Western blot, cell proliferation, and migration assays were performed to assess the ability of IGF2BP3 in A375 cell line. Results Differently expressed m6A regulators between tumor samples and normal samples were analyzed. A three-gene prognostic signature including IGF2BP3, RBM15B, and METTL16 was constructed, and the risk score of this signature was identified to be an independent prognostic indicator for melanoma. In addition, IGF2BP3 was verified to promote melanoma cell proliferation and migration in vitro and associate with lymph node metastasis in clinical samples. Moreover, risk score and the expression of IGF2BP3 were positively associated with the infiltrating immune cells and these hub genes made excellent potential drug targets in melanoma. Conclusion We identified the genetic changes in m6A regulatory genes and constructed a three-gene risk signature with distinct prognostic value in melanoma. This research provided new insights into the epigenetic understanding of m6A regulators and novel therapeutic strategies in melanoma.
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TL;DR: In this article , the authors investigated the expression, roles, and mechanisms of action of the RNA methyltransferase methyl transferase-like protein 16 (METTL16) in HCC.
Abstract: Abstract Background The molecular mechanisms driving hepatocellular carcinoma (HCC) remain largely unclear. As one of the major epitranscriptomic modifications, N 6 -methyladenosine (m 6 A) plays key roles in HCC. The aim of this study was to investigate the expression, roles, and mechanisms of action of the RNA methyltransferase methyltransferase-like protein 16 (METTL16) in HCC. Methods The expression of METTL16 and RAB11B-AS1 was determined by RT-qPCR. The regulation of RAB11B-AS1 by METTL16 was investigated by RNA immunoprecipitation (RIP), methylated RIP (MeRIP), and RNA stability assays. In vitro and in vivo gain- and loss-of-function assays were performed to investigate the roles of METTL16 and RAB11B-AS1. Results METTL16 was upregulated in HCC, and its increased expression was correlated with poor prognosis of HCC patients. METTL16 promoted HCC cellular proliferation, migration, and invasion, repressed HCC cellular apoptosis, and promoted HCC tumoral growth in vivo. METTL16 directly bound long noncoding RNA (lncRNA) RAB11B-AS1, induced m 6 A modification of RAB11B-AS1, and decreased the stability of RAB11B-AS1 transcript, leading to the downregulation of RAB11B-AS1. Conversely to METTL16, RAB11B-AS1 is downregulated in HCC, and its decreased expression was correlated with poor prognosis of patients with HCC. Furthermore, the expression of RAB11B-AS1 was negatively correlated with METTL16 in HCC tissues. RAB11B-AS1 repressed HCC cellular proliferation, migration, and invasion, promoted HCC cellular apoptosis, and inhibited HCC tumoral growth in vivo. Functional rescue assays revealed that overexpression of RAB11B-AS1 reversed the oncogenic roles of METTL16 in HCC. Conclusions This study identified the METTL16/RAB11B-AS1 regulatory axis in HCC, which represented novel targets for HCC prognosis and treatment.
32 citations
TL;DR: In this paper , the authors investigated the expression, roles, and mechanisms of action of the RNA methyltransferase methyl transferase-like protein 16 (METTL16) in HCC.
Abstract: Abstract Background The molecular mechanisms driving hepatocellular carcinoma (HCC) remain largely unclear. As one of the major epitranscriptomic modifications, N 6 -methyladenosine (m 6 A) plays key roles in HCC. The aim of this study was to investigate the expression, roles, and mechanisms of action of the RNA methyltransferase methyltransferase-like protein 16 (METTL16) in HCC. Methods The expression of METTL16 and RAB11B-AS1 was determined by RT-qPCR. The regulation of RAB11B-AS1 by METTL16 was investigated by RNA immunoprecipitation (RIP), methylated RIP (MeRIP), and RNA stability assays. In vitro and in vivo gain- and loss-of-function assays were performed to investigate the roles of METTL16 and RAB11B-AS1. Results METTL16 was upregulated in HCC, and its increased expression was correlated with poor prognosis of HCC patients. METTL16 promoted HCC cellular proliferation, migration, and invasion, repressed HCC cellular apoptosis, and promoted HCC tumoral growth in vivo. METTL16 directly bound long noncoding RNA (lncRNA) RAB11B-AS1, induced m 6 A modification of RAB11B-AS1, and decreased the stability of RAB11B-AS1 transcript, leading to the downregulation of RAB11B-AS1. Conversely to METTL16, RAB11B-AS1 is downregulated in HCC, and its decreased expression was correlated with poor prognosis of patients with HCC. Furthermore, the expression of RAB11B-AS1 was negatively correlated with METTL16 in HCC tissues. RAB11B-AS1 repressed HCC cellular proliferation, migration, and invasion, promoted HCC cellular apoptosis, and inhibited HCC tumoral growth in vivo. Functional rescue assays revealed that overexpression of RAB11B-AS1 reversed the oncogenic roles of METTL16 in HCC. Conclusions This study identified the METTL16/RAB11B-AS1 regulatory axis in HCC, which represented novel targets for HCC prognosis and treatment.
31 citations
TL;DR: Wang et al. as mentioned in this paper found that m6A reader YTHDF3 could affect the metastasis of melanoma both in vitro and in vivo, and they used CRISPR-Cas13b-based epitranscriptome engineering.
Abstract: Background A number of studies have demonstrated that N6-methyladenosine (m6A) plays a vital role in the pathological process of various tumours. Recently, it was found that m6A writers or erasers affect the tumourigenesis of melanoma. However, the relationship between m6A readers such as YTH domain family (YTHDF) proteins and melanoma was still elusive. Methods RT-qPCR, Western blot and immunohistochemistry were conducted to measure the expression level of YTH N6–methyladenosine RNA binding protein 3 (YTHDF3) and lysyl oxidase–like 3 (LOXL3) in melanoma tissues and cells. The effects of YTHDF3 and LOXL3 on melanoma were verified in vitro and in vivo. Multi-omics analysis including RNA-seq, MeRIP-seq, RIP-seq and mass spectrometry analyses was performed to identify the target. The interaction between YTHDF3 and LOXL3 was verified by RT-PCR, Western blot, MeRIP-qPCR, RIP-qPCR and CRISPR-Cas13b-based epitranscriptome engineering. Results In this study, we found that m6A reader YTHDF3 could affect the metastasis of melanoma both in vitro and in vivo. The downstream targets of YTHDF3, such as LOXL3, phosphodiesterase 3A (PDE3A) and chromodomain helicase DNA-binding protein 7 (CHD7) were identified by means of RNA-seq, MeRIP-seq, RIP-seq and mass spectrometry analyses. Besides, RT-qPCR, Western blot, RIP-qPCR and MeRIP-qPCR were performed for subsequent validation. Among various targets of YTHDF3, LOXL3 was found to be the optimal target of YTHDF3. With the application of CRISPR–Cas13b-based epitranscriptome engineering, we further confirmed that the transcript of LOXL3 was captured and regulated by YTHDF3 via m6A binding sites. YTHDF3 augmented the protein expression of LOXL3 without affecting its mRNA level via the enrichment of eukaryotic translation initiation factor 3 subunit A (eIF3A) on the transcript of LOXL3. LOXL3 downregulation inhibited the metastatic ability of melanoma cells, and overexpression of LOXL3 ameliorated the inhibition of melanoma metastasis caused by YTHDF3 downregulation. Conclusions The YTHDF3-LOXL3 axis could serve as a promising target to be interfered with to inhibit the metastasis of melanoma.
3 citations
TL;DR: An immune prognosis model using RBM38-related immune DEGs that may help evaluate melanoma patient prognosis and immunotherapy modalities is constructed that shows superior prognosis capacity compared with other melanoma prognostic signatures.
Abstract: Simple Summary The primary treatment of malignant melanoma is a classical regimen of surgery combined with chemotherapy, targeted drugs, and immunotherapy. The purpose of this study was to explore the immune response mechanism of RNA binding protein RBM38 in the development of melanoma with the screening of effective immunodiagnostic models and targeted therapy. We found that RBM38, as an oncogene, promotes the proliferation, invasion, and migration of melanoma cells and is associated with immune infiltration and pathways. Our investigation presented the prognostic significance of RBM38-associated immune signature. In addition, this model may provide a potential strategy for improving the survival and immunotherapy of melanoma patients. Abstract Background: Current studies have revealed that RNA-binding protein RBM38 is closely related to tumor development, while its role in malignant melanoma remains unclear. Therefore, this research aimed to investigate the function of RBM38 in melanoma and the prognosis of the disease. Methods: Functional experiments (CCK-8 assay, cell colony formation, transwell cell migration/invasion experiment, wound healing assay, nude mouse tumor formation, and immunohistochemical analysis) were applied to evaluate the role of RBM38 in malignant melanoma. Immune-associated differentially expressed genes (DEGs) on RBM38 related immune pathways were comprehensively analyzed based on RNA sequencing results. Results: We found that high expression of RBM38 promoted melanoma cell proliferation, invasion, and migration, and RBM38 was associated with immune infiltration. Then, a five-gene (A2M, NAMPT, LIF, EBI3, and ERAP1) model of RBM38-associated immune DEGs was constructed and validated. Our signature showed superior prognosis capacity compared with other melanoma prognostic signatures. Moreover, the risk score of our signature was connected with the infiltration of immune cells, immune-regulatory proteins, and immunophenoscore in melanoma. Conclusions: We constructed an immune prognosis model using RBM38-related immune DEGs that may help evaluate melanoma patient prognosis and immunotherapy modalities.
1 citations
TL;DR: Wang et al. as mentioned in this paper showed that FARSB mRNA and protein levels were upregulated in hepatocellular carcinoma (HCC) and were closely related to many clinicopathological characteristics.
Abstract: Purpose: Hepatocellular carcinoma (HCC) is a prevalent tumor with high morbidity, and an unfavourable prognosis. FARSB is an aminoacyl tRNA synthase, and plays a key role in protein synthesis in cells. Furthermore, previous reports have indicated that FARSB is overexpressed in gastric tumor tissues and is associated with a poor prognosis and tumorigenesis. However, the function of FARSB in HCC has not been studied. Results: The results showed that FARSB mRNA and protein levels were upregulated in HCC and were closely related to many clinicopathological characteristics. Besides, according to multivariate Cox analysis, high FARSB expression was linked with a shorter survival time in HCC and may be an independent prognostic factor. In addition, the FARSB promoter methylation level was negatively associated with the expression of FARSB. Furthermore, enrichment analysis showed that FARSB was related to the cell cycle. And TIMER analysis revealed that the FARSB expression was closely linked to tumor purity and immune cell infiltration. The TCGA and ICGC data analysis suggested that FARSB expression is greatly related to m6A modifier related genes. Potential FARSB-related ceRNA regulatory networks were also constructed. What’s more, based on the FARSB-protein interaction network, molecular docking models of FARSB and RPLP1 were constructed. Finally, drug susceptibility testing revealed that FARSB was susceptible to 38 different drugs or small molecules. Conclusions: FARSB can serve as a prognostic biomarker for HCC and provide clues about immune infiltration, and m6A modification.
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TL;DR: Many of the estimated cancer cases and deaths can be prevented through reducing the prevalence of risk factors, while increasing the effectiveness of clinical care delivery, particularly for those living in rural areas and in disadvantaged populations.
Abstract: With increasing incidence and mortality, cancer is the leading cause of death in China and is a major public health problem. Because of China's massive population (1.37 billion), previous national incidence and mortality estimates have been limited to small samples of the population using data from the 1990s or based on a specific year. With high-quality data from an additional number of population-based registries now available through the National Central Cancer Registry of China, the authors analyzed data from 72 local, population-based cancer registries (2009-2011), representing 6.5% of the population, to estimate the number of new cases and cancer deaths for 2015. Data from 22 registries were used for trend analyses (2000-2011). The results indicated that an estimated 4292,000 new cancer cases and 2814,000 cancer deaths would occur in China in 2015, with lung cancer being the most common incident cancer and the leading cause of cancer death. Stomach, esophageal, and liver cancers were also commonly diagnosed and were identified as leading causes of cancer death. Residents of rural areas had significantly higher age-standardized (Segi population) incidence and mortality rates for all cancers combined than urban residents (213.6 per 100,000 vs 191.5 per 100,000 for incidence; 149.0 per 100,000 vs 109.5 per 100,000 for mortality, respectively). For all cancers combined, the incidence rates were stable during 2000 through 2011 for males (+0.2% per year; P = .1), whereas they increased significantly (+2.2% per year; P < .05) among females. In contrast, the mortality rates since 2006 have decreased significantly for both males (-1.4% per year; P < .05) and females (-1.1% per year; P < .05). Many of the estimated cancer cases and deaths can be prevented through reducing the prevalence of risk factors, while increasing the effectiveness of clinical care delivery, particularly for those living in rural areas and in disadvantaged populations.
13,073 citations
TL;DR: Estimating cancer prevalence in the United States using incidence and survival data from the Surveillance, Epidemiology, and End Results cancer registries; vital statistics from the Centers for Disease Control and Prevention's National Center for Health Statistics; and population projections from the US Census Bureau is presented.
Abstract: The number of cancer survivors continues to increase in the United States because of the growth and aging of the population as well as advances in early detection and treatment. To assist the public health community in better serving these individuals, the American Cancer Society and the National Cancer Institute collaborate every 3 years to estimate cancer prevalence in the United States using incidence and survival data from the Surveillance, Epidemiology, and End Results cancer registries; vital statistics from the Centers for Disease Control and Prevention's National Center for Health Statistics; and population projections from the US Census Bureau. Current treatment patterns based on information in the National Cancer Data Base are presented for the most prevalent cancer types. Cancer-related and treatment-related short-term, long-term, and late health effects are also briefly described. More than 16.9 million Americans (8.1 million males and 8.8 million females) with a history of cancer were alive on January 1, 2019; this number is projected to reach more than 22.1 million by January 1, 2030 based on the growth and aging of the population alone. The 3 most prevalent cancers in 2019 are prostate (3,650,030), colon and rectum (776,120), and melanoma of the skin (684,470) among males, and breast (3,861,520), uterine corpus (807,860), and colon and rectum (768,650) among females. More than one-half (56%) of survivors were diagnosed within the past 10 years, and almost two-thirds (64%) are aged 65 years or older. People with a history of cancer have unique medical and psychosocial needs that require proactive assessment and management by follow-up care providers. Although there are growing numbers of tools that can assist patients, caregivers, and clinicians in navigating the various phases of cancer survivorship, further evidence-based resources are needed to optimize care.
2,924 citations
TL;DR: This work introduces a pathwise algorithm for the Cox proportional hazards model, regularized by convex combinations of ℓ1 andℓ2 penalties (elastic net), and employs warm starts to find a solution along a regularization path.
Abstract: We introduce a pathwise algorithm for the Cox proportional hazards model, regularized by convex combinations of l1 and l2 penalties (elastic net). Our algorithm fits via cyclical coordinate descent, and employs warm starts to find a solution along a regularization path. We demonstrate the efficacy of our algorithm on real and simulated data sets, and find considerable speedup between our algorithm and competing methods.
1,579 citations
TL;DR: It is found that METTL3 promotes translation of certain mRNAs including epidermal growth factor receptor (EGFR) and the Hippo pathway effector TAZ in human cancer cells.
1,035 citations
TL;DR: It is shown that FTO, as an m6A demethylase, plays a critical oncogenic role in acute myeloid leukemia (AML) and provides profound insights into leukemogenesis and drug response.
998 citations