The m6A methylation landscape stratifies hepatocellular carcinoma into 3 subtypes with distinct metabolic characteristics

Objective:Epigenetic aberration plays an important role in the development and progression of hepatocellular carcinoma(HCC).However,the alteration of RNA N6-methyladenosine(m6A)modifications and its role in HCC progression remain unclear.We therefore aimed to provide evidence using bioinformatics analysis.Methods:We comprehensively analyzed the m6A regulator modification patterns of 605 HCC samples and correlated them with metabolic alteration characteristics.We elucidated 390 gene-based m6A-related signatures and defined an m6Ascore to quantify m6A modifications.We then assessed their values for predicting prognoses and therapeutic responses in HCC patients.Results:We identified 3 distinct m6A modification patterns in HCC,and each pattern had distinct metabolic characteristics.The evaluation of m6A modification patterns using m6Ascores could predict the prognoses,tumor stages,and responses to sorafenib treatments of HCC patients.A nomogram based on m6Ascores showed high accuracy in predicting the overall survival of patients.The area under the receiver operating characteristic curve of predictions of 1,3,and 5-year overall survivals were 0.71,0.69,and 0.70 in the training cohort,and in the test cohort it was 0.74,0.75,and 0.71,respectively.M6Acluster C1,which corresponded to hypoactive mRNA methylation,lower expression of m6A regulators,and a lower m6Ascore,was characterized by metabolic hyperactivity,lower tumor stage,better prognosis,and lower response to sorafenib treatment.In contrast,m6Acluster C3 was distinct in its hyperactive mRNA methylations,higher expression of m6A regulators,and higher m6Ascores,and was characterized by hypoactive metabolism,advanced tumor stage,poorer prognosis,and a better response to sorafenib.The m6Acluster,C2,was intermediate between C1 and C3.Conclusions:HCCs harbored distinct m6A regulator modification patterns that contributed to the metabolic heterogeneity and diversity of HCC.Development of m6A gene signatures and the m6Ascore provides a more comprehensive understanding of m6A modifications in HCC,and helps predict the prognosis and treatment response.

Sex differences in traumatic brain injury:a multi-dimensional exploration in genes,hormones,cells,individuals,and society

Traumatic brain injury(TBI)is exceptionally prevalent in society and often imposes a massive burden on patients'families and poor prognosis.The evidence reviewed here suggests that gender can influence clinical outcomes of TBI in many aspects,ranges from patients'mortality and short-term outcome to their long-term outcome,as well as the incidence of cognitive impairment.We mainly focused on the causes and mechanisms underlying the differences between male and female after TBI,from both biological and sociological views.As it turns out that multiple factors contribute to the gender differences after TBI,not merely the perspective of gender and sex hormones.Centered on this,we discussed how female steroid hormones exert neuroprotective effects through the anti-inflammatory and antioxidant mechanism,along with the cognitive impairment and the social integration problems it caused.As to the treatment,both instant and long-term treatment of TBI requires adjustments according to gender.A further study with more focus on this topic is therefore suggested to provide better treatment options for these patients.

A Prognostic Nomogram for Hepatocellular Carcinoma Based on Wound Healing and Immune Checkpoint Genes

Background and Aims:Wound healing and tumor progression share some common biological features;however,how variations in wound healing patterns affect hepatocellular carcinoma(HCC)prognosis remains unclear.Methods:We analyzed the wound healing patterns of 594 HCC samples from The Cancer Genome Atlas(TCGA)and the International Cancer Genome Consortium(ICGC)and correlated them with immune infiltration and the expression levels of immune checkpoint genes.A risk score,which we named the“heal.immune”score,was established via stepwise Cox estimation.We constructed a nomogram based on age,sex,TNM stage,and heal.immune score and explored its predictive value for HCC prognosis.Seventy-four clinical patients were enrolled in this study,and all were from Huashan Hospital of Fudan University between 2015 and 2017 to serve as an independent validation group.Results:We identified two distinct wound healing patterns in HCC.The biological processes of healing cluster 1(C1)are related to metabolism,while those of healing cluster 2(C2)are related to the inflammatory response and immune cell accumulation.A total of 565 wound healing-related genes(based on Gene Ontology)and 25 immune checkpoint genes were considered.By analyzing differentially expressed genes and implementing a stepwise Cox estimation analysis,six genes with p values less than 0.02 in a multivariate Cox estimation were chosen as the“heal.immune”gene set(FCER1G,PLAT,ITGA5,CCNB1,CD86 and CD40).The“heal.immune”gene set,as an OS risk factor,was further validated in Fudan cohort.We constructed a nomogram to predict the 1-,3-and 5-year overall survival(OS)in the TCGA cohort.The area under curve vales of the receiver characteristic operator curves were 0.82,0.76 and 0.73 in the training group and 0.84,0.76 and 0.72 in the test group.Conclusions:We established a prognostic nomogram based on the heal.immune gene signature,which includes six wound healing-and immunity-related genes.This nomogram accurately predicts the OS of HCC patients.