Conditional Deletion of Eaf1 Induces Murine Prostatic Intraepithelial Neoplasia in Mice

Identification of prognostic biomarkers for hepatocellular carcinoma with vascular invasion

OBJECTIVE

Vascular invasion (VI) profoundly impacts the prognosis of hepatocellular carcinoma (HCC), yet the underlying biomarkers and mechanisms remain elusive. This study aimed to identify prognostic biomarkers for HCC patients with VI.

METHODS

Transcriptome data from primary HCC tissues and HCC tissues with VI were obtained through the Genome Expression Omnibus database. Differentially expressed genes (DEGs) in the two types of tissues were analyzed using functional enrichment analysis to evaluate their biological functions. We examined the correlation between DEGs and prognosis by combining HCC transcriptome data and clinical information from The Cancer Genome Atlas database. Univariate and multivariate Cox regression analyses, along with the least absolute shrinkage and selection operator (LASSO) method were utilized to develop a prognostic model. The effectiveness of the model was assessed through time-dependent receiver operating characteristic (ROC) curve, calibration diagram, and decision curve analysis.

RESULTS

In the GSE20017 and GSE5093 datasets, a total of 83 DEGs were identified. Gene Ontology analysis indicated that these DEGs were predominantly associated with xenobiotic stimulus, collagen-containing extracellular matrix, and oxygen binding. Additionally, Kyoto Encyclopedia of Genes and Genomes analysis revealed that the DEGs were primarily involved in immune defense and cellular signal transduction. Cox and LASSO regression further identified 7 genes (HSPA8, ABCF2, EAF1, MARCO, EPS8L3, PLA3G1B, C6), which were used to construct a predictive model in the training cohort. We used X-tile software to calculate the optimal cut-off value to stratify HCC patients into low-risk and high-risk groups. Notably, the high-risk group exhibited poorer prognosis than the low-risk group (P < 0.001). The model demonstrated area under the ROC curve (AUC) values of 0.815, 0.730, and 0.710 at 1-year, 3-year, and 5-year intervals in the training cohort, respectively. In the validation cohort, the corresponding AUC values were 0.701, 0.571, and 0.575, respectively. The C-index of the calibration curve for the training and validation cohorts were 0.716 and 0.665. Decision curve analysis revealed the model's efficacy in guiding clinical decision-making.

CONCLUSIONS

The study indicates that 7 genes may be potential prognostic biomarkers and treatment targets for HCC patients with VI.

SEC: A core hub during cell fate alteration

Pol II pause release is a rate-limiting step in gene transcription, influencing various cell fate alterations. Numerous proteins orchestrate Pol II pause release, thereby playing pivotal roles in the intricate process of cellular fate modulation. Super elongation complex (SEC), a large assembly comprising diverse protein components, has garnered attention due to its emerging significance in orchestrating physiological and pathological cellular identity changes by regulating the transcription of crucial genes. Consequently, SEC emerges as a noteworthy functional complex capable of modulating cell fate alterations. Therefore, a comprehensive review is warranted to systematically summarize the core roles of SEC in different types of cell fate alterations. This review focuses on elucidating the current understanding of the structural and functional basis of SEC. Additionally, we discuss the intricate regulatory mechanisms governing SEC in various models of cell fate alteration, encompassing both physiological and pathological contexts. Furthermore, leveraging the existing knowledge of SEC, we propose some insightful directions for future research, aiming to enhance our mechanistic and functional comprehension of SEC within the diverse landscape of cell fate alterations.

Comprehensive analysis of peroxisome proliferator-activated receptors to predict the drug resistance, immune microenvironment, and prognosis in stomach adenocarcinomas

Background

Peroxisome proliferator-activated receptors (PPARs) exert multiple functions in the initiation and progression of stomach adenocarcinomas (STAD). This study analyzed the relationship between PPARs and the immune status, molecular mutations, and drug therapy in STAD.

Methods

The expression profiles of three PPAR genes (PPARA, PPARD and PPARG) were downloaded from The Cancer Genome Atlas (TCGA) dataset to analyze their expression patterns across pan-cancer. The associations between PPARs and clinicopathologic features, prognosis, tumor microenvironment, genome mutation and drug sensitivity were also explored. Co-expression between two PPAR genes was calculated using Pearson analysis. Regulatory pathways of PPARs were scored using gene set variation analysis (GSVA) package. Quantitative real-time polymerase chain reaction (qRT-PCR), Western blot, Cell Counting Kit-8 (CCK-8) assay and transwell assay were conducted to analyze the expression and function of the PPAR genes in STAD cell lines (AGS and SGC7901 cells).

Results

PPARA, PPARD and PPARG were more abnormally expressed in STAD samples and cell lines when compared to most of 32 type cancers in TCGA. In STAD, the expression of PPARD was higher in Grade 3+4 and male patients, while that of PPARG was higher in patient with Grade 3+4 and age > 60. Patients in high-PPARA expression group tended to have longer survival time. Co-expression analysis revealed 6 genes significantly correlated with the three PPAR genes in STAD. Single-sample GSEA (ssGSEA) showed that the three PPAR genes were enriched in 23 pathways, including MITOTIC_SPINDLE, MYC_TARGETS_V1, E2F_TARGETS and were closely correlated with immune cells, including NK_cells_resting, T_cells_CD4_memory_resting, and macrophages_M0. Immune checkpoint genes (CD274, SIGLEC15) were abnormally expressed between high-PPAR expression and low-PPAR expression groups. TTN, MUC16, FAT2 and ANK3 genes had a high mutation frequency in both high-PPARA/PPARG and low-PPARA/PPARG expression group. Fourteen and two PPARA/PPARD drugs were identified to be able to effectively treat patients in high-PPARA/PPARG and low-PPARA/PPARG expression groups, respectively. We also found that the chemotherapy drug Vinorelbine was positively correlated with the three PPAR genes, showing the potential of Vinorelbine to serve as a treatment drug for STAD. Furthermore, cell experiments demonstrated that PPARG had higher expression in AGS and SGC7901 cells, and that inhibiting PPARG suppressed the viability, migration and invasion of AGS and SGC7901 cells.

Conclusions

The current results confirmed that the three PPAR genes (PPARA, PPARD and PPARG) affected STAD development through mediating immune microenvironment and genome mutation.

Plasma Exosome Gene Signature Differentiates Colon Cancer from Healthy Controls

BACKGROUND

Liquid biopsies have become an integral part of cancer management as minimally invasive options to detect molecular and genetic changes. However, current options show poor sensitivity in peritoneal carcinomatosis (PC). Novel exosome-based liquid biopsies may provide critical information on these challenging tumors. In this initial feasibility analysis, we identified an exosome gene signature of 445 genes (ExoSig445) from colon cancer patients, including those with PC, that is distinct from healthy controls.

METHODS

Plasma exosomes from 42 patients with metastatic and non-metastatic colon cancer and 10 healthy controls were isolated and verified. RNAseq analysis of exosomal RNA was performed and differentially expressed genes (DEGs) were identified by the DESeq2 algorithm. The ability of RNA transcripts to discriminate control and cancer cases was assessed by principal component analysis (PCA) and Bayesian compound covariate predictor classification. An exosomal gene signature was compared with tumor expression profiles of The Cancer Genome Atlas.

RESULTS

Unsupervised PCA using exosomal genes with greatest expression variance showed stark separation between controls and patient samples. Using separate training and test sets, gene classifiers were constructed capable of discriminating control and patient samples with 100% accuracy. Using a stringent statistical threshold, 445 DEGs fully delineated control from cancer samples. Furthermore, 58 of these exosomal DEGs were found to be overexpressed in colon tumors.

CONCLUSIONS

Plasma exosomal RNAs can robustly discriminate colon cancer patients, including patients with PC, from healthy controls. ExoSig445 can potentially be developed as a highly sensitive liquid biopsy test in colon cancer.

Development and Validation of a Novel Diagnostic Model for Childhood Autism Spectrum Disorder Based on Ferroptosis-Related Genes

Autism spectrum disorder (ASD) is a highly genetic heterogeneous neurodevelopmental disorder, which is usually considered a heritable and heterogeneous neurodevelopmental disorder and has caused a great burden to society and families. Emerging roles of ferroptosis have been observed in neurological disorders. This study aimed to construct a diagnostic model based on ferroptosis-related genes (FRGs) to contribute to the early and precise diagnosis of childhood ASD. In the candidate FRGs, we identified 27 differentially expressed genes (DEGs) between ASD patients and typically developing (TD) controls. Four key FRGs were identified using the random forest analysis for further analysis. Utilization of the four gene expression, we constructed a diagnostic model and the AUC value in the training dataset (GSE18123) is 0.7002. We deem that a patient with a score less than 0.9904 is likely to have ASD. Three validation datasets (GSE111176, GSE113834, and GSE28521) were collected and the AUC value is 0.7442, 0.7444, and 0.6474, respectively. A multi-factor regulatory network based on four FRGs indicated that RORA, EAF1, NFYB, miR-4703-3p, and miR-6073 may play a role in the development of ASD. In addition, we found piperaquine may have the potential to be a promising drug for the treatment of ASD. Overall, we constructed a diagnostic model of childhood ASD, which could contribute to the precision diagnosis and timely treatment of childhood ASD.

Systematic expression analysis of EAF family reveals the importance of EAF2 in melanoma

BACKGROUND

Skin cutaneous melanoma (SKCM) accounts for over 75% of skin cancer-related deaths each year. EAF2, as a member of EAF family, has been found in several cancers, however, the role of EAF2 in SKCM is rarely studied.

METHODS

In this study, we utilized multiple bioinformatics tools to systematically analyze the expression of EAF family and investigate the prognostic value of EAF2 in melanoma.

RESULTS

We found both transcriptional and proteomics expression expressions of EAF2 were elevated in SKCM. Survival analysis and ROC curves showed significant diagnostic and prognostic ability of EAF2. Importantly, EAF2 expression was closely associated with the immune-infiltrating levels of B cells, CD4+ T, CD8+ T, neutrophils, macrophages and dendritic cells. Co-expression analysis showed EAF2 has a strong positive correlation with CD19, implying they may be functional partners in the immune response of SKCM.

CONCLUSIONS

In summary, our study is the first to reveal that increased expression of EAF2 is significantly correlated with tumor progression and better prognosis in SKCM patients. The role of EAF2 in SKCM demonstrated that it might be a potential and promising biomarker for the diagnosis and prediction of prognosis in patients with SKCM.

Keeping RNA polymerase II on the run: Functions of MLL fusion partners in transcriptional regulation

Since the identification of key MLL fusion partners as transcription elongation factors regulating expression of HOX cluster genes during hematopoiesis, extensive work from the last decade has resulted in significant progress in our overall mechanistic understanding of role of MLL fusion partner proteins in transcriptional regulation of diverse set of genes beyond just the HOX cluster. In this review, we are going to detail overall understanding of role of MLL fusion partner proteins in transcriptional regulation and thus provide mechanistic insights into possible MLL fusion protein-mediated transcriptional misregulation leading to aberrant hematopoiesis and leukemogenesis.