Vertebrates diverged from other chordates ~500 Myr ago and experienced successful innovations and adaptations, but the genomic basis underlying vertebrate origins are not fully understood. Here we suggest, through comparison with multiple lancelet (amphioxus) genomes, that ancient vertebrates experienced high rates of protein evolution, genome rearrangement and domain shuffling and that these rates greatly slowed down after the divergence of jawed and jawless vertebrates. Compared with lancelets, modern vertebrates retain, at least relatively, less protein diversity, fewer nucleotide polymorphisms, domain combinations and conserved non-coding elements (CNE). Modern vertebrates also lost substantial transposable element (TE) diversity, whereas lancelets preserve high TE diversity that includes even the long-sought RAG transposon. Lancelets also exhibit rapid gene turnover, pervasive transcription, fastest exon shuffling in metazoans and substantial TE methylation not observed in other invertebrates. These new lancelet genome sequences provide new insights into the chordate ancestral state and the vertebrate evolution.

Lung adenocarcinoma (LUAD) is the most prevalent subtype of non-small cell lung cancer. Additionally, disulfidptosis, a newly discovered type of cell death, has been found to be closely associated with the onset and progression of tumors. The study first identified genes related to disulfidptosis through correlation analysis. These genes were then screened using univariate cox regression and LASSO regression, and a prognostic model was constructed through multivariate cox regression. A nomogram was also created to predict the prognosis of LUAD. The model was validated in three independent data sets: GSE72094, GSE31210, and GSE37745. Next, patients were grouped based on their median risk score, and differentially expressed genes between the two groups were analyzed. Enrichment analysis, immune infiltration analysis, and drug sensitivity evaluation were also conducted. In this study, we examined 21 genes related to disulfidptosis and developed a gene signature that was found to be associated with a poorer prognosis in LUAD. Our model was validated using three independent datasets and showed AUC values greater than 0.5 at 1, 3, and 5 years. Enrichment analysis revealed that the disulfidptosis-related genes signature had a multifaceted impact on LUAD, particularly in relation to tumor development, proliferation, and metastasis. Patients in the high-risk group exhibited higher tumor purity and lower stromal score, ESTIMATE score, and Immune score. This study constructed a gene signature related to disulfidptosis in lung adenocarcinoma and analyzed its impact on the disease and its association with the tumor microenvironment. The findings of this research provide valuable insights into the understanding of lung adenocarcinoma and could potentially lead to the development of new treatment strategies.

Increasing amounts of genes have been shown to utilize alternative polyadenylation (APA) 3′-processing sites depending on the cell and tissue type and/or physiological and pathological conditions at the time of processing, and the construction of genome-wide database regarding APA is urgently needed for better understanding poly(A) site selection and APA-directed gene expression regulation for a given biology. Here we present a web-accessible database, named APASdb (http://mosas.sysu.edu.cn/utr), which can visualize the precise map and usage quantification of different APA isoforms for all genes. The datasets are deeply profiled by the sequencing alternative polyadenylation sites (SAPAS) method capable of high-throughput sequencing 3′-ends of polyadenylated transcripts. Thus, APASdb details all the heterogeneous cleavage sites downstream of poly(A) signals, and maintains near complete coverage for APA sites, much better than the previous databases using conventional methods. Furthermore, APASdb provides the quantification of a given APA variant among transcripts with different APA sites by computing their corresponding normalized-reads, making our database more useful. In addition, APASdb supports URL-based retrieval, browsing and display of exon-intron structure, poly(A) signals, poly(A) sites location and usage reads, and 3′-untranslated regions (3′-UTRs). Currently, APASdb involves APA in various biological processes and diseases in human, mouse and zebrafish.

Stomach adenocarcinoma (STAD) is a type of cancer which often at itsadvanced stage apon diagnosis and mortality in clinical practice. Several factors influencethe prognosis of STAD, including the expression and regulation of immune cells in the tumor microenvironment. We here investigated the biomarkers related to the diagnosis and prognosis of gastric cancer, hoping to provide insights for the diagnosis and treatment of gastric cancer in the future. STAD and normal patient RNA sequencing data sets were accessed from the cancer genome atlas (TCGA database). Differential genes were determined and obtained by using the R package DESeq2. The stromal, immune, and ESTIMATE scores are calculated by the ESTIMATE algorithm, followed by the modular genes screening using the R package WGCNA. Subsequently, the intersection between the modular gene and the differential gene was taken and the STRING database was used for PPI network module analysis. The R packages clusterProfiler, enrichplot, and ggplot2 were used for GO and KEGG enrichment analysis. Cox regression analysis was used to screen survival-related genes, and finally, the R package Venn Diagram was used to take the intersection and obtain 7 hub genes. The time-dependent ROC curve and Kaplan–Meier survival curve were used to find the SERPINE1 gene, which plays a critical role in prognosis. Finally, the expression pattern, clinical characteristics, and regulatory mechanism of SERPINE1 were analyzed in STAD. We revealed that the expression of SERPINE1 was significantly increased in the samples from STAD compared with normal samples. Cox regression, time-dependent ROC, and Kaplan–Meier survival analyses demonstrated that SERPINE1 was significantly related to the adverse prognosis of STAD patients. The expression of SERPINE1 increased with the progression of T, N, and M classification of the tumor. In addition, the results of immune infiltration analysis indicated that the immune cells’ expression were higher in high SERPINE1 expression group than that in low SERPINE1 expression group, including CD4⁺ T cells, B cells, CD8⁺ T cells, macrophages, neutrophils and other immune cells. SERPINE1 was closely related to immune cells in the STAD immune microenvironment and had a synergistic effect with the immune checkpoints PD1 and PD-L1. In conclusion, we proved that SERPINE1 is a promising prognostic and diagnostic biomarker for STAD and a potential target for immunotherapy.