Gene regulatory networks (GRNs) formed by transcription factors (TFs) and their downstream target genes play essential roles in gene expression regulation. Moreover, GRNs can be dynamic changing across different conditions, which are crucial for understanding the underlying mechanisms of disease pathogenesis. However, no existing database provides comprehensive GRN information for various human and mouse normal tissues and diseases at the single-cell level. Based on the known TF-target relationships and the large-scale single-cell RNA-seq data collected from public databases as well as the bulk data of The Cancer Genome Atlas and the Genotype-Tissue Expression project, we systematically predicted the GRNs of 184 different physiological and pathological conditions of human and mouse involving >633 000 cells and >27 700 bulk samples. We further developed GRNdb, a freely accessible and user-friendly database (http://www.grndb.com/) for searching, comparing, browsing, visualizing, and downloading the predicted information of 77 746 GRNs, 19 687 841 TF-target pairs, and related binding motifs at single-cell/bulk resolution. GRNdb also allows users to explore the gene expression profile, correlations, and the associations between expression levels and the patient survival of diverse cancers. Overall, GRNdb provides a valuable and timely resource to the scientific community to elucidate the functions and mechanisms of gene expression regulation in various conditions.

Recent retrospective studies of severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) disease (COVID‐19) revealed that the patients with common comorbidities of cancers and chronic diseases face significantly poorer clinical outcomes than those without. Since the expression profile of ACE2, a crucial cell entry receptor for SARS‐CoV‐2, could indicate the susceptibility to SARS‐CoV‐2 infection, here we systematically dissected ACE2 expression using large‐scale multi‐omics data from 30 organs/tissues, 33 cancer types and some common chronic diseases involving >28 000 samples. It was found that sex and age could be correlated with the susceptibility of SARS‐CoV‐2 infection for certain tissues. Strikingly, ACE2 was up‐regulated in cervical squamous cell carcinoma and endocervical adenocarcinoma, colon adenocarcinoma, oesophageal carcinoma, kidney renal papillary cell carcinoma, lung adenocarcinoma and uterine corpus endometrial carcinoma compared to controls. Furthermore, the patients with common chronic diseases regarding angiocardiopathy, type 2 diabetes, liver, pneumonia and hypertension were also with higher ACE2 expression compared to related controls, which were validated using independent data sets. Collectively, our study may reveal a novel important mechanism that the patients with certain cancers and chronic diseases may express higher ACE2 expression compared to the individuals without diseases, which could lead to their higher susceptibility to multi‐organ injury of SARS‐CoV‐2 infection.

Overall survival (OS) benefits of neoadjuvant immunotherapy remain elusive in locally advanced esophageal squamous cell carcinomas (ESCC). Here, we reported the results of a phase 1b trial of neoadjuvant PD-L1 blockade with adebrelimab in resectable ESCC. Patients received two neoadjuvant doses of adebrelimab followed by surgery. The primary endpoints were safety and feasibility; secondary endpoints included pathologic complete response (pCR) and OS. Our data showed the primary endpoints of safety and feasibility had been met. Common treatment-related adverse events were anorexia (32%) and fatigue (16%), without grade 3 or more adverse events. Of the 30 patients enrolled in the trial, 25 underwent successful resection without surgery delay and 24% had major pathologic responses including a pCR rate of 8%. The 2-year OS was 92%. Responsive patients had an immune-enriched tumor microenvironment phenotype, whereas nonresponsive patients had greater infiltration of cancer-associated fibroblasts at baseline. Clonotypic dynamics of pre-existing intratumoral T cells was a hallmark of responsive patients. These findings provide a rational for neoadjuvant anti-PD-L1 monotherapy as a therapeutic strategy for patients with resectable ESCC.

Single-cell RNA-seq (scRNA-seq) technologies are broadly applied to dissect the cellular heterogeneity and expression dynamics, providing unprecedented insights into single-cell biology. Most of the scRNA-seq studies mainly focused on the dissection of cell types/states, developmental trajectory, gene regulatory network, and alternative splicing. However, besides these routine analyses, many other valuable scRNA-seq investigations can be conducted. Here, we first review cell-to-cell communication exploration, RNA velocity inference, identification of large-scale copy number variations and single nucleotide changes, and chromatin accessibility prediction based on single-cell transcriptomics data. Next, we discuss the identification of novel genes/transcripts through transcriptome reconstruction approaches, as well as the profiling of long non-coding RNAs and circular RNAs. Additionally, we survey the integration of single-cell and bulk RNA-seq datasets for deconvoluting the cell composition of large-scale bulk samples and linking single-cell signatures to patient outcomes. These additional analyses could largely facilitate corresponding basic science and clinical applications.