It has been known that, the novel coronavirus, 2019-nCoV, which is considered similar to SARS-CoV and originated from Wuhan (China), invades human cells via the receptor angiotensin converting enzyme II (ACE2). Moreover, lung cells that have ACE2 expression may be the main target cells during 2019-nCoV infection. However, some patients also exhibit non-respiratory symptoms, such as kidney failure, implying that 2019-nCoV could also invade other organs. To construct a risk map of different human organs, we analyzed the single-cell RNA sequencing (scRNA-seq) datasets derived from major human physiological systems, including the respiratory, cardiovascular, digestive, and urinary systems. Through scRNA-seq data analyses, we identified the organs at risk, such as lung, heart, esophagus, kidney, bladder, and ileum, and located specific cell types (i.e., type II alveolar cells (AT2), myocardial cells, proximal tubule cells of the kidney, ileum and esophagus epithelial cells, and bladder urothelial cells), which are vulnerable to 2019-nCoV infection. Based on the findings, we constructed a risk map indicating the vulnerability of different organs to 2019-nCoV infection. This study may provide potential clues for further investigation of the pathogenesis and route of 2019-nCoV infection.
To clarify the significance of circulating tumor cells (CTC) undergoing epithelial-mesenchymal transition (EMT) in patients with hepatocellular carcinoma (HCC), we used an advanced CanPatrol CTC-enrichment technique and hybridization to enrich and classify CTC from blood samples. One hundred and one of 112 (90.18%) patients with HCC were CTC positive, even with early-stage disease. CTCs were also detected in 2 of 12 patients with hepatitis B virus (HBV), both of whom had small HCC tumors detected within 5 months. CTC count ≥16 and mesenchymal-CTC (M-CTC) percentage ≥2% prior to resection were significantly associated with early recurrence, multi-intrahepatic recurrence, and lung metastasis. Postoperative CTC monitoring in 10 patients found that most had an increased CTC count and M-CTC percentage before clinically detectable recurrence nodules appeared. Analysis of HCC with high CTC count and high M-CTC percentage identified 67 differentially expressed cancer-related genes involved in cancer-related biological pathways (e.g., cell adhesion and migration, tumor angiogenesis, and apoptosis). One of the identified genes, BCAT1, was significantly upregulated, and knockdown in Hepg2, Hep3B, and Huh7 cells reduced cell proliferation, migration, and invasion while promoting apoptosis. A concomitant increase in epithelial marker expression (EpCAM and E-cadherin) and reduced mesenchymal marker expression (vimentin and Twist) suggest that BCAT1 may trigger the EMT process. Overall, CTCs were highly correlated with HCC characteristics, representing a novel marker for early diagnosis and a prognostic factor for early recurrence. BCAT1 overexpression may induce CTC release by triggering EMT and may be an important biomarker of HCC metastasis. In liver cancer, CTC examination may represent an important "liquid biopsy" tool to detect both early disease and recurrent or metastatic disease, providing cues for early intervention or adjuvant therapy. .
The human genome sequence defines our inherent biological potential; the realization of the biology encoded therein requires knowledge of the function of each gene. Currently, our knowledge in this area is still limited. Several lines of investigation have been used to elucidate the structure and function of the genes in the human genome. Even so, gene prediction remains a difficult task, as the varieties of transcripts of a gene may vary to a great extent. We thus performed an exhaustive integrative characterization of 41,118 full-length cDNAs that capture the gene transcripts as complete functional cassettes, providing an unequivocal report of structural and functional diversity at the gene level. Our international collaboration has validated 21,037 human gene candidates by analysis of high-quality full-length cDNA clones through curation using unified criteria. This led to the identification of 5,155 new gene candidates. It also manifested the most reliable way to control the quality of the cDNA clones. We have developed a human gene database, called the H-Invitational Database (H-InvDB; http://www.h-invitational.jp/). It provides the following: integrative annotation of human genes, description of gene structures, details of novel alternative splicing isoforms, non-protein-coding RNAs, functional domains, subcellular localizations, metabolic pathways, predictions of protein three-dimensional structure, mapping of known single nucleotide polymorphisms (SNPs), identification of polymorphic microsatellite repeats within human genes, and comparative results with mouse full-length cDNAs. The H-InvDB analysis has shown that up to 4% of the human genome sequence (National Center for Biotechnology Information build 34 assembly) may contain misassembled or missing regions. We found that 6.5% of the human gene candidates (1,377 loci) did not have a good protein-coding open reading frame, of which 296 loci are strong candidates for non-protein-coding RNA genes. In addition, among 72,027 uniquely mapped SNPs and insertions/deletions localized within human genes, 13,215 nonsynonymous SNPs, 315 nonsense SNPs, and 452 indels occurred in coding regions. Together with 25 polymorphic microsatellite repeats present in coding regions, they may alter protein structure, causing phenotypic effects or resulting in disease. The H-InvDB platform represents a substantial contribution to resources needed for the exploration of human biology and pathology.
Previous studies have shown that hepatocyte nuclear factor-4␣ (HNF4␣) is a central regulator of differentiated hepatocyte phenotype and forced expression of HNF4␣ could promote reversion of tumors toward a less invasive phenotype. However, the effect of HNF4␣ on cancer stem cells (CSCs) and the treatment of hepatocellular carcinoma (HCC) with HNF4␣ have not been reported. In this study, an adenovirus-mediated gene delivery system, which could efficiently transfer and express HNF4␣, was generated to determine its effect on hepatoma cells (Hep3B and H epatocellular carcinoma (HCC) is one of the most common cancers worldwide, and in the United States its incidence has increased by more than 90% in the past three decades. 1 Despite great advances in detection and treatment of the disease, the mortality rate remains high-especially in the advanced stage, when the disease is usually diagnosed. Even if anticancer therapies could shrink primary and metastatic tumors, such effects are usually transient, and most metastatic cancers relapse frequently.Recent evidence has demonstrated that tumors are organized in a hierarchy of heterogeneous cell populations with different biologic properties and that the populations consist of cancer stem cells (CSCs), proliferating Abbreviations: CSC, cancer stem cell; GFP, green fluorescent protein; HCC, hepatocellular carcinoma; HNF4␣, mRNA, messenger RNA; PBS, PCR, polymerase chain reaction; From the
Concerted examination of multiple collections of single-cell RNA sequencing (RNA-seq) data promises further biological insights that cannot be uncovered with individual datasets. Here we present scMerge, an algorithm that integrates multiple single-cell RNA-seq datasets using factor analysis of stably expressed genes and pseudoreplicates across datasets. Using a large collection of public datasets, we benchmark scMerge against published methods and demonstrate that it consistently provides improved cell type separation by removing unwanted factors; scMerge can also enhance biological discovery through robust data integration, which we show through the inference of development trajectory in a liver dataset collection.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.