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Li, Z.-S.

Publications and source records attributed to Li, Z.-S..

3 recordsLinked to original sources

Knowledge Mapping of Alternative Splicing of Cancer From 2012 to 2021: A Bibliometric Analysis

BackgroundAs a processing method of RNA precursors, alternative splicing plays a critical role in normal cell physiological activities. Aberrant alternative splicing events are associated with cancer development and are promising targets for cancer treatment. However, no detailed and unbiased study describes the current state of alternative splicing of cancer research. This study aims to conduct a bibliometric analysis of alternative splicing of cancer research in the last decade to measure and recognize the current state and trends. MethodsWeb of Science Core Collection was used to acquire the articles. Utilizing three bibliometric tools (CiteSpace, VOSviewer, R-bibliometrix), we were able to measure and recognize the influence and collaboration data of individual articles, journals, and co-citations. Analysis of co-occurrence and bursts information helped us identify the trending research areas related to alternative splicing of cancer. ResultsFrom 2012 to 2021, the total number of papers on alternative splicing of cancer published in 766 academic journals was 3,507, authored by 20,406 researchers in 405 institutions from 80 countries/regions. Research involving alternative splicing of cancer genes was primarily conducted in the United States and China, with the United States retaining the prime status; simultaneously, the Chinese Academy of Sciences, Fudan University and National Cancer Institute were the institutions with strong research capabilities. Scorilas Andreas is the scholar with the most publications, while the most co-citations were generated by Wang, Eric T. Plos One published the most papers on alternative splicing of cancer, while J biol chem was the most co-cited academic journal in this field. Furthermore, these publications covered a wide range of areas, but were still primarily focused on the fields of molecular, biology, and immunology. The results of keyword co-occurrence analysis can be divided into three types: molecular (P53, CD44, Androgen receptor, SRSF3, ESRP1), pathological process (apoptosis, EMT, metastasis, angiogenesis, proliferation), and disease (breast cancer, colorectal cancer, prostate cancer, hepatocellular carcinoma, gastric cancer). ConclusionResearch on alternative splicing of cancer has been a hot topic over the past decade, increasing in intensity each year. Current alternative splicing of cancer studies focused on hallmarks of alternative splicing in cancer, and alternative splicing signatures including diagnostic and therapeutic targets. Among them, the current trends are splicing factors regulating epithelial-mesenchymal transition and other hallmarks, aberrant splicing events in tumors, and further mechanisms. These might give researchers interested in this field a forward-looking perspective and inform further research.

cancer biology↗

Genetic analysis of the STIM1 gene in chronic pancreatitis

Chronic pancreatitis is a complex disease that involves many factors, both genetic and environmental. Over the past two decades, molecular genetic analysis of five genes that are highly expressed in human pancreatic acinar cells, namely PRSS1, PRSS2, SPINK1, CTRC and CTRB1/CTRB2, has established that a trypsin-dependent pathway plays a key role in the etiology of chronic pancreatitis. Since Ca2+ deregulation can lead to intracellular trypsin activation in experimental acute pancreatitis, we analyzed STIM1 (encoding stromal interaction molecule-1, the main regulator of Ca2+ homeostasis in pancreatic acinar cells) as a candidate modifier gene in French, German and Chinese patients with chronic pancreatitis. The French and German subjects were analyzed by Sanger sequencing whereas the Chinese subjects were analyzed by targeted next-generation sequencing confirmed by Sanger sequencing. A total of 37 rare coding variants (35 missense and 2 nonsense) were identified, which were enriched in patients as compared with controls [2.28% (47/2,057) vs. 0.99% (33/3,322); odds ratio = 2.33, P = 0.0001]. This is the first large case-control study to demonstrate a putative association of rare STIM1 coding variants with chronic pancreatitis. Functional analysis will be required to clarify whether or not the rare STIM1 variants detected predispose to pancreatitis.

genetics↗

First estimation of the scale of canonical 5’ splice site GT>GC mutations generating wild-type transcripts and their medical genetic implications

It has long been known that canonical 5 splice site (5SS) GT>GC mutations may be compatible with normal splicing. However, to date, the true scale of canonical 5SS GT>GC mutations generating wild-type transcripts, both in the context of the frequency of such mutations and the level of wild-type transcripts generated from the mutation alleles, remain unknown. Herein, combining data derived from a meta-analysis of 45 informative disease-causing 5SS GT>GC mutations (from 42 genes) and a cell culture-based full-length gene splicing assay of 103 5SS GT>GC mutations (from 30 genes), we estimate that [~]15-18% of the canonical GT 5SSs are capable of generating between 1 and 84% normal transcripts as a consequence of the substitution of GT by GC. We further demonstrate that the canonical 5SSs whose substitutions of GT by GC generated normal transcripts show stronger complementarity to the 5 end of U1 snRNA than those sites whose substitutions of GT by GC did not lead to the generation of normal transcripts. We also observed a correlation between the generation of wild-type transcripts and a milder than expected clinical phenotype but found that none of the available splicing prediction tools were able to accurately predict the functional impact of 5SS GT>GC mutations. Our findings imply that 5SS GT>GC mutations may not invariably cause human disease but should also help to improve our understanding of the evolutionary processes that accompanied GT>GC subtype switching of U2-type introns in mammals.

genetics↗