ArticleMilitary Medical Research2022
Expression dynamics of periodic transcripts during cancer cell cycle progression and their correlation with anticancer drug sensitivity.
Article in Military Medical Research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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17 citing papers in PubMed, 19 citations in OpenAlex.
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- Exploration of the ubiquitination-related molecular classification and signature to predict the survival and immune microenvironment in colon cancer.Frontiers in genetics · 2024Article
- Development of a cell adhesion-based prognostic model for multiple myeloma: Insights into chemotherapy response and potential reversal of adhesion effects.Oncology research · 2024Article
- PANoptosis-based molecular subtyping and HPAN-index predicts therapeutic response and survival in hepatocellular carcinoma.Frontiers in immunology · 2023Article
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14 authors at 1 institution in 2 countries.
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No grant is acknowledged in the PubMed record.
Abstract
backgroundThe cell cycle is at the center of cellular activities and is orchestrated by complex regulatory mechanisms, among which transcriptional regulation is one of the most important components. Alternative splicing dramatically expands the regulatory network by producing transcript isoforms of genes to exquisitely control the cell cycle. However, the patterns of transcript isoform expression in the cell cycle are unclear. Therapies targeting cell cycle checkpoints are commonly used as anticancer therapies, but none of them have been designed or evaluated at the alternative splicing transcript level. The utility of these transcripts as markers of cell cycle-related drug sensitivity is still unknown, and studies on the expression patterns of cell cycle-targeting drug-related transcripts are also rare.
methodsTo explore alternative splicing patterns during cell cycle progression, we performed sequential transcriptomic assays following cell cycle synchronization in colon cancer HCT116 and breast cancer MDA-MB-231 cell lines, using flow cytometry and reference cell cycle transcripts to confirm the cell cycle phases of samples, and we developed a new algorithm to describe the periodic patterns of transcripts fluctuating during the cell cycle. Genomics of Drug Sensitivity in Cancer (GDSC) drug sensitivity datasets and Cancer Cell Line Encyclopedia (CCLE) transcript datasets were used to assess the correlation of genes and their transcript isoforms with drug sensitivity. We identified transcripts associated with typical drugs targeting cell cycle by determining correlation coefficients. Cytotoxicity assays were used to confirm the effect of ENST00000257904 against cyclin dependent kinase 4/6 (CDK4/6) inhibitors. Finally, alternative splicing transcripts associated with mitotic (M) phase arrest were analyzed using an RNA synthesis inhibition assay and transcriptome analysis.
resultsWe established high-resolution transcriptome datasets of synchronized cell cycle samples from colon cancer HCT116 and breast cancer MDA-MB-231 cells. The results of the cell cycle assessment showed that 43,326, 41,578 and 29,244 transcripts were found to be periodically expressed in HeLa, HCT116 and MDA-MB-231 cells, respectively, among which 1280 transcripts showed this expression pattern in all three cancer cell lines. Drug sensitivity assessments showed that a large number of these transcripts displayed a higher correlation with drug sensitivity than their corresponding genes. Cell cycle-related drug screening showed that the level of the CDK4 transcript ENST00000547281 was more significantly associated with the resistance of cells to CDK4/6 inhibitors than the level of the CDK4 reference transcript ENST00000257904. The transcriptional inhibition assay following M phase arrest further confirmed the M-phase-specific expression of the splicing transcripts. Combined with the cell cycle-related drug screening, the results also showed that a set of periodic transcripts, for example, ENST00000314392 (a dolichyl-phosphate mannosyltransferase polypeptide 2 isoform transcript), was more associated with drug sensitivity than the levels of their corresponding gene transcripts.
conclusionsIn summary, we identified a panel of cell cycle-related periodic transcripts and found that the levels of transcripts of drug target genes showed different values for predicting drug sensitivity, providing novel insights into alternative splicing-related drug development and evaluation.
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