Expression dynamics of periodic transcripts during cancer cell cycle progression and their correlation with anticancer drug sensitivity

Chun-Xiao Li; Jin-Song Wang; Wen-Na Wang; Dong-Kui Xu; Yan-Tong Zhou; Fang-Zhou Sun; Yi-Qun Li; Feng-Zhu Guo; Jia-Lu Ma; Xue-Yan Zhang; Meng-Jiao Chang; Bing-He Xu; Fei Ma; Hai-Li Qian

doi:10.1186/s40779-022-00432-w

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Expression dynamics of periodic transcripts during cancer cell cycle progression and their correlation with anticancer drug sensitivity

RESEARCH | Updated：2023-09-05

- Expression dynamics of periodic transcripts during cancer cell cycle progression and their correlation with anticancer drug sensitivity
- Expression dynamics of periodic transcripts during cancer cell cycle progression and their correlation with anticancer drug sensitivity
- MMR 2023年10卷第4期页码：444-460
- Affiliations：
  
  1.State Key Laboratory of Molecular Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
  2.Department of Medical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
  3.Department of VIP, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
- Author bio：
  
  * xubinghe@medmail.com.cn;
  drmafei@126.com;
  qianhaili001@163.com
- Funds：
  
  grants from the National Key Research and Development Program of China(2021YFF1201300);the National Natural Science Foundation of China(81872280;82073094);the CAMS Innovation Fund for Medical Sciences (CIFMS)(2021-I2M-1-014);the Open Issue of State Key Laboratory of Molecular Oncology(SKL-KF-2021-16);the Independent Issue of State Key Laboratory of Molecular Oncology(SKL-2021-16)
- DOI：10.1186/s40779-022-00432-w
  中图分类号：
- 纸质出版：2023-08
- Accepted：
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Expression dynamics of periodic transcripts during cancer cell cycle progression and their correlation with anticancer drug sensitivity[J]. MMR, 2023,10(4):444-460.

Li CX, Wang JS, Wang WN, Xu DK, Zhou YT, Sun FZ, et al. Expression dynamics of periodic transcripts during cancer cell cycle progression and their correlation with anticancer drug sensitivity. Mil Med Res. 2022;9(1):71.
Expression dynamics of periodic transcripts during cancer cell cycle progression and their correlation with anticancer drug sensitivity[J]. MMR, 2023,10(4):444-460. DOI： 10.1186/s40779-022-00432-w.

Li CX, Wang JS, Wang WN, Xu DK, Zhou YT, Sun FZ, et al. Expression dynamics of periodic transcripts during cancer cell cycle progression and their correlation with anticancer drug sensitivity. Mil Med Res. 2022;9(1):71. DOI： 10.1186/s40779-022-00432-w.

摘要

Abstract

Background:

The 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.

Methods:

To 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.

Results:

We 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

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.

Conclusions:

In 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.

关键词

Keywords

references

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