Abstract

Alternative cleavage and polyadenylation within introns (intronic APA) generate shorter mRNA isoforms; however, their physiological significance remains elusive. In this study, we developed a comprehensive workflow to analyze intronic APA profiles using the mammalian target of rapamycin (mTOR)-regulated transcriptome as a model system. Our investigation revealed two contrasting effects within the transcriptome in response to fluctuations in cellular mTOR activity: an increase in intronic APA for a subset of genes and a decrease for another subset of genes. The application of this workflow to RNA-seq data from The Cancer Genome Atlas demonstrated that this dichotomous intronic APA pattern is a consistent feature in transcriptomes across both normal tissues and various cancer types. Notably, our analyses of protein length changes resulting from intronic APA events revealed two distinct phenomena in proteome programming: a loss of functional domains due to significant changes in protein length or minimal alterations in C-terminal protein sequences within unstructured regions. Focusing on conserved intronic APA events across 10 different cancer types highlighted the prevalence of the latter cases in cancer transcriptomes, whereas the former cases were relatively enriched in normal tissue transcriptomes. These observations suggest potential, yet distinct, roles for intronic APA events during pathogenic processes and emphasize the abundance of protein isoforms with similar lengths in the cancer proteome. Furthermore, our investigation into the isoform-specific functions of JMJD6 intronic APA events supported the hypothesis that alterations in unstructured C-terminal protein regions lead to functional differences. Collectively, our findings underscore intronic APA events as a discrete molecular signature present in both normal tissues and cancer transcriptomes, highlighting the contribution of APA to the multifaceted functionality of the cancer proteome.

Dichotomous intronic APA effects: unveiling proteome programming in cancer

Understanding our genes is vital for combating diseases like cancer. A crucial gene expression process is alternative polyadenylation. These versions can influence cell behavior and are associated with various diseases, including cancer. The role of a specific APA type, intronic APA, in cancer was unclear. This study examined intronic APA’s effect on cancer by analyzing cancer patient data. They found that intronic APA profiles vary greatly between normal and tumor tissues across different cancer types, indicating that intronic APA plays a complex role in cancer biology. The results showed that intronic APA contributes to the diversity of mRNA endings in cancer, affecting gene expression. This could lead to new diagnosis or treatment approaches. The researchers concluded that intronic APA is a key factor in cancer’s molecular landscape, providing new insights into cancer development and progression.

This summary was initially drafted using artificial intelligence, then revised and fact-checked by the author.

Details

Title
Dichotomous intronic polyadenylation profiles reveal multifaceted gene functions in the pan-cancer transcriptome
Author
Sun, Jiao 1 ; Kim, Jin-Young 2 ; Jun, Semo 3 ; Park, Meeyeon 4 ; de Jong, Ebbing 5 ; Chang, Jae-Woong 4 ; Cheng, Sze 4 ; Fan, Deliang 6 ; Chen, Yue 4 ; Griffin, Timothy J. 4 ; Lee, Jung-Hee 3 ; You, Ho Jin 2   VIAFID ORCID Logo  ; Zhang, Wei 7   VIAFID ORCID Logo  ; Yong, Jeongsik 4   VIAFID ORCID Logo 

 University of Central Florida, Department of Computer Science, Orlando, USA (GRID:grid.170430.1) (ISNI:0000 0001 2159 2859); St. Jude Children’s Research Hospital, Department of Biostatistics, Memphis, USA (GRID:grid.240871.8) (ISNI:0000 0001 0224 711X) 
 Chosun University School of Medicine, Department of Pharmacology, Gwangju, Republic of Korea (GRID:grid.254187.d) (ISNI:0000 0000 9475 8840) 
 Chosun University School of Medicine, Department of Cellular and Molecular Medicine, Gwangju, Republic of Korea (GRID:grid.254187.d) (ISNI:0000 0000 9475 8840) 
 University of Minnesota Twin Cities, Department of Biochemistry, Molecular Biology and Biophysics, Minneapolis, USA (GRID:grid.17635.36) (ISNI:0000 0004 1936 8657) 
 University of Minnesota Twin Cities, Department of Biochemistry, Molecular Biology and Biophysics, Minneapolis, USA (GRID:grid.17635.36) (ISNI:0000 0004 1936 8657); SUNY Upstate Medical University, Syracuse, USA (GRID:grid.411023.5) (ISNI:0000 0000 9159 4457) 
 Johns Hopkins University, Department of Electrical and Computer Engineering, Baltimore, USA (GRID:grid.21107.35) (ISNI:0000 0001 2171 9311) 
 University of Central Florida, Department of Computer Science, Orlando, USA (GRID:grid.170430.1) (ISNI:0000 0001 2159 2859) 
Pages
2145-2161
Publication year
2024
Publication date
Oct 2024
Publisher
Springer Nature B.V.
ISSN
12263613
e-ISSN
20926413
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
3124945142
Copyright
© The Author(s) 2024. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.