Multi-omics analyses revealed three Golgi apparatus genes potentially associated with poor prognosis in colorectal cancer patients
Year: 2025
Type: article
Abstract: The identification of novel functional biomarkers is crucial in recognizing high-risk colorectal cancer (CRC) patients. Despite this need, no prognostic biomarker has been implemented in clinical practice for CRC. To address this gap, we utilized integrated transcriptomic data from public databases alongside our original multi-omics data, including proteome and chromatin accessibility datasets. Bioinformatics studies on transcriptomic datasets from 487 CRC patients led us to identify three Golgi apparatus prognostic genes: NIPAL1, ZYG11B, and PARP10. We found that decreased expression of NIPAL1 and ZYG11B, as well as increased expression of PARP10, elevated the risk of CRC. These genes are potentially involved in cellular processes such as nucleotide excision repair and DNA replication. Additionally, our original multi-omics datasets, encompassing proteomic data and chromatin accessibility profiling from assay for transposase-accessible chromatin with sequencing (ATAC-Seq), identified alterations in protein levels of potential upstream transcription factors CDX2 and YY1 for three genes. Furthermore, chromatin accessibility at DNA binding regions corresponding to transcription factors such as SPI1 and JUND changed, potentially explaining the observed variations in mRNA levels for these genes. Our findings highlight the biological activities of these genes, including NIPAL1, PARP10, and ZYG11B, and their upstream regulators, offering a functional context for future in-depth mechanistic studies.
Source: Genetics and Molecular Biology
Authors: Peng Zhu, Shisi Shen, Xi Wang, Jie Li, Donge Tang, Yong Dai, Min Tang, Wei Zhang, Guoping Sun
Institutions: Shenzhen University, Shenzhen University Health Science Center, Southern Medical University, Chinese Academy of Medical Sciences & Peking Union Medical College, Peking Union Medical College Hospital, Shenzhen Traditional Chinese Medicine Hospital, Peking University Shenzhen Hospital, Anhui University of Science and Technology, Chongqing Medical University
Language: English
Subfield: Pathology and Forensic Medicine
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $700
OpenAlex ID: W4414624722
