Abstract 98P
Background
Most late-stage colorectal cancer (CRC) patients experience lethal metastasis, often to the liver. However, the molecular mechanisms that drive metastatic progression and adaptation to new tissue environments remain challenging to study in patients.
Methods
To investigate molecular changes associated with CRC liver metastasis, we analyzed genomic and transcriptomic profiles in a discovery cohort of 49 patients with paired primary and metastatic colorectal cancer samples, along with an independent single-cell RNA sequencing (scRNA-seq) dataset from 16 patients with matched primary and liver metastasis samples. We found that noise arising from tissue-specific gene expression signatures obscured conventional bulk-tumor analytical approaches to profile transcriptomic alterations associated with metastatic progression. To address this challenge, we employed a tumor transcriptome deconvolution approach to specifically profile transcriptomic differences between primary and metastatic cancer cells, localized in the colon and liver tissue environments, respectively.
Results
We integrated these results with the scRNA-seq cohort to identify high-confidence transcriptomic alterations associated with cancer-cell metastatic progression in CRC. Intriguingly, metastatic cancer cells showed significant upregulation of genes linked to embryonic development. Surprisingly, our analysis also revealed marked downregulation of cell cycle checkpoint pathways, suggesting impaired cell cycle regulation and proliferation in metastatic lesions, which may limit the efficacy of cytotoxic chemotherapy.
Conclusions
Overall, our study demonstrates the importance of tumor transcriptome deconvolution when analyzing and interpreting tumor gene expression data from metastatic lesions. Our results highlight specific molecular alterations in metastatic colorectal cancer cells, which could serve as novel biomarkers or therapeutic targets to detect and prevent lethal disease spread.
Clinical trial identification
Editorial acknowledgement
Legal entity responsible for the study
Genome Institute of Singapore (GIS), Agency for Science, Technology and Research (A*STAR).
Funding
Agency for Science, Technology and Research (A*STAR).
Disclosure
All authors have declared no conflicts of interest.