Background and aims: Genomic instability, as reflected in specific chromosomal aneuploidies and variation in the nuclear DNA content, is a defining feature of human carcinomas. It is solidly established that the degree of genomic instability influences clinical outcome. We have recently identified a 12-gene expression signature that discerned genomically stable from unstable breast carcinomas. This gene expression signature was also useful to predict, with high accuracy, the clinical course in independent multiple published breast cancer cohorts. From a biological point of view, this result confirmed the central role of genomic instability for a tumor's ability to adapt to external challenges and selective pressure, and hence for continued survival fitness. This prompted us to investigate whether this genomic instability signature could also predict clinical outcome in other cancer types of epithelial origin, including colorectal tumors, non-small cell lung carcinomas, and ovarian cancer.
Results: The results show that the gene expression signature that defines genomic instability and poor outcome in breast cancer contributes significantly more accurate (p<0.05 compared with random prediction) prognostic information in multiple cancer types independent of established clinical parameters. The 12-gene genomic instability signature stratified patients into high- and low-risk groups with distinct postoperative survival in three non-small cell lung cancer cohorts (n=637) in Kaplan-Meier analyses (log-rank p<0.05). It predicted recurrence in colon cancer patients (n=92) with an overall accuracy greater than 69% (p=0.04) in cross-cohort validation. It quantified relapse-free survival in ovarian cancer (n=124; log-rank p<0.05). Functional pathway analysis revealed interactions between the 12 signature genes and well-known cancer hallmarks.
Conclusion: The degree of genomic instability has diagnostic and prognostic implications. It is tempting to speculate that pursuing genomic instability therapeutically could provide entry points for a target that is unique to cancer cells.