Personalizing treatment for colorectal cancer patients by combining tissue-based biomarkers and ctDNA
Cancer recurrence is estimated to occur in 80% of patients with colorectal cancer (CRC) within 3 years after surgery. The selection of adjuvant therapy depends on conventional histopathological staging procedures, which constitute a blunt tool for patient stratification. The benefits of adjuvant therapy are relatively marginal, and it is clear that there is a need for better methods for selecting patients who will benefit the most from the treatment whilst sparing those who will not derive benefit.
-"The better we understand the likelihood of cancer recurrence, the better we can tailor our adjuvant therapy, providing a more truly personalized treatment", emphasizes David Kerr, Professor at the University of Oxford and former president of the European Society for Medical Oncology (ESMO)
Liquid biopsies detecting ctDNA have been shown to have clinical utility for early detection of recurrence through surveillance and thus have the potential to personalize the management of CRC patients. However, the analysis of ctDNA is costly, and the initial assessment of a patient's status usually occurs at least four weeks following curative surgery and two weeks after completing systemic therapy. This delay is due to the persistence of elevated levels of cell-free DNA for several weeks post-treatment. Given the uncertain consequences of delaying potential chemotherapy and the fact that some patients may not show detectable ctDNA at their initial follow-up assessment, we propose using tissue-based biomarkers to facilitate an early pre-selection of treatment.
Improved patient management
Current clinicopathological markers are insufficient to stratify patients with early-stage CRC accurately. In 2020, Skrede et al. demonstrated how artificial intelligence (AI) can be used to predict CRC patient outcome in a study in The Lancet (Skrede et al., The Lancet 2020). The AI marker, named DoMore-v1-CRC, predicts the likelihood of cancer-specific death directly from images of routine histopathology sections. Building on these findings, the marker has since then been integrated with established clinicopathological markers to provide a clinical decision support system (CDSS) for guiding the choice of adjuvant chemotherapy in stage II and III CRC without residual disease after surgery (Kleppe et al., Lancet Oncology 2022).
Compared to conventional risk stratification for adjuvant therapy, the proposed CDSS identifies a much larger group of patients with an excellent prognosis that are likely to have similar survival with and without adjuvant chemotherapy and can, therefore, be spared the severe side effects of the treatment.
Since the CDSS's recommendation can be determined within a few days after surgery, patients identified as high-risk can begin treatment soon after surgery. In addition, the CDSS would identify additional strong candidates for adjuvant chemotherapy among those who are ctDNA negative at first assessment. Patients classified as low risk by the CDSS would then enter a ctDNA monitoring program and receive treatment upon ctDNA detection, if any.
- "I believe that integrating tissue and blood-borne prognostic biomarkers, as we suggest in this article, does make sense in regard to a more personalized treatment", says Professor Kerr. With this combined approach, more than half the patients with high-risk stage II and III CRC can be spared from adjuvant treatment, as they are very unlikely to benefit from it. This novel paradigm will reduce the economic cost and personnel requirements and improve patient management by more truly personalized treatment – which is ultimately the goal!