Stage II colorectal cancer(CRC) patients after surgery alone have a five-year survival rate of ~60-80%; the incremental benefit of adjuvant chemotherapy is <5%. Predicting risk of recurrence and selecting effective personalized adjuvant drugs for stage II CRC using formalin-fixed, paraffin-embedded(FFPE) samples is a major challenge.1319 stage II CRC patients who enrolled in 2011-2019 at Sun Yat-sen University Cancer Center were screened. RNAseq data of FFPE tumor samples of 222 stage II microsatellite stable(MSS) CRC patients(recurrence (n=47), norecurrence (n=175), median follow-up=41 months) were used to develop a method TFunctionalProg for dissecting heterogeneous subgroups of recurrence and predicting risk of recurrence.TFunctionalProg showed significant predictive values in 222 stage II MSS CRCs. The TFunctionalProg low-risk group had significantly better recurrence free survival (validation set: HR=4.78, p-value=1e-4, low-risk group three-year recurrence free survival=92.6%, high-risk group three-year recurrence free survival=59.7%). TFunctionalProg dissected two subgroups of transition states of stage II MSS CRCs at a high risk of recurrence; each state displays distinct levels of hybrid epithelial-mesenchymal traits, CD8+ T cell suppression mechanisms and FOLFOX resistance. Based on mechanisms in two subgroups, TFunctionalProg proposed personalized rational adjuvant drug combinations of immunotherapy, chemotherapy and repurposed CNS drugs. TFunctionalProg provides different utilities from ctDNA-based prognostic biomarkers.TFunctionalProg was validated using FFPE samples to predict the risk of recurrence and propose rational adjuvant drug combinations for stage II CRC.
Abstract Background Stage II colorectal cancer(CRC) patients after surgery alone have a five-year survival rate of ∼60-80%; the incremental benefit of adjuvant chemotherapy is <5%. Predicting risk of recurrence and selecting effective personalized adjuvant drugs for stage II CRC using formalin-fixed, paraffin-embedded(FFPE) samples is a major challenge. Methods 1319 stage II CRC patients who enrolled in 2011-2019 at Sun Yat-sen University Cancer Center were screened. RNAseq data of FFPE tumor samples of 222 stage II MSS CRC patients(n.recurrence=47, n.norecurrence=175, median follow-up=41 months) were used to develop a method TFunctionalProg for dissecting heterogeneous subgroups of recurrence, predicting risk of recurrence and proposing adjuvant drugs. Results TFunctionalProg showed significant predictive values in 222 stage II MSS CRCs. The TFunctionalProg low-risk group had significantly better RFS (validation set (HR=4.78, p-value=1e-4, low-risk group three-year RFS=92.6%, high-risk group three-year RFS=59.7%). TFunctionalProg dissected two subgroups of transition states of stage II MSS CRCs at a high risk of recurrence; each state displays distinct levels of hybrid epithelial-mesenchymal traits, cytotoxic cell inhibition and FOLFOX resistance. Based on mechanisms in two subgroups, TFunctionalProg proposed personalized rational adjuvant drug combinations of immunotherapy, chemotherapy and repurposed CNS drugs. The complementary utility of TFunctionalProg and ctDNA-based prognostic biomarkers were presented. Conclusion TFunctionalProg was validated using FFPE samples to predict the risk of recurrence and propose rational adjuvant drug combinations for stage II CRCs.
Abstract Background FOLFOX is a combination of drugs that is widely used to treat colorectal cancer. The response rate of FOLFOX in colorectal cancer(CRC) is 30-50%. We develop a method that analyzes mechanisms of FOLFOX resistance and predicts whether a patient will benefit from FOLFOX. Methods Gene expression data of 83 stage IV CRC tumor samples (FOLFOX responder n=42, non-responder n=41) were used to develop a supervised learning method IML and analyze subgroups of FOLFOX resistance mechanism. Datasets of 32 FOLFOX treated stage IV CRC patients and 55 FOLFOX treated stage III CRC patients were used as independent validations. Results An iterative supervised learning (IML) method identified two distinct subgroups of CRC patients who resist FOLFOX. Each subgroup relies on different types of DNA damage repair proteins and they are mutually exclusive. Protein-protein networks showed the main mechanism might be the synergistic effect of resisting apoptosis and an altered cell cycle. IML method was validated in two independent validation sets, one FOLFOX treated stage IV CRC patients(HR=2.6, p-value=0.02, 3-years survival rate of the predicted responder group 61.9%, predicted nonresponder group 18.8%) and one FOLFOX treated stage III CRC patients (estimated HR=2.36, p-value=0.02). A subgroup of mesenchymal subtype patients shows the pattern as FOLFOX responders. Conclusions IML method reflects the underlying biology of FOLFOX resistance and predicts FOLFOX response.
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