Project Background

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Colorectal cancer is the second leading cause of cancer-related deaths in the developed world. Recently, the treatment paradigm for metastatic colorectal cancer (mCRC) has evolved in complexity to include newly developed targeted therapeutics. The past decades have seen chemotherapy and targeted therapies double median overall survival in metastatic colorectal cancer from 12 months with bolus fluorouracil [1] to almost 24 months in recent trials [2]. Nevertheless, despite these interventions, additional options are required for mCRC patients who have disease progression despite all currently available standard therapies. Regorafenib (REG, Stivarga, developed & marketed by Bayer Healthcare) is a novel oral multi-kinase inhibitor that blocks the activity of several protein kinases, including those involved in the regulation of tumour angiogenesis, oncogenesis and the tumour microenvironment. In September 2012 the Food and Drug Administration (FDA) approved REG monotherapy for the treatment of patients with mCRC who had been previously treated with fluoropyrimidine-, oxaliplatin-, and irinotecan-based chemotherapy, with an anti-VEGF therapy, and, if KRAS wild type, with an anti-EGFR therapy. Approval was based on the outcome of an international randomized double-blind, placebo-controlled trial ['CORRECT' trial] [3] that showed a statistically significant prolongation in overall survival (6.4 months vs 5 months. Hazard Ratio: 0.77) and progression free survival (2 months vs 1.7 months). Currently, elucidation of the mCRC patient subset most likely to derive clinical benefit is of high priority [4].

Neither robust, validated predictive imaging or 'omic markers, nor associated companion diagnostics for REG currently exist. To this end, a state of the art mCRC Patient Derived Xenograft (PDX) platform will be established to enable the systematic and integrated interrogation of predictive 'omic and imaging markers of intrinsic sensitivity or resistance to REG. Ultimately, emergent pre-clinical biomarker data may be cross-validated with clinically pertinent biomarker candidates arising from genomic biomarker discovery studies implementing clinical samples.

Uniquely, data emerging from Coloforetell will be integrated and analysed using conventional statistics and systems modeling approaches according to a novel 'panomics' strategy.





[1] Verdecchia, A., et al., Eur J Public Health, 2008. 18(5): p. 527-32.

[2] Saltz, L.B., et al., N Engl J Med, 2000. 343(13): p. 905-14.

[3] Grothey, A., et al., Lancet, 2013. 381(9863): p. 303-12.

[4] Waddell, T. and D. Cunningham, Lancet, 2013. 381(9863): p. 273-5.