Colon cancer is among one of the most common cancer diagnoses in men and women, with nearly 107,000 new cases estimated to arise this year in the United States alone.1 Of those, 10-20% will exhibit microsatellite instability (MSI), an indicator of mismatch repair deficiency (dMMR), which is a distinct DNA damage repair deficit that directly influences a patient’s prognosis and treatment.2 Yet today, many of those cases are being overlooked. Although testing for MSI status is recommended by several international guidelines,3 it is not performed in every lab on every case, with some recent studies showing as few as 28% of eligible adult patients being screened.4
Paige Colon MSI is an AI-assisted digital biomarker identifying MSI-H and dMMR phenotypes in colon cancer tumors, designed with hope of helping close the testing gap*. Paige’s application works on H&E-stained tissue alone, and herein lies its unique potential: as a pre-screening tool, Paige Colon MSI can automatically predict potential MSI-H status in every colon cancer case, which may help resolve many of the common challenges that have kept MSI-H patients from being consistently tested and diagnosed today.
A pre-screening approach could minimize time pressure by allowing pathologists to more easily jump to cases that might benefit from additional testing and evaluate any tissue that has been flagged as containing possible dMMR/MSI phenotypes. Pathologists can then send those cases off for IHC, PCR, or NGS confirmation of MSI-H status, helping screen cases for research applications, or perhaps one day in the clinical workflow, which could reduce total turnaround times and payor spending on more expensive, tissue intensive PCR, NGS, or IHC. Likewise, pre-screening could allow the approximately 80-85% of patients who are highly likely to not have MSI-H status to avoid the long delays that come with an IHC, PCR or NGS highly likely to show no MSI-H.5
In addition to time savings, decreasing unnecessary IHC, NGS, or PCR also offers important cost-savings, as such processes can be quite expensive, as well as better distribution of resources. Inexpensive screening assays in general can help reduce cost in resource reluctant or resource constrained healthcare systems. Additionally, with sufficient clinical evidence, pre-screening of cases for MSI-H might democratize access to MSI testing by detecting and prioritizing cases that truly need confirmatory evaluation, even in limited resource settings.
When Paige Colon MSI is used in combination with traditional IHC, PCR, and NGS, users can feel confident that they have identified the great majority of cases with MSI-H status. In fact, in an internal analytical study, Colon MSI showed 98% sensitivity for MSI positive patients and ruled out over 67% of MSI negative patients**, with a robust ground truth data curated from dMMR IHC and molecular testing. Researchers and tissue banks can more efficiently screen for dMMR/MSI-H cases, exploring the unique pathology, histology, and treatment and medical genetics associations of dMMR/MSI-H. This research may lead to future insights for oncologists and the rest of the care team, who can translate these insights in ways that could potentially help guide treatment selection. For example, MSI-H tumors in certain clinical settings may not require chemotherapy or extensive surgery but would instead be strong candidates for immunotherapy.2 Armed with the insights provided by research assisted with Paige Colon MSI, the entire cancer care team can more confidently deliver the best possible care to their patients.
Using AI for such biomarker detection is an innovative approach, but it’s one that can immediately inform research into MSI-H and dMMR, with the potential to transform the entire cancer care process and diagnostic workflow for colorectal carcinoma. Learn more about Paige Colon MSI with a custom demo.
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1American Cancer Society. Key Statistics for Colorectal Cancer. Cancer.org. Published January 13, 2023. Accessed October 24, 2023. https://www.cancer.org/cancer/types/colon-rectal-cancer/about/key-statistics.html
2Echle A, Grabsch HI, Quirke P, et al. Clinical-Grade Detection of Microsatellite Instability in Colorectal Tumors by Deep Learning. Gastroenterology. 2020;159(4):1406-1416.e11. doi:10.1053/j.gastro.2020.06.021
3CAP Guidelines, NIH Guidelines, Annals of Oncology
4Shaikh T, Handorf EA, Meyer JE, Hall MJ, Esnaola NF. Mismatch Repair Deficiency Testing in Patients With Colorectal Cancer and Nonadherence to Testing Guidelines in Young Adults. JAMA Oncol. 2018;4(2):e173580. doi:10.1001/jamaoncol.2017.3580
5Maria Lorenzi, Mayur Amonkar, Jacky Zhang, Shivani Mehta, Kai-Li Liaw, “Epidemiology of Microsatellite Instability High (MSI-H) and Deficient Mismatch Repair (dMMR) in Solid Tumors: A Structured Literature Review”, Journal of Oncology, vol. 2020, Article ID 1807929, 17 pages, 2020. https://doi.org/10.1155/2020/1807929
*Where permitted, Paige Colon MSI is for research use only (RUO), not for use in diagnostic procedures
**Internal study consisting of 50 MSI-H positive and 300 MSI-H negative patient data
