Detection of microsatellite instability (MSI) with a novel set of 7 Idylla biomarkers on colorectal cancer samples in a multi-center study

Craene, Bram De; Velde, Jan Van de; Bellon, Ellen; Gazin, Muriel; Rondelez, Evelien; Vandenbroeck, L.; Vanhoey, Thierry; Elsen, Natasja; Melchior, Linea Cecilie; Willemoe, Gro Linno; Watkin, Emmanuel; Arens, Norbert; Altmann, C.; Decanniere, Klaas; Sablon, Erwin; Maertens, Geert

doi:10.1093/annonc/mdy269.160

Cited by 3 publications

(2 citation statements)

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“…In contrast, the Idylla™ MSI assay’s software decision tree is fully automated, and therefore, results are not prone to subjective interpretation. A previous analysis of consecutive sections of 182 samples with three methodologies revealed a higher number of invalid results for the Promega MSI Analysis System (3.8%) and IHC (13.2%) compared with the prototype Idylla™ MSI assay (2.2%) [ 26 ]. As to interpretation strategies used for IHC results in the current study, the majority of the sites classified samples with at least one deficient marker as dMMR but two sites needed at least two deficient markers to do so.…”

Section: Discussionmentioning

confidence: 99%

Multi-center real-world comparison of the fully automated Idylla™ microsatellite instability assay with routine molecular methods and immunohistochemistry on formalin-fixed paraffin-embedded tissue of colorectal cancer

et al. 2020

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Microsatellite instability (MSI) is present in 15–20% of primary colorectal cancers. MSI status is assessed to detect Lynch syndrome, guide adjuvant chemotherapy, determine prognosis, and use as a companion test for checkpoint blockade inhibitors. Traditionally, MSI status is determined by immunohistochemistry or molecular methods. The Idylla™ MSI Assay is a fully automated molecular method (including automated result interpretation), using seven novel MSI biomarkers (ACVR2A, BTBD7, DIDO1, MRE11, RYR3, SEC31A, SULF2) and not requiring matched normal tissue. In this real-world global study, 44 clinical centers performed Idylla™ testing on a total of 1301 archived colorectal cancer formalin-fixed, paraffin-embedded (FFPE) tissue sections and compared Idylla™ results against available results from routine diagnostic testing in those sites. MSI mutations detected with the Idylla™ MSI Assay were equally distributed over the seven biomarkers, and 84.48% of the MSI-high samples had ≥ 5 mutated biomarkers, while 98.25% of the microsatellite-stable samples had zero mutated biomarkers. The concordance level between the Idylla™ MSI Assay and immunohistochemistry was 96.39% (988/1025); 17/37 discordant samples were found to be concordant when a third method was used. Compared with routine molecular methods, the concordance level was 98.01% (789/805); third-method analysis found concordance for 8/16 discordant samples. The failure rate of the Idylla™ MSI Assay (0.23%; 3/1301) was lower than that of referenced immunohistochemistry (4.37%; 47/1075) or molecular assays (0.86%; 7/812). In conclusion, lower failure rates and high concordance levels were found between the Idylla™ MSI Assay and routine tests.

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Section: Discussionmentioning

confidence: 99%

Multi-center real-world comparison of the fully automated Idylla™ microsatellite instability assay with routine molecular methods and immunohistochemistry on formalin-fixed paraffin-embedded tissue of colorectal cancer

et al. 2020

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“…Various commercial platforms are available for identifying actionable mutations in CRC such as Idylla or OncoBEAM, Idylla platform being used also for MSI detection ( 201 – 203 ). Vidal and colleagues ( 204 ) revealed a 93% overall agreement between the mutational status of RAS when comparing tissue and plasma samples.…”

Section: Liquid Biopsy In Colorectal Malignanciesmentioning

confidence: 99%

Liquid Biopsy and Artificial Intelligence as Tools to Detect Signatures of Colorectal Malignancies: A Modern Approach in Patient’s Stratification

et al. 2022

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Colorectal cancer (CRC) is the second most frequently diagnosed type of cancer and a major worldwide public health concern. Despite the global efforts in the development of modern therapeutic strategies, CRC prognosis is strongly correlated with the stage of the disease at diagnosis. Early detection of CRC has a huge impact in decreasing mortality while pre-lesion detection significantly reduces the incidence of the pathology. Even though the management of CRC patients is based on robust diagnostic methods such as serum tumor markers analysis, colonoscopy, histopathological analysis of tumor tissue, and imaging methods (computer tomography or magnetic resonance), these strategies still have many limitations and do not fully satisfy clinical needs due to their lack of sensitivity and/or specificity. Therefore, improvements of the current practice would substantially impact the management of CRC patients. In this view, liquid biopsy is a promising approach that could help clinicians screen for disease, stratify patients to the best treatment, and monitor treatment response and resistance mechanisms in the tumor in a regular and minimally invasive manner. Liquid biopsies allow the detection and analysis of different tumor-derived circulating markers such as cell-free nucleic acids (cfNA), circulating tumor cells (CTCs), and extracellular vesicles (EVs) in the bloodstream. The major advantage of this approach is its ability to trace and monitor the molecular profile of the patient’s tumor and to predict personalized treatment in real-time. On the other hand, the prospective use of artificial intelligence (AI) in medicine holds great promise in oncology, for the diagnosis, treatment, and prognosis prediction of disease. AI has two main branches in the medical field: (i) a virtual branch that includes medical imaging, clinical assisted diagnosis, and treatment, as well as drug research, and (ii) a physical branch that includes surgical robots. This review summarizes findings relevant to liquid biopsy and AI in CRC for better management and stratification of CRC patients.

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Idylla microsatellite instability assay versus mismatch repair immunohistochemistry: a retrospective comparison in gastric adenocarcinoma

2020

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Up to 22% of all gastric adenocarcinomas are of the microsatellite instability (MSI) subtype. This subtype may not benefit from conventional adjuvant chemotherapy but does respond to novel immunotherapies. A proportion of MSI gastric adenocarcinomas are associated with inherited disease, inferring an opportunity to screen for further cancers in the patient while also identifying at-risk relatives. Although the importance of MSI subtyping is clear, the methods of detection vary. The main techniques are MSI testing and mismatch repair (MMR) immunohistochemistry (IHC). This study compares a novel Idylla (Biocartis) MSI assay to MMR IHC across 50 biopsies of gastric adenocarcinoma. The methods were concordant across 48 cases. The two discrepant results demonstrated known difficulties in the interpretation of IHC. Idylla MSI testing presents several advantages over MMR IHC but both methods are well established in detecting this subtype of gastric adenocarcinoma. The methods are best regarded as complementary tests, performing most optimally when combined.

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Detection of microsatellite instability (MSI) with a novel set of 7 Idylla biomarkers on colorectal cancer samples in a multi-center study

Cited by 3 publications

References 0 publications

Multi-center real-world comparison of the fully automated Idylla™ microsatellite instability assay with routine molecular methods and immunohistochemistry on formalin-fixed paraffin-embedded tissue of colorectal cancer

Multi-center real-world comparison of the fully automated Idylla™ microsatellite instability assay with routine molecular methods and immunohistochemistry on formalin-fixed paraffin-embedded tissue of colorectal cancer

Liquid Biopsy and Artificial Intelligence as Tools to Detect Signatures of Colorectal Malignancies: A Modern Approach in Patient’s Stratification

Idylla microsatellite instability assay versus mismatch repair immunohistochemistry: a retrospective comparison in gastric adenocarcinoma

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