A robust method for the rapid detection of microsatellite instability in colorectal cancer

Performance assessment of computational tools to detect microsatellite instability

Microsatellite instability (MSI) is a phenomenon seen in several cancer types, which can be used as a biomarker to help guide immune checkpoint inhibitor treatment. To facilitate this, researchers have developed computational tools to categorize samples as having high microsatellite instability, or as being microsatellite stable using next-generation sequencing data. Most of these tools were published with unclear scope and usage, and they have yet to be independently benchmarked. To address these issues, we assessed the performance of eight leading MSI tools across several unique datasets that encompass a wide variety of sequencing methods. While we were able to replicate the original findings of each tool on whole exome sequencing data, most tools had worse receiver operating characteristic and precision-recall area under the curve values on whole genome sequencing data. We also found that they lacked agreement with one another and with commercial MSI software on gene panel data, and that optimal threshold cut-offs vary by sequencing type. Lastly, we tested tools made specifically for RNA sequencing data and found they were outperformed by tools designed for use with DNA sequencing data. Out of all, two tools (MSIsensor2, MANTIS) performed well across nearly all datasets, but when all datasets were combined, their precision decreased. Our results caution that MSI tools can have much lower performance on datasets other than those on which they were originally evaluated, and in the case of RNA sequencing tools, can even perform poorly on the type of data for which they were created.

An Innovative and Accurate Next-Generation Sequencing-Based Microsatellite Instability Detection Method for Colorectal and Endometrial Tumors

The detection of microsatellite instability (MSI) and mismatch repair (MMR) deficiency has become mandatory for most tumors in recent years, owing to the development of immune checkpoint inhibitors as a highly effective therapy for MMR deficiency/MSI tumors. The timely and efficient detection of MSI is valuable, and new methods are increasingly being developed. To date, MMR assessment has been performed using immunohistochemistry of the 4 MMR proteins and/or microsatellite stability/MSI using PCR, mostly using the pentaplex panel. The implementation of next-generation sequencing (NGS) for MSI analysis would improve the effectiveness at a lower cost and in less time. This study describes the development of 8 new microsatellites combined with a classification algorithm, termed "Octaplex CaBio-MSID" (for Cancérologie Biologique MSI Detection tool), to assess MSI using NGS. A series of 303 colorectal cancer and 88 endometrial cancer samples were assessed via MSI testing using NGS using the Octaplex CaBio-MSID algorithm. The sensitivity and specificity of Octaplex CaBio-MSID were 98.4% and 98.4% for colorectal cancers, and 89.3% and 100% for endometrial cancers, respectively. This new NGS-based MSI detection method outperforms previously published methods (ie, Idylla [Biocartis], OncoMate MSI Dx [Promega], and Foundation One CDx [Roche Foundation Medicine]). Although highly efficient, Octaplex CaBio-MSID requires validation in a larger independent series of different tumor types.

Detecting Microsatellite Instability in Endometrial, Colon, and Stomach Cancers Using Targeted NGS

PURPOSE

To develop a method for testing the MSI based on targeted NGS.

METHODS

Based on the results of previous studies, 81 microsatellite loci with high variability in MSI-H tumors were selected, and a method for calculating the MSI score was developed. Using the MSI score, we defined the MSI status in endometral (162), colon (153), and stomach (190) cancers. Accuracy of the MSI scores was evaluated by comparison with MMR immunohistochemistry for 137 endometrium (63 dMMR and 74 pMMR), 76 colon (29 dMMR and 47 pMMR), and 81 stomach (8 dMMR and 73 pMMR) cancers.

RESULTS

Classification of MSS and MSI-H tumors was performed with AUC (0.99), sensitivity (92%), and specificity (98%) for all tumors without division into types. The accuracy of MSI testing in endometrial cancer was lower than for stomach and colon cancer (0.98, 87%, and 100%, respectively). The use of 27 loci only, the most informative for endometrial cancer, increased the overall accuracy (1.00, 99%, and 99%). Comparison of MSI score values in 505 tumors showed that MSI score is significantly higher in colon (p < 10-5) and stomach (p = 0.008) cancer compared with endometrial cancer.

CONCLUSION

The MSI score accurately determines MSI status for endometrial, colon, and stomach cancers and can be used to quantify the degree of MSI.

Microsatellite instability assessment is instrumental for Predictive, Preventive and Personalised Medicine: status quo and outlook

A form of genomic alteration called microsatellite instability (MSI) occurs in a class of tandem repeats (TRs) called microsatellites (MSs) or short tandem repeats (STRs) due to the failure of a post-replicative DNA mismatch repair (MMR) system. Traditionally, the strategies for determining MSI events have been low-throughput procedures that typically require assessment of tumours as well as healthy samples. On the other hand, recent large-scale pan-tumour studies have consistently highlighted the potential of massively parallel sequencing (MPS) on the MSI scale. As a result of recent innovations, minimally invasive methods show a high potential to be integrated into the clinical routine and delivery of adapted medical care to all patients. Along with advances in sequencing technologies and their ever-increasing cost-effectiveness, they may bring about a new era of Predictive, Preventive and Personalised Medicine (3PM). In this paper, we offered a comprehensive analysis of high-throughput strategies and computational tools for the calling and assessment of MSI events, including whole-genome, whole-exome and targeted sequencing approaches. We also discussed in detail the detection of MSI status by current MPS blood-based methods and we hypothesised how they may contribute to the shift from conventional medicine to predictive diagnosis, targeted prevention and personalised medical services. Increasing the efficacy of patient stratification based on MSI status is crucial for tailored decision-making. Contextually, this paper highlights drawbacks both at the technical level and those embedded deeper in cellular/molecular processes and future applications in routine clinical testing.

Sensitive detection of microsatellite instability in tissues and liquid biopsies: Recent developments and updates

Microsatellite instability (MSI), a phenotype displayed as deletions/insertions of repetitive genomic sequences, has drawn great attention due to its application in cancer including diagnosis, prognosis and immunotherapy response prediction. Several methods have been developed for the detection of MSI, facilitating the MSI classification of cancer patients. In view of recent interest in minimally-invasive detection of MSI via liquid biopsy samples, which requires methods with high sensitivity to identify small fractions of altered DNA in the presence of large amount of wild type copies, sensitive MSI detection approaches are emerging. Here we review the available MSI detection methods and their detection limits and focus on recently developed next-generation-sequencing based approaches and bioinformatics algorithms available for MSI analysis in various cancer types.

MEM: An Algorithm for the Reliable Detection of Microsatellite Instability (MSI) on a Small NGS Panel in Colorectal Cancer

Simple Summary

Microsatellite instability (MSI) assessment has become a major issue in the management of colorectal cancer, with the recent approval of anti-PD1 immunotherapies in MSI-metastatic colorectal cancer. The reference PCR method (MSI-PCR) can be costly, time and tissue-consuming. However, NGS could facilitate the assessment of MSI status while simultaneously screening for targetable oncogenic mutations (KRAS, NRAS, BRAF) for any colorectal cancer, but the algorithms developed to date use a large number of microsatellites that have not been approved by international guidelines and which are generally incompatible with small NGS panels. We present the MEM algorithm, which mimics the interpretation of MSI-PCR data by a human operator to reliably assess MSI status using only five validated microsatellites (BAT-25, BAT-26, NR-21, NR-24 and NR-27). We demonstrated that the MEM algorithm was in perfect agreement with MSI-PCR results, in terms of both MSI status and individual microsatellite status, in a cohort of 146 patients.

Abstract

Purpose: MEM is an NGS algorithm that uses Expectation-Maximisation to detect the presence of unstable alleles from the NGS sequences of five microsatellites (BAT-25, BAT-26, NR-21, NR-24 and NR-27). The purpose of this study was to compare the MEM algorithm with a reference PCR method (MSI-PCR) and MisMatch Repair protein immunohistochemistry (MMR-IHC). Methods: FFPE colorectal cancer samples from 146 patients were analysed in parallel by MSI-PCR and NGS using the MEM algorithm. MMR-IHC results were available for 133 samples. Serial dilutions of an MSI positive control were performed to estimate the limit of detection. Results: the MEM algorithm was able to detect unstable alleles of each microsatellite with up to a 5% allelic fraction. Of the 146 samples, 28 (19.2%) were MSI in MSI-PCR. MEM algorithm results were in perfect agreement with those of MSI-PCR, at both MSI status and individual microsatellite level (Cohen’s kappa = 1). A high level of agreement was noted between MSI-PCR/MEM algorithm results and MMR-IHC results (Cohen’s kappa = 0.931). Conclusion: the MEM algorithm can determine the MSI status of colorectal cancer samples on a small NGS panel, using only five microsatellites approved by international guidelines, and can be combined with screening for targetable mutations.

Detection of Microsatellite Instability: State of the Art and Future Applications in Circulating Tumour DNA (ctDNA)

Simple Summary

Microsatellite instability (MSI) is a molecular fingerprint for defects in the mismatch repair system (dMMR) and is associated with higher risks of cancers. MSI/dMMR tumours are characterized by the accumulation of mutations throughout the genome, and particularly in microsatellite (MS) DNA repeat sequences. MSI stands as a major biomarker for familial cancer risk assessment, cancer prognosis, and therapeutic choices. Standard-of-care classification of MSI/dMMR tumours is most frequently achieved using immunohistochemistry or PCR-based assay directed against a set of five MS regions. However, novel molecular methods based on tumour tissue or plasma samples have been developed and could enter in the future trends of MSI testing. Here, we provide insights into these emerging approaches and discuss their advantages and limitations.

Abstract

Microsatellite instability (MSI) is a molecular scar resulting from a defective mismatch repair system (dMMR) and associated with various malignancies. MSI tumours are characterized by the accumulation of mutations throughout the genome and particularly clustered in highly repetitive microsatellite (MS) regions. MSI/dMMR status is routinely assessed in solid tumours for the initial screening of Lynch syndrome, the evaluation of cancer prognosis, and treatment decision-making. Currently, pentaplex PCR-based methods and MMR immunohistochemistry on tumour tissue samples are the standard diagnostic methods for MSI/dMMR. Other tissue methods such as next-generation sequencing or real-time PCR-based systems have emerged and represent viable alternatives to standard MSI testing in specific settings. The evolution of the standard molecular techniques has offered the opportunity to extend MSI determination to liquid biopsy based on the analysis of cell-free DNA (cfDNA) in plasma. This review aims at synthetizing the standard and emerging techniques used on tumour tissue samples for MSI/dMMR determination. We also provide insights into the MSI molecular techniques compatible with liquid biopsy and the potential clinical consequences for patients with solid cancers.

Managing Difficulties of Microsatellite Instability Testing in Endometrial Cancer-Limitations and Advantages of Four Different PCR-Based Approaches

Microsatellite instability (MSI), a common alteration in endometrial cancers (EC) is known as a biomarker for immune checkpoint therapy response alongside screening for Lynch Syndrome (LS). However, former studies described challenging MSI profiles in EC hindering analysis by using MSI testing methods intensively validated for colorectal cancer (CRC) only. In order to reduce false negatives, this study examined four different PCR-based approaches for MSI testing using 25 EC samples already tested for mismatch repair deficiency (dMMR). In a follow up validation set of 75 EC samples previously tested both for MMR and MSI, the efficiency of a seven-marker system corresponding to the Idylla system was further analyzed. Both Bethesda and Promega marker panels require trained operators to overcome interpretation complexities caused by either hardly visible additional peaks of one and two nucleotides, or small shifts in microsatellite repeat length. Using parallel sequencing adjustment of bioinformatics is needed. Applying the Idylla MSI assay, an evaluation of input material is more crucial for reliable results and is indispensable. Following MMR deficiency testing as a first-line screening procedure, additional testing with a PCR-based method is necessary if inconclusive staining of immunohistochemistry (IHC) must be clarified.