Evaluating mismatch repair deficiency for solid tumor immunotherapy eligibility: immunohistochemistry versus microsatellite molecular testing

Recent developments in immunotherapy for gastrointestinal tract cancers

The past few decades have witnessed the rise of immunotherapy for Gastrointestinal (GI) tract cancers. The role of immune checkpoint inhibitors (ICIs), particularly programmed death protein 1 (PD-1) and PD ligand-1 antibodies, has become increasingly pivotal in the treatment of advanced and perioperative GI tract cancers. Currently, anti-PD-1 plus chemotherapy is considered as first-line regimen for unselected advanced gastric/gastroesophageal junction adenocarcinoma (G/GEJC), mismatch repair deficient (dMMR)/microsatellite instability-high (MSI-H) colorectal cancer (CRC), and advanced esophageal cancer (EC). In addition, the encouraging performance of claudin18.2-redirected chimeric antigen receptor T-cell (CAR-T) therapy in later-line GI tract cancers brings new hope for cell therapy in solid tumour treatment. Nevertheless, immunotherapy for GI tumour remains yet precise, and researchers are dedicated to further maximising and optimising the efficacy. This review summarises the important research, latest progress, and future directions of immunotherapy for GI tract cancers including EC, G/GEJC, and CRC.

Characterization of discordance between mismatch repair deficiency and microsatellite instability testing may prevent inappropriate treatment with immunotherapy

In the Drug Rediscovery Protocol (DRUP), patients with cancer are treated based on their tumor molecular profile with approved targeted and immunotherapies outside the labeled indication. Importantly, patients undergo a tumor biopsy for whole-genome sequencing (WGS) which allows for a WGS-based evaluation of routine diagnostics. Notably, we observed that not all biopsies of patients with dMMR/MSI-positive tumors as determined by routine diagnostics were classified as microsatellite-unstable by subsequent WGS. Therefore, we aimed to evaluate the discordance rate between routine dMMR/MSI diagnostics and WGS and to further characterize discordant cases. We assessed patients enrolled in DRUP with dMMR/MSI-positive tumors identified by routine diagnostics, who were treated with immune checkpoint blockade (ICB) and for whom WGS data were available. Patient and tumor characteristics, study treatment outcomes, and material from routine care were retrieved from the patient medical records and via Palga (the Dutch Pathology Registry), and were compared with WGS results. Initially, discordance between routine dMMR/MSI diagnostics and WGS was observed in 13 patients (13/121; 11%). The majority of these patients did not benefit from ICB (11/13; 85%). After further characterization, we found that in six patients (5%) discordance was caused by dMMR tumors that did not harbor an MSI molecular phenotype by WGS. In six patients (5%), discordance was false due to the presence of multiple primary tumors (n = 3, 2%) and misdiagnosis of dMMR status by immunohistochemistry (n = 3, 2%). In one patient (1%), the exact underlying cause of discordance could not be identified. Thus, in this group of patients limited to those initially diagnosed with dMMR/MSI tumors by current routine diagnostics, the true assay-based discordance rate between routine dMMR/MSI-positive diagnostics and WGS was 5%. To prevent inappropriate ICB treatment, clinicians and pathologists should be aware of the risk of multiple primary tumors and the limitations of different tests. © 2024 The Pathological Society of Great Britain and Ireland.

Liquid biopsy for human cancer: cancer screening, monitoring, and treatment

Currently, tumor treatment modalities such as immunotherapy and targeted therapy have more stringent requirements for obtaining tumor growth information and require more accurate and easy-to-operate tumor information detection methods. Compared with traditional tissue biopsy, liquid biopsy is a novel, minimally invasive, real-time detection tool for detecting information directly or indirectly released by tumors in human body fluids, which is more suitable for the requirements of new tumor treatment modalities. Liquid biopsy has not been widely used in clinical practice, and there are fewer reviews of related clinical applications. This review summarizes the clinical applications of liquid biopsy components (e.g., circulating tumor cells, circulating tumor DNA, extracellular vesicles, etc.) in tumorigenesis and progression. This includes the development process and detection techniques of liquid biopsies, early screening of tumors, tumor growth detection, and guiding therapeutic strategies (liquid biopsy-based personalized medicine and prediction of treatment response). Finally, the current challenges and future directions for clinical applications of liquid biopsy are proposed. In sum, this review will inspire more researchers to use liquid biopsy technology to promote the realization of individualized therapy, improve the efficacy of tumor therapy, and provide better therapeutic options for tumor patients.

Evaluation of mismatch-repair and microsatellite-instability status in a Chinese colorectal cancer Cohort

BACKGROUND

Immunohistochemistry (IHC) and traditional polymerase chain reaction (PCR) are the methods of choice in clinical practice to identify the mismatch repair (MMR) and microsatellite instability (MSI) status in colorectal cancer (CRC). In some previous researches, the concordance rate between two methods was different and discordance existed in about 1 %-9.7 %.

METHODS

We retrospectively reviewed 406 patients received surgical CRC resections and tests of both MMR IHC and MSI PCR from January 2019 to April 2022 in Shanghai Changzheng Hospital. The incidence of deficient mismatch repair (dMMR) or microsatellite instability-high (MSI-H) CRCs, the concordance rate between two methods, and the reasons for discordant results were evaluated with clinicopathological data, immunochemical staining, whole-exome sequencing, and MLH1 methylation analysis.

RESULTS

Among 406 patients, the incidence of MSI-H CRCs was 7.88 %. Nearly a quarter of the cases under reexamination of IHC was initial misinterpreted. Besides, the concordance rate between MMR IHC and MSI PCR was 99.26 % (401 of 404) and the Kappa value was 0.945 (p < 0.001). Finally, some somatic variants of MMR and POLE genes which may explain the discordance were identified.

CONCLUSION

The incidence rate of MSI-H in Chinese patients with CRC might be relatively low owing to tumor location. Although MSI and IHC analyses are highly concordant, both MMR IHC and MSI PCR tests should be simultaneously performed and MMR IHC should be interpreted by experienced pathologists. In the future, further studies on discordant results should be carried out to improve the personalized management of CRC.

A retrospective study of consistency between immunohistochemistry and polymerase chain reaction of microsatellite instability in endometrial cancer

Objectives

Identification of endometrial cancers (EC) with mismatch repair deficiency (dMMR) or microsatellite instability-high (MSI-H) is essential for Lynch syndrome screening and treatment stratification. We aimed to assess the utility of immunohistochemistry (IHC) staining for MMR protein expression and polymerase chain reaction (PCR)-based MSI assays in EC and the correlation between MMR/MSI status and various clinicopathological parameters.

Methods

We reviewed the clinical and pathological information of 333 patients with EC. MMR protein expression was assessed as retained or lost to determine MMR status by IHC staining, and MSI status was identified by PCR capillary electrophoresis (PCR-CE) testing with a National Cancer Institute (NCI) panel. The correlation of MMR/MSI status with clinicopathological features was determined by statistical analysis. Discrepant results were further analyzed using an alternative PCR-CE MSI (Promega panel) method, MLH1 promoter methylation assays, and next-generation sequencing (NGS).

Results

Among the EC patients, the overall percentage of dMMR was 25.2%, and the overall percentage of MSI-H was 24%. Among the dMMR patients, 50 (59.5%) showed loss of MLH1 and PMS2 expression, 19 (22.6%) loss of MSH2 and MSH6 expression, and seven (8.3%) and eight (9.5%) loss of PMS2 and MSH6 expression, respectively. The dMMR subgroup was significantly younger than the pMMR subgroup, especially for <60-years-old patients (p = 0.038). In addition, we identified a strong correlation between MMR/MSI status and high-grade endometrioid or nonendometrioid components (p = 0.004 or p = 0.003). IHC staining and PCR-CE assay results showed a high level of overall concordance (98.8%, Cohen's κ = 0.98). Four patients were found to have dMRR/MSS in both examinations. We reanalyzed them with additional methods. One case showed MLH1 promotor methylation, and the other three cases harbored MSH6 germline pathogenic variations. One of the cases with MSH6 deficiency was reanalyzed as MSI-H by alternative PCR-CE assay or NGS testing.

Conclusions

This study indicates that the combined use of MMR-IHC and PCR-CE MSI analyses may effectively avoid misdiagnoses of EC patients with dMMR/MSI-H. However, use of PCR-CE alone to evaluate MMR/MSI status may lead to missed diagnosis, especially for EC patients with MSH6 deficiency and presenting MSS.

DNA Damage Repair Pathways in Prostate Cancer: A Narrative Review of Molecular Mechanisms, Emerging Biomarkers and Therapeutic Targets in Precision Oncology

Prostate cancer (PCa) has a distinct molecular signature, including characteristic chromosomal translocations, gene deletions and defective DNA damage repair mechanisms. One crucial pathway involved is homologous recombination deficiency (HRD) and it is found in almost 20% of metastatic castrate-resistant PCa (mCRPC). Inherited/germline mutations are associated with a hereditary predisposition to early PCa development and aggressive behavior. BRCA2, ATM and CHECK2 are the most frequently HRD-mutated genes. BRCA2-mutated tumors have unfavorable clinical and pathological characteristics, such as intraductal carcinoma. PARP inhibitors, due to the induction of synthetic lethality, have been therapeutically approved for mCRPC with HRD alterations. Mutations are detected in metastatic tissue, while a liquid biopsy is utilized during follow-up, recognizing acquired resistance mechanisms. The mismatch repair (MMR) pathway is another DNA repair mechanism implicated in carcinogenesis, although only 5% of metastatic PCa is affected. It is associated with aggressive disease. PD-1 inhibitors have been used in MMR-deficient tumors; thus, the MMR status should be tested in all metastatic PCa cases. A surrogate marker of defective DNA repair mechanisms is the tumor mutational burden. PDL-1 expression and intratumoral lymphocytes have ambivalent predictive value. Few experimental molecules have been so far proposed as potential biomarkers. Future research may further elucidate the role of DNA damage pathways in PCa, revealing new therapeutic targets and predictive biomarkers.

Locally advanced rectal cancer with dMMR/MSI-H may be excused from surgery after neoadjuvant anti-PD-1 monotherapy: a multiple-center, cohort study

Objective

Examine patients with locally advanced rectal cancer (LARC) with deficient mismatch repair (dMMR) or microsatellite instability-high (MSI-H) who received neoadjuvant immunotherapy (nIT), and compare the outcomes of those who chose a watch-and-wait (WW) approach after achieving clinical complete response (cCR) or near-cCR with those who underwent surgery and were confirmed as pathological complete response (pCR).

Methods

LARC patients with dMMR/MSI-H who received nIT were retrospectively examined. The endpoints were 2-year overall survival (OS), 2-year disease-free survival (DFS), local recurrence (LR), and distant metastasis (DM). The efficacy of programmed cell death protein-1 (PD-1) inhibitor, immune-related adverse events (irAEs), surgery-related adverse events (srAEs), and enterostomy were also recorded.

Results

Twenty patients who received a PD-1 inhibitor as initial nIT were examined. Eighteen patients (90%) achieved complete response (CR) after a median of 7 nIT cycles, including 11 with pCR after surgery (pCR group), and 7 chose a WW strategy after evaluation as cCR or near-cCR (WW group). Both groups had median follow-up times of 25.0 months. Neither group had a case of LR or DM, and the 2-year DFS and OS in each group was 100%. The two groups had similar incidences of irAEs (P=0.627). In the pCR group, however, 2 patients (18.2%) had permanent colostomy, 3 (27.3%) had temporary ileostomy, and 2 (18.2%) had srAEs.

Conclusion

Neoadjuvant PD-1 blockade had high efficacy and led to a high rate of CR in LARC patients with dMMR/MSI-H. A WW strategy appears to be a safe and reliable option for these patients who achieve cCR or near-cCR after nIT.

Deep learning-based methods for classification of microsatellite instability in endometrial cancer from HE-stained pathological images

BACKGROUND

Microsatellite instability (MSI) is one of the essential tumor biomarkers for cancer treatment and prognosis. The presence of more significant PD-L1 expression on the surface of tumor cells in endometrial cancer with MSI suggests that MSI may be a promising biomarker for anti-PD-1/PD-L1 immunotherapy. However, the conventional testing methods are labor-intensive and expensive for patients.

METHODS

Inspired by classifiers for MSI based on fast and low-cost deep-learning methods in previous investigations, a new architecture for MSI classification based on an attention module is proposed to extract features from pathological images. Especially, slide-level microsatellite status will be obtained by the bag of words method to aggregate probabilities predicted by the proposed model. The H&E-stained whole slide images (WSIs) from The Cancer Genome Atlas endometrial cohort are collected as the dataset. The performances of the proposed model were primarily evaluated by the area under the receiver-operating characteristic curve, accuracy, sensitivity, and F1-Score.

RESULTS

On the randomly divided test dataset, the proposed model achieved an accuracy of 0.80, a sensitivity of 0.857, a F1-Score of 0.826, and an AUROC of 0.799. We then visualize the results of the microsatellite status classification to capture more specific morphological features, helping pathologists better understand how deep learning performs the classification.

CONCLUSIONS

This study implements the prediction of microsatellite status in endometrial cancer cases using deep-learning methods directly from H&E-stained WSIs. The proposed architecture can help the model capture more valuable features for classification. In contrast to current laboratory testing methods, the proposed model creates a more convenient screening tool for rapid automated testing for patients. This method can potentially be a clinical method for detecting the microsatellite status of endometrial cancer.

Artificial Intelligence for Predicting Microsatellite Instability Based on Tumor Histomorphology: A Systematic Review

Microsatellite instability (MSI)/defective DNA mismatch repair (dMMR) is receiving more attention as a biomarker for eligibility for immune checkpoint inhibitors in advanced diseases. However, due to high costs and resource limitations, MSI/dMMR testing is not widely performed. Some attempts are in progress to predict MSI/dMMR status through histomorphological features on H&E slides using artificial intelligence (AI) technology. In this study, the potential predictive role of this new methodology was reviewed through a systematic review. Studies up to September 2021 were searched through PubMed and Embase database searches. The design and results of each study were summarized, and the risk of bias for each study was evaluated. For colorectal cancer, AI-based systems showed excellent performance with the highest standard of 0.972; for gastric and endometrial cancers they showed a relatively low but satisfactory performance, with the highest standard of 0.81 and 0.82, respectively. However, analyzing the risk of bias, most studies were evaluated at high-risk. AI-based systems showed a high potential in predicting the MSI/dMMR status of different cancer types, and particularly of colorectal cancers. Therefore, a confirmation test should be required only for the results that are positive in the AI test.

xDEEP-MSI: Explainable Bias-Rejecting Microsatellite Instability Deep Learning System in Colorectal Cancer

The prediction of microsatellite instability (MSI) using deep learning (DL) techniques could have significant benefits, including reducing cost and increasing MSI testing of colorectal cancer (CRC) patients. Nonetheless, batch effects or systematic biases are not well characterized in digital histology models and lead to overoptimistic estimates of model performance. Methods to not only palliate but to directly abrogate biases are needed. We present a multiple bias rejecting DL system based on adversarial networks for the prediction of MSI in CRC from tissue microarrays (TMAs), trained and validated in 1788 patients from EPICOLON and HGUA. The system consists of an end-to-end image preprocessing module that tile samples at multiple magnifications and a tissue classification module linked to the bias-rejecting MSI predictor. We detected three biases associated with the learned representations of a baseline model: the project of origin of samples, the patient's spot and the TMA glass where each spot was placed. The system was trained to directly avoid learning the batch effects of those variables. The learned features from the bias-ablated model achieved maximum discriminative power with respect to the task and minimal statistical mean dependence with the biases. The impact of different magnifications, types of tissues and the model performance at tile vs patient level is analyzed. The AUC at tile level, and including all three selected tissues (tumor epithelium, mucin and lymphocytic regions) and 4 magnifications, was 0.87 ± 0.03 and increased to 0.9 ± 0.03 at patient level. To the best of our knowledge, this is the first work that incorporates a multiple bias ablation technique at the DL architecture in digital pathology, and the first using TMAs for the MSI prediction task.