Maxim Ivanov

MGI platforms hold promise to become a widespread instrument for various clinical next-generation sequencing applications, from whole genome sequencing to COVID-19 genotyping. However, in the clinical oncology setting it is still restricted to large panel sequencing limiting capacity for routine biomarker screening. In this article, we describe our experience of tailoring amplicon-based library construction for the MGI platform. Illumina compatible reagents served as a prototype in order to introduce platform specific adapters. Elaborated reagent kits were used for BRCA1/2 or 34 oncogenes testing both with whole blood and FFPE-derived DNA. Our data show that amplicon-based DNBSEQ-tailored library preparation demonstrates sufficient analytical efficiency in terms of coverage uniformity (average MAPD 1.08 and 1.19 for ABC plus and Atlas plus panels) and amplicon drop-out rate (ranging from 0.3% to 2.5%). Additionally, it shows efficiency in terms of single sample sensitivity, maintaining 99% sensitivity compared to 99% for the Illumina prototype. We show that it also outreaches expected diagnostic parameters of MGI exome sequencing (99% vs 95% for WES). Per-amplicon coverage of sticky-end libraries sequenced on Illumina and MGI were highly correlated demonstrating that the platform itself does not introduce any bias to amplicon coverage. Across three tested variations of library preparation protocol, discordances were related to ligation mix component composition and resulted in underrepresentation of GC-low and GC-high amplicons and low uniformity as a result. Overall, we outline the successful adaptation of PCR-based library preparation for MGI signifying the importance of tailoring component composition of reagent kit for uniform coverage.

MSI is a crucial biomarker for selecting CRC patients for immunotherapy. Here, we analyze the first results from the observational prospective trial BLOOMSI (NCT06414304), which investigated the impact of MSI/dMMR testing methods and baseline tumor heterogeneity on treatment outcomes. Thirty MSI/dMMR+ CRC patients, who were candidates for immunotherapy, were enrolled. Depending on the local test used for MSI/dMMR, central PCR/IHC was performed. Baseline FFPE and liquid biopsy (LB) were analyzed with NGS. ORR (objective response rate) in the ITT population was 50% (95% CI, 31.3–68.7%). Concordance between local/central dMMR/MSI testing was 81%, and the concordance of IHC, PCR, NGS/FFPE, and NGS/LB was 68.4%. The ORR was similar for IHC+, PCR+, NGS/FFPE+, and NGS/LB+ patients (55.6%, 55.6%, 55%, and 57.9%, respectively). The ORR among patients with discordant IHC/PCR results was 0%, and the ORR among patients with NGS/LB-ORR was 25% (2/8 CR). Next, we performed quantitative MSI analysis, reflecting the clonality of MSI+ tumor cells. Multivariate analysis identified MSI clonality in FFPE (HR 0.63, 95% CI, 0.39–0.99, p = 0.0487) and LB (HR 3.05, 95% CI, 2.01–4.65, p < 0.00001) as independent predictors of progression. The ORR in patients with high clonality (≥7%, n = 4, NGS/LB) was 25%. We describe baseline methodological predictors of non-response to immunotherapy and propose a strategy for selecting potential non-responders. These findings warrant further investigation.

Background: Next‐generation sequencing (NGS) is increasingly integrated into cancer patient management, necessitating cost‐effective, reliable tests for companion diagnostics. We present the validation of the Solo‐test Driver panel, a custom NGS amplicon‐based tool for DNA analysis of 34 oncogenes, addressing key clinical needs.Methods: The panel's performance was validated for detecting SNVs, CNVs, and MSI. Analytical validation used 182 samples, while clinical validation involved 130 samples, both encompassing diverse tumor types and specimen formats.Results: The Solo‐test Driver panel has the potential to identify an additional 18.3%, 16.5%, and 8.7% of RAS+ colorectal, PIK3CA+ breast, and EGFR+ lung cancer patients, respectively, when compared to FDA‐approved PCR tests. Analytical validation demonstrated high intra‐lab robustness (coefficient of variation of coverage uniformity 6.4%) and high inter‐lab robustness (PCC of per‐amplicon coverage 0.82, 0.84, 0.9 for three different labs). Estimated in silico sensitivity was 100% for detecting clinically actionable SNVs at 250x, corresponding to only 60,000 read pairs per sample. In vitro mixing experiments determined LoD starting from 3.3% VAF. Estimated in silico LoD ranged from 0.5% to 5% at 1000× (1% to 5% at 650x). Clinical validation demonstrated PPA/NPA of 100%/80%, 95%/100%, and 100%/100% for detecting MSI, SNVs, and CNVs, respectively.Conclusions: The Solo‐test Driver panel offers a reliable, cost‐effective solution for detecting somatic alterations and genomic signatures, making it suitable for routine companion diagnostics in solid tumors.

Molecular genetic profiling of solid tumors by next generation sequencing (NGS) is widely used to select targeted therapy. At the same time, with rare exceptions, NGS has not proven to be a reliable tool for differential diagnosis of diseases. However, some types of tumors have specific somatic mutations, and their detection can serve as a reason for clarifying the diagnosis using standard methods. An example of such mutations are specific abnormalities in the EGFR gene, which occur exclusively in lung cancer. In the described clinical case, the patient was diagnosed with skin adenocarcinoma. Molecular genetic profiling revealed an EGFR exon 19 deletion mutation, which served as a reason for additional histological studies and revision of the diagnosis in favor of lung adenocarcinoma, and demonstrates the possibility of using the results of molecular profiling as an auxiliary method for differentiating cancer subtypes.

Molecular genetic profiling of solid tumors by next-generation sequencing (NGS) is widely used to select targeted therapy. At the same time, with rare exceptions, NGS has not proven to be a reliable tool for differential diagnosis of diseases. However, some types of tumors have specific somatic mutations, and their detection can serve as a reason for clarifying the diagnosis using standard methods. An example of such mutations are specific abnormalities in the EGFR gene, which occur exclusively in lung cancer. In the described clinical case, the patient was diagnosed with skin adenocarcinoma. Molecular genetic profiling revealed an EGFR exon 19 deletion mutation, which served as a reason for additional histological studies and revision of the diagnosis in favor of lung adenocarcinoma, and demonstrates the possibility of using the results of molecular profiling as an auxiliary method for differentiating cancer subtypes.

Introduction. Currently in routine clinical practice, standard methods based on polymerase chain reaction (PCR) and immunohistochemical examination are used to determine microsatellite instability (MSI) and deficient mismatch repair system (dMMR). MSI identification using high-throughput sequencing (next generation sequencing, NGS) is of special interest because it allows to analyze a large number of microsatellites and simultaneously study alterations in therapeutically significant genes.Aim. To validate of amplicon-based NGS panel for analysis of MSI and alterations in clinically significant genes in colorectal cancer.Materials and methods. High-throughput sequencing for MSI analysis was performed on formalin-fixed paraffinembedded (FFPE) samples from patients with colorectal cancer of any stage using amplicon-based panel “Solo-test Driver” (Russia) which covers 38 genes and 39 short tandem repeats (mononucleotides). As a reference method, 5-loci (BAT25, BAT26, NR21, NR24 and NR27) PCR was used. In NGS, MSI was evaluated based on κmer distribution. Statistical analysis was performed using Cohen’s kappa (κ), Mann-Whitney u test, and Fisher’s exact test.Results. An amplicon-based NGS panel for analysis of MSI in 39 loci and alterations in 39 genes was developed and validated on 160 archival FFPE samples of colorectal cancer. Per PCR, 42 (26.25 %) samples were MSI-positive, 118 (73.75 %) were MSI-negative. The results of PCR and NGS were concordant in 98.75 % (158/160) cases.Conclusion. The κ coefficient was 0.97 which demonstrates high concordance of MSI analyses using PCR and the developed NGS-based assay system.

Analysis of serial liquid biopsy (LB) samples has been found to be a promising approach for the monitoring of tumor dynamics in the course of therapy for patients with colorectal cancer (CRC). Currently, somatic mutations are used for tracing the dynamics of the tumor via LB. However, the analysis of the dynamic changes in the molecular signatures such as microsatellite instability (MSI) is not currently used. We hypothesized that changes in blood MSI burden (bMSI) could be registered using serial LB sampling in the course of immune checkpoint inhibitors (ICI), and that its changes could potentially correlate with treatment outcomes. We report the preliminary findings of the observational trial launched to study (NCT06414304) the dynamics of bMSI in 9 MSI-positive CRC patients receiving ICI. NGS-based MSI testing was performed on both pre-treatment FFPE and serial LB samples. For patients who had detectable bMSI burden in any of the LB samples (n = 8, 89%), median bMSI was 1.4% (range, 0.01-40%). Among patients with detectable MSI in available FFPE samples, median MSI burden was 29.3% (range, 10–40%). bMSI detected in baseline LB and FFPE samples were positively correlated (Pearson’s R 0.47). Maximal variant allele frequencies of driver mutations observed in LB were also positively correlated with bMSI burden (Pearson’s R 0.7). Patients who had clinical benefit had undetectable bMSI burden at follow-up. Our results provide the rationale for further validation of bMSI as a predictive biomarker of ICI in MSI-positive patients.

Untapped Potential of Poly(ADP-Ribose) Polymerase Inhibitors: Lessons Learned From the Real-World Clinical Homologous Recombination Repair Mutation Testing

Introduction: Immune checkpoint inhibitors are highly effective in treating various cancers. We analyzed the significance of the KRAS/STK11 co-mutation in relation to the efficacy of immune checkpoint inhibitors in pan-cancer patient cohort. Methods: We analyzed data from open-access research: MSK-IMPACT (molecular profiling data from patients receiving systemic antitumor therapy) and MSK-TMB (molecular profiling data from patients receiving immune checkpoint inhibitors). In both studies, high throughput sequencing was used for molecular profiling. Results: A total of 10,336 patients receiving antitumor therapy (MSK-IMPACT study) and 1661 patients receiving immune checkpoint inhibitors (MSK-TMB study) were included in the analysis. Co-mutation STK11/KRAS was found in 156 (1.5%) and 46 (2.8%) patients in the two studies, respectively. Most patients with the STK11/KRAS co-mutation had non-small cell lung cancer (83% and 85% in the two studies, respectively). Among non-small cell lung cancer patients, the STK11 mutation was associated with a worse outcome for patients receiving systemic antitumor therapy, but not immune checkpoint inhibition therapy (HR for OS 1.90 [95% CI 1.36-2.65] and 1.44 [95% CI 0.88-2.37]). Co-mutation STK11/KRAS was also not associated with patient outcome in any of the studies (HR for OS 0.93 [95% CI 0.56-1.52] and 1.09 [95% CI 0.54-2.19]). High tumor mutational burden was associated with better outcome in the cohort of patients receiving immune checkpoint inhibitors. An analogous analysis among patients in the pan-cancer cohort (excluding patients with non-small cell lung cancer) showed STK11 mutations and high tumor mutational burden have a predictive role for the efficacy of immune checkpoint inhibitors, but not STK11/KRAS co-mutation. Conclusions: Co-mutation STK11/KRAS is common among patients with non-small cell lung cancer and is not an independent predictive marker for the efficacy of immune checkpoint inhibitors. Further studies are required to clarify the role of STK11 mutations in immune checkpoint inhibitor treatment response.