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Comparison of three commercial decision support platforms for matching of next-generation sequencing results with therapies in patients with cancer.

ABSTRACT: OBJECTIVE:Precision oncology depends on translating molecular data into therapy recommendations. However, with the growing complexity of next-generation sequencing-based tests, clinical interpretation of somatic genomic mutations has evolved into a formidable task. Here, we compared the performance of three commercial clinical decision support tools, that is, NAVIFY Mutation Profiler (NAVIFY; Roche), QIAGEN Clinical Insight (QCI) Interpret (QIAGEN) and CureMatch Bionov (CureMatch). METHODS:In order to obtain the current status of the respective tumour genome, we analysed cell-free DNA from patients with metastatic breast, colorectal or non-small cell lung cancer. We evaluated somatic copy number alterations and in parallel applied a 77-gene panel (AVENIO ctDNA Expanded Panel). We then assessed the concordance of tier classification approaches between NAVIFY and QCI and compared the strategies to determine actionability among all three platforms. Finally, we quantified the alignment of treatment suggestions across all decision tools. RESULTS:Each platform varied in its mode of variant classification and strategy for identifying druggable targets and clinical trials, which resulted in major discrepancies. Even the frequency of concordant actionable events for tier I-A or tier I-B classifications was only 4.3%, 9.5% and 28.4% when comparing NAVIFY with QCI, NAVIFY with CureMatch and CureMatch with QCI, respectively, and the obtained treatment recommendations differed drastically. CONCLUSIONS:Treatment decisions based on molecular markers appear at present to be arbitrary and dependent on the chosen strategy. As a consequence, tumours with identical molecular profiles would be differently treated, which challenges the promising concepts of genome-informed medicine.

SUBMITTER: Perakis SO

PROVIDER: S-EPMC7513637 | biostudies-literature | 2020 Sep

REPOSITORIES: biostudies-literature

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Comparison of three commercial decision support platforms for matching of next-generation sequencing results with therapies in patients with cancer.

Perakis Samantha O SO Weber Sabrina S Zhou Qing Q Graf Ricarda R Hojas Sabine S Riedl Jakob M JM Gerger Armin A Dandachi Nadia N Balic Marija M Hoefler Gerald G Schuuring Ed E Groen Harry J M HJM Geigl Jochen B JB Heitzer Ellen E Speicher Michael R MR

ESMO open 20200901 5

<h4>Objective</h4>Precision oncology depends on translating molecular data into therapy recommendations. However, with the growing complexity of next-generation sequencing-based tests, clinical interpretation of somatic genomic mutations has evolved into a formidable task. Here, we compared the performance of three commercial clinical decision support tools, that is, NAVIFY Mutation Profiler (NAVIFY; Roche), QIAGEN Clinical Insight (QCI) Interpret (QIAGEN) and CureMatch Bionov (CureMatch).<h4>Me ...[more]

PMID: 32967919

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Project description:Purpose: In oncology, precision medicine centers on tailoring the most appropriate therapy to a patient according to their tumor molecular profile. We addressed the question whether there is a consensus in the classification of actionability of somatic variants and their alignment to treatment recommendations. To this end, we evaluated three commercial clinical decision support tools to assess their variant classification and drug matching strategies.Methods: In this two centers study 48 patients with metastatic breast (n=12), colorectal (n=17) or non-small cell lung cancer (n=19) were recruited based on circulating tumor DNA levels in peripheral blood. In individual patientsÃ¢Â€Â™ plasma samples, we established somatic copy number alterations and somatic mutations across a 77 cancer-associated gene panel and exposed the obtained molecular profiles to the decision support packages NAVIFY Mutation Profiler (NMP; Roche), Qiagen Clinical Insight (QCI) Interpret (Qiagen) and CureMatch Bionov (CureMatch).Results: In the plasma samples, altogether 492 somatic alterations were assessed. Each decision support platform varied in their format of data input, mode of variant classification and strategies for identifying druggable targets and clinical trials, which resulted in discrepancies in tier classification as well as designations of actionability. The frequency of concordant actionable events for tier I-A or tier I-B classifications, i.e. those with the strongest clinical evidence, was only 4.3%, 9.5% and 28.4% when comparing NMP with QCI, NMP with CureMatch, and CureMatch with QCI, respectively. As a consequence, the obtained treatment recommendations differed drastically, and alignment of treatment recommendations was limited to established predictive markers.Conclusions: The lack of standards for the extraction of treatment recommendations from comprehensive tumor molecular profiling data challenge the promising concepts of precision oncology.

Project description:BACKGROUND: The introduction of benchtop sequencers has made adoption of whole genome sequencing possible for a broader community of researchers than ever before. Concurrently, metagenomic sequencing (MGS) is rapidly emerging as a tool for interrogating complex samples that defy conventional analyses. In addition, next-generation sequencers are increasingly being used in clinical or related settings, for instance to track outbreaks. However, information regarding the analytical sensitivity or limit of detection (LoD) of benchtop sequencers is currently lacking. Furthermore, the specificity of sequence information at or near the LoD is unknown. RESULTS: In the present study, we assess the ability of three next-generation sequencing platforms to identify a pathogen (viral or bacterial) present in low titers in a clinically relevant sample (blood). Our results indicate that the Roche-454 Titanium platform is capable of detecting Dengue virus at titers as low as 1X102.5 pfu/mL, corresponding to an estimated 5.4X104 genome copies/ml maximum. The increased throughput of the benchtop sequencers, the Ion Torrent PGM and Illumina MiSeq platforms, enabled detection of viral genomes at concentrations as low as 1X104 genome copies/mL. Platform-specific biases were evident in sequence read distributions as well as viral genome coverage. For bacterial samples, only the MiSeq platform was able to provide sequencing reads that could be unambiguously classified as originating from Bacillus anthracis. CONCLUSION: The analytical sensitivity of all three platforms approaches that of standard qPCR assays. Although all platforms were able to detect pathogens at the levels tested, there were several noteworthy differences. The Roche-454 Titanium platform produced consistently longer reads, even when compared with the latest chemistry updates for the PGM platform. The MiSeq platform produced consistently greater depth and breadth of coverage, while the Ion Torrent was unequaled for speed of sequencing. None of the platforms were able to verify a single nucleotide polymorphism responsible for antiviral resistance in an Influenza A strain isolated from the 2009 H1N1 pandemic. Overall, the benchtop platforms perform well for identification of pathogens from a representative clinical sample. However, unlike identification, characterization of pathogens is likely to require higher titers, multiple libraries and/or multiple sequencing runs.

Project description:PurposePrior molecular profiling of hepatocellular carcinoma (HCC) has identified actionable findings that may have a role in guiding therapeutic decision-making and clinical trial enrollment. We implemented prospective next-generation sequencing (NGS) in the clinic to determine whether such analyses provide predictive and/or prognostic information for HCC patients treated with contemporary systemic therapies.Experimental designMatched tumor/normal DNA from patients with HCC (N = 127) were analyzed using a hybridization capture-based NGS assay designed to target 341 or more cancer-associated genes. Demographic and treatment data were prospectively collected with the goal of correlating treatment outcomes and drug response with molecular profiles.ResultsWNT/β-catenin pathway (45%) and TP53 (33%) alterations were frequent and represented mutually exclusive molecular subsets. In sorafenib-treated patients (n = 81), oncogenic PI3K-mTOR pathway alterations were associated with lower disease control rates (DCR, 8.3% vs. 40.2%), shorter median progression-free survival (PFS; 1.9 vs. 5.3 months), and shorter median overall survival (OS; 10.4 vs. 17.9 months). For patients treated with immune checkpoint inhibitors (n = 31), activating alteration WNT/β-catenin signaling were associated with lower DCR (0% vs. 53%), shorter median PFS (2.0 vs. 7.4 months), and shorter median OS (9.1 vs. 15.2 months). Twenty-four percent of patients harbored potentially actionable alterations including TSC1/2 (8.5%) inactivating/truncating mutations, FGF19 (6.3%) and MET (1.5%) amplifications, and IDH1 missense mutations (<1%). Six percent of patients treated with systemic therapy were matched to targeted therapeutics.ConclusionsLinking NGS to routine clinical care has the potential to identify those patients with HCC likely to benefit from standard systemic therapies and can be used in an investigational context to match patients to genome-directed targeted therapies.See related commentary by Pinyol et al., p. 2021.

Dataset Information

Comparison of three commercial decision support platforms for matching of next-generation sequencing results with therapies in patients with cancer.

Publications

Comparison of three commercial decision support platforms for matching of next-generation sequencing results with therapies in patients with cancer.

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