Whole exome sequencing in molecular diagnostics of cancer decreases over time: evidence from a cost analysis in the French setting

[Cost of high-throughput sequencing (NGS) technologies: Literature review and insights]

Although high-throughput sequencing technologies (Next-Generation Sequencing [NGS]) are revolutionizing medicine, the estimation of their production cost for pricing/tariffication by health systems raises methodological questions. The objective of this review of cost studies of high-throughput sequencing techniques is to draw lessons for producing robust cost estimates of these techniques. We analyzed, using an eleven item analysis framework, micro-costing studies of high-throughput sequencing technologies (n=17), including two studies conducted in the French context. The factors of variability between the studies that we identified were temporality (early evaluation of the innovation vs. evaluation of a mature technology), the choice of cost evaluation method (scope, micro- vs. gross-costing technique), the choice of production steps observed and the transposability of these studies. The lessons we have learned are that it is necessary to have a comprehensive vision of the sequencing production process by integrating all the steps from the collection of the biological sample to the delivery of the result to the clinician. It is also important to distinguish between what refers to the local context and what refers to the general context, by favouring the use of mixed methods to calculate costs. Finally, sensitivity analyses and periodic re-estimation of the costs of the techniques must be carried out in order to be able to revise the tariffs according to changes linked to the diffusion of the technology and to competition between reagent suppliers.

Cost of exome analysis in patients with intellectual disability: a micro-costing study in a French setting

BACKGROUND

With the development of next generation sequencing technologies in France, exome sequencing (ES) has recently emerged as an opportunity to improve the diagnosis rate of patients presenting an intellectual disability (ID). To help French policy makers determine an adequate tariff for ES, we aimed to assess the unit cost per ES diagnostic test for ID from the preparation of the pre-analytical step until the report writing step and to identify its main cost drivers.

METHODS

A micro-costing bottom-up approach was conducted for the year 2018 in a French setting as part of the DISSEQ study, a cost-effectiveness study funded by the Ministry of Health and performed in collaboration with the GAD (Génétique des Anomalies du Développement), a genetic team from the Dijon University Hospital, and a public sequencing platform, the Centre National de Recherche en Génomique Humaine (CNRGH). The analysis was conducted from the point of view of these two ES stakeholders. All of the resources (labor, equipment, disposables and reagents, reusable material) required to analyze blood samples were identified, collected and valued. Several sensitivity analyses were performed.

RESULTS

The unit nominal cost per ES diagnostic test for ID was estimated to be €2,019.39. Labor represented 50.7% of the total cost. The analytical step (from the preparation of libraries to the analysis of sequences) represented 88% of the total cost. Sensitivity analyses suggested that a simultaneous price decrease of 20% for the capture kit and 50% for the sequencing support kit led to an estimation of €1,769 per ES diagnostic test for ID.

CONCLUSION

This is the first estimation of ES cost to be done in the French setting of ID diagnosis. The estimation is especially influenced by the price of equipment kits, but more generally by the organization of the centers involved in the different steps of the analysis and the time period in which the study was conducted. This information can now be used to define an adequate tariff and assess the efficiency of ES.

TRIAL REGISTRATION

ClinicalTrials.gov identifier NCT03287206 on September 19, 2017.

DivBrowse-interactive visualization and exploratory data analysis of variant call matrices

BACKGROUND

The sequencing of whole genomes is becoming increasingly affordable. In this context, large-scale sequencing projects are generating ever larger datasets of species-specific genomic diversity. As a consequence, more and more genomic data need to be made easily accessible and analyzable to the scientific community.

FINDINGS

We present DivBrowse, a web application for interactive visualization and exploratory analysis of genomic diversity data stored in Variant Call Format (VCF) files of any size. By seamlessly combining BLAST as an entry point together with interactive data analysis features such as principal component analysis in one graphical user interface, DivBrowse provides a novel and unique set of exploratory data analysis capabilities for genomic biodiversity datasets. The capability to integrate DivBrowse into existing web applications supports interoperability between different web applications. Built-in interactive computation of principal component analysis allows users to perform ad hoc analysis of the population structure based on specific genetic elements such as genes and exons. Data interoperability is supported by the ability to export genomic diversity data in VCF and General Feature Format 3 files.

CONCLUSION

DivBrowse offers a novel approach for interactive visualization and analysis of genomic diversity data and optionally also gene annotation data by including features like interactive calculation of variant frequencies and principal component analysis. The use of established standard file formats for data input supports interoperability and seamless deployment of application instances based on the data output of established bioinformatics pipelines.

Mutation burden-orthogonal tumor genomic subtypes delineate responses to immune checkpoint therapy

Background

In cancer therapy, higher-resolution tumor-agnostic biomarkers that predict response to immune checkpoint inhibitor (ICI) therapy are needed. Mutation signatures reflect underlying oncogenic processes that can affect tumor immunogenicity, and thus potentially delineate ICI treatment response among tumor types.

Methods

Based on mutational signature analysis, we developed a stratification for all solid tumors in The Cancer Genome Atlas (TCGA). Subsequently, we developed a new software (Genomic Subtyping and Predictive Response Analysis for Cancer Tumor ICi Efficacy, GS-PRACTICE) to classify new tumors submitted to whole-exome sequencing. Using existing data from 973 pan-cancer ICI-treated cases with outcomes, we evaluated the subtype-response predictive performance.

Results

Systematic analysis on TCGA samples identified eight tumor genomic subtypes, which were characterized by features represented by smoking exposure, ultraviolet light exposure, APOBEC enzyme activity, POLE mutation, mismatch repair deficiency, homologous recombination deficiency, genomic stability, and aging. The former five subtypes were presumed to form an immune-responsive group acting as candidates for ICI therapy because of their high expression of immune-related genes and enrichment in cancer types with FDA approval for ICI monotherapy. In the validation cohort, the samples assigned by GS-PRACTICE to the immune-reactive subtypes were significantly associated with ICI response independent of cancer type and TMB high or low status.

Conclusions

The new tumor subtyping method can serve as a tumor-agnostic biomarker for ICI response prediction and will improve decision making in cancer treatment.

Accurate recombination estimation from pooled genotyping and sequencing: a case study on barley

Sexual reproduction involves meiotic recombination and the creation of crossing over between homologous chromosomes, which leads to new allele combinations. We present a new approach that uses the allele frequency differences and the physical distance of neighboring polymorphisms to estimate the recombination rate from pool genotyping or sequencing. This allows a considerable cost reduction compared to conventional mapping based on genotyping or sequencing data of single individuals. We evaluated the approach based on computer simulations at various genotyping depths and population sizes as well as applied it to experimental data of 45 barley populations, comprising 4182 RIL. High correlations between the recombination rates from this new pool genetic mapping approach and conventional mapping in simulated and experimental barley populations were observed. The proposed method therefore provides a reliable genetic map position and recombination rate estimation in defined genomic windows.