Tumor mutational burden assessment and standardized bioinformatics approach using custom NGS panels in clinical routine.

BACKGROUND: High tumor mutational burden (TMB) was reported to predict the efficacy of immune checkpoint inhibitors (ICIs). Pembrolizumab, an anti-PD-1, received FDA-approval for the treatment of unresectable/metastatic tumors with high TMB as determined by the FoundationOne®CDx test. It remains to be determined how TMB can also be calculated using other tests. RESULTS: FFPE/frozen tumor samples from various origins were sequenced in the frame of the Institut Curie (IC) Molecular Tumor Board using an in-house next-generation sequencing (NGS) panel. A TMB calculation method was developed at IC (IC algorithm) and compared to the FoundationOne® (FO) algorithm. Using IC algorithm, an optimal 10% variant allele frequency (VAF) cut-off was established for TMB evaluation on FFPE samples, compared to 5% on frozen samples. The median TMB score for MSS/POLE WT tumors was 8.8 mut/Mb versus 45 mut/Mb for MSI/POLE-mutated tumors. When focusing on MSS/POLE WT tumor samples, the highest median TMB scores were observed in lymphoma, lung, endometrial, and cervical cancers. After biological manual curation of these cases, 21% of them could be reclassified as MSI/POLE tumors and considered as "true TMB high." Higher TMB values were obtained using FO algorithm on FFPE samples compared to IC algorithm (40 mut/Mb [10-3927] versus 8.2 mut/Mb [2.5-897], p < 0.001). CONCLUSIONS: We herein propose a TMB calculation method and a bioinformatics tool that is customizable to different NGS panels and sample types. We were not able to retrieve TMB values from FO algorithm using our own algorithm and NGS panel.

biogitflow: development workflow protocols for bioinformatics pipelines with git and GitLab.

The use of a bioinformatics pipeline as a tool to support diagnostic and theranostic decisions in the healthcare process requires the definition of detailed development workflow guidelines. Therefore, we implemented protocols that describe step-by-step all the command lines and actions that the developers have to follow. Our protocols capitalized on two powerful and widely used tools: git and GitLab. They address two use cases: a nominal mode to develop a new feature in the bioinformatics pipeline and a hotfix mode to correct a bug that occurred in the production environment. The protocols are available as a comprehensive documentation at https://biogitflow.readthedocs.io and the main concepts, steps and principles are presented in this report.

Relevance of a molecular tumour board (MTB) for patients' enrolment in clinical trials: experience of the Institut Curie.

BACKGROUND: High throughput molecular screening techniques allow the identification of multiple molecular alterations, some of which are actionable and can be targeted by molecularly targeted agents (MTA). We aimed at evaluating the relevance of using this approach in the frame of Institut Curie Molecular Tumor Board (MTB) to guide patients with cancer to clinical trials with MTAs. PATIENTS AND METHODS: We included all patients presented at Institut Curie MTB from 4 October 2014 to 31 October 2017. The following information was extracted from the chart: decision to perform tumour profiling, types of molecular analyses, samples used, molecular alterations identified and those which are actionable, and inclusion in a clinical trial with matched MTA. RESULTS: 736 patients were presented at the MTB. Molecular analyses were performed in 442 patients (60%). Techniques used included next-generation sequencing, comparative genomic hybridisation array and/or other techniques including immunohistochemistry in 78%, 51% and 58% of patients, respectively. Analyses were performed on a fresh frozen biopsy in 91 patients (21%), on archival tissue (fixed or frozen) in 326 patients (74%) and on both archival and fresh frozen biopsy in 25 patients (6%). At least one molecular alteration was identified in 280 analysed patients (63%). An actionable molecular alteration was identified in 207 analysed patients (47%). Forty-five analysed patients (10%) were enrolled in a clinical trial with matched MTA and 29 additional patients were oriented and included in a clinical trial based on a molecular alteration identified prior to the MTB analysis. Median time between date of specimen reception and molecular results was 28 days (range: 5-168). CONCLUSIONS: The implementation of an MTB at Institut Curie enabled the inclusion of 10% of patients into a clinical trial with matched therapy.

Precision medicine in cancer: challenges and recommendations from an EU-funded cervical cancer biobanking study.

BACKGROUND: Cervical cancer (CC) remains a leading cause of gynaecological cancer-related mortality worldwide. CC pathogenesis is triggered when human papillomavirus (HPV) inserts into the genome, resulting in tumour suppressor gene inactivation and oncogene activation. Collecting tumour and blood samples is critical for identifying these genetic alterations. METHODS: BIO-RAIDs is the first prospective molecular profiling clinical study to include a substantial biobanking effort that used uniform high-quality standards and control of samples. In this European Union (EU)-funded study, we identified the challenges that were impeding the effective implementation of such a systematic and comprehensive biobanking effort. RESULTS: The challenges included a lack of uniform international legal and ethical standards, complexities in clinical and molecular data management, and difficulties in determining the best technical platforms and data analysis techniques. Some difficulties were encountered by all investigators, while others affected only certain institutions, regions, or countries. CONCLUSIONS: The results of the BIO-RAIDs programme highlight the need to facilitate and standardise regulatory procedures, and we feel that there is also a need for international working groups that make recommendations to regulatory bodies, governmental funding agencies, and academic institutions to achieve a proficient biobanking programme throughout EU countries. This represents the first step in precision medicine.

Improving prokaryotic transposable elements identification using a combination of de novo and profile HMM methods.

BACKGROUND: Insertion Sequences (ISs) and their non-autonomous derivatives (MITEs) are important components of prokaryotic genomes inducing duplication, deletion, rearrangement or lateral gene transfers. Although ISs and MITEs are relatively simple and basic genetic elements, their detection remains a difficult task due to their remarkable sequence diversity. With the advent of high-throughput genome and metagenome sequencing technologies, the development of fast, reliable and sensitive methods of ISs and MITEs detection become an important challenge. So far, almost all studies dealing with prokaryotic transposons have used classical BLAST-based detection methods against reference libraries. Here we introduce alternative methods of detection either taking advantages of the structural properties of the elements (de novo methods) or using an additional library-based method using profile HMM searches. RESULTS: In this study, we have developed three different work flows dedicated to ISs and MITEs detection: the first two use de novo methods detecting either repeated sequences or presence of Inverted Repeats; the third one use 28 in-house transposase alignment profiles with HMM search methods. We have compared the respective performances of each method using a reference dataset of 30 archaeal and 30 bacterial genomes in addition to simulated and real metagenomes. Compared to a BLAST-based method using ISFinder as library, de novo methods significantly improve ISs and MITEs detection. For example, in the 30 archaeal genomes, we discovered 30 new elements (+20%) in addition to the 141 multi-copies elements already detected by the BLAST approach. Many of the new elements correspond to ISs belonging to unknown or highly divergent families. The total number of MITEs has even doubled with the discovery of elements displaying very limited sequence similarities with their respective autonomous partners (mainly in the Inverted Repeats of the elements). Concerning metagenomes, with the exception of short reads data (<300 bp) for which both techniques seem equally limited, profile HMM searches considerably ameliorate the detection of transposase encoding genes (up to +50%) generating low level of false positives compare to BLAST-based methods. CONCLUSION: Compared to classical BLAST-based methods, the sensitivity of de novo and profile HMM methods developed in this study allow a better and more reliable detection of transposons in prokaryotic genomes and metagenomes. We believed that future studies implying ISs and MITEs identification in genomic data should combine at least one de novo and one library-based method, with optimal results obtained by running the two de novo methods in addition to a library-based search. For metagenomic data, profile HMM search should be favored, a BLAST-based step is only useful to the final annotation into groups and families.

Polyglutamine repeats are associated to specific sequence biases that are conserved among eukaryotes.

Nine human neurodegenerative diseases, including Huntington's disease and several spinocerebellar ataxia, are associated to the aggregation of proteins comprising an extended tract of consecutive glutamine residues (polyQs) once it exceeds a certain length threshold. This event is believed to be the consequence of the expansion of polyCAG codons during the replication process. This is in apparent contradiction with the fact that many polyQs-containing proteins remain soluble and are encoded by invariant genes in a number of eukaryotes. The latter suggests that polyQs expansion and/or aggregation might be counter-selected through a genetic and/or protein context. To identify this context, we designed a software that scrutinize entire proteomes in search for imperfect polyQs. The nature of residues flanking the polyQs and that of residues other than Gln within polyQs (insertions) were assessed. We discovered strong amino acid residue biases robustly associated to polyQs in the 15 eukaryotic proteomes we examined, with an over-representation of Pro, Leu and His and an under-representation of Asp, Cys and Gly amino acid residues. These biases are conserved amongst unrelated proteins and are independent of specific functional classes. Our findings suggest that specific residues have been co-selected with polyQs during evolution. We discuss the possible selective pressures responsible of the observed biases.