Sequencing technology status of BRCA1/2 testing in Latin American Countries

Real-world data on triple-negative breast cancer in Latin America and the Caribbean

Breast cancer (BC) is the most prevalent cancer in women in Latin America and the Caribbean. We compiled real-world data (RWD) on the epidemiology, diagnosis, treatment, and patient outcomes of triple-negative breast cancer (TNBC), addressing the main barriers to optimal care in Latin America. The prevalence of TNBC varies between 11% and 38.5% of all BC cases diagnosed in the region, and TNBC primarily affects young patients. Delays in BC diagnosis, with consequent advanced disease stages and barriers to access efficient therapies, particularly due to high costs, negatively impact patient outcomes. Cancer clinical trials are an opportunity to access standard and novel therapies for patients with this aggressive BC subtype and thus must be prioritised. Finally, generating RWD and cost-effectiveness studies in a region with limited resources is critical for decision-makers to define the incorporation of new technologies for the treatment of BC.

Evaluation of the Available Variant Calling Tools for Oxford Nanopore Sequencing in Breast Cancer

The goal of biomarker testing, in the field of personalized medicine, is to guide treatments to achieve the best possible results for each patient. The accurate and reliable identification of everyone’s genome variants is essential for the success of clinical genomics, employing third-generation sequencing. Different variant calling techniques have been used and recommended by both Oxford Nanopore Technologies (ONT) and Nanopore communities. A thorough examination of the variant callers might give critical guidance for third-generation sequencing-based clinical genomics. In this study, two reference genome sample datasets (NA12878) and (NA24385) and the set of high-confidence variant calls provided by the Genome in a Bottle (GIAB) were used to allow the evaluation of the performance of six variant calling tools, including Human-SNP-wf, Clair3, Clair, NanoCaller, Longshot, and Medaka, as an integral step in the in-house variant detection workflow. Out of the six variant callers understudy, Clair3 and Human-SNP-wf that has Clair3 incorporated into it achieved the highest performance rates in comparison to the other variant callers. Evaluation of the results for the tool was expressed in terms of Precision, Recall, and F1-score using Hap.py tools for the comparison. In conclusion, our findings give important insights for identifying accurate variants from third-generation sequencing of personal genomes using different variant detection tools available for long-read sequencing.