Search PubMed⌕ Search

Biomedical subjects

Conxi Lázaro

Publications and source records attributed to Conxi Lázaro.

4 recordsLinked to original sources
PubMed2026

RNA splicing evidence enables robust classification of BRCA1 exon 18 variants: Results from the ENIGMA consortium.

The Evidence-based Network for the Interpretation of Germline Mutant Alleles (ENIGMA) research consortium conducted a comprehensive study to characterize spliceogenic variants in BRCA1 exon 18. The absence of systematic RNA-based assessment for these variants has led to inconsistent interpretation, limiting accurate classification and management of individuals and their families. The splicing profile of 166 variants was assessed using minigene assays; 32 were additionally analyzed in blood-derived RNA from 51 individuals and 18 in mouse embryonic stem cell (mESC)-based assays to evaluate homology-directed repair (HDR) capacity. mRNA assessment by RT-PCR in blood samples and minigene assays showed a significant positive correlation, with splicing analysis in mESCs displaying highly concordant results. The mESC-based HDR assay showed that the in-frame exon 18 skipping (&#x394;18) transcript encodes a non-functional protein lacking rescue activity. Linear regression analysis using mESC splicing and functional data indicated that &#x2265;59% of full-length (FL) levels and <34% of &#x394;18 were associated with benign HDR activity. These thresholds differ from those recommended by the ClinGen ENIGMA BRCA1 and BRCA2 Variant Curation Expert Panel American College of Medical Genetics and Genomics (ACMG)/Association for Molecular Pathology (AMP) specifications for applying BP7_strong(RNA): >30% functional transcripts or <70% non-functional transcripts. Incorporation of RNA splicing evidence into variant interpretation increased pathogenic (28.6%-31.7%) and benign (3.7%-24.4%) classifications while reducing likely pathogenic (19.5%-17.7%), uncertain (18.9%-8.5%), and likely benign (29.3%-17.7%) categories. Experimental mRNA profiling impacted the interpretation of 34% of variants and resolved uncertainty in approximately 10% of cases. Exon 18 skipping was less tolerated, indicating that the degree of splice perturbation required to impair BRCA1 function may depend on the nature of the resulting non-functional transcript.

Humans↗
PubMed2026

Worldwide Innovative Network Consortium: Building a Common Global Cancer Database.

This review shares the ongoing work of the global Worldwide Innovative Network (WIN) Consortium for Precision Medicine to synthesize emerging cancer treatment data and to define the requirements for a common global cancer database that can truly support precision oncology. We performed a narrative review of emerging cancer treatment data, molecular profiling technologies, and existing clinicogenomic databases, focusing on how tumors are characterized, how subgroups are defined, and how demographic, lifestyle, and environmental factors are captured. The growth in molecular profiling technologies and the development of new targeted therapies are transforming cancer care. Tumors, regardless of tissue origin, are increasingly defined as composites of multiple, often rare, subgroups, each with distinct biology and likely response to specific therapies, based on multidimensional profiling of the tumor and its microenvironment. The solution lies in building vast databases that capture racial and ethnic diversity, reflected in genomic data, as well as diet and lifestyle factors that may have epigenetic impact on gene expression and post-translational modifications. A truly inclusive and informative data set must reflect global diversity, and there are multiple examples of demography-dependent differences in genomic signals. With members caring for and studying patients with cancer across five continents, WIN is actively exploring pathways to create a global cancer database, rich in clinical and molecular detail, granular enough for precise analysis, and large enough to power artificial intelligence-driven insights, provided appropriate data quality, validation, and governance frameworks are in place. This review surveys the current landscape and outlines practical paths forward to achieve this goal.

Humans↗
PubMed2026

Optimizing GRIDSS for clinical use: A targeted NGS filtering strategy for germline structural variant detection.

Detecting intermediate-sized structural variants (SVs) remains challenging in diagnostics, as tools for single-nucleotide and copy-number variants, particularly read-depth-based methods, are often insufficient. GRIDSS addresses this gap by integrating paired-end mapping, split-read analysis, and assembly-based approaches. However, its use in targeted sequencing and diagnostic workflows remains complex. NGS panel data from 9726 patients with suspected hereditary cancer were analyzed using GRIDSS. A filtering strategy was developed to prioritize clinically relevant germline SVs. Multiple parameter settings were tested to optimize performance. The initial dataset of 1,307,592 variants was reduced to 89 candidates after applying the selected filtering strategy. Of these, 24 had been previously detected by routine callers and were not further analyzed. Among the remaining 65, 13 were considered likely true positives after visual inspection using IGV. Experimental validation was performed by Sanger/Nanopore long-read sequencing for these variants, all of which were confirmed. Eight were classified as (likely) pathogenic, including two frameshift duplications in MSH6, one splicing variant in BARD1, and five mobile element insertions in APC, BRCA2, and PALB2. Altogether, GRIDSS implementation increased diagnostic yield while maintaining feasibility for diagnostic workflows. Comprehensive workflow scheme for germline structural variant detection and results in our diagnostic setting.

Humans↗
PubMed2026

Personalized medicine strategy for MPNSTs: using precision oncology on PDOX models to inform tumor boards.

BACKGROUND: Malignant peripheral nerve sheath tumors (MPNSTs) are a heterogeneous group of aggressive soft tissue sarcomas with poor prognosis. Currently there is a lack of effective treatments for MPNSTs. Here, we propose a personalized medicine approach that integrates a precision oncology strategy guided by MPNST genomic analysis, with a functional validation of treatment response in an orthotopic xenograft model (PDOX) derived from the same MPNST. METHODS: Comprehensive whole genome sequencing analysis was performed in primary MPNSTs, relapses and (in one case) metastases, following disease progression in two independent individuals. Matched MPNST PDOX models were generated by orthotopically implanting tumor fragments near the sciatic nerve of immunodeficient mice. Candidate targeted combination therapies were prioritized based on genomic alterations and tested in vivo in the PDOX models. RESULTS: The feasibility of the developed strategy is illustrated for two MPNST patients, one Neurofibromatosis type 1 (NF1) individual that developed two independent MPNSTs and another sporadic MPNST case with multiple metastatic relapses. Genomic analysis revealed a remarkable degree of genomic stability across primary MPNSTs and their successive relapses in each patient, and even metastases in one individual. While based on a small number of cases requiring additional analyses, this finding aligns with previous evidence suggesting a fair genomic conservation throughout tumor evolution. This stability supports the identification of consistent therapeutic vulnerabilities throughout disease progression. Among the therapies tested, co-treatment of MEK inhibitor (MEKi) plus bromodomain inhibitor (BETi) elicited the highest antitumor activity, resulting in approximately 60% tumor volume reduction in the sporadic MPNST PDX model, whose patient has been receiving this therapy for eight months with sustained remission. CONCLUSIONS: This study demonstrates the feasibility and clinical utility of integrating genomic-driven precision oncology with PDOX-based functional testing for MPNSTs. This strategy may support molecular tumor boards (MTBs) in their treatment decisions. The observed genomic stability supports the use of longitudinal tumor profiling to guide treatment, and the success of MEKi+BETi highlights its potential as a combination therapy for MPNSTs.

Precision Medicine↗