David Gómez-Peregrina

ORCID: 0000-0003-1126-897X
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About
Contact & Profiles
Research Areas
  • Gastrointestinal Tumor Research and Treatment
  • Sarcoma Diagnosis and Treatment
  • Cancer Genomics and Diagnostics
  • Gastric Cancer Management and Outcomes
  • Neurofibromatosis and Schwannoma Cases
  • melanin and skin pigmentation
  • Tumors and Oncological Cases
  • Ocular Disorders and Treatments
  • Cancer-related molecular mechanisms research
  • CRISPR and Genetic Engineering
  • Artificial Intelligence in Healthcare
  • Metastasis and carcinoma case studies
  • Gastrointestinal disorders and treatments
  • Autophagy in Disease and Therapy
  • Extracellular vesicles in disease
  • DNA Repair Mechanisms
  • Soft tissue tumor case studies

Vall d'Hebron Institute of Oncology
2021-2025

Vall d'Hebron Institut de Recerca
2025

Queen Mary University of London
2023

Vall d'Hebron Hospital Universitari
2021-2023

PURPOSE Less than 5% of GI stromal tumors (GISTs) are driven by the loss succinate dehydrogenase (SDH) complex, resulting in a pervasive DNA hypermethylation pattern that leads to unique clinical features. Advanced SDH-deficient GISTs usually treated with same therapies targeting KIT and PDGFRA receptors as those used metastatic GIST. However, these treatments display less activity absence alternative therapeutic options. Therefore, it is critical identify novel actionable alterations...

10.1200/po-24-00497 article EN JCO Precision Oncology 2025-01-01

This review explores the role of circulating tumor (ct)DNA as a biomarker for clinical decision-making and monitoring purposes in metastatic gastrointestinal stromal (GIST) patients. We discuss key insights from recent trials anticipate future perspectives ctDNA profiling within landscape GIST.

10.1097/cco.0000000000001040 article EN Current Opinion in Oncology 2024-04-19

11522 Background: Molecular knowledge of GIST is limited due to its rarity, few genes have been identified as relevant determinants outcomes, tumor evolution and therapeutic targets. Therefore, we aimed dissect the molecular landscape in largest series real-world patients reported date. Methods: 946 patient samples (536 localized, 369 metastatic, 41 unknown) underwent next-gen sequencing DNA (592-gene, N = 495; whole exome, 451) RNA (whole transcriptome, 592) at Caris Life Sciences (Phoenix,...

10.1200/jco.2023.41.16_suppl.11522 article EN Journal of Clinical Oncology 2023-06-01

101 Background: The genotype of primary mutations predicts imatinib response in untreated metastatic GIST. However, the sequence salvage treatments GIST is based solely on chronological order registration trials. ctDNA sequencing offers a powerful diagnostic tool to detect resistance but has not been shown correlate with outcomes clinical trials pretreated patients (pts). We analyzed samples collected at baseline phase III VOYAGER trial (NCT03465722) describe landscape KIT alterations and...

10.1200/jco.2022.40.16_suppl.101 article EN Journal of Clinical Oncology 2022-06-01

ABSTRACT Previous studies have identified Microphthalmia-associated Transcription Factor (MITF) involvement in regulating Gastrointestinal Stromal Tumors (GIST) growth and cell cycle progression. This study uses Chromatin Immunoprecipitation combined with high-throughput sequencing (ChIP-seq) RNA to explore MITF-modulated genes GIST. Our findings reveal that MITF regulates involved lysosome biogenesis, vesicle generation, autophagy, mTOR signaling pathways. Comparative transcriptome analysis...

10.1101/2024.09.10.612253 preprint EN bioRxiv (Cold Spring Harbor Laboratory) 2024-09-15

Abstract Cancer genomes exhibit extensive chromosomal alterations caused by ongoing Chromosomal Instability (CIN). The ensuing cell-cell heterogeneity facilitates evolution and cancer cell plasticity that can drive therapy resistance, yet CIN driver mechanisms remain essentially uncharacterised. This lack of knowledge presents an untapped opportunity to target vulnerabilities associated with for therapy. Existing methods investigate the cellular responsible rely on laborious functional...

10.1101/2023.09.27.559836 preprint EN bioRxiv (Cold Spring Harbor Laboratory) 2023-09-29

Background:Current large-scale clinical genomics studies consisting of ten thousands whole genome sequences require a platform with the ability to analyze billions unique variants over hundreds terabytes data. Description:OpenCGA is an open-source project that implements high-performance, scalable and secure for genomic data analysis visualisation. It relies on current big technologies such as Hadoop, Spark, MongoDB or Solr implement advanced analytical variant storage engine can index...

10.6084/m9.figshare.12895910.v1 article EN 2020-09-05
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