Ibai Goicoechea
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Ibai Goicoechea has a total of 32 co-authors. Here are the top co-authors by number of shared publications:
- Alberto Maillo
Division of Biomedical Sciences, King Abdullah University of Science and Technology, Thuwal, Saudi Arabia
1 shared publication - Ander Urruticoechea
Biogipuzkoa (previously known as Biodonostia) Health Research Institute, San Sebastián, Spain; Gipuzkoa Cancer Unit/OSI Donostialdea - Onkologikoa, San Sebastián, Spain
1 shared publication - Carla Solé
Molecular Oncology Group, Biogipuzkoa Health Research Institute, Paseo Dr. Begiristain s/n, 20014 San Sebastian, Spain
1 shared publication - Charles Henderson Lawrie
Radcliffe Department of Medicine University of Oxford Oxford UK
1 shared publication - Daniel Lopez
National Centre for Biotechnology, Spanish National Research Council (CNB-CSIC), Madrid, Spain
1 shared publication - David Gomez-Cabrero
Division of Biomedical Sciences, King Abdullah University of Science and Technology (KAUST), Thuwal, Saudi Arabia
1 shared publication
Latest Publications
- Open Access
- 20 December 2024
- Published by MDPI AG in International Journal of Molecular Sciences
- Vol. 25 (24) , 13630
Use of Gain-of-Function Screening to Identify miRNAs Involved in Paclitaxel Resistance in Triple-Negative Breast Cancer
Paclitaxel is a widely used chemotherapeutic agent for the treatment of breast cancer (BC), including as a front-line treatment for triple-negative breast cancer (TNBC) patients. However, resistance to paclitaxel remains one of the major causes of death associated with treatment failure. Multiple studies have demonstrated that miRNAs play a role in paclitaxel resistance and are associated with both disease progression and metastasis. In the present study, we used a miRNA-encoding lentiviral library as a gain-of-function screen for paclitaxel resistance in the MDA-MB-231 TNBC cell line. We identified that miR-181b, miR-29a, miR-30c, miR-196 and miR-1295 conferred a resistant phenotype to cells. The expression of miR-29a also induced resistance to eribulin and vinorelbine, while miR-181b and miR-30c induced resistance to vinorelbine. We measured the levels of these miRNAs in breast cancer patients and observed higher levels of miR-29a in treatment-refractory patients. Taken together, we suggest that miR-29a and miR-181b may be good candidates for miRNA inhibition to overcome resistance to chemotherapy.
- 20 December 2024
- Published by MDPI AG in International Journal of Molecular Sciences
- Vol. 25 (24) , 13630
Open AccessUse of Gain-of-Function Screening to Identify miRNAs Involved in Paclitaxel Resistance in Triple-Negative Breast Cancer
Paclitaxel is a widely used chemotherapeutic agent for the treatment of breast cancer (BC), including as a front-line treatment for triple-negative breast cancer (TNBC) patients. However, resistance to paclitaxel remains one of the major causes of death associated with treatment failure. Multiple studies have demonstrated that miRNAs play a role in paclitaxel resistance and are associated with both disease progression and metastasis. In the present study, we used a miRNA-encoding lentiviral library as a gain-of-function screen for paclitaxel resistance in the MDA-MB-231 TNBC cell line. We identified that miR-181b, miR-29a, miR-30c, miR-196 and miR-1295 conferred a resistant phenotype to cells. The expression of miR-29a also induced resistance to eribulin and vinorelbine, while miR-181b and miR-30c induced resistance to vinorelbine. We measured the levels of these miRNAs in breast cancer patients and observed higher levels of miR-29a in treatment-refractory patients. Taken together, we suggest that miR-29a and miR-181b may be good candidates for miRNA inhibition to overcome resistance to chemotherapy.
- Open Access
Characterization of the Common Genetic Variation in the Spanish Population of Navarre
Large-scale genomic studies have significantly increased our knowledge of genetic variability across populations. Regional genetic profiling is essential for distinguishing common benign variants from disease-causing ones. To this end, we conducted a comprehensive characterization of exonic variants in the population of Navarre (Spain), utilizing whole genome sequencing data from 358 unrelated individuals of Spanish origin. Our analysis revealed 61,410 biallelic single nucleotide variants (SNV) within the Navarrese cohort, with 35% classified as common (MAF > 1%). By comparing allele frequency data from 1000 Genome Project (excluding the Iberian cohort of Spain, IBS), Genome Aggregation Database, and a Spanish cohort (including IBS individuals and data from Medical Genome Project), we identified 1069 SNVs common in Navarre but rare (MAF ≤ 1%) in all other populations. We further corroborated this observation with a second regional cohort of 239 unrelated exomes, which confirmed 676 of the 1069 SNVs as common in Navarre. In conclusion, this study highlights the importance of population-specific characterization of genetic variation to improve allele frequency filtering in sequencing data analysis to identify disease-causing variants.
Open AccessCharacterization of the Common Genetic Variation in the Spanish Population of Navarre
Large-scale genomic studies have significantly increased our knowledge of genetic variability across populations. Regional genetic profiling is essential for distinguishing common benign variants from disease-causing ones. To this end, we conducted a comprehensive characterization of exonic variants in the population of Navarre (Spain), utilizing whole genome sequencing data from 358 unrelated individuals of Spanish origin. Our analysis revealed 61,410 biallelic single nucleotide variants (SNV) within the Navarrese cohort, with 35% classified as common (MAF > 1%). By comparing allele frequency data from 1000 Genome Project (excluding the Iberian cohort of Spain, IBS), Genome Aggregation Database, and a Spanish cohort (including IBS individuals and data from Medical Genome Project), we identified 1069 SNVs common in Navarre but rare (MAF ≤ 1%) in all other populations. We further corroborated this observation with a second regional cohort of 239 unrelated exomes, which confirmed 676 of the 1069 SNVs as common in Navarre. In conclusion, this study highlights the importance of population-specific characterization of genetic variation to improve allele frequency filtering in sequencing data analysis to identify disease-causing variants.