Revista de Medicina de Laboratorio 00039 / http://dx.doi.org/10.20960/revmedlab.00039

Resumen| PDF

Revisiones - Metaanálisis

Utilidad de los algoritmos de priorización de variantes con significado clínico desconocido en el síndrome de cáncer de mama y ovario hereditario

Verónica Castillo Guardiola, M.ª Desamparados Sarabia Meseguer, Laura Rosado Jiménez, Miguel Marín Vera, José Antonio Macías Cerrolaza, Encarnación Cuevas Tortosa, Francisco Ruiz Espejo, José Antonio Noguera Velasco

Prepublicado: 2021-03-08

Publicado: 2021-04-28

VOLUMEN 2, NÚM. 1, enero-abril (2021), PAG. 21-29

Logo Descargas Número de descargas: 58892 Logo Visitas Número de visitas: 19033 Citas Citas: 0

Compártelo:

La aparición de la secuenciación de nueva generación ha supuesto una revolución en el estudio genético del síndrome de cáncer de mama y ovario hereditario (SCMOH), ya que ha permitido la incorporación a la práctica clínica de paneles de genes, o incluso de exomas y genomas completos. El gran aumento de la información que se obtiene de un estudio genético ha ido unido a un incremento de la incertidumbre debido al mayor número de variantes con significado desconocido (VUS) halladas. En consecuencia, recientemente se ha acuñado el concepto de VUS priorizada, que hace referencia a aquellas variantes con significado clínico desconocido que, según la bibliografía disponible, presentan un mayor riesgo de ser deletéreas. En esta revisión se pretende mostrar la evolución de las guías de clasificación clínica de variantes, destacar la necesidad del desarrollo de algoritmos de priorización para seleccionar estas VUS priorizadas que permitan optimizar la realización de estudios complementarios, así como advertir de la importancia de realizar un correcto proceso de asesoramiento genético que haga entender al paciente las posibles consecuencias de dicho análisis.

Palabras Clave: Síndrome de cáncer de mama y ovario hereditario. Priorización. Variante con significado clínico desconocido.

Descargar PDF

Bibliografía
Artículos Relacionados

[1] Winters S, Martin C, Murphy D, et al. Breast Cancer Epidemiology, Prevention, and Screening. Prog Mol Biol Transl Sci 2017; 151: 1–32.
DOI: 10.1016/bs.pmbts.2017.07.002

[2] Bray F, Ferlay J, Soerjomataram I, et al. Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA: A Cancer Journal for Clinicians 2018; 68: 394–424.
DOI: 10.3322/caac.21492

[3] Las cifras del cáncer en España 2018, https://www.seom.org/ultimas-noticias/106525-las-cifras-del-cancer-en-espana-2018 (accessed 6 September 2018).

[4] López-Abente G, Aragonés N, Pérez-Gómez B, et al. Time trends in municipal distribution patterns of cancer mortality in Spain. BMC Cancer 2014; 14: 535.
DOI: 10.1186/1471-2407-14-535

[5] Ferlay J, Soerjomataram I, Dikshit R, et al. Cancer incidence and mortality worldwide: sources, methods and major patterns in GLOBOCAN 2012. Int J Cancer 2015; 136: E359-386.
DOI: 10.1002/ijc.29210

[6] Meinhold-Heerlein I, Hauptmann S. The heterogeneity of ovarian cancer. Arch Gynecol Obstet 2014; 289: 237–239.
DOI: 10.1007/s00404-013-3114-3

[7] Llort G, Chirivella I, Morales R, et al. SEOM clinical guidelines in Hereditary Breast and ovarian cancer. Clin Transl Oncol 2015; 17: 956–961.
DOI: 10.1007/s12094-015-1435-3

[8] Richards CS, Bale S, Bellissimo DB, et al. ACMG recommendations for standards for interpretation and reporting of sequence variations: Revisions 2007. Genet Med 2008; 10: 294–300.
DOI: 10.1097/GIM.0b013e31816b5cae

[9] Lindor NM, Goldgar DE, Tavtigian SV, et al. BRCA1/2 sequence variants of uncertain significance: a primer for providers to assist in discussions and in medical management. Oncologist 2013; 18: 518–524.
DOI: 10.1634/theoncologist.2012-0452

[10] Thompson BA, Spurdle AB, Plazzer J-P, et al. Application of a 5-tiered scheme for standardized classification of 2,360 unique mismatch repair gene variants in the InSiGHT locus-specific database. Nat Genet 2014; 46: 107–115.
DOI: 10.1038/ng.2854

[11] Richards S, Aziz N, Bale S, et al. Standards and Guidelines for the Interpretation of Sequence Variants: A Joint Consensus Recommendation of the American College of Medical Genetics and Genomics and the Association for Molecular Pathology. Genet Med 2015; 17: 405–424.
DOI: 10.1038/gim.2015.30

[12] Nykamp K, Anderson M, Powers M, et al. Sherloc: a comprehensive refinement of the ACMG-AMP variant classification criteria. Genet Med 2017; 19: 1105–1117.
DOI: 10.1038/gim.2017.37

[13] Mucaki EJ, Caminsky NG, Perri AM, et al. A unified analytic framework for prioritization of non-coding variants of uncertain significance in heritable breast and ovarian cancer. BMC Med Genomics 2016; 9: 19.
DOI: 10.1186/s12920-016-0178-5

[14] Caminsky NG, Mucaki EJ, Perri AM, et al. Prioritizing Variants in Complete Hereditary Breast and Ovarian Cancer Genes in Patients Lacking Known BRCA Mutations. Hum Mutat 2016; 37: 640–652.
DOI: 10.1002/humu.22972

[15] Bonache S, Esteban I, Moles-Fernández A, et al. Multigene panel testing beyond BRCA1/2 in breast/ovarian cancer Spanish families and clinical actionability of findings. J Cancer Res Clin Oncol 2018; 144: 2495–2513.
DOI: 10.1007/s00432-018-2763-9

[16] Gabaldó Barrios X, Sarabia Meseguer MD, Marín Vera M, et al. Molecular characterization and clinical interpretation of BRCA1/BRCA2 variants in families from Murcia (south-eastern Spain) with hereditary breast and ovarian cancer: clinical-pathological features in BRCA carriers and non-carriers. Fam Cancer 2017; 16: 477–489.
DOI: 10.1007/s10689-017-9985-x

[17] Sheikh A, Hussain SA, Ghori Q, et al. The spectrum of genetic mutations in breast cancer. Asian Pac J Cancer Prev 2015; 16: 2177–2185.
DOI: 10.7314/APJCP.2015.16.6.2177

[18] Blanco A, de la Hoya M, Osorio A, et al. Analysis of PALB2 gene in BRCA1/BRCA2 negative Spanish hereditary breast/ovarian cancer families with pancreatic cancer cases. PLoS ONE 2013; 8: e67538.
DOI: 10.1371/journal.pone.0067538

[19] Gracia-Aznarez FJ, Fernandez V, Pita G, et al. Whole exome sequencing suggests much of non-BRCA1/BRCA2 familial breast cancer is due to moderate and low penetrance susceptibility alleles. PLoS ONE 2013; 8: e55681.
DOI: 10.1371/journal.pone.0055681

[20] Desmond A, Kurian AW, Gabree M, et al. Clinical Actionability of Multigene Panel Testing for Hereditary Breast and Ovarian Cancer Risk Assessment. JAMA Oncol 2015; 1: 943–951.
DOI: 10.1001/jamaoncol.2015.2690

[21] Buys SS, Sandbach JF, Gammon A, et al. A study of over 35,000 women with breast cancer tested with a 25-gene panel of hereditary cancer genes. Cancer 2017; 123: 1721–1730.
DOI: 10.1002/cncr.30498

[22] Manahan ER, Sebastian M, Hughes KS, et al. Consensus Guideline on Genetic Testing for Hereditary Breast Cancer.

[23] Daly MB, Pilarski R, Berry M, et al. NCCN Guidelines Insights: Genetic/Familial High-Risk Assessment: Breast and Ovarian, Version 2.2017. J Natl Compr Canc Netw 2017; 15: 9–20.
DOI: 10.6004/jnccn.2017.0003

[24] ClinVar, https://www.ncbi.nlm.nih.gov/clinvar/ (accessed 29 May 2018).

[25] Sherry ST, Ward M-H, Kholodov M, et al. dbSNP: the NCBI database of genetic variation. Nucleic Acids Res 2001; 29: 308–311.
DOI: 10.1093/nar/29.1.308

[26] HGMD® home page, http://www.hgmd.cf.ac.uk/ac/index.php (accessed 30 May 2018).

[27] Home - LOVD - An Open Source DNA variation database system, http://www.lovd.nl/3.0/home (accessed 29 May 2018).

[28] LitVar, https://www.ncbi.nlm.nih.gov/CBBresearch/Lu/Demo/LitVar/ (accessed 8 November 2018).

[29] PolyPhen-2: prediction of functional effects of human nsSNPs, http://genetics.bwh.harvard.edu/pph2/ (accessed 25 September 2018).

[30] Sim N-L, Kumar P, Hu J, et al. SIFT web server: predicting effects of amino acid substitutions on proteins. Nucleic Acids Res 2012; 40: W452–W457.
DOI: 10.1093/nar/gks539

[31] Schwarz JM, Cooper DN, Schuelke M, et al. MutationTaster2: mutation prediction for the deep-sequencing age. Nat Methods 2014; 11: 361–362.
DOI: 10.1038/nmeth.2890

[32] Align GVGD, http://agvgd.hci.utah.edu/ (accessed 2 November 2018).

[33] Grantham R. Amino acid difference formula to help explain protein evolution. Science 1974; 185: 862–864.
DOI: 10.1126/science.185.4154.862

[34] Cooper GM, Stone EA, Asimenos G, et al. Distribution and intensity of constraint in mammalian genomic sequence. Genome Res 2005; 15: 901–913.
DOI: 10.1101/gr.3577405

[35] Garber M, Guttman M, Clamp M, et al. Identifying novel constrained elements by exploiting biased substitution patterns. Bioinformatics 2009; 25: i54–i62.
DOI: 10.1093/bioinformatics/btp190

[36] Pollard KS, Hubisz MJ, Rosenbloom KR, et al. Detection of nonneutral substitution rates on mammalian phylogenies. Genome Res 2010; 20: 110–121.
DOI: 10.1101/gr.097857.109

[37] Pertea M, Lin X, Salzberg SL. GeneSplicer: a new computational method for splice site prediction. Nucleic Acids Res 2001; 29: 1185–1190.
DOI: 10.1093/nar/29.5.1185

[38] Zhang MQ. Statistical features of human exons and their flanking regions. Hum Mol Genet 1998; 7: 919–932.
DOI: 10.1093/hmg/7.5.919

[39] Reese MG, Eeckman FH, Kulp D, et al. Improved splice site detection in Genie. J Comput Biol 1997; 4: 311–323.
DOI: 10.1089/cmb.1997.4.311

[40] Yeo G, Burge CB. Maximum entropy modeling of short sequence motifs with applications to RNA splicing signals. J Comput Biol 2004; 11: 377–394.
DOI: 10.1089/1066527041410418

[41] Varsome The Human Genomics Community, https://varsome.com/ (accessed 4 February 2020).

[42] Li Q, Wang K. InterVar: Clinical Interpretation of Genetic Variants by the 2015 ACMG-AMP Guidelines. The American Journal of Human Genetics 2017; 100: 267–280.
DOI: 10.1016/j.ajhg.2017.01.004

[43] Soto-Martínez, JL. Módulo 2. Diagnóstico genético. In: Curso de cáncer hereditario (IX Edición). 2019.

[44] Singer CF, Balmaña J, Bürki N, et al. Genetic counselling and testing of susceptibility genes for therapeutic decision-making in breast cancer-an European consensus statement and expert recommendations. Eur J Cancer 2019; 106: 54–60.
DOI: 10.1016/j.ejca.2018.10.007

Revisiones - Metaanálisis: RAD51C y RAD51D en el síndrome de cáncer de mama y ovario hereditario

Ana Isabel Sánchez Bermúdez , M.ª Desamparados Sarabia Meseguer , Verónica Castillo Guardiola , Francisco Ruiz Espejo , José Antonio Noguera Velasco

Publicado: 2020-04-22 / http://dx.doi.org/10.20960/revmedlab.00024

Resumen | PDF

Originales: Priorización de variantes de exoma mediante un sistema automático que emplea términos HPO

José Miguel Lezana Rosales , Diego Tuñón Le Poultel , Juan Francisco Quesada Espinosa , Emma Soengas Gonda , Ana Arteche-López , Carmen Palma Milla , Irene Gómez Manjón , María Isabel Álvarez-Mora , Rubén Pérez de la Fuente , María Teresa Sánchez Calvín , María José Gómez Rodríguez , Marta Moreno García

Publicado: 2021-03-30 / http://dx.doi.org/10.20960/revmedlab.00077

Resumen | PDF

Artículos más populares

Licencia creative commons: Open Access bajo la licencia Creative Commons 4.0 CC BY-NC-SA
https://creativecommons.org/licenses/by-nc-sa/4.0/legalcode

Diseño y Desarrollo web Im3diA comunicación