Rapid detection of copy number variations and point mutations in BRCA1/2 genes using a single workflow by ion semiconductor sequencing pipeline

Molecular analysis of BRCA1 (MIM# 604370) and BRCA2 (MIM #600185) genes is essential for familial breast and ovarian cancer prevention and treatment. An efficient, rapid, cost-effective accurate strategy for the detection of pathogenic variants is crucial. Mutations detection of BRCA1/2 genes includes screening for single nucleotide variants (SNVs), small insertions or deletions (indels), and Copy Number Variations (CNVs). Sanger sequencing is unable to identify CNVs and therefore Multiplex Ligation Probe amplification (MLPA) or Multiplex Amplicon Quantification (MAQ) is used to complete the BRCA1/2 genes analysis. The rapid evolution of Next Generation Sequencing (NGS) technologies allows the search for point mutations and CNVs with a single platform and workflow. In this study we test the possibilities of NGS technology to simultaneously detect point mutations and CNVs in BRCA1/2 genes, using the OncomineTM BRCA Research Assay on Personal Genome Machine (PGM) Platform with Ion Reporter Software for sequencing data analysis (Thermo Fisher Scientific). Comparison between the NGS-CNVs, MLPA and MAQ results shows how the NGS approach is the most complete and fast method for the simultaneous detection of all BRCA mutations, avoiding the usual time consuming multistep approach in the routine diagnostic testing of hereditary breast and ovarian cancers

Monozygotic twins discordant for constitutive BRCA1 promoter methylation, childhood cancer and secondary cancer

We describe monozygotic twins discordant for childhood leukemia and secondary thyroid carcinoma. We used bisulfite pyrosequencing to compare the constitutive promoter methylation of BRCA1 and several other tumor suppressor genes in primary fibroblasts. The affected twin displayed an increased BRCA1 methylation (12%), compared with her sister (3%). Subsequent bisulfite plasmid sequencing demonstrated that 13% (6 of 47) BRCA1 alleles were fully methylated in the affected twin, whereas her sister displayed only single CpG errors without functional implications. This between-twin methylation difference was also found in irradiated fibroblasts and untreated saliva cells. The BRCA1 epimutation may have originated by an early somatic event in the affected twin: approximately 25% of her body cells derived from different embryonic cell lineages carry one epigenetically inactivated BRCA1 allele. This epimutation was associated with reduced basal protein levels and a higher induction of BRCA1 after DNA damage. In addition, we performed a genome-wide microarray analysis of both sisters and found several copy number variations, i.e., heterozygous deletion and reduced expression of the RSPO3 gene in the affected twin. This monozygotic twin pair represents an impressive example of epigenetic somatic mosaicism, suggesting a role for constitutive epimutations, maybe along with de novo genetic alterations in recurrent tumor development

Syövän syntyyn vaikuttavat geneettiset ja epigeneettiset tekijät Lynchin ja Lynch-like syndroomassa

Lynch syndrome is the most prevalent cancer predisposition syndrome that causes significantly increased lifetime risk of cancer in multiple organs such as colorectum, endometrium and ovarium. The predisposition is caused by germline mutations in DNA mismatch repair (MRR) genes MLH1, MSH2, MSH6, and PMS2. Lynch-like syndrome colorectal tumors, like Lynch syndrome tumors, are MMR-deficient. Nevertheless, Lynch-like syndrome tumors do not bear germline mutations in MMR genes nor methylation of the promoter regions of MMR genes that would explain the deficiency. Instead, MMR deficiency in majority of Lynch-like syndrome tumors is caused by two somatic mutations in the MMR genes. Dysfunctional MMR protein complex enables accumulation of mutations in the genome (mutator phenotype) and, eventually, microsatellite instability and cancer. The reasons behind organ selectivity in MMR-deficient tumors are unknown, and whether breast cancer is part of the Lynch syndrome spectrum is under debate. The germline mutations in MMR genes are well studied, but molecular characteristics of Lynch syndrome tumors remain to be studied further. Lynch-like syndrome tumors remain less well characterized: besides the double somatic MMR mutations as a cause of MMR deficiency, their molecular and clinicopathological features as well as their incidence in the population remain poorly known. Currently, the only possibility to diagnose Lynch-like syndrome is by ruling out the possibility of germline mutations in MMR genes (Lynch syndrome) or methylation of the promoter regions of MMR genes. Synchronous ovarian and endometrial carcinomas are common in Lynch syndrome; whether they are of same origin (metastatic cancer) or two independently developed primary cancers remains to be resolved. We aimed to characterize the epigenetic and somatic mutation profiles in Lynch syndrome representing colorectal, ovarian, endometrial and breast carcinomas, and to identify new unique features that could be used in evaluating cancer risk, diagnosis and targeted treatment. We used targeted high-throughput sequencing of 578 known cancer genes to investigate the somatic mutation profiles, and methylation-specific multiplex ligation-dependent probe amplification to study the epigenetic profiles of the tumors. Non-synonymous somatic mutations were detected from sequencing data of the paired tumor and normal tissues to determine mutation signatures and identify potential driver genes. The data was also compared statistically between tumors of different origin, epigenetic status, and between breast carcinomas from Lynch syndrome mutation carriers and their known non-carrier family members. We observed that Lynch- and Lynch-like syndrome tumors have unique somatic mutation and methylation profiles. We were able to link the methylator phenotype to high somatic mutation rates, and Lynch-like colorectal tumors to hypermethylated CpG island methylator phenotype (CIMP), which are novel findings. Our discovery of high mutation burden in genes associated with epigenetic regulation provides a new link between genetic and epigenetic factors in tumorigenesis. Genetic and epigenetic characterization of synchronous ovarian and endometrial carcinomas indicated shared origin, in analogy to sporadic cases. Molecular characteristics and especially mutational signatures of breast tumors of Lynch syndrome mutation carriers indicated that breast carcinoma is likely to be part of the Lynch syndrome tumor spectrum. These findings bear potential clinical relevance since the molecular tumor profiles may be used in diagnosis and may guide tailored management of the patients. Many of the mutated genes are part of signaling routes to which targeted molecules either exist or can be developed.Lynchin syndrooma on yleisin syövälle altistava perinnöllinen syndrooma, joka lisää muun muassa suolisto-, kohtu- ja munasarjasyövän riskiä. Alttiuden aiheuttavat perinnölliset mutaatiot DNA:n emäspariutumisvirheitä korjaavissa (engl. DNA mismatch repair, MMR) geeneissä MLH1, MSH2, MSH6, and PMS2. MMR-proteiineista koostuvan koneiston puutteellinen toiminta johtaa mutaatioiden kertymiseen genomiin ja lopulta mikrosatelliitti-epätasapainoon ja syövän syntyyn. Lynchin kaltaisen (engl. Lynch-like) syndrooman suolistokasvainten MMR-proteiinien puutos ei selity ituratamutaatioilla tai MMR-geenien promoottorialueiden hypermetylaatiolla. Tiedetään, että valtaosassa tapauksista Lynch-like -kasvainten MMR-geenien normaali toiminta on hiljentynyt kahden somaattisen eli hankitun mutaation seurauksena. Kudosspesifisyyden syitä syövissä, joissa MMR-koneiston toiminta on puutteellista, ei vielä tunneta. Rintasyövän kuulumisesta Lynchin syndrooman syöpäspektriin on ristiriitaisia tutkimustuloksia, ja synkronisten munasarja- ja kohdunrungonsyövän alkuperästä (metastasoitunut kasvain vai itsenäisesti kehittyneet primaarikasvaimet) ei löydy julkaistua tutkimustietoa. MMR-geenien perinnölliset mutaatiot tunnetaan jo melko hyvin, mutta Lynchin syndrooman kasvainten muista molekulaarisista ominaisuuksista tarvitaan vielä lisää tutkimustietoa. Lynch-like -kasvaimista on niukemmin tutkimustietoa: kahden somaattisen MMR-mutaation lisäksi niiden molekulaarisista ja kliinispatologisista ominaisuuksista sekä kyseisen tautimuodon esiintyvyydestä populaatiotasolla tiedetään hyvin vähän. Toistaiseksi Lynch-like -syndrooma on mahdollista diagnosoida vain poissulkemalla Lynchin syndrooma ja MMR-geenien hypermetylaatio. Tavoitteenamme oli kartoittaa Lynchin ja Lynch-like -syndroomaan kuuluvien suolisto-, munasarja-, kohdunrungon ja rintasyöpien somaattisia ja epigeneettisiä muutoksia. Näiden piirteiden tunnistaminen eri syöpätyypeissä mahdollistaisi syövän riskin arvioinnin, tarkemman diagnosoinnin sekä kohdennetun hoidon kehittämisen. Tutkimme somaattisia mutaatioita sekvensoimalla kasvainten DNA:ta paneelilla, joka kattaa 578 tunnettua syöpägeeniä, sekä niiden metylaatioprofiilia ns. MS-MLPA (eng. methylation-specific multiplex ligation-dependent probe amplification) -tekniikan avulla. Tunnistimme ei-synonyymiset mutaatiot parittaisesta kasvain- ja normaalikudosten sekvenssidatasta määrittääksemme mutaatioprofiilit sekä syövänkehityksen ajurigeenit (engl. driver genes). Tilastolliset vertailut tehtiin eri kudosten ja metylaatiostatusten kesken. Lisäksi Lynchin syndrooman mutaationkantajilta peräisin olevia rintasyöpiä verrattiin rintasyöpiin sukulaisilta, jotka eivät olleet perineet sukunsa alttiusmutaatiota. Havaitsimme, että Lynchin ja Lynch-like syndroomien syövillä on niille luonteenomaiset epigeneettiset ja somaattiset mutaatioprofiilit. Uusina löydöksinä osoitimme yhteyden yleistyneen hypermetylaatio- ja mutaatiotaipumuksen välillä, sekä yhteyden Lynch-like -kasvainten ja hypermetyloituneen fenotyypin välillä. Epigeneettiseen säätelyyn osallistuvien geenien sekä DNA:n korjausgeenien lisääntynyt mutaatioherkkyys liittää geneettiset ja epigeneettiset tekijät uudella tavalla toisiinsa syövänkehityksessä. Se, että synkroniset munasarjan ja kohdunrungon kasvaimet olivat geneettisesti ja epigeneettisesti yhteneväisiä, osoittaa, että kasvaimet ovat samaa alkuperää, eli edustavat metastasoitunutta kasvainta, kuten vastaavissa sporadisissa syövissä on aiemmin osoitettu. Lynchin syndrooman kantajien ja ei-kantajien rintasyöpien molekulaariset tutkimukset ja erityisesti mutaatioprofiilit toivat viitteitä siitä, että rintasyöpä kuuluu Lynchin syndrooman kasvainspektriin. Tutkimus tuo tärkeää uutta tietoa Lynchin ja Lynch-like syndrooman syöpien syntymekanismeista sekä ominaispiirteistä, joita on mahdollista hyödyntää syövän diagnosoinnissa sekä kohdennettua hoitoa suunniteltaessa. Monet mutatoituneista geeneistä kuuluvat säätelyreitteihin, joihin on joko olemassa tai kehitettävissä kohdennettuja lääkemolekyylejä

HRDetect is a predictor of BRCA1 and BRCA2 deficiency based on mutational signatures.

Approximately 1-5% of breast cancers are attributed to inherited mutations in BRCA1 or BRCA2 and are selectively sensitive to poly(ADP-ribose) polymerase (PARP) inhibitors. In other cancer types, germline and/or somatic mutations in BRCA1 and/or BRCA2 (BRCA1/BRCA2) also confer selective sensitivity to PARP inhibitors. Thus, assays to detect BRCA1/BRCA2-deficient tumors have been sought. Recently, somatic substitution, insertion/deletion and rearrangement patterns, or 'mutational signatures', were associated with BRCA1/BRCA2 dysfunction. Herein we used a lasso logistic regression model to identify six distinguishing mutational signatures predictive of BRCA1/BRCA2 deficiency. A weighted model called HRDetect was developed to accurately detect BRCA1/BRCA2-deficient samples. HRDetect identifies BRCA1/BRCA2-deficient tumors with 98.7% sensitivity (area under the curve (AUC) = 0.98). Application of this model in a cohort of 560 individuals with breast cancer, of whom 22 were known to carry a germline BRCA1 or BRCA2 mutation, allowed us to identify an additional 22 tumors with somatic loss of BRCA1 or BRCA2 and 47 tumors with functional BRCA1/BRCA2 deficiency where no mutation was detected. We validated HRDetect on independent cohorts of breast, ovarian and pancreatic cancers and demonstrated its efficacy in alternative sequencing strategies. Integrating all of the classes of mutational signatures thus reveals a larger proportion of individuals with breast cancer harboring BRCA1/BRCA2 deficiency (up to 22%) than hitherto appreciated (∼1-5%) who could have selective therapeutic sensitivity to PARP inhibition

Genomic instability as a predictive biomarker for the application of DNA-damaging therapies in gynecological cancer patients

[ES] El curso natural de los tumores va acompañado de la acumulación progresiva de alteraciones genómicas, propiciando una cadena de eventos que resultan en inestabilidad genómica (IG). Éste fenómeno, caracterizado por alteraciones en el número de copias, constituye un hallmark genómico con impacto pronóstico más allá de la histología y otras características moleculares del tumor. En el ámbito de la investigación en oncología ginecológica, la IG ha ganado fuerza en los últimos años, permitiendo la estratificación de pacientes de acuerdo al pronóstico y la respuesta a agentes que dañan el ADN, como las terapias basadas en platinos y los inhibidores de PARP. En el cáncer de ovario, en particular, se ha descrito un subgrupo molecular caracterizado por alta incidencia de alteraciones en el número de copias relacionado con un mejor pronóstico y respuesta a quimioterapia. Esta correlación presenta la IG como un buen marcador predictivo y pronóstico. Así, un modelo basado en la IG trasladable a la práctica clínica constituirá una herramienta útil para la optimización de la toma de decisiones. La era de la medicina personalizada llegó de la mano de los estudios integrativos, donde las técnicas de alto rendimiento se aplican de manera combinada para obtener una visión molecular global de los tumores, completando y complementando la caracterización clásica a nivel anatómico e histológico. Esta tesis propone un estudio global de la IG como biomarcador pronóstico y predictivo de respuesta en cáncer ginecológico, haciendo hincapié en el cáncer de ovario seroso de alto grado y cáncer de endometrio. A través de la aplicación de estrategias basadas en NGS con la adaptación de pipelines de análisis disponibles obtuvimos los perfiles de IG de muestras de tejido fijadas en formol y embebidas en parafina, de una manera fiable, portable y coste efectiva, combinando herramientas de machine learning para ajustar modelos predictivos y pronósticos. Partiendo de esta premisa, ajustamos y validamos, en cohortes clínicas bien caracterizadas, tres modelos a partir de los datos ómicos individuales y un modelo integrativo (Scarface Score) que demostró la capacidad de predecir la respuesta a agentes que dañan el ADN en un escenario clínico concreto de pacientes con cáncer de ovario seroso de alto grado. Paralelamente, desarrollamos y validamos un algoritmo basado en el perfil de mutaciones, con impacto pronóstico, en cáncer de endometrio. Este algoritmo consiguió una estratificación que respondía al perfil de IG de los pacientes. Finalmente, se caracterizó un panel de líneas celulares de cáncer de ovario a nivel de respuesta, genético y genómico. Se interrogó el estatus de la vía de recombinación homóloga y su asociación a patrones de IG, completando el perfil molecular y estableciendo las bases para futuros estudios preclínicos y clínicos. Los resultados obtenidos en esta tesis doctoral presentan herramientas de gran valor para el manejo clínico en cuanto a la búsqueda de una medicina personalizada. Adicionalmente, diferentes estudios para trasladar el modelo predictivo a otros escenarios clínicos pueden ser explorados, usando como base el planteado, pero restableciendo puntos de corte nuevos y específicos.[CA] El curs natural dels tumors va acompanyat de l'acumulació progressiva d'alteracions genòmiques, propiciant una cadena d'esdeveniments que resulten en inestabilitat genòmica (IG). Aquest fenomen, caracteritzat per la presencia de alteracions en el nombre de cópies, constitueix un hallmark genòmic amb impacte pronòstic més enllà de la histologia i altres característiques moleculars del tumor. En l'àmbit de la recerca en oncologia ginecològica, la IG ha guanyat força en els últims anys, permetent l'estratificació de pacients d'acord amb el pronòstic i la resposta d'agents que danyen l'ADN, com les teràpies basades en platins i els inhibidors de PARP. En el càncer d'ovari en particular, s'ha descrit un subgrup molecular caracteritzat per una alta incidència d'alteracions en el nombre de còpies relacionat amb un millor pronòstic i resposta a quimioteràpia. Aquesta correlació presenta la IG com un marcador predictiu i pronòstic adeqüat. Així, un model basat en la IG traslladable a la pràctica clínica constituirà una eina útil per a l'optimització de la presa de decisions. L'era de la medicina personalitzada va arribar de la mà dels estudis integratius, on les tècniques d'alt rendiment s'apliquen de manera combinada per a obtenir una visió molecular global dels tumors, completant i complementant la caracterització clàssica a nivell anatòmic i histològic. Aquesta tesi proposa un estudi global de la IG com a biomarcador pronòstic i predictiu de resposta en càncer ginecològic, posant l'accent en el càncer d'ovari serós d'alt grau i càncer d'endometri. A través de la aplicación d'estratègies basades en NGS amb l'adaptació de pipelines d'anàlisis disponibles, vam obtenir els perfils de IG de mostres de teixit fixades en formol i embegudes en parafina d'una manera fiable, portable i cost efectiva, combinant eines de machine learning per a ajustar models predictius i pronòstics. Partint d'aquesta premissa, vam ajustar i validar, en cohortes clíniques ben caracteritzades, tres models a partir de les dades omiques individuals i un model integratiu (Scarface Score) que va demostrar la capacitat de predir la resposta a agents que danyen l'ADN en un escenari clínic concret de pacients amb càncer d'ovari serós d'alt grau. Paral·lelament, desenvoluparem i validarem un algoritme basat en el perfil de mutacions amb impacte pronòstic en càncer d'endometri. Aquest algoritme va aconseguir una estratificació que responia al perfil de IG dels pacients. Finalment, es va caracteritzar un panell de línies cel·lulars de càncer d'ovari a nivell de resposta, genètic i genòmic. Es varen interrogar l'estatus de la via de recombinació homòloga i la seua associació a patrons de IG, completant el perfil molecular i establint les bases per a futurs estudis preclínics i clínics. Els resultats obtinguts en aquesta tesi doctoral presenten eines de gran valor per al maneig clínic en quant a la cerca d'una medicina personalitzada. Addicionalment, diferents estudis per a traslladar el model predictiu a altres escenaris clínics poden ser plantejats, usant com a base el propost però restablint punts de tall nous i específics.[EN] The natural course of tumors matches the progressive accumulation of genomic alterations, triggering a cascade of events that results in genomic instability (GI). This phenomenon includes copy number alterations and constitutes a genomic hallmark that defines specific outcomes beyond histology and other molecular features of the tumor. In the context of gynaecologic oncology research, GI has gained strength in the last years allowing the stratification of patients according to prognosis and response to certain DNA-damaging agents, such as platinum-based therapies and PARP inhibitors. Particularly in ovarian and endometrial cancers, it has been described a molecular subgroup characterized by high copy number alterations (CNA) related to good prognosis and better response to chemotherapy. This relationship highlights GI as a predictive and prognostic biomarker. Hence, a GI-based model translated into clinical practice would constitute a tool for optimizing clinical decision-making. The era of personalised medicine arrived together with the coming of integrative studies, where results of high-throughput techniques are combined to obtain a comprehensive molecular landscape of the diseases, bringing a new paradigm to characterize the tumors beyond classical anatomic and histological characteristics. This thesis proposes a global study of the phenomenon of GI as a prognostic and predictive biomarker of treatment response in gynaecological cancers, mainly focused on high-grade ovarian cancer and endometrial cancer. Through the development of an NGS-based strategy with the adaptation of available pipelines of analysis, we obtained GI profiles on formalin-fixed paraffin-embedded samples in a reliable, portable, and cost-effective approach, with the combination of Machine Learning tools to fit prognostic and predictive models based on the integration of omic data. Based on that premise, we fit and validated, in well-characterized clinical cohorts, three single-source models and an integrative ensemble model (Scarface Score) that proved to be able to predict response to DNA-damaging agents in a clinical scenario of High-Grade Serous Ovarian Cancer. In addition, a mutational-based algorithm (12g algorithm) with prognostic impact was developed and validated for endometrial cancer patients. This algorithm achieved a GI-based stratification of patients. Finally, a panel of ovarian cancer cell lines was characterized at the response, genetic and genomic level, interrogating homologous recombination repair pathway status and its associated GI profiles, completing the molecular landscape, and establishing the basis and breeding ground of future preclinical and clinical studies. The results reported in this Doctoral Thesis provide valuable clinical management tools in the accomplishment of a reliable tailored therapy. Additionally, future studies in different tumor types and drugs for implementation of the predictive model can be planned, using as a base the defined one but re-establishing new and specific cut-offs.The present doctoral thesis was partially funded by GVA Grants “Subvencions per a la realització de projectes d’i+d+i desenvolupats per grups d’investigació emergents (GV/2020/158)” and “Ayudas para la contratación de personal investigador en formación de carácter predoctoral” (ACIF/2016/008), “Beca de investigación traslacional Andrés Poveda 2020” from GEICO group and Phase II clinical trial (POLA: NCT02684318, EudraCT 2015-001141-08, 03.10.2015). This study was awarded the Prize “Antonio Llombart Rodriguez-FINCIVO 2020” from the Royal Academy of Medicine of the Valencian CommunityLópez Reig, R. (2023). Genomic instability as a predictive biomarker for the application of DNA-damaging therapies in gynecological cancer patients [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/19902

A Unified Framework for the Prioritization of Variants of Uncertain Significance in Hereditary Breast and Ovarian Cancer Patients

A significant proportion of hereditary breast and ovarian cancer (HBOC) patients receive uninformative genetic testing results, an issue exacerbated by the overwhelming quantity of variants of uncertain significance identified. This thesis describes a framework where, aside from protein coding changes, information theory (IT)-based sequence analysis identifies and prioritizes pathogenic variants occurring within sequence elements predicted to be recognized by proteins involved in mRNA splicing, transcription, and untranslated region binding and structure. To support the utilization of IT analysis, we established IT-based variant interpretation accuracy by performing a comprehensive review of mutations altering mRNA splicing in rare and common diseases. Custom probes targeting 20 complete HBOC genes for sequencing in 379 BRCA-uninformative patients identified 47,501 unique variants and we prioritized 429 variants in both BRCA and non-BRCA genes. Our approach focuses attention on a limited set of variants from a spectrum of functional mutation types for downstream functional and co-segregation analysis

Diagnostic, Prognostic and Therapeutic Value of Gene Signatures

Gene expression studies have revealed diagnostic profiles and upregulation of specific pathways in many solid tumors. Some gene-expression signatures are already used as predictors of relapse in early breast cancer patients. The explosion of new information in gene expression profiling could potentially lead to the development of tailored treatments in many solid tumors. In addition, many studies are ongoing to validate these signatures also in predicting response to hormonal, chemotherapeutic, and targeted agents in breast cancer as well as in other tumors. This book has been carried out with the aim of providing readers a useful and comprehensive resource about the range of applications of microarray technology on oncological diseases. The book is principally addressed to resident and fellow physicians, medical oncologists, molecular biologists, biotechnologists, and those who study oncological diseases. The chapters have been written by leading international researchers on these topics who have prepared their manuscripts according to current literature and field experience with microarray technology

Prediction of "BRCAness" in breast cancer by array comparative genomic hybridization

Predicting the likelihood that an individual is a BRCA mutation carrier is the first step to genetic counseling, followed by germ-line mutation testing in many family cancer clinics. Individuals who have been diagnosed as BRCA mutation-positive are offered special medical care; however, clinical management in the case of a negative test result or an unclassified variant in BRCA1 or BRCA2 can be difficult. Since it is estimated that 15% of BRCA mutation carriers are missed by current diagnostics and assessment of the clinical significance of many unclassified variants is complex and time consuming, new strategies are emerging that are able to predict BRCA dysfunction based on molecular tumor information (BRCAness) rather than on family history. This thesis starts with reviewing the importance of BRCA status assessment, followed by the studies performed by SA Joosse in which array comparative genomic hybridization has been utilized for the prediction of the involvement of BRCA in tumorigenesis.Dutch Cancer Society (KWF)UBL - phd migration 201

Genetic Anticipation Is Associated with Telomere Shortening in Hereditary Breast Cancer

There is increasing evidence suggesting that short telomeres and subsequent genomic instability contribute to malignant transformation. Telomere shortening has been described as a mechanism to explain genetic anticipation in dyskeratosis congenita and Li-Fraumeni syndrome. Since genetic anticipation has been observed in familial breast cancer, we aimed to study telomere length in familial breast cancer patients and hypothesized that genetic defects causing this disease would affect telomere maintenance resulting in shortened telomeres. Here, we first investigated age anticipation in mother-daughter pairs with breast cancer in 623 breast cancer families, classified as BRCA1, BRCA2, and BRCAX. Moreover, we analyzed telomere length in DNA from peripheral blood leukocytes by quantitative PCR in a set of 198 hereditary breast cancer patients, and compared them with 267 control samples and 71 sporadic breast cancer patients. Changes in telomere length in mother-daughter pairs from breast cancer families and controls were also evaluated to address differences through generations. We demonstrated that short telomeres characterize hereditary but not sporadic breast cancer. We have defined a group of BRCAX families with short telomeres, suggesting that telomere maintenance genes might be susceptibility genes for breast cancer. Significantly, we described that progressive telomere shortening is associated with earlier onset of breast cancer in successive generations of affected families. Our results provide evidence that telomere shortening is associated with earlier age of cancer onset in successive generations, suggesting that it might be a mechanism of genetic anticipation in hereditary breast cancer