Conxi Lázaro

Dr. Conxi Lázaro

Coordinator of the Molecular Diagnostics Unit Hereditary Cancer Program, Catalan Institute of Oncology (ICO-IDIBELL), Barcelona, Spain

Research Focus & Metrics

Academic Career Length

35Years (1992-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 January 2012 in Cancer Epidemiology, Biomarkers & Prevention
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NMNasim Mavaddat
Nasim Mavaddat
DBDaniel Barrowdale
Daniel Barrowdale
IAIrene L. Andrulis
Irene L. Andrulis
SDSusan M. Domchek
Susan M. Domchek
DEDiana Eccles
Diana Eccles
AAAntonis C. Antoniou
Antonis C. Antoniou
Background: Previously, small studies have found that BRCA1 and BRCA2 breast tumors differ in their pathology. Analysis of larger datasets of mutation carriers should allow further tumor characterization. Methods: We used data from 4,325 BRCA1 and 2,568 BRCA2 mutation carriers to analyze the pathology of invasive breast, ovarian, and contralateral breast cancers. Results: There was strong evidence that the proportion of estrogen receptor (ER)-negative breast tumors decreased with age at diagnosis among BRCA1 (P-trend = 1.2 × 10−5), but increased with age at diagnosis among BRCA2, carriers (P-trend = 6.8 × 10−6). The proportion of triple-negative tumors decreased with age at diagnosis in BRCA1 carriers but increased with age at diagnosis of BRCA2 carriers. In both BRCA1 and BRCA2 carriers, ER-negative tumors were of higher histologic grade than ER-positive tumors (grade 3 vs. grade 1; P = 1.2 × 10−13 for BRCA1 and P = 0.001 for BRCA2). ER and progesterone receptor (PR) expression were independently associated with mutation carrier status [ER-positive odds ratio (OR) for BRCA2 = 9.4, 95% CI: 7.0–12.6 and PR-positive OR = 1.7, 95% CI: 1.3–2.3, under joint analysis]. Lobular tumors were more likely to be BRCA2-related (OR for BRCA2 = 3.3, 95% CI: 2.4–4.4; P = 4.4 × 10−14), and medullary tumors BRCA1-related (OR for BRCA2 = 0.25, 95% CI: 0.18–0.35; P = 2.3 × 10−15). ER-status of the first breast cancer was predictive of ER-status of asynchronous contralateral breast cancer (P = 0.0004 for BRCA1; P = 0.002 for BRCA2). There were no significant differences in ovarian cancer morphology between BRCA1 and BRCA2 carriers (serous: 67%; mucinous: 1%; endometrioid: 12%; clear-cell: 2%). Conclusions/Impact: Pathologic characteristics of BRCA1 and BRCA2 tumors may be useful for improving risk-prediction algorithms and informing clinical strategies for screening and prophylaxis. Cancer Epidemiol Biomarkers Prev; 21(1); 134–47. ©2011 AACR.

7 October 2007 in Nature Genetics
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MPMiguel Angel Pujana
Miguel Angel Pujana
JHJing-Dong J Han
Jing-Dong J Han
LSLea M Starita
Lea M Starita
KSKristen N Stevens
Kristen N Stevens
MTMuneesh Tewari
Muneesh Tewari
MVMarc Vidal
Marc Vidal

27 March 2017 in Nature Genetics
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CPCatherine M Phelan
Catherine M Phelan
KKKaroline B Kuchenbaecker
Karoline B Kuchenbaecker
JTJonathan P Tyrer
Jonathan P Tyrer
SKSiddhartha P. Kar
Siddhartha P. Kar
KLKate Lawrenson
Kate Lawrenson
PPPaul Pharoah
Paul Pharoah
Paul Pharoah and colleagues report the results of a large genome-wide association study of ovarian cancer. They identify new susceptibility loci for different epithelial ovarian cancer histotypes and use integrated analyses of genes and regulatory features at each locus to predict candidate susceptibility genes, including OBFC1. To identify common alleles associated with different histotypes of epithelial ovarian cancer (EOC), we pooled data from multiple genome-wide genotyping projects totaling 25,509 EOC cases and 40,941 controls. We identified nine new susceptibility loci for different EOC histotypes: six for serous EOC histotypes (3q28, 4q32.3, 8q21.11, 10q24.33, 18q11.2 and 22q12.1), two for mucinous EOC (3q22.3 and 9q31.1) and one for endometrioid EOC (5q12.3). We then performed meta-analysis on the results for high-grade serous ovarian cancer with the results from analysis of 31,448 BRCA1 and BRCA2 mutation carriers, including 3,887 mutation carriers with EOC. This identified three additional susceptibility loci at 2q13, 8q24.1 and 12q24.31. Integrated analyses of genes and regulatory biofeatures at each locus predicted candidate susceptibility genes, including OBFC1, a new candidate susceptibility gene for low-grade and borderline serous EOC.

25 January 2009 in Nature Genetics
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Rafael de CidRafael de Cid
Rafael de Cid
EREva Riveira-Munoz
Eva Riveira-Munoz
PZPatrick Zeeuwen
Patrick Zeeuwen
JRJason Robarge
Jason Robarge
WLWilson Liao
Wilson Liao
XEXavier Estivill
Xavier Estivill

23 October 2017 in Nature Genetics
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AIABCTB Investigators
ABCTB Investigators
RMRoger L Milne
Roger L Milne
EMEmbrace
Embrace
GCGEMO Study Collaborators
GEMO Study Collaborators
HEHebon
Hebon
JSJacques Simard
Jacques Simard
Roger Milne and colleagues conduct a genome-wide association study for estrogen receptor (ER)-negative breast cancer combined with BRCA1 mutation carriers in a large cohort. They identify ten new risk variants and find high genetic correlation between breast cancer risk for BRCA1 mutation carriers and risk of ER-negative breast cancer in the general population. Most common breast cancer susceptibility variants have been identified through genome-wide association studies (GWAS) of predominantly estrogen receptor (ER)-positive disease1. We conducted a GWAS using 21,468 ER-negative cases and 100,594 controls combined with 18,908 BRCA1 mutation carriers (9,414 with breast cancer), all of European origin. We identified independent associations at P < 5 × 10−8 with ten variants at nine new loci. At P < 0.05, we replicated associations with 10 of 11 variants previously reported in ER-negative disease or BRCA1 mutation carrier GWAS and observed consistent associations with ER-negative disease for 105 susceptibility variants identified by other studies. These 125 variants explain approximately 16% of the familial risk of this breast cancer subtype. There was high genetic correlation (0.72) between risk of ER-negative breast cancer and breast cancer risk for BRCA1 mutation carriers. These findings may lead to improved risk prediction and inform further fine-mapping and functional work to better understand the biological basis of ER-negative breast cancer.

15 February 2018 in Human Mutation
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TRTimothy R. Rebbeck
Timothy R. Rebbeck
TFTara M. Friebel
Tara M. Friebel
EFEitan Friedman
Eitan Friedman
UHUte Hamann
Ute Hamann
DHDezheng Huo
Dezheng Huo
KNKatherine L. Nathanson
Katherine L. Nathanson