Skip to main content
Key Specialties
Cardiology Diabetology Endocrinology Gastroenterology Geriatrics and Gerontology Gynecology and Obstetrics Hematology Infectious Disease Internal Medicine Nephrology Neurology Oncology Pediatrics Respiratory Medicine Rheumatology Surgery
Congress Coverage
2024 ACC Congress 2023 ESMO Congress 2023 EASD Congress 2023 ERS Congress 2023 ESC Congress
Clinical Collections
Advances in Alzheimer’s

At a glance: The STEP trials

A round-up of the STEP phase 3 clinical trials evaluating semaglutide for weight loss in people with overweight or obesity.
ADVANCED SEARCH
Log in
Top
Breast Cancer Research and Treatment
Published in: Breast Cancer Research and Treatment 2/2017

01-01-2017 | Epidemiology

Previous GWAS hits in relation to young-onset breast cancer

Authors: Min Shi, Katie M. O’Brien, Dale P. Sandler, Jack A. Taylor, Dmitri V. Zaykin, Clarice R. Weinberg

Published in: Breast Cancer Research and Treatment | Issue 2/2017

Login to get access

Abstract

Purpose

Genome-wide association studies (GWAS) have identified dozens of single-nucleotide polymorphisms (SNPs) associated with breast cancer. Few studies focused on young-onset breast cancer, which exhibits etiologic and tumor-type differences from older-onset disease. Possible confounding by prenatal effects of the maternal genome has also not been considered.

Methods

Using a family-based design for breast cancer before age 50, we assessed the relationship between breast cancer and 77 GWAS-identified breast cancer risk SNPs. We estimated relative risks (RR) for inherited and maternally mediated genetic effects. We also used published RR estimates to calculate genetic risk scores and model joint effects.

Results

Seventeen of the candidate SNPs were nominally associated with young-onset breast cancer in our 1296 non-Hispanic white affected families (uncorrected p value <0.05). Top-ranked SNPs included rs3803662-A (TOX3, RR = 1.39; p = 7.0 × 10−6), rs12662670-G (ESR1, RR = 1.56; p = 5.7 × 10−4), rs2981579-A (FGFR2, RR = 1.24; p = 0.002), and rs999737-G (RAD51B, RR = 1.37; p = 0.003). No maternally mediated effects were found. A risk score based on all 77 SNPs indicated that their overall relationship to young-onset breast cancer risk was more than additive (additive-fit p = 2.2 × 10−7) and consistent with a multiplicative joint effect (multiplicative-fit p = 0.27). With the multiplicative formulation, the case sister’s genetic risk score exceeded that of her unaffected sister in 59% of families.

Conclusions

The results of this family-based study indicate that no effects of previously identified risk SNPs were explained by prenatal effects of maternal variants. Many of the known breast cancer risk variants were associated with young-onset breast cancer, with evidence that TOX3, ESR1, FGFR2, and RAD51B are important for young-onset disease.
Appendix
Available only for authorised users
Literature
1.
Ahsan H, Halpern J, Kibriya MG, Pierce BL, Tong L, Gamazon E et al (2014) A genome-wide association study of early-onset breast cancer identifies PFKM as a novel breast cancer gene and supports a common genetic spectrum for breast cancer at any age. Cancer Epidemiol Biomark Prev 23(4):658–669CrossRef
2.
Antoniou AC, Wang X, Fredericksen ZS, McGuffog L, Tarrell R, Sinilnikova OM et al (2010) A locus on 19p13 modifies risk of breast cancer in BRCA1 mutation carriers and is associated with hormone receptor-negative breast cancer in the general population. Nat Genet 42(10):885–892CrossRefPubMedPubMedCentral
3.
Cai Q, Long J, Lu W, Qu S, Wen W, Kang D et al (2011) Genome-wide association study identifies breast cancer risk variant at 10q21.2: results from the Asia Breast Cancer Consortium. Hum Mol Genet 20(24):4991–4999CrossRefPubMedPubMedCentral
4.
Cai Q, Zhang B, Sung H, Low SK, Kweon SS, Lu W et al (2014) Genome-wide association analysis in East Asians identifies breast cancer susceptibility loci at 1q32.1, 5q14.3 and 15q26.1. Nat Genet 46(8):886–890CrossRefPubMedPubMedCentral
5.
Chen F, Chen GK, Stram DO, Millikan RC, Ambrosone CB, John EM et al (2013) A genome-wide association study of breast cancer in women of African ancestry. Hum Genet 132(1):39–48CrossRefPubMed
6.
Couch FJ, Wang X, McGuffog L, Lee A, Olswold C, Kuchenbaecker KB et al (2013) Genome-wide association study in BRCA1 mutation carriers identifies novel loci associated with breast and ovarian cancer risk. PLoS Genet 9(3):e1003212CrossRefPubMedPubMedCentral
7.
Easton DF, Pooley KA, Dunning AM, Pharoah PD, Thompson D, Ballinger DG et al (2007) Genome-wide association study identifies novel breast cancer susceptibility loci. Nature 447(7148):1087–1093CrossRefPubMedPubMedCentral
8.
Elgazzar S, Zembutsu H, Takahashi A, Kubo M, Aki F, Hirata K et al (2012) A genome-wide association study identifies a genetic variant in the SIAH2 locus associated with hormonal receptor-positive breast cancer in Japanese. J Hum Genet 57(12):766–771CrossRefPubMed
9.
Fejerman L, Ahmadiyeh N, Hu D, Huntsman S, Beckman KB, Caswell JL et al (2014) Genome-wide association study of breast cancer in Latinas identifies novel protective variants on 6q25. Nat Commun 5:5260CrossRefPubMedPubMedCentral
10.
Fletcher O, Johnson N, Orr N, Hosking FJ, Gibson LJ, Walker K et al (2011) Novel breast cancer susceptibility locus at 9q31.2: results of a genome-wide association study. J Natl Cancer Inst 103(5):425–435CrossRefPubMed
11.
Garcia-Closas M, Couch FJ, Lindstrom S, Michailidou K, Schmidt MK, Brook MN et al (2013) Genome-wide association studies identify four ER negative-specific breast cancer risk loci. Nat Genet 45(4):392–398CrossRefPubMedPubMedCentral
12.
Gaudet MM, Kirchhoff T, Green T, Vijai J, Korn JM, Guiducci C et al (2010) Common genetic variants and modification of penetrance of BRCA2-associated breast cancer. PLoS Genet 6(10):e1001183CrossRefPubMedPubMedCentral
13.
Gold B, Kirchhoff T, Stefanov S, Lautenberger J, Viale A, Garber J et al (2008) Genome-wide association study provides evidence for a breast cancer risk locus at 6q22.33. Proc Natl Acad Sci USA 105(11):4340–4345CrossRefPubMedPubMedCentral
14.
Haiman CA, Chen GK, Vachon CM, Canzian F, Dunning A, Millikan RC et al (2011) A common variant at the TERT-CLPTM1L locus is associated with estrogen receptor-negative breast cancer. Nat Genet 43(12):1210–1214CrossRefPubMedPubMedCentral
15.
Hunter DJ, Kraft P, Jacobs KB, Cox DG, Yeager M, Hankinson SE et al (2007) A genome-wide association study identifies alleles in FGFR2 associated with risk of sporadic postmenopausal breast cancer. Nat Genet 39(7):870–874CrossRefPubMedPubMedCentral
16.
Kibriya MG, Jasmine F, Argos M, Andrulis I, John EM, Chang-Claude J et al (2009) A pilot genome-wide association study of early-onset breast cancer. Breast Cancer Res Treat 114(3):463–467CrossRefPubMed
17.
Kim HC, Lee JY, Sung H, Choi JY, Park SK, Lee KM et al (2012) A genome-wide association study identifies a breast cancer risk variant in ERBB4 at 2q34: results from the Seoul Breast Cancer Study. Breast Cancer Res 14(2):R56CrossRefPubMedPubMedCentral
18.
Li J, Humphreys K, Darabi H, Rosin G, Hannelius U, Heikkinen T et al (2010) A genome-wide association scan on estrogen receptor-negative breast cancer. Breast Cancer Res 12(6):R93CrossRefPubMedPubMedCentral
19.
Li J, Humphreys K, Heikkinen T, Aittomaki K, Blomqvist C, Pharoah PD et al (2011) A combined analysis of genome-wide association studies in breast cancer. Breast Cancer Res Treat 126(3):717–727CrossRefPubMed
20.
Long J, Cai Q, Shu XO, Qu S, Li C, Zheng Y et al (2010) Identification of a functional genetic variant at 16q12.1 for breast cancer risk: results from the Asia Breast Cancer Consortium. PLoS Genet 6(6):e1001002CrossRefPubMedPubMedCentral
21.
Long J, Cai Q, Sung H, Shi J, Zhang B, Choi JY et al (2012) Genome-wide association study in east Asians identifies novel susceptibility loci for breast cancer. PLoS Genet 8(2):e1002532CrossRefPubMedPubMedCentral
22.
Low SK, Takahashi A, Ashikawa K, Inazawa J, Miki Y, Kubo M et al (2013) Genome-wide association study of breast cancer in the Japanese population. PLoS ONE 8(10):e76463CrossRefPubMedPubMedCentral
23.
Michailidou K, Hall P, Gonzalez-Neira A, Ghoussaini M, Dennis J, Milne RL et al (2013) Large-scale genotyping identifies 41 new loci associated with breast cancer risk. Nat Genet 45(4):353–361CrossRefPubMedPubMedCentral
24.
Murabito JM, Rosenberg CL, Finger D, Kreger BE, Levy D, Splansky GL et al (2007) A genome-wide association study of breast and prostate cancer in the NHLBI’s Framingham Heart Study. BMC Med Genet 8(Suppl 1):S6CrossRefPubMedPubMedCentral
25.
Purrington KS, Slager S, Eccles D, Yannoukakos D, Fasching PA, Miron P et al (2014) Genome-wide association study identifies 25 known breast cancer susceptibility loci as risk factors for triple-negative breast cancer. Carcinogenesis 35(5):1012–1019CrossRefPubMed
26.
Rinella ES, Shao Y, Yackowski L, Pramanik S, Oratz R, Schnabel F et al (2013) Genetic variants associated with breast cancer risk for Ashkenazi Jewish women with strong family histories but no identifiable BRCA1/2 mutation. Hum Genet 132(5):523–536CrossRefPubMedPubMedCentral
27.
Sehrawat B, Sridharan M, Ghosh S, Robson P, Cass CE, Mackey JR et al (2011) Potential novel candidate polymorphisms identified in genome-wide association study for breast cancer susceptibility. Hum Genet 130(4):529–537CrossRefPubMedPubMedCentral
28.
Siddiq A, Couch FJ, Chen GK, Lindstrom S, Eccles D, Millikan RC et al (2012) A meta-analysis of genome-wide association studies of breast cancer identifies two novel susceptibility loci at 6q14 and 20q11. Hum Mol Genet 21(24):5373–5384CrossRefPubMedPubMedCentral
29.
Song C, Chen GK, Millikan RC, Ambrosone CB, John EM, Bernstein L et al (2013) A genome-wide scan for breast cancer risk haplotypes among African American women. PLoS ONE 8(2):e57298CrossRefPubMedPubMedCentral
30.
Stacey SN, Manolescu A, Sulem P, Rafnar T, Gudmundsson J, Gudjonsson SA et al (2007) Common variants on chromosomes 2q35 and 16q12 confer susceptibility to estrogen receptor-positive breast cancer. Nat Genet 39(7):865–869CrossRefPubMed
31.
Thomas G, Jacobs KB, Kraft P, Yeager M, Wacholder S, Cox DG et al (2009) A multistage genome-wide association study in breast cancer identifies two new risk alleles at 1p11.2 and 14q24.1 (RAD51L1). Nat Genet 41(5):579–584CrossRefPubMedPubMedCentral
32.
Turnbull C, Ahmed S, Morrison J, Pernet D, Renwick A, Maranian M et al (2010) Genome-wide association study identifies five new breast cancer susceptibility loci. Nat Genet 42(6):504–507CrossRefPubMedPubMedCentral
33.
Zheng W, Long J, Gao YT, Li C, Zheng Y, Xiang YB et al (2009) Genome-wide association study identifies a new breast cancer susceptibility locus at 6q25.1. Nat Genet 41(3):324–328CrossRefPubMedPubMedCentral
34.
Campa D, Kaaks R, Le Marchand L, Haiman CA, Travis RC, Berg CD et al (2011) Interactions between genetic variants and breast cancer risk factors in the breast and prostate cancer cohort consortium. J Natl Cancer Inst 103(16):1252–1263CrossRefPubMedPubMedCentral
35.
Hutter CM, Young AM, Ochs-Balcom HM, Carty CL, Wang T, Chen CT et al (2011) Replication of breast cancer GWAS susceptibility loci in the Women’s Health Initiative African American SHARe Study. Cancer Epidemiol Biomark Prev 20(9):1950–1959CrossRef
36.
O’Brien KM, Cole SR, Poole C, Bensen JT, Herring AH, Engel LS et al (2014) Replication of breast cancer susceptibility loci in whites and African Americans using a Bayesian approach. Am J Epidemiol 179(3):382–394CrossRefPubMed
37.
Reeves SG, Meldrum C, Groombridge C, Spigelman A, Suchy J, Kurzawski G et al (2012) DNA repair gene polymorphisms and risk of early onset colorectal cancer in Lynch syndrome. Cancer Epidemiol 36(2):183–189CrossRefPubMed
38.
Slattery ML, Baumgartner KB, Giuliano AR, Byers T, Herrick JS, Wolff RK (2011) Replication of five GWAS-identified loci and breast cancer risk among Hispanic and non-Hispanic white women living in the Southwestern United States. Breast Cancer Res Treat 129(2):531–539CrossRefPubMedPubMedCentral
39.
Zheng W, Cai Q, Signorello LB, Long J, Hargreaves MK, Deming SL et al (2009) Evaluation of 11 breast cancer susceptibility loci in African-American women. Cancer Epidemiol Biomarkers Prev 18(10):2761–2764CrossRefPubMedPubMedCentral
40.
Elematore I, Gonzalez-Hormazabal P, Reyes JM, Blanco R, Bravo T, Peralta O et al (2014) Association of genetic variants at TOX3, 2q35 and 8q24 with the risk of familial and early-onset breast cancer in a South-American population. Mol Biol Rep 41(6):3715–3722CrossRefPubMed
41.
Fu F, Wang C, Huang M, Song C, Lin S, Huang H (2012) Polymorphisms in second intron of the FGFR2 gene are associated with the risk of early-onset breast cancer in Chinese Han Women. Tohoku J Exp Med 226(3):221–229CrossRefPubMed
42.
Jara L, Gonzalez-Hormazabal P, Cerceno K, Di Capua GA, Reyes JM, Blanco R et al (2013) Genetic variants in FGFR2 and MAP3K1 are associated with the risk of familial and early-onset breast cancer in a South-American population. Breast Cancer Res Treat 137(2):559–569CrossRefPubMed
43.
Tapper W, Hammond V, Gerty S, Ennis S, Simmonds P, Collins A et al (2008) The influence of genetic variation in 30 selected genes on the clinical characteristics of early onset breast cancer. Breast Cancer Res 10(6):R108CrossRefPubMedPubMedCentral
44.
Anderson WF, Matsuno RK, Sherman ME, Lissowska J, Gail MH, Brinton LA et al (2007) Estimating age-specific breast cancer risks: a descriptive tool to identify age interactions. Cancer Causes Control 18(4):439–447CrossRefPubMed
45.
Michels KB, Xue F (2006) Role of birthweight in the etiology of breast cancer. Int J Cancer 119(9):2007–2025CrossRefPubMed
46.
Trentham-Dietz A, Sprague BL, Hampton JM, Miglioretti DL, Nelson HD, Titus LJ et al (2014) Modification of breast cancer risk according to age and menopausal status: a combined analysis of five population-based case-control studies. Breast Cancer Res Treat 145(1):165–175CrossRefPubMedPubMedCentral
47.
Van den Brandt PA, Spiegelman D, Yaun SS, Adami HO, Beeson L, Folsom AR et al (2000) Pooled analysis of prospective cohort studies on height, weight, and breast cancer risk. Am J Epidemiol 152:514–527CrossRefPubMed
48.
Collaborative Group on Hormonal Factors in Breast Cancer (2001) Familial breast cancer: collaborative reanalysis of individual data from 52 epidemiological studies including 58 209 women with breast cancer and 101 986 women without the disease. Lancet 358(9291):1389–1399CrossRef
49.
Althuis MD, Brogan DD, Coates RJ, Daling JR, Gammon MD, Malone K et al (2003) Breast cancers among very young premenopausal women (United States). Cancer Causes Control 14:151–160CrossRefPubMed
50.
Anders CK, Hsu DS, Broadwater G, Acharya CR, Foekens JA, Zhang Y et al (2008) Young age at diagnosis correlates with worse prognosis and defines a subset of breast cancers with shared patterns of gene expression. J Clin Oncol 26(20):3324–3330CrossRefPubMed
51.
Carey LA, Perou CM, Livasy CA, Dressler LG, Cowan D, Conway K et al (2006) Race, breast cancer subtypes, and survival in the Carolina Breast Cancer Study. JAMA 295(21):2492–2502CrossRefPubMed
52.
Broeks A, Schmidt MK, Sherman ME, Couch FJ, Hopper JL, Dite GS et al (2011) Low penetrance breast cancer susceptibility loci are associated with specific breast tumor subtypes: findings from the Breast Cancer Association Consortium. Hum Mol Genet 20(16):3289–3303CrossRefPubMedPubMedCentral
53.
Chan M, Ji SM, Liaw CS, Yap YS, Law HY, Yoon CS et al (2012) Association of common genetic variants with breast cancer risk and clinicopathological characteristics in a Chinese population. Breast Cancer Res Treat 136(1):209–220CrossRefPubMed
54.
Han W, Woo JH, Yu JH, Lee MJ, Moon HG, Kang D et al (2011) Common genetic variants associated with breast cancer in Korean women and differential susceptibility according to intrinsic subtype. Cancer Epidemiol Biomark Prev 20(5):793–798CrossRef
55.
O’Brien KM, Cole SR, Engel LS, Bensen JT, Poole C, Herring AH et al (2014) Breast cancer subtypes and previously established genetic risk factors: a bayesian approach. Cancer Epidemiol Biomark Prev 23(1):84–97CrossRef
56.
Rebbeck TR, DeMichele A, Tran TV, Panossian S, Bunin GR, Troxel AB et al (2009) Hormone-dependent effects of FGFR2 and MAP3K1 in breast cancer susceptibility in a population-based sample of post-menopausal African-American and European-American women. Carcinogenesis 30(2):269–274CrossRefPubMed
57.
Laird NM, Lange C (2006) Family-based designs in the age of large-scale gene-association studies. Nat Rev Genet 7(5):385–394CrossRefPubMed
58.
Weinberg CR, Wilcox AJ, Lie RT (1998) A log-linear approach to case-parent-triad data: assessing effects of disease genes that act either directly or through maternal effects and that may be subject to parental imprinting. Am J Hum Genet 62:969–978CrossRefPubMedPubMedCentral
59.
O’Brien KM, Shi M, Sandler DP, Taylor JA, Zaykin DV, Keller J et al (2016) A family-based, genome-wide association study of young-onset breast cancer: inherited variants and maternally mediated effects. Eur J Hum Genet
60.
Mavaddat N, Pharoah PD, Michailidou K, Tyrer J, Brook MN, Bolla MK et al (2015) Prediction of breast cancer risk based on profiling with common genetic variants. J Natl Cancer Inst 107(5):djv036CrossRefPubMedPubMedCentral
61.
The 1000 Genomes Project Consortium (2012) An integrated map of genetic variation from 1,092 human genomes. Nature 491(7422):56–65CrossRefPubMedCentral
62.
Delaneau O, Marchini J, Zagury JF (2012) A linear complexity phasing method for thousands of genomes. Nat Methods 9(2):179–181CrossRef
63.
Howie BN, Donnelly P, Marchini J (2009) A flexible and accurate genotype imputation method for the next generation of genome-wide association studies. PLoS Genet 5(6):e1000529CrossRefPubMedPubMedCentral
64.
Shi M, Umbach DM, Weinberg CR (2013) Case-sibling studies that acknowledge unstudied parents and permit the inclusion of unmatched individuals. Int J Epidemiol 42(1):298–307CrossRefPubMed
65.
66.
Dittmer S, Kovacs Z, Yuan SH, Siszler G, Kogl M, Summer H et al (2011) TOX3 is a neuronal survival factor that induces transcription depending on the presence of CITED1 or phosphorylated CREB in the transcriptionally active complex. J Cell Sci 124(Pt 2):252–260CrossRefPubMed
67.
Cowper-Sal R, Zhang X, Wright JB, Bailey SD, Cole MD, Eeckhoute J et al (2012) Breast cancer risk-associated SNPs modulate the affinity of chromatin for FOXA1 and alter gene expression. Nat Genet 4(11):1191–1198CrossRef
68.
Riaz M, Berns EM, Sieuwerts AM, Ruigrok-Ritstier K, de Weerd V, Groenewoud A et al (2012) Correlation of breast cancer susceptibility loci with patient characteristics, metastasis-free survival, and mRNA expression of the nearest genes. Breast Cancer Res Treat 133(3):843–851CrossRefPubMed
69.
Barzan D, Veldwijk MR, Herskind C, Li Y, Zhang B, Sperk E et al (2013) Comparison of genetic variation of breast cancer susceptibility genes in Chinese and German populations. Eur J Hum Genet 21(11):1286–1292CrossRefPubMedPubMedCentral
70.
ESR1 estrogen receptor 1 [Homo sapiens (human)] (Internet). 22 Dec 2015]
71.
Stevens KN, Vachon CM, Lee AM, Slager S, Lesnick T, Olswold C et al (2011) Common breast cancer susceptibility loci are associated with triple-negative breast cancer. Cancer Res 71(19):6240–6249CrossRefPubMedPubMedCentral
72.
Sun Y, Ye C, Guo X, Wen W, Long J, Gao YT et al (2015) Evaluation of potential regulatory function of breast cancer risk locus at 6q25.1. Carcinogenesis 37(2):163–168CrossRefPubMedPubMedCentral
73.
Jain VK, Turner NC (2012) Challenges and opportunities in the targeting of fibroblast growth factor receptors in breast cancer. Breast Cancer Res 14:208CrossRefPubMedPubMedCentral
74.
Kawase T, Matsuo K, Suzuki T, Hiraki A, Watanabe M, Iwata H et al (2009) FGFR2 intronic polymorphisms interact with reproductive risk factors of breast cancer: results of a case control study in Japan. Int J Cancer 125(8):1946–1952CrossRefPubMed
75.
Roy R, Chun J, Powell SN (2012) BRCA1 and BRCA2: different roles in a common pathway of genome protection. Nat Rev Cancer 12(1):68–78CrossRef
76.
Dong H, Gao Z, Li C, Wang J, Jin M, Rong H et al (2014) Analyzing 395,793 samples shows significant association between rs999737 polymorphism and breast cancer. Tumor Biol 35(6):6083–6087CrossRef
77.
Dite GS, MacInnis RJ, Bickerstaffe A, Dowty JG, Allman R, Apicella C et al (2015) Breast cancer risk prediction using clinical models and 77 independent risk-associated SNPs for women aged under 50 years: Australian Breast Cancer Family Registry. Cancer Epidemiol Biomark Prev 25(2):359–365CrossRef
78.
Kraft P (2008) Curses—winner’s and otherwise—in genetic epidemiology. Epidemiology 19(5):649–651 discussion 57-8 CrossRefPubMed
79.
Machiela MJ, Chen CY, Chen C, Chanock SJ, Hunter DJ, Kraft P (2011) Evaluation of polygenic risk scores for predicting breast and prostate cancer risk. Genet Epidemiol 35(6):506–514PubMedPubMedCentral
80.
Joshi AD, Lindstrom S, Husing A, Barrdahl M, VanderWeele TJ, Campa D et al (2014) Additive interactions between susceptibility single-nucleotide polymorphisms identified in genome-wide association studies and breast cancer risk factors in the Breast and Prostate Cancer Cohort Consortium. Am J Epidemiol 180(10):1018–1027CrossRefPubMedPubMedCentral
81.
Metadata
Title
Previous GWAS hits in relation to young-onset breast cancer
Authors
Min Shi
Katie M. O’Brien
Dale P. Sandler
Jack A. Taylor
Dmitri V. Zaykin
Clarice R. Weinberg
Publication date
01-01-2017
Publisher
Springer US
Published in
Breast Cancer Research and Treatment / Issue 2/2017
Print ISSN: 0167-6806
Electronic ISSN: 1573-7217
DOI
https://doi.org/10.1007/s10549-016-4053-z

Other articles of this Issue 2/2017

Breast Cancer Research and Treatment 2/2017 Go to the issue

Preclinical Study

Using machine learning to parse breast pathology reports

Epidemiology

Up to one-third of breast cancer cases in post-menopausal Mediterranean women might be avoided by modifying lifestyle habits: the EPIC Italy study

Preclinical study

Contribution of BRCA1 large genomic rearrangements to early-onset and familial breast/ovarian cancer in Pakistan

Rebuttal Letter

In reply to Kadri Altundag

Epidemiology

Discordance between original and central laboratories in ER and HER2 results in a diverse, population-based sample

Preclinical study

Endocan as a prognostic biomarker of triple-negative breast cancer
Webinar | 19-02-2024 | 17:30 (CET)

Keynote webinar | Spotlight on antibody–drug conjugates in cancer

Watch now

Antibody–drug conjugates (ADCs) are novel agents that have shown promise across multiple tumor types. Explore the current landscape of ADCs in breast and lung cancer with our experts, and gain insights into the mechanism of action, key clinical trials data, existing challenges, and future directions.

Dr. Véronique Diéras
Prof. Fabrice Barlesi
Developed by: Springer Medicine
Image Credits