Couch, Fergus J.

Abstract Women who carry a pathogenic mutation in the BRCA1 or BRCA2 gene are at high risk of breast (BC) and ovarian cancer (OC). Their clinical management usually includes invasive risk-reducing interventions with substantial side effects. Improved personalized cancer risk estimates may help to identify women at particularly high risk or with high risk of disease at early ages who may benefit from early intervention as well as women at lower risk who may opt to delay surgery or chemoprevention. Genome-wide association studies have identified >100 common genetic variants that are associated with BC or OC risks. Several of these variants are also individually associated with risk of BC or OC for BRCA1 and BRCA2 mutation carriers. However, no study has evaluated the combined effects of all the known common genetic variants on BC or OC risk for BRCA1/2 mutation carriers. We constructed polygenic risk scores (PRS) based on results of genetic association studies conducted in the general population. Each PRS was formed by the sum of the number of risk alleles across the variants weighted by their log-Odds Ratio estimate from population-based studies of BC or OC. We investigated 3 PRS for BC (overall, estrogen receptor (ER) positive, and ER-negative) and one PRS for OC. We used data for 15,252 BRCA1 and 8,211 BRCA2 female carriers. The association of each PRS with BC or OC risk was evaluated using a weighted cohort analysis with time to diagnosis as the outcome and estimated the Hazard Ratios (HR) per standard deviation increase in the PRS. All PRS were significantly associated with cancer risks for BRCA1/2 carriers. The PRS for ER-negative BC displayed the strongest association with BC risk in BRCA1 carriers (HR = 1.29 [1.25-1.33], p = 8×10−64). In BRCA2 carriers, the strongest association was seen for the overall BC PRS (HR = 1.26 [1.21-1.31], p = 3×10−27). The OC PRS was strongly associated with OC risk for both BRCA1 and BRCA2 carriers. These relative risks translate to large differences in absolute risks for carriers: e.g., the OC risk was 6% by age 80 for BRCA2 carriers at the 10th percentile of the OC PRS compared with 19% risk for those at the 90th percentile of PRS. Our findings demonstrate that BC and OC PRS derived from studies in the general population are predictive of cancer risks in BRCA1 and BRCA2 carriers. Incorporation of the PRS into risk prediction models would improve risk prediction and hence inform decisions on cancer risk management. Citation Format: Karoline Kuchenbaecker, Jacques Simard, Kenneth Offit, Fergus J. Couch, Douglas F. Easton, Georgia Chenevix-Trench, Antonis C. Antoniou, Consortium of Investigators of Modifiers of BRCA1/2. Predicting breast and ovarian cancer risks for BRCA1 and BRCA2 mutation carriers using polygenic risk scores. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 2598.

Abstract Multigene panel testing (MGPT) for hereditary cancer is increasing in popularity in the USA. Many panels include genes identified as hereditary breast and/or ovarian cancer (HBOC) genes despite limited data regarding the precise cancer risks associated with mutations in these genes. Here we report on results from BreastNext and OvaNext panel testing of 20 genes (ATM, BARD1, BRCA1, BRCA2, BRIP1, CDH1, CHEK2, MLH1, MRE11A, MSH2, MSH6, NBN, NF1, PALB2, PMS2, PTEN, RAD50, RAD51C, RAD51D, TP53) in a cohort of 15,083 individuals. The majority of individuals were from high-risk breast and/or ovarian (Br/Ov) cancer families, with 92.4% of all probands meeting National Comprehensive Cancer Network HBOC testing criteria. Pathogenic mutations were identified in 9.4% of the overall cohort. To estimate gene-specific breast and ovarian cancer risks, case-control analyses were performed comparing the frequencies of pathogenic mutations from Caucasian breast or ovarian cancer cases from BreastNext and OvaNext with frequencies from Caucasian, non-Finnish, non-TCGA controls from the Exome Aggregation Consortium (ExAC) database. Mutations in the well studied ATM and CHEK2 genes were associated with moderate risks (OR>2) of breast cancer and mutations in PALB2 were associated with high-risks (OR>5) of breast cancer, consistent with previous reports. In addition, the study suggested that pathogenic mutations in MSH6, RAD51D, CDH1, and NF1 are associated with moderate to high risks of breast cancer. In contrast, RAD51C, RAD51D, and BRIP1 mutations were associated with high risks of ovarian cancer, PALB2 mutations were associated with moderate risks, but ATM and CHEK2 mutations were not associated with increased ovarian cancer risk. In addition, modeling of missense mutations in the predisposition genes using in silico prediction algorithms suggested that missense mutations in CDH1, CHEK2, MSH2, and MSH6 are associated with moderate risks of breast cancer and missense mutations in RAD51C increase risks of ovarian cancer. This large breast and ovarian cancer case-control analysis provides useful data for many predisposition genes previously lacking risk estimates, and should prove useful for clinical risk management of patients after clinical panel testing. Citation Format: Fergus J. Couch, David E. Goldgar, Steven N. Hart, Emily Hallberg, Raymond Moore, Huong Meeks, Robert Huether, Holly LaDuca, Elizabeth Chao, Jill Dolinsky. Breast and ovarian cancer risks associated with cancer predisposition gene mutations identified by multigene panel testing. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 2597.

Abstract Percent mammographic density (PMD) is a risk factor for estrogen receptor (ER)-positive and ER-negative invasive breast cancer (BC). Gene expression profiling has identified molecular signatures that classify invasive BC into distinct subtypes that vary in their clinical behavior, response to treatment and likely, etiology. Immunohistochemical (IHC) staining of tumor sections using antibody panels can be used to classify these ‘intrinsic’ molecular subtypes. We evaluated whether density measures [PMD, absolute dense area (DA) and non-dense area (NDA)], are associated equally with all ‘intrinsic’ molecular subtypes. Pooled analysis of six cohort or case-control studies included 3492 women with invasive BC and 10,148 without, who underwent screening mammography a median 4 years prior to diagnosis (for cases). PMD, DA, and NDA were assessed from digitized film-screen mammograms using a computer-assisted thresholding technique, and categorized as 0-10%, 11-25%, 26-50% and 51%+ (PMD) or into quartiles (DA and NDA). Receptor status was abstracted from pathology records and supplemented by IHC staining. We classified tumors as Luminal A (ER+ and/or PR+ and HER2- and grade 1 or 2), Luminal B (ER+ and/or PR+ and HER2+ or Luminal A and grade 3), HER2 expressing (HER2+/ER-/PR-) and triple negative (TN) (ER-/PR-/HER2-). For TN, we also differentiated basal-like tumors (positive for EGFR and/or CK 5/6) from unclassified (negative on both markers). We used polytomous logistic regression to calculate the odds ratio (OR) of each ‘intrinsic’ subtype of BC by categories of PMD, DA or NDA, adjusting for age, body mass index and study. We tested for statistical heterogeneity of associations by subtype. Of 3492 invasive BC cases, 2217 (63%) were classified as Luminal A, 747 (21%) as Luminal B, 159 (5%) as HER2 expressing, and 369 (11%) as TN. Of TN, 203 were evaluated for CK 5/6 and EGFR, with 167 (82%) classified as basal-like and 36 (18%) unclassified. PMD was associated with BC risk across all subtypes. For Luminal A, compared to women with 11-25% PMD (reference), women with 0-10% had a reduced risk of BC (OR = 0.63 [95% confidence interval: 0.55, 0.74]) while women with 26-50% had an OR = 1.5 [1.3, 1.7] and women with 51%+ had the highest risk, OR = 2.3 [2.0, 2.7]. Similar BC associations were seen across PMD categories when comparing the five subtypes (P-heterogeneity = 0.63). Similar trends were seen for DA and BC across the five subtypes (P-het = 0.25). NDA was inversely associated with BC across subtypes, and there was suggestion of a stronger inverse trend among HER2-expressing BC compared to other subtypes (P-het = 0.09). Our results suggest mammographic density measures are associated with all ‘intrinsic’ molecular subtypes. However, NDA may be more strongly inversely associated with HER2-expressing than other subtypes. Understanding the importance of density measures for BC subtypes has significance for subtype-specific risk models. Citation Format: Aaron D. Norman, Rulla M. Tamimi, Christopher G. Scott, Kimberly A. Bertrand, Matthew R. Jensen, Daniel W. Visscher, Fergus J. Couch, John Shepherd, Bo Fan, Yunn-Yi Chen, Lin Ma, Andrew Beck, Vernon S. Pankratz, Karla Kerlikowske, Celine M. Vachon. Association of mammographic density measures and breast cancer ‘intrinsic’ molecular subtypes. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 2593.

Abstract Breast, ovarian, and prostate cancers are hormone-related and may have a shared genetic basis, but this has not been investigated systematically by genome-wide association (GWA) studies. Meta-analyses combining the largest GWA meta-analysis data sets for these cancers totaling 112,349 cases and 116,421 controls of European ancestry, all together and in pairs, identified at P < 10−8 seven new cross-cancer loci: three associated with susceptibility to all three cancers (rs17041869/2q13/BCL2L11; rs7937840/11q12/INCENP; rs1469713/19p13/GATAD2A), two breast and ovarian cancer risk loci (rs200182588/9q31/SMC2; rs8037137/15q26/RCCD1), and two breast and prostate cancer risk loci (rs5013329/1p34/NSUN4; rs9375701/6q23/L3MBTL3). Index variants in five additional regions previously associated with only one cancer also showed clear association with a second cancer type. Cell-type–specific expression quantitative trait locus and enhancer–gene interaction annotations suggested target genes with potential cross-cancer roles at the new loci. Pathway analysis revealed significant enrichment of death receptor signaling genes near loci with P < 10−5 in the three-cancer meta-analysis. Significance: We demonstrate that combining large-scale GWA meta-analysis findings across cancer types can identify completely new risk loci common to breast, ovarian, and prostate cancers. We show that the identification of such cross-cancer risk loci has the potential to shed new light on the shared biology underlying these hormone-related cancers. Cancer Discov; 6(9); 1052–67. ©2016 AACR. This article is highlighted in the In This Issue feature, p. 932

Abstract Gene expression profiling has identified molecular subtypes that classify invasive breast cancers into distinct categories that vary in their clinical behavior and response to treatment. These subtypes highlight the many possible biologically and clinically distinct types of breast cancer. Immunohistochemical (IHC) staining of tumor sections using antibody panels has been used as a surrogate for the molecular subtypes identified through gene expression profiling, resulting in a set of intrinsic molecular subtypes. Given the heterogeneity within breast cancer, one might expect that different risk factors influence specific subtypes of breast cancer through various etiologic pathways. We evaluated whether percent mammographic density (MD), the proportion of fibroglandular or white tissue on a mammogram and one of the strongest and most consistent risk factors for breast cancer, is associated equally with all intrinsic molecular subtypes. Data were pooled from six cohort or case-control studies including 3389 women with invasive breast cancer and 9860 without, who underwent screening mammography. Percent MD was assessed from digitized film-screen mammograms (for cases, at a median 4 years prior to diagnosis) using a computer-assisted threshold technique, and categorized as 0-10%, 11-25%, 26-50% and 51%+. Receptor status was abstracted from clinical pathology records and supplemented by IHC staining of tumor sections or microarrays. With estrogen receptor (ER), progesterone receptor (PR) and human epidermal growth factor receptor (HER2) information, we classified tumors into the intrinsic molecular subtypes: Luminal A ( ER+ and/or PR+ and HER2- and grade 1 or 2), Luminal B (ER+ and/or PR+ and HER2+ or Luminal A and grade 3), HER2 expressing (HER2+/ER-/PR-) and triple negative (ER-/PR-/HER2-). For cancers found to be triple negative (TN), we also stained for epidermal growth factor receptor (EGFR) and cytokeratins (CK) 5/6 to differentiate basal-like tumors (positive for EGFR and/or CK 5/6) from the unclassifieds (negative on both EGFR and CK 5/6). We used polytomous logistic regression to calculate the odds (OR) of each of the intrinsic subtypes of breast cancer by categories of percent MD, adjusting for age, BMI and study. Contrasts were constructed and tested within the polytomous model framework to investigate differences in the strength of association of percent MD across subtypes. On average, cases were slightly older (56.4 years [SD=11.3]) than controls (55.8 [10.9]). Of the 3389 invasive breast cancer cases, 2146 (63%) were classified as Luminal A, 709 (21%) as Luminal B, 169 (5%) as HER-2 expressing, and 365(11%) as triple negative (TN). Of the TN tumors, 203 had tumor tissue available and were evaluated for CK 5/6 and EGFR, with 167 (82%) classified as basal-like and 36 (18%) as unclassified. Percent (%) MD was associated with breast cancer risk across all intrinsic subtypes. For Luminal A, compared to women with 11-25% MD (reference), women with 0-10% MD had a reduced risk of breast cancer (OR=0.64 [95% confidence interval (CI): 0.55, 0.74]) while women with 26-50% MD had an OR=1.5 (1.3,1.7) and women with 51%+ MD had the highest risk, OR=2.4 (2.0, 2.8). Similar associations were seen for Luminal B, HER2 expressing, and TN across percent MD categories. The small differences among the percent MD-breast cancer associations observed for the different subtypes were not statistically significant, either when comparing the four (Luminal A, Luminal B, HER-2 expressing and TN; p=0.61) or five categories of subtypes (Luminal A, Luminal B, HER-2 expressing, basal-like, unclassified; p=0.66). Our results suggest percent MD is a risk factor for all intrinsic molecular subtypes. Additional study is needed to examine whether these results hold for younger and older aged women. Understanding the importance of mammographic density measures for subtypes of breast cancer has significance for development of subtype-specific risk models. Citation Format: Celine Vachon, Rulla Tamimi, Yunn-Yi Chen, Christopher Scott, Kimberly Bertrand, Matthew Jensen, Daniel Visscher, Aaron Norman, Fergus Couch, John Shepherd, Bo Fan, Fang-Fang Wu, Lin Ma, Andrew Beck, Steve Cummings, V. Shane Pankratz, Karla Kerlikowske. Mammographic density: A risk factor for all breast cancers or only specific subtypes? [abstract]. In: Proceedings of the Eighth AACR Conference on The Science of Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; Nov 13-16, 2015; Atlanta, GA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2016;25(3 Suppl):Abstract nr IA22.

Abstract Background: Mutations in BRCA1 and BRCA2 influence the molecular pathogenesis of breast cancer. However, little is known about the association between mutations, response to therapy, and prognosis. We therefore analysed these associations in triple negative breast cancer (TNBC) patients in the neoadjuvant GeparQuinto Study. Methods: The GeparQuinto study recruited 1956 patients with HER2 negative disease including a prespecified group of 671 TNBC patients with untreated breast cancer. Patients were randomized to receive four cycles EC (90/600 mg/m2; q3w) followed by four cycles docetaxel (100 mg/m2; q3w), with or without bevacizumab (15 mg/kg). Here we present the analysis for both randomization arms combined. Sufficient blood was available of 482 TNBC patients. BRCA1 and BRCA2 genotyping was successful in 469 patients with available germline DNA and was conducted by SureSelect custom capture and sequencing on HiSeq 2500. Mutation status was correlated with pathological complete response rates (pCR) and disease free survival (DFS). Results: A total of 74 (15.8%) mutations in BRCA1 (n=61) and BRCA2 (n=13) were detected after initial sequencing. A pCR (ypT0/ypN0) was observed in 50% (n=37) of mutation carriers but only 31.1% (n=123) of patients without mutations (p=0.002). Similar results were observed for pCR (pT0is/pN0) (52.7% vs. 36.5%; p=0.010). pCR (ypT0/ypN0) was predictive of disease free survival (DFS) in all patients (Hazard Ratio, HR=0.23; 95%CI: 0.15-0.37; p<0.001) and in patients without BRCA mutations pCR (ypT0/ypN0) (HR= 0.20; 95%CI: 0.11-0.34; p<0.001). However in mutation carriers this effect was reduced (HR=0.48; 95%CI: 0.18 1.27; p=0.129). Conclusion: TNBC Patients with BRCA mutations showed a higher frequency of pCR than patients without BRCA mutations after treatment with epirubicin, cyclophosphamide and docetaxel (+/ bevacizumab), suggesting that BRCA mutations may influence pCR in response to treatment regimens that do not include platin chemotherapy. pCR as a surrogate marker for DFS was also confirmed in patients without BRCA mutations. In addition, the effect of pCR on prognosis seemed to be smaller among the mutation carriers, although the number of mutation carriers was too low to test for differences between mutation carriers and wildtype patients. The project has partly been funded within NIH-NIGMS U19 GM61388 and the Breast Cancer Research Foundation. Citation Format: Fasching PA, Loibl S, Eidtmann H, Tesch H, Untch M, Hilfrich J, Schem C, Rezai M, Gerber B, Costa SD, Blohmer JU, Fehm TN, Huober J, Liedtke C, Müller V, Nekljudova V, Weber K, Rack B, Rübner M, Wang L, Ingle JN, Weinshilboum RM, von Minckwitz G, Couch F. BRCA mutations, therapy response and prognosis in the neoadjuvant GeparQuinto study. [abstract]. In: Proceedings of the Thirty-Eighth Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2015 Dec 8-12; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2016;76(4 Suppl):Abstract nr S5-06.

Abstract Background: Chemotherapy-related amenorrhea (CRA) impacts quality of life and reproductive options, and may play a role in treatment decision-making for young breast cancer patients. Although age, increasing doses of alkylating agents, and tamoxifen are known to increase the risk of chemotherapy-related amenorrhea (CRA), it is difficult to predict which women will develop CRA in order to inform fertility preservation and treatment decisions. We sought to investigate whether single nucleotide polymorphisms (SNPs) that have been associated with a younger age at natural menopause and ovarian reserve in non-oncologic populations were predictive of CRA in two large German clinical trials that administered gonadotoxic chemotherapy. Methods: A total of 1322 premenopausal participants under age 50 who enrolled in SUCCESS B (a phase 3 trial of FEC-docetaxel-trastuzumab +/- gemcitabine for high risk early stage breast cancer) or SUCCESS C (a phase 3 trial of FEC-docetaxel-cyclophosphamide vs. docetaxel-cyclophosphamide that also tested the efficacy of a weight loss intervention in early stage breast cancer patients) were eligible for this study. We excluded patients who were receiving ovarian suppression. On these trials, menstrual status was self-reported as amenorrheic or not every three months after chemotherapy. Bloods were stored and patients provided consent for DNA analysis. We genotyped nine candidate SNPs in six genes (rs2002555 and rs11170547 in AMHR2, rs6166 in FSHR, rs10852344 <60kb from TNFRSF17/RUNDC2A/ GSPT1, rs12461110 in NLRP11, rs1801133 in MTHFR, rs2066470 in MTHRF, rs3810682 in BMP15, and rs615942 in COASY), and examined their association with CRA at 12-month and 24-month time points using logistic regression adjusted for age, BMI, and tamoxifen. Results: Of the 554 eligible women with SNP data and menstrual data at 12 months, 70% reported CRA; of the 458 eligible women with SNP data and menstrual data at 24 months, 69% reported CRA. The two SNPs in AMHR2 showed suggestive associations with CRA at 12 and 24 months. [Final results pending]. Conclusions: Genetic variation in AMHR2 may be associated with CRA. Additional research will be needed to validate these findings in other breast cancer survivors and to identify additional SNPs that may be associated with CRA. Together with other clinical factors, genetic variation may improve our ability to predict who will experience CRA, and may inform reproductive and treatment decision-making in cancer patients. Citation Format: Ruddy KJ, Rack B, Schwitulla J, Lambrechts D, Haeberle L, Schramm A, Trapp E, Scholz C, Beutler AS, Ginsburg E, Couch F, Partridge AH, Wang L, Weinshilboum RM, Janni W, Vachon C, Fasching P. Genetic predictors of chemotherapy-related amenorrhea. [abstract]. In: Proceedings of the Thirty-Eighth Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2015 Dec 8-12; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2016;76(4 Suppl):Abstract nr P4-10-07.

Background BRCA1 interacting protein C-terminal helicase 1 (BRIP1) is one of the Fanconi Anaemia Complementation (FANC) group family of DNA repair proteins. Biallelic mutations in BRIP1 are responsible for FANC group J, and previous studies have also suggested that rare protein truncating variants in BRIP1 are associated with an increased risk of breast cancer. These studies have led to inclusion of BRIP1 on targeted sequencing panels for breast cancer risk prediction. Methods We evaluated a truncating variant, p.Arg798Ter (rs137852986), and 10 missense variants of BRIP1, in 48 144 cases and 43 607 controls of European origin, drawn from 41 studies participating in the Breast Cancer Association Consortium (BCAC). Additionally, we sequenced the coding regions of BRIP1 in 13 213 cases and 5242 controls from the UK, 1313 cases and 1123 controls from three population-based studies as part of the Breast Cancer Family Registry, and 1853 familial cases and 2001 controls from Australia. Results The rare truncating allele of rs137852986 was observed in 23 cases and 18 controls in Europeans in BCAC (OR 1.09, 95% CI 0.58 to 2.03, p=0.79). Truncating variants were found in the sequencing studies in 34 cases (0.21%) and 19 controls (0.23%) (combined OR 0.90, 95% CI 0.48 to 1.70, p=0.75). Conclusions These results suggest that truncating variants in BRIP1, and in particular p.Arg798Ter, are not associated with a substantial increase in breast cancer risk. Such observations have important implications for the reporting of results from breast cancer screening panels.

Previous genome‐wide association studies among women of European ancestry identified two independent breast cancer susceptibility loci represented by single nucleotide polymorphisms (SNPs) rs13281615 and rs11780156 at 8q24. A fine‐mapping study across 2.06 Mb (chr8:127,561,724–129,624,067, hg19) in 55,540 breast cancer cases and 51,168 controls within the Breast Cancer Association Consortium was conducted. Three additional independent association signals in women of European ancestry, represented by rs35961416 (OR = 0.95, 95% CI = 0.93–0.97, conditional p = 5.8 × 10−6), rs7815245 (OR = 0.94, 95% CI = 0.91–0.96, conditional p = 1.1 × 10−6) and rs2033101 (OR = 1.05, 95% CI = 1.02–1.07, conditional p = 1.1 × 10−4) were found. Integrative analysis using functional genomic data from the Roadmap Epigenomics, the Encyclopedia of DNA Elements project, the Cancer Genome Atlas and other public resources implied that SNPs rs7815245 in Signal 3, and rs1121948 in Signal 5 (in linkage disequilibrium with rs11780156, r2 = 0.77), were putatively functional variants for two of the five independent association signals. The results highlighted multiple 8q24 variants associated with breast cancer susceptibility in women of European ancestry.

AbstractAutomated methods are needed to facilitate high‐throughput and reproducible scoring of Ki67 and other markers in breast cancer tissue microarrays (TMAs) in large‐scale studies. To address this need, we developed an automated protocol for Ki67 scoring and evaluated its performance in studies from the Breast Cancer Association Consortium. We utilized 166 TMAs containing 16,953 tumour cores representing 9,059 breast cancer cases, from 13 studies, with information on other clinical and pathological characteristics. TMAs were stained for Ki67 using standard immunohistochemical procedures, and scanned and digitized using the Ariol system. An automated algorithm was developed for the scoring of Ki67, and scores were compared to computer assisted visual (CAV) scores in a subset of 15 TMAs in a training set. We also assessed the correlation between automated Ki67 scores and other clinical and pathological characteristics. Overall, we observed good discriminatory accuracy (AUC = 85%) and good agreement (kappa = 0.64) between the automated and CAV scoring methods in the training set. The performance of the automated method varied by TMA (kappa range= 0.37–0.87) and study (kappa range = 0.39–0.69). The automated method performed better in satisfactory cores (kappa = 0.68) than suboptimal (kappa = 0.51) cores (p‐value for comparison = 0.005); and among cores with higher total nuclei counted by the machine (4,000–4,500 cells: kappa = 0.78) than those with lower counts (50–500 cells: kappa = 0.41; p‐value = 0.010). Among the 9,059 cases in this study, the correlations between automated Ki67 and clinical and pathological characteristics were found to be in the expected directions. Our findings indicate that automated scoring of Ki67 can be an efficient method to obtain good quality data across large numbers of TMAs from multicentre studies. However, robust algorithm development and rigorous pre‐ and post‐analytical quality control procedures are necessary in order to ensure satisfactory performance.