Ki67 Expression and Its Association With Clinicopathological Factors and Intrinsic Subtypes of Male Breast Cancer in Uganda: A Cross-sectional Study

Molecular profiling of male breast cancer – Lost in translation?

Background: There has been a paradigm shift in the way we understand, classify, diagnose, and treat breast cancer in the last two decades, mainly due to breakthrough in the knowledge and understanding the biology of the disease. The panel of St. Gallen meeting proposed to classify tumors based on intrinsic subtypes based on the immune-histochemical pattern for therapeutic purposes. Each subtype is unique in incidence, biological behavior, survival outcome, and response to therapy. Aim: To analyze the relevance of intrinsic molecular subtypes of breast cancer with clinico-pathological features with regard to patient characteristics, disease biology, management, and outcome at 2 years follow-up. Materials and Methods: St. Gallen International Expert Consensus Recommendation 2011 was used for this study. Clinico-pathological features (age, stage of disease, histological type and grade, tumor size, lymph node status, and lympho-vascular invasion) were analyzed among the subgroups. Results: In our study, we had 64 (34.4%) luminal A, 37 (19.9%) luminal B HER2 negative, 6 (3.2%) luminal B HER2 positive, 33 (17.7%) HER2 enriched, and 46 (24.7%) triple negative breast cancer (TNBC). The disease free survival and overall survival at 2 years of follow-up was 92.2% and 100% in luminal A, 89.2% and 100% in luminal B HER2 negative, 83.3% in luminal B HER2 positive, 78.8% and 90.9% in HER2 enriched, and 71.8% and 80.4% in TNBC subgroups, respectively. Conclusion: Intrinsic subtyping with immunohistochemistry corresponds well with clinico-pathological features and outcomes. This helps in prognosticating the outcome and administration of appropriate adjuvant therapy.

Wide variability in breast cancer, between patients and within each individual neoplasm, adds confounding complexity to the treatment of the disease. In clinical practice, hormone receptor status has been used to classify breast tumours and to guide treatment. Modern classification systems should take the wide tumour heterogeneity into account to improve patient outcome. This article reviews the identification of the intrinsic molecular subtypes of breast cancer, their prognostic and therapeutic implications, and the impact of tumour heterogeneity on cancer progression and treatment. The possibility of functionally addressing tumour-specific characteristics in in vivo models to inform decisions for precision therapies is also discussed. Despite the robust breast tumour classification system provided by gene expression profiling, heterogeneity is also evident within these molecular portraits. A complicating factor in breast cancer classification is the process of selective clonality within developing neoplasms. Phenotypically and functionally distinct clones representing the intratumour heterogeneity might confuse molecular classification. Molecular portraits of the heterogeneous primary tumour might not necessarily reflect the subclone of cancer cells that causes the disease to relapse. Studies of reciprocal relationships between cancer cell subpopulations within developing tumours are therefore needed, and are possible only in genetically engineered mouse models or patient-derived xenograft models, in which the treatment-induced selection pressure on individual cell clones can be mimicked. In the future, more refined classifications, based on integration of information at several molecular levels, are required to improve treatment guidelines. Large-scale translational research efforts paved the way for identification of the intrinsic subtypes, and are still fundamental for ensuring future progress in cancer care.

BackgroundBreast cancer is a heterogeneous disease with many histological and molecular/intrinsic breast cancer subtypes. Intrinsic breast cancer subtypes include luminal A, luminal B, human epidermal growth factor receptor 2 (HER2/neu), and triple-negative subtypes. The intrinsic breast cancer typing is based on the expression of estrogen receptor (ER), progesterone receptor (PR), HER2/neu, and Ki67-labeling index. One of these patients' foremost prognostic factors upon surgical resection is a response to neoadjuvant chemotherapy. The presence of a pathologically complete response (pCR) indicates a favorable patient outcome compared with a pathologically partial response (pPR). In this study, we compared the neoadjuvant chemotherapy response in breast cancer in different intrinsic breast cancer subtypes.MethodologyIt was a retrospective cross-sectional study conducted in the Department of Histopathology, Liaquat National Hospital, from January 2019 to December 2022, over three years. A total of 287 post-neoadjuvant chemotherapy cases of breast cancer were included. Anthracyclines and taxanes, coupled with or without anti-HER2/neu therapy, have been used in the neoadjuvant chemotherapy treatment setting contingent upon the patients' HER2/neu status. The post-chemotherapy response was assessed pathologically and categorized into pCR and pPR.ResultsThe mean age of the patients was 47.90 ± 10.34 years, with a mean tumor size and Ki67 index of 5.36 ± 2.59 cm and 36.30 ± 22.14%, respectively. Invasive breast carcinoma of no special type (IBC-NST) made up 88.2% of cases, while grade 2 carcinomas made up 45.5%. The majority of tumors (42.7%) belonged to tumor (T) stage T2, and nodal metastasis was detected in 59.7% of patients. The intrinsic breast cancer subtypes luminal B (40.6%) and triple negative (33.3%) were the most prevalent, followed by luminal A (15.8%) and HER2/neu (10.3%). In 81 cases (24.5%), pCR was detected. The association of post-neoadjuvant chemotherapy response with intrinsic breast cancer subtypes showed a significant difference (P < 0.001). The highest frequency of pCR was noted in HER2/neu cancers (58.8%), followed by luminal B (25.4%) and triple negative (23.6%). Regarding age, T-stage, tumor grade, and histological type of carcinoma, there was no discernible difference between pCR and pPR. Conversely, a significant association was noted for the Ki67 index. A Ki67 index higher than 25% showed a significantly higher frequency of pCR.ConclusionsIn postchemotherapy specimens, the HER2/neu breast cancer subtype substantially displayed higher pCR, followed by luminal B and triple-negative subtypes. After identifying the patients' subtypes, intrinsic subtyping can help determine the prognosis and anticipated response to chemotherapy. Furthermore, prechemotherapy breast specimens with high Ki67 index values have shown a direct association with neoadjuvant chemotherapy response.

Many studies have investigated the association between the molecular subtypes of breast cancer and survival. The aim of this study was to identify the effects of intrinsic subtypes of breast cancer and the other clinicopathological factors on postmastectomy locoregional recurrence (LRR) in patients with early breast cancer. The records of 1,195 consecutive early breast cancer patients treated with modified radical mastectomy between 2004 and 2008 were retrospectively evaluated. The effects of intrinsic subtypes of the tumor (luminal A, luminal B, HER2-overexpressing, and triple-negative) and classical clinicopathological factors on LRR were identified by univariate and multivariate statistical analyses. The median follow-up time was 44 months, and 16 (1.3%) patients experienced a LRR during this period. In univariate analysis, the intrinsic subtypes of breast cancer had a significant effect on LRR (p = 0.002). In multivariate analysis, only extranodal invasion and estrogen receptor (ER) status were significant predictors of LRR (p = 0.003 and 0.0001, respectively), whereas intrinsic subtypes did not reveal a significant relationship with LRR (p = 0.57; hazard ratio, 2.9; 95% confidence interval, 0.2-4.7). The results of this study suggest that the extranodal invasion and negative ER status should potentially be considered when evaluating the risk of LRR. The predictive power of intrinsic subtypes for LRR is less than that of classical pathological indicators. This information may be useful in planning management of LRR in early breast cancer patients treated with mastectomy.

Background: Though several genome-wide association studies (GWAS) of breast cancer (BC) have identified common variants which differ between intrinsic subtypes, the genes through which these variants act through to impact BC risk have not been fully established. Furthermore, transcriptome-wide association studies (TWAS) have thus far been primarily employed to identify genes associated with overall BC risk, while overlooking how the influence of common variation on gene expression may contribute to subtype-specific differences. Methods: In this study, we performed two complementary multi-tissue TWASs for each of the following BC intrinsic subtypes: Luminal A-like, Luminal B-like, Luminal B/HER2-negative-like, HER2-enriched-like, Triple Negative BC. These two approaches included 1) an expression-based approach that collated TWAS signals from expression quantitative trait loci (eQTLs) across multiple tissues using the Aggregated Cauchy Association Test (ACAT) and 2) a splicing-based approach that utilized two applications of ACAT to collate splicing QTLs (sQTLs) for a given gene in a tissue and then across tissues. To perform these two TWASs, we utilized e/sQTL models trained in 11 tissues from the Genotype-Tissue Expression Project including breast, ovary, uterus, vagina, EBV-transformed lymphocytes, whole blood, spleen, liver, subcutaneous adipose, visceral adipose, and cell-cultured fibroblasts. GWAS summary statistics were previously generated from 133,384 BC cases and 113,789 controls who were participants in the Breast Cancer Association Consortium (BCAC). We further performed our TWAS while conditioning e/sQTL effect sizes on nearby GWAS index SNPs. Additionally, we utilized gene-based fine-mapping of eQTLs and sQTL to identify candidate causal genes for each intrinsic subtype. Results: Overall, we identified 164 genes in 69 loci that were associated with Luminal A-like, 19 genes in 9 loci with Luminal B-like, 18 genes in 11 loci with Luminal B/HER2-negative-like, 10 genes in 7 loci with HER2-enriched-like, and 29 genes in 12 loci with TNBC. Among these genes, 17 genes had not been reported in previous TWAS of BC, and 140 genes, 1 gene, 2 genes, 2 genes, and 16 genes were uniquely associated with each of the intrinsic subtypes, respectively. Additionally, we identified one gene associated with Luminal A-like and one gene with Luminal B-like BC that were each in a locus located at least 1.4 Mb from published GWAS hits. Furthermore, we identified 106, 11, 10, 5, and 21 candidate causal genes for each of the intrinsic subtypes, respectively, that had a posterior inclusion probability of 0.9 in at least one e/sQTL. Conclusion: In summary, our multi-tissue TWAS corroborated previous GWAS loci for overall BC risk and intrinsic subtypes, while underscoring how common variation impacts BC etiology by modulating the expression and splicing of genes in multiple tissue types. Citation Format: James Li, Julian McClellan, Haoyu Zhang, Guimin Gao, Dezheng Huo. Multi-tissue transcriptome-wide association studies identified genes for intrinsic subtypes of breast cancer [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO5-09-03.

Aim: Epithelial ovarian cancer is one of the most lethal female cancers. It is a heterogeneous group of neoplasms and the different histologic subtypes are thought to constitute separate disease entities. Efforts have been made to characterize ovarian cancers further and molecular subgroups that correlate to clinical features have been reported, but are still not in clinical use (Tothill et al., Clin Cancer Res, 2008). The subgroups, called C1-C6, represent serous and endometrioid ovarian tumors with the C1-C2 and C4-C5 subgroups characterizing high-grade serous tumors and correlated to a worse prognosis. The C3 and C6 subtypes represent borderline and low-grade tumors and show a favorable prognosis. We aimed to further outline and refine the genetic differences between malignant, benign and borderline ovarian tumors and to investigate similarities between ovarian cancer and the well described intrinsic subtypes of breast cancer (Perou et al., Nature, 2000). Materials and methods: Global gene expression profiling (Illumina HT-12 bead arrays) was applied to 72 fresh-frozen serous ovarian tumors (37 adenocarcinomas, 17 adenomas, 5 borderline tumors,13 biological replicates) collected in the ovarian tumor tissue biobank at Skane University Hospital, Sweden (2004-2011). We performed nearest centroid classification of our tumors for the molecular subtypes of ovarian cancer (“C-signatures”) as well as for the intrinsic subgroups of breast cancer (luminal A, luminal B, basal-like, normal-like, and HER2) using the genes from Hu et al. (BMC Genomics, 2006). The results were validated by performing nearest centroid classification of the intrinsic breast cancer subtypes and the C-signatures on the ovarian tumors in the Tothill cohort as well. Results: Our malignant tumors correlated significantly to the basal-like breast cancer subtype (p&amp;lt;0.001) and to the ovarian C1, C2 and C4 signatures (p=0.020). The basal-like tumors, in turn, correlated significantly to the C2 and C4 signatures (p=0.019 and p=0.001, respectively), thus supporting a link between molecular subtypes of ovarian and breast cancers. The borderline and benign tumors showed a significant correlation to the normal-like breast cancer subtype and the ovarian C3 signature, and these signatures also correlated significantly with each other (p&amp;lt;0.001). These findings were supported when the breast cancer subtypes were applied to the Tothill cohort; the basal-like subtype correlated significantly to the C2 signature and the normal-like subtype to the C3 signature (p&amp;lt;0.001). Of interest, there was a tendency towards worse prognosis among malignant tumors that correlated to the basal-like breast cancer subtype compared to the other malignant tumors, which is in line with similar findings in breast cancer. All reported p-values are calculated using Fischer's Exact Test. Conclusion: Both epithelial ovarian cancers and breast cancers are heterogeneous diseases, nevertheless they share many similarities such as hormonal influence and varying long-term prognosis. Our novel findings support a link between previously reported molecular subtypes in ovarian cancer and the well-established intrinsic subtypes of breast cancer, which could potentially be of use for further investigations of biomarkers in ovarian cancer and new thinking regarding the use of chemotherapeutic agents as well as targeted treatments. Citation Format: Jenny-Maria Jönsson, Mev Dominguez-Valentin, Ida Johansson, Siker Kimbung, Mats Jönsson, Anna Måsbäck, Susanne Malander, Mef Nilbert. Molecular subtyping of epithelial ovarian cancer reveals connections to intrinsic breast cancer subtypes. [abstract]. In: Proceedings of the AACR Special Conference on Advances in Ovarian Cancer Research: From Concept to Clinic; Sep 18-21, 2013; Miami, FL. Philadelphia (PA): AACR; Clin Cancer Res 2013;19(19 Suppl):Abstract nr B8.

Backgrounds: Breast cancer (BC) is a heterogeneous disease and usually divided into 5 subtypes according to clinicopathologic features. These subtypes have concordance with mRNA-based subtypes called as "intrinsic subtypes". Further gene expression analysis categorized triple negative BCs into 7 sub-subtypes which relate to clinical behaviors. DNA methylation is one of the epigenetic systems to regulate gene transcription. DNA methylation in CpG islands (CGIs) associated with the gene promoter region affects gene expression levels. Recently genome-wide analyses suggested that methylation status not only in CGIs, but also in CpG shores (within 2000 bps from CGIs) and CpG shelves (2000-4000 bps from CGIs) contribute to gene silencing. Thus, we hypothesized that intrinsic subtypes may possess specific methylation profiles especially in regions surrounding CGIs (islands, shores and shelves). To date, several reports demonstrated each intrinsic subtype has specific methylation patterns in CGIs. They indicate that DNA methylation is promising markers for cancer detection, prediction of therapeutic response and clinical outcomes. However, there were no report that conducted a genome-wide high-resolution epigenetic analysis for BC. Objectives: This study aims to determine whether specific DNA methylation patterns exist in CGIs, shores and shelves in BC cells, and whether the DNA methylation-based classification correlates with intrinsic subtypes, furthermore, to identify the subtype specific epigenetic markers using high-resolution methylation array. Materials and Methods: DNA was extracted from 31 samples of 28 BC cell lines (8 luminal, 18 basal, 2 unclassified) and 3 samples of 3 non-BC cell lines. We performed genome-wide methylation analysis using Illumina Infinium HumanMethylation450 BeadChip. We did unsupervised hierarchical clustering analysis of cell lines using top 3000 variably methylated (VM) loci among cancer cell lines. We also analyzed top 3000 VM CGI-related loci. Gene functional annotation clustering was performed using DAVID. Results: In top 3000 VM loci, CGIs were most frequently observed (43.0%). According to clustering analysis using top 3000 VM loci, cell lines were roughly classified into 4 clusters. There were trends that cell lines of same subtype fell into the same cluster, but not definitely. In case of clustering using top 3000 VM CGI-related loci, cell lines were clearly divided into 2 clusters, high and low methylated clusters. High methylated cluster contained almost all luminal cell lines and low methylated cluster contained most of basal cell lines and all non-BC cell lines. In low methylated cluster, cell lines of the same sub-subtype, such as Basal-like 1 and 2, were clustered closely. Gene functional annotation clustering suggested that genes related to "transcription" and "differentiation" were more frequently regulated by epigenetics. Conclusions: High-resolution methylation analysis revealed methylation-based clusters were concordant with intrinsic subtypes in BC cells. Transcriptional factors and differentiation-related genes could be differently regulated by epigenetics among different subtypes of BC. Citation Format: Natsue Uehiro, Fumiaki Sato, Sunao Tanaka, Fengling Pu, Junji Itou, Shigehira Saji, Masakazu Toi. DNA methylation-based classification are mostly concordant with intrinsic subtypes of breast cancer [abstract]. In: Proceedings of the Thirty-Seventh Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2014 Dec 9-13; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2015;75(9 Suppl):Abstract nr P1-06-05.

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.

The present study evaluated whether Prosigna® breast cancer assay intrinsic subtype (IST) can be predicted using a specified cutoff for Ki67 proliferation index and immunohistochemical (IHC) biological subtype estimation, complemented by estrogen receptor (ER) and progesterone receptor (PR) expression in a clinical cohort. Our study included 185 cases of early stage ER-positive, HER2-negative breast cancer treated at the Comprehensive Cancer Center of the Medical University of Vienna between 2014 and 2019. Prosigna® breast cancer assay was performed when recommended by the institutional multidisciplinary tumor board to aid adjuvant therapy decision. Pathological diagnostics was carried out according to current WHO and EU breast cancer screening and diagnostics guidelines. Immunohistochemical assessment of ER, PR, human epidermal growth factor receptor 2 (HER2) and proliferation index by Ki67 was performed using Ventana Benchmark Ultra (Tucson, AR, USA) according to recent ASCO/USCAP guidelines. Univariable logistic regression was used to verify that Ki67 positivity is predictive for IST LumA and LumB tumors according to Prosigna® IST. Probability for luminal B IST was estimated by receiver operating characteristics and Youden index was calculated. Next, multivariable logistic regression was applied to test the hypothesis that additional inclusion of ER and PR receptor expression contain additional information regarding IST. Median age of patients was 56 years. 52 patients (28%) had tumors larger than 2 cm (pT2-pT3). 75 patients (41%) had lymph node metastases. 83 (45%), 98 (53%) and 3 (2%) of tumors were diagnosed as luminal A, luminal B and HER2-enriched subtype by Prosigna®, respectively. 19 (10%), 77 (42%) and 89 (48%) tumors could be allocated in the low, intermediate and high risk groups, respectively. Univariable logistic regression confirmed that higher Ki67 positivity significantly, yet insufficiently predicts luminal B tumor subtype (p&amp;lt;0.0001). There was no justification for an optimal Ki67 cutoff and irrespective of its value, no more than 70% of tumors could correctly be assigned to the IST, according to a Youden-Index of maximum 0.42. The hypothesis that including ER and PR expression improves accuracy could not be confirmed (p=0.14). Although higher Ki67 positivity significantly predicted luminal B tumor subtype, the Prosigna® breast cancer assay provided independent information for adjuvant therapy decision in cases where Ki67 IST estimation alone is not sufficient. Irrespective of the chosen cutoff value, a maximum accuracy of 70% was achieved for correctly predicting IST, including ER and PR expression into our model did not improve accuracy. Therefore, IST determination by the Prosigna® breast cancer assay cannot be replaced by immunohistochemical parameters. Citation Format: Ulrike Heber, Kristina Tendl-Schulz, Stefan Heber, Sabine Danzinger, Rupert Bartsch, Christian F. Singer, Florian Fitzal, Ruth Exner, Michael F. Gnant, Leonhard Müllauer, Zsuzsanna Bago-Horvath. Prediction of Prosigna® breast cancer intrinsic subtype by immunohistochemical ER, PR and Ki67 expression [abstract]. In: Proceedings of the 2021 San Antonio Breast Cancer Symposium; 2021 Dec 7-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2022;82(4 Suppl):Abstract nr P1-02-06.

Background: Male breast cancer (MaBC) is rare, comprising &amp;lt;1% of all breast cancers in the United States. The low incidence of MaBC limits the ability to conduct clinical trials specifically for this population. Due to the paucity of research on MaBC, current understanding regarding MaBC biology, pathology, and treatment strategies has been primarily based on evidence extrapolated from research on female breast cancer (FBC) patients. Traditional diagnostic biomarkers such as ER, PR, and HER2, as well as newer multi-gene prognostic signatures, are employed when making treatment decisions for both MaBC and FBC. However, limited empirical data is available to support the use of identical laboratory biomarkers and molecular signatures in both MaBC and FBC. The 70-gene risk of distant recurrence signature, MammaPrint (MP), and the 80-gene molecular subtyping signature, BluePrint (BP), are commonly used to help make treatment decisions for both MaBC and FBC patients. To support the clinical utility of MP and BP in MaBC, this study aims to elucidate whether significant molecular biological differences exist between MaBC and FBC. To address this knowledge gap, we evaluated and compared 1) MP index results within Low Risk (LR) and High Risk (HR) groups, 2) MP and BP gene expression, and 3) differentially expressed genes within the full genome and their associated biological pathways between tumors from MaBC and FBC. Methods: This analysis included a total of 817 breast tumor samples sent to Agendia, Inc. (Irvine, CA) for MP and BP testing. Full-transcriptome microarray data were available for 1) a subset of 400 post-menopausal FBC patients enrolled in the FLEX Registry (NCT03053193) and 2) 80 MaBC pateints, 32 of whom enrolled in the FLEX registry and 48 non-study patients for whom data were limited to metadata and quality metrics routinely captured for diagnostic testing. Data from all patients were de-indentified. Differences in mean MP indices between FBC (N=400) and MaBC (N=417) according to MP Risk classification (LR or HR) were analyzed using a Z-test. Differential gene expression analysis was performed using the R-limma package in which gene expression data were quantile normalized. Pathway analyses were performed using GOseq. Differentially expressed genes (DEGs) were identified between FBC (N=400) and MaBC (N=80) for whom full transcriptome microarray data were available. DEGs were defined as those with a fold change of &amp;gt; 2 and an adjusted P value of &amp;lt; 0.05. Results: All patients in this study had hormone positive, HER2 negative early-stage breast cancer. There was no statistical difference in the average MP index between MaBC and FBC classified as MP LR (P=0.273) or those classified as MP HR (P=0.692). Gene expression comparison revealed 166 DEGs between MaBC (N=80) and FBC (N=400), 99 DEGs between MP HR MaBC (N=42) and MP HR FBC (N=200), and 290 DEGs between MP LR MaBC (N=38) and MP LR FBC (N=200). Pathway analyses revealed that downregulated genes in MaBC compared to FBC enriched to immune-related functions, including B-cell mediated immunity, whereas upregulated genes were associated with hormone metabolic processes. In all comparisons, expression of MP or BP genes was not significantly different. Conclusions: We found similar MP index distributions between MaBC and FBC. Importantly, differential gene expression between MaBC and FBC provides novel insight into the mechanisms underlying MaBC. Although these data reveal biological distinctions between male and female breast cancer, MP and BP assay performance is preserved across both groups. Further studies are needed to assess clinical outcomes; however, these findings support the use of MP risk of recurrence assay and BP molecular subtyping assay for prognosis and informing treatment decisions in MaBC. Citation Format: Jennifer Crozier, Julie Barone, Kalyan Banda, Beth Lesnikoski, Robert Maganini, Sami Diab, Ian Grady, Thomas Lomis, Charles Cox, Amy Truitt, Benjamin Nota, Andrea Menicucci, Erin Yoder, William Audeh, FLEX Investigators Group. Differential gene expression analysis and clinical utility of MammaPrint and BluePrint in male breast cancer patients [abstract]. In: Proceedings of the 2020 San Antonio Breast Cancer Virtual Symposium; 2020 Dec 8-11; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2021;81(4 Suppl):Abstract nr PS14-11.

Aim: To determine the predictive value of intrinsic subtypes for response to adjuvant chemotherapy using specimens from a randomized clinical trial. Background: Several studies have shown distinct clinical profiles of intrinsic breast cancer subtypes. The Luminal A subtype has a favorable prognosis with higher survival rate and lower recurrence in comparison to other breast cancer subtypes (luminal B, HER2 and basal-like). In addition, there is mounting evidence suggesting that intrinsic breast cancer subtypes differ in their responsiveness to adjuvant chemotherapy. Based on these data, we hypothesized that Luminal A breast cancer patients derive no benefit from adjuvant chemotherapy whereas other intrinsic subtypes do. Randomized breast cancer trials with a no chemotherapy arm and available tissues are rare, but represent the best materials to test for markers predicting chemotherapy benefit. The 77B clinical trial from the Danish Breast Cancer Cooperative Group (DBCG) offers a unique opportunity to test such hypotheses as it randomized 1146 premenopausal women, who had positive axillary lymph nodes or tumors &amp;gt;5 cm, to two chemotherapy arms (single-agent oral cyclophosphamide, or cyclophosphamide-methotrexate-fluorouracil (CMF)), and two no chemotherapy arms (levamisole, or no agent). All arms included radiotherapy but no endocrine therapy. Methods: We performed a full intrinsic subtype analysis on the 709 breast cancers available from DBCG77B on tissue microarrays using previously published, locked-down immunohistochemical (IHC) methods and intrinsic subtype definitions based on ER, PR, HER2, Ki67 and basal markers (Prat et al. JCO 2014). Biomarker scoring was performed in Vancouver by researchers with no access to the clinical database. A full statistical plan was prespecified in the Material Transfer Agreement and executed accordingly by the DBCG Statistical Office. 10-year invasive disease-free survival (IDFS) was the primary end point in DBCG77B; overall survival was also a predefined endpoint. The primary hypothesis was to assess interaction between benefit of chemotherapy (chemotherapy yes vs no) and subtype (Luminal A vs non-luminal A). This was analyzed in multivariate Cox proportional hazards models using the Wald test for interaction. Results: 709 patients had tissue available and completed IHC intrinsic subtyping. The effect of chemotherapy in this subset of patients was similar to the original trial: hazard ratio 0.56, favoring chemotherapy for 10-yr IDFS. IHC classified 165 as luminal A, 319 luminal B, 58 HER2E and 91 as triple negative (including 82 core basal). Patients with luminal A breast tumors did not benefit from chemotherapy (HR = 1.07, 95% CI = 0.53-2.14, p = 0.86), whereas patients with non-luminal A subtypes did (HR = 0.50, 95% CI = 0.38-0.66, p &amp;lt; 0.001). This heterogeneity was statistically significant (p=0.048). A similar trend for 25-yr OS was seen, although not significant. Conclusions: In a formal prospective-retrospective analysis of the DBCG 77B study randomizing women to adjuvant cyclophosphamide-based chemotherapy vs. no chemotherapy arms, patients with non-luminal A breast tumors (defined by IHC), but not luminal A tumors, benefit from adjuvant chemotherapy. Citation Format: Nielsen TO, Jensen [lrm] M-B, Gao D, Leung S, Burugu S, Liu S, Tykjær Jørgensen CL, Balslev E, Ejlertsen B. High risk premenopausal luminal A breast cancer patients derive no benefit from adjuvant chemotherapy: Results from DBCG77B randomized trial. [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 S1-08.

Recently identified genetic variants from genome-wide association studies (GWAS) on breast cancer have not been validated in Asian populations, except in China. In this study, we sought to confirm the association between known variants and breast cancer in Korean women and further evaluate the associations of individual single nucleotide polymorphisms (SNP) with different intrinsic subtypes of breast cancer. In total, 3,321 invasive breast cancer patients and 3,500 healthy controls were genotyped for five SNPs by using the TaqMan assay. The SNPs genotyped included rs2046210 (6q25.1), rs2981582 (FGFR2), rs889312 (MAP3K1), rs3803662 (TOX3/TNRC9), and rs4973768 (SLC4A7). Tumors were classified into four intrinsic subtypes based on estrogen receptor (ER), progesterone receptor, HER2, and Ki67 expression. All five SNPs were significantly associated with risk of breast cancer in dominant, recessive, and additive models. ORs per risk allele (95% CI) were 1.29 (1.16-1.43), 1.40 (1.18-1.68), 1.22 (1.06-1.41), 1.52 (1.30-1.77), and 1.20 (1.08-1.33) for rs2046210, rs2981582, rs889312, rs3803662, and rs4973768, respectively. A multigene logistic regression risk model was generated with the SNPs. In subtype analysis, all 5 SNPs were associated with the Luminal A subtype. Two SNPs (rs2046210 and rs3803662) were linked to the ER(-)HER2(+) subtype, and only rs2046210 SNP was associated with the triple-negative subtype. The five SNPs from GWAS were significantly associated with breast cancer risk in Korean women. Associations were heterogeneous according to the intrinsic subtype of breast cancer. Our result is an important contribution to the literature about genetic susceptibility for breast cancer in nonwhite populations.

Breast cancer is one of the main causes of morbidity and mortality among women around the world. In Peru, it has recently surpassed cervical cancer as the most commonly reported cancer. Studying the relationship between intrinsic breast cancer subtypes and disease staging can optimize diagnosis, prognosis, and treatment. Therefore, there is a need for better risk stratification, selection of personalized treatment, and improved early detection strategies. We conducted this study to address the lack of data on underrepresented populations such as the Peruvian population. The objective of the study was to analyze the distribution of intrinsic subtypes of breast cancer and their correlation with prognostic factors and demographic characteristics among women in Peru. A descriptive, retrospective observational study was conducted, analyzing 67 cases of breast cancer of various intrinsic subtypes diagnosed at a referral hospital in Peru. Clinical, demographic, and pathological data were collected, including histological type, intrinsic subtype, tumor stage, and geographic origin of the patients. Intrinsic subtypes were classified through immunohistochemistry, and the data were processed to determine their distribution and correlation with prognostic factors such as disease stage. The mean age of the 67 patients included in the study was 54.2 years. The majority of cases originated from the city of Cajamarca (56.7%, n = 38). Invasive breast carcinoma of no special type was the most common histological type (62.7%, n = 42). Among the intrinsic subtypes, luminal B was the most common (31.3%, n = 21), followed by luminal A and triple-negative (22.4%, n = 15), both with the same frequency. Furthermore, 16.4% (n = 11) of patients presented with metastasis at the time of evaluation. A high frequency of tumors was observed in Tumor, Nodes, Metastasis (TNM) stages 3 and 4, accounting for 49.2% (n = 33). This study describes the heterogeneity of breast cancer based on the identification of intrinsic subtypes within the analyzed population. The high frequency of luminal B, luminal A, and triple-negative subtypes is notable. The highest frequency of identified cases was in the advanced stages, highlighting the need for personalized treatments and improved early detection strategies.

Introduction: APOlipoprotein B mRNA Editing enzyme Catalytic peptide-like, APOBEC, is a family of innate immune enzymes that catalyze cytosine to uracil deamination in single-stranded DNA, which lead to mutations in preferred trinucleotide contexts. APOBEC mutagenesis portends a worse prognosis in several breast cancer subtypes and associates with increased tumor mutational burden (TMB). Specific mutations enriched with APOBEC mutation signatures and immune phenotypes are not well described. The purpose of our study was to identify genes enriched for APOBEC mutagenesis and determine their relationship to intrinsic subtypes, TMB, and the immune composition of the transcriptome in breast cancers. Methods: We queried TCGA breast cancer database involving 980 breast cancer samples. We used consensus mutation calls from four somatic mutation callers (MuTect2, VarScan2, MuSE, and SomaticSniper). APOBEC mutagenesis scores were calculated for each tumor using a published method (Nik-Zainal et al. 2012) and a modified version thereof. The score was calculated at the gene-level, to identify genes enriched for APOBEC mutagenesis, and the cancer sample-level to investigate the relationship of APOBEC mutagenesis scores with intrinsic subtypes (using PAM50), APOBEC3A and 3B expression levels, and TMB. We also undertook differential expression analysis of CIBERSORT gene signatures and individual genes from the innate immune system, IFN, TGFB, WNT, and immune checkpoints with respect to common somatic mutations in APOBEC enriched genes. Results: The genes with the strongest statistical evidence for enrichment of APOBEC mutagenesis were PIK3CA, TP53, MUC16, and TTN. Among three common somatic mutations in PIK3CA (E542K, E545K, H1047R), the APOBEC score was only observed to be associated with E542K (q=2.47 × 10−2) and E545K (q=9.81 × 10−6) mutations. APOBEC mutagenesis revealed a high degree of enrichment across all breast cancer intrinsic subtypes, 75% in luminal A, 68% in luminal B, 91% in HER2 enriched, 73% in basal, and 89% in normal-like phenotypes. APOBEC mutagenesis scores were observed to significantly associate with APOBEC3A expression (q=1.1 × 10−9) and as a trend of association with APOBEC3B expression (q=1.62 × 10−1). A strong association was observed between APOBEC mutagenesis score and elevated TMB (p&amp;lt;2 × 10−16). No checkpoint genes (i.e. CTLA-4, PD-1, and PD-L1) were observed to be significantly overexpressed among those tumors with E542K and E545K PIK3CA mutations. The CIBERSORT mast cell gene signature (q=1.32 × 10−2) and the individual genes TGFB3 (q=5 × 10−3), ROR (q=7.91 × 10−3), and WNT5A (q=1.92 × 10-2) were overexpressed in breast tumors with E542K PIK3CA mutations. Conclusion: APOBEC mutagenesis patterns are seemingly prevalent across all breast cancer intrinsic subtypes and associate with elevated TMB and mutations in the PIK3CA helical loop domain and TP53 gene in TCGA breast cancer samples. Cancers with PIK3CA mutations in the helical loop domain did not demonstrate checkpoint gene overexpression, but were associated with other immunosuppressive features (e.g. TGFB3 and WNT5A overexpression). Investigation into innate immune cell signaling, mast cell immune signaling, and immunosuppressive expression profiles in APOBEC mutated breast cancers with and without PIK3CA mutations may help to identify novel immune targets to combine with PI3K inhibitors in breast cancer. Citation Format: Jeremy Force, Xiaodi Qin, Dadong Zhang, P. Kelly Marcom, Jeffrey Marks, Mary Love Taylor, Carey Anders, Kouros Owzar, Jichun Xie. Characterization of gene- and sample-level APOBEC mutagenesis enrichment with respect to intrinsic subtypes, tumor mutational burden, and immune composition in breast cancer [abstract]. In: Proceedings of the 2019 San Antonio Breast Cancer Symposium; 2019 Dec 10-14; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2020;80(4 Suppl):Abstract nr P1-06-02.