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Purpose: Recent guidelines defined a new reporting category of ER-low-positive breast cancer based on immunohistochemistry (IHC). While low positivity of either hormone receptor is uncommon in invasive lobular carcinoma (ILC), we sought to investigate whether relatively low hormone receptor positivity was associated with tumor characteristics and patient outcomes in a single institutional cohort., Methods: We searched an institutional database for cases of stage I-III ILC with available IHC reports. Based on prior published categories in ILC, ER was classified as low, medium, or high as defined by ER staining of 10-69%, 70-89%, and ≥ 90% respectively. PR low and high tumors were defined by < 20%, or ≥ 20% staining respectively. We used chi-squared tests, t-tests, and Cox proportional hazards models to evaluate associations between ER/PR categories and tumor characteristics or disease-free survival (DFS)., Results: The cohort consisted of 707 ILC cases, with 11% of cases categorized as ER low, 15.1% as medium, and 73.8% as high. The majority (67.6%) were PR high. Patients with ER low/medium expression were significantly younger, and more likely to also have PR low and/or HER2 positive tumors compared to those that were ER high. In a Cox proportional hazards model adjusting for age, stage, grade, pleomorphic histology, and treatment, ER category was not prognostic for DFS, but PR negative and PR low status each had significantly worse DFS compared to PR high status (HR 3.5, 95% CI 1.8-6.7, p < 0.001; and HR 2.0, 95% CI 1.1-3.5, p = 0.015, respectively)., Conclusion: These findings highlight the relevance of quantifying ER and PR within ILC., (© 2023. The Author(s).)

Purpose: Neoadjuvant anti-PD-(L)1 therapy improves the pathological complete response (pCR) rate in unselected triple-negative breast cancer (TNBC). Given the potential for long-term morbidity from immune-related adverse events (irAEs), optimizing the risk-benefit ratio for these agents in the curative neoadjuvant setting is important. Suboptimal clinical response to initial neoadjuvant therapy (NAT) is associated with low rates of pCR (2-5%) and may define a patient selection strategy for neoadjuvant immune checkpoint blockade. We conducted a single-arm phase II study of atezolizumab and nab-paclitaxel as the second phase of NAT in patients with doxorubicin and cyclophosphamide (AC)-resistant TNBC (NCT02530489)., Methods: Patients with stage I-III, AC-resistant TNBC, defined as disease progression or a < 80% reduction in tumor volume after 4 cycles of AC, were eligible. Patients received atezolizumab (1200 mg IV, Q3weeks × 4) and nab-paclitaxel (100 mg/m 2 IV,Q1 week × 12) as the second phase of NAT before undergoing surgery followed by adjuvant atezolizumab (1200 mg IV, Q3 weeks, × 4). A two-stage Gehan-type design was employed to detect an improvement in pCR/residual cancer burden class I (RCB-I) rate from 5 to 20%., Results: From 2/15/2016 through 1/29/2021, 37 patients with AC-resistant TNBC were enrolled. The pCR/RCB-I rate was 46%. No new safety signals were observed. Seven patients (19%) discontinued atezolizumab due to irAEs., Conclusion: This study met its primary endpoint, demonstrating a promising signal of activity in this high-risk population (pCR/RCB-I = 46% vs 5% in historical controls), suggesting that a response-adapted approach to the utilization of neoadjuvant immunotherapy should be considered for further evaluation in a randomized clinical trial., (© 2023. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

Purpose: HER2 overexpression has a central role in breast cancer carcinogenesis and is associated with poor prognosis if untreated. Lately, identification of HER2-low breast cancer has been proposed to select patients for novel HER2-directed chemotherapy and includes cancers with immunohistochemistry 1 + or 2 + with negative FISH, encompassing approximately 55-60% of all breast carcinomas. In early-stage breast cancer, the prognostic significance of HER2 low-disease is less well understood, with a particular paucity of data evaluating the prevalence and implications of HER2-low status in invasive lobular carcinoma (ILC)., Methods: We evaluated 666 stage I-III ILC tumors from a prospectively maintained institutional database, comparing clinicopathologic features and disease-free survival (DFS) using a multivariable Cox proportional hazards model., Results: HER2-low status was common in this cohort of patients with ILC, but most clinicopathologic features did not differ between HER2-low and HER2-negative cases. However, when adjusting for tumor size, number of positive nodes, ER/PR status, and local therapy received, patients with HER2-low status had worse disease-free survival (DFS) than those with HER2-negative tumors (hazard ratio 2.0, 95% confidence interval 1.0-4.1, p = 0.05)., Conclusion: This difference in DFS supports the notion that HER2-low and HER2-negative early stage ILC may differ clinically, despite similar clinicopathologic features. Further investigation into the potential benefit of HER2 targeted therapy in HER2-low early-stage breast cancer, and specifically lobular cancer, is warranted to ensure optimal outcomes in this distinct tumor subtype., (© 2023. The Author(s).)

Introduction: We hypothesized that breast tissue not involved by tumor in inflammatory breast cancer (IBC) patients contains intrinsic differences, including increased mammary stem cells and macrophage infiltration, which may promote the IBC phenotype., Materials and Methods: Normal breast parenchyma ≥ 5 cm away from primary tumors was obtained from mastectomy specimens. This included an initial cohort of 8 IBC patients and 60 non-IBC patients followed by a validation cohort of 19 IBC patients and 25 non-IBC patients. Samples were immunostained for either CD44 + CD49f + CD133/2 + mammary stem cell markers or the CD68 macrophage marker and correlated with IBC status. Quantitation of positive cells was determined using inForm software from PerkinElmer. We also examined the association between IBC status and previously published tumorigenic stem cell and IBC tumor signatures in the validation cohort samples., Results: 8 of 8 IBC samples expressed isolated CD44 + CD49f + CD133/2 + stem cell marked cells in the initial cohort as opposed to 0/60 non-IBC samples (p = 0.001). Similarly, the median number of CD44 + CD49f + CD133/2 + cells was significantly higher in the IBC validation cohort as opposed to the non-IBC validation cohort (25.7 vs. 14.2, p = 0.007). 7 of 8 IBC samples expressed CD68 + histologically confirmed macrophages in initial cohort as opposed to 12/48 non-IBC samples (p = 0.001). In the validation cohort, the median number of CD68 + cells in IBC was 3.7 versus 1.0 in the non-IBC cohort (p = 0.06). IBC normal tissue was positively associated with a tumorigenic stem cell signature (p = 0.02) and with a 79-gene IBC signature (p < 0.001)., Conclusions: Normal tissue from IBC patients is enriched for both mammary stem cells and macrophages and has higher association with both a tumorigenic stem cell signature and IBC-specific tumor signature. Collectively, these data suggest that IBC normal tissue differs from non-IBC tissue. Whether these changes occur before the tumor develops or is induced by tumor warrants further investigation.

A subset of early stage estrogen receptor (ER)-positive breast cancers considered "high risk" for recurrence with endocrine therapy alone by current genomic prognostic predictors, such as Oncotype DX, is no longer high risk after receiving adjuvant chemotherapy. We hypothesized that a recently described gene expression-based outcome predictor adjuvant chemotherapy and endocrine therapy sensitivity (ACES) could re-stratify these patients into high and low risk groups for relapse when treated with both chemo- and endocrine therapies. ACES involves four separate modules (endocrine sensitivity, chemotherapy sensitivity, chemotherapy resistance, and survival prediction) that yield a prediction for good or poor outcome with current standard of care multimodality therapy. ACES was applied to Affymetrix gene expression data from 2 retrospectively collected ER-positive and HER2-negative patient cohorts that were uniformly treated with adjuvant endocrine and chemotherapy (n = 250). Each sample was first risk stratified by a genomic surrogate of Oncotype DX, and the high risk patients (n = 76) were re-stratified by ACES. Recurrence-free survival (RFS) was evaluated with ACES risk categories. The Oncotype DX high risk but ACES good prognosis patients (n = 24, 32%) had an RFS of 95% compared to 76% in the poor prognosis group (n = 52; log-rank p = 0.033) at 5 years. ACES risk category remained an independent predictor in multivariate analysis after adjusting for age, T-stage, and lymph node involvement at diagnosis (hazard ratio 0.15; p = 0.072). Tertiary risk prediction that takes into account chemotherapy and endocrine sensitivity, and baseline prognosis may help identify high risk ER-positive patients who have excellent survival after chemotherapy.

The goal of this analysis was to develop a computational tool that integrates the totality of gene expression, DNA copy number, and sequence abnormalities in individual cancers in the framework of biological processes. We used the hierarchical structure of the gene ontology (GO) database to create a reference network and projected mRNA expression, DNA copy number and mutation anomalies detected in single samples into this space. We applied our method to 59 breast cancers where all three types of molecular data were available. Each cancer had a large number of disturbed biological processes. Locomotion, multicellular organismal process, and signal transduction pathways were the most commonly affected GO terms, but the individual molecular events were different from case-to-case. Estrogen receptor-positive and -negative cancers had different repertoire of anomalies. We tested the functional impact of 27 mRNAs that had overexpression in cancer with variable frequency (<2-42 %) using an siRNA screen. Each of these genes inhibited cell growth in at least some of 18 breast cancer cell lines. We developed a free, on-line software tool ( http://netgoplot.org ) to display the complex genomic abnormalities in individual cancers in the biological framework of the GO biological processes. Each cancer harbored a variable number of pathway anomalies and the individual molecular events that caused an anomaly varied from case-to-case. Our in vitro experiments indicate that rare case-specific molecular abnormalities can play a functional role and driver events may vary from case-to-case depending on the constellation of other molecular anomalies.

We examined estrogen receptor (ER) mRNA expression and molecular subtypes in stage I-III breast cancers that are progesterone receptor (PR) positive but ER and HER2 negative by immunohistochemistry (IHC) or fluorescent in situ hybridization. The ER, PR, and HER2 status was determined by IHC as part of routine clinical assessment (N = 501). Gene expression profiling was done with the Affymetrix U133A gene chip. We compared expressions of ESR1 and MKI67 mRNA, distribution of molecular subtypes by the PAM50 classifier, the sensitivity to endocrine therapy index, and the DLDA30 chemotherapy response predictor signature among ER/PR-positive (n = 223), ER-positive/PR-negative (n = 73), ER-negative/PR-positive (n = 20), and triple-negative (n = 185) cancers. All patients received neoadjuvant chemotherapy with an anthracycline and taxane and had adjuvant endocrine therapy only if ER or PR > 10 % positive. ESR1 expression was high in 25 % of ER-negative/PR-positive, in 79 % of ER-positive/PR-negative, in 96 % of ER/PR-positive, and in 12 % of triple-negative cancers by IHC. The average MKI67 expression was significantly higher in the ER-negative/PR-positive and triple-negative cohorts. Among the ER-negative/PR-positive patients, 15 % were luminal A, 5 % were Luminal B, and 65 % were basal like. The relapse-free survival rate of ER-negative/PR-positive patients was equivalent to ER-positive cancers and better than the triple-negative cohort. Only 20-25 % of the ER-negative/PR-positive tumors show molecular features of ER-positive cancers. In this rare subset of patients (i) a second RNA-based assessment may help identifying the minority of ESR1 mRNA-positive, luminal-type cancers and (ii) the safest clinical approach may be to consider both adjuvant endocrine and chemotherapy.

The goal of this study was to assess the prognostic value of a 3-gene (TOP2A, FOXM1, and MKI67) proliferation score and use it to risk stratify grade-2, estrogen receptor (ER)-positive breast cancers into low- and high-risk groups. We used 4 different breast cancer gene expression datasets including two cohorts of patients who received no systemic adjuvant therapy (Mainz: n = 206, TRANSBIG: n = 134) and two other cohorts that received adjuvant tamoxifen (JBI: n = 227, MDACC/SET: n = 192). We compared individual and combined expression values of the 3 genes between grade 1, 2, and 3 tumors and plotted distant metastasis-free survival (DMFS) curves by the 3-gene score for grade-2 cancers. We compared the prognostic value of the 3-gene score to the Genomic Grade Index (GGI). The individual and combined expression of TOP2A, FOXM1, and MKI67 were significantly different between the 3 histological grade groups with the highest expression in grade-3 and the lowest in grade-1 cancers. Expression levels were variable in grade-2 cancers. Grade-2 tumors with high expression of the 3 genes (>median) showed significantly worse DMFS in one prognostic and one tamoxifen-treated set and showed a similar but non-significant trend for worse survival in the remaining two datasets. The 3-gene score performed equally well in risk stratification as the GGI. A 3-gene proliferation score shows similar prognostic value as the GGI in ER-positive, grade-2 cancers and may serve as basis for a PCR-based assay that could aid prognostic prediction for clinically intermediate-risk cancers.

The mutation pattern of breast cancer molecular subtypes is incompletely understood. The purpose of this study was to identify mutations in genes that may be targeted with currently available investigational drugs in the three major breast cancer subtypes (ER+/HER2-, HER2+, and Triple Negative). We extracted DNA from fine needle aspirations of 267 stage I-III breast cancers. These tumor specimens typically consisted of >80% neoplastic cells. We examined 28 genes for 163 known cancer-related nucleic acid variations by Sequenom technology. We observed at least one mutation in 38 alleles corresponding to 15 genes in 108 (40%) samples, including PIK3CA (16.1% of all samples), FBXW7 (8%), BRAF (3.0%), EGFR (2.6%), AKT1 and CTNNB1 (1.9% each), KIT and KRAS (1.5% each), and PDGFR-α (1.1%). We also checked for the polymorphism in PHLPP2 that is known to activate AKT and it was found at 13.5% of the patient samples. PIK3CA mutations were more frequent in estrogen receptor-positive cancers compared to triple negative breast cancer (TNBC) (19 vs. 8%, p=0.001). High frequency of PIK3CA mutations (28%) were also found in HER2+ breast tumors. In TNBC, FBXW7 mutations were significantly more frequent compared to ER+ tumors (13 vs. 5%, p=0.037). We performed validation for all mutated alleles with allele-specific PCR or direct sequencing; alleles analyzed by two different sequencing techniques showed 95-100% concordance for mutation status. In conclusion, different breast cancer subtypes harbor different type of mutations and approximately 40 % of tumors contained individually rare mutations in signaling pathways that can be potentially targeted with drugs. Simultaneous testing of many different mutations in a single needle biopsy is feasible and allows the design of prospective clinical trials that could test the functional importance of these mutations in the future.

The aims of this study were to compare the performance of six different genomic prognostic markers to predict long-term survival and chemotherapy response on the same patient cohort and assess if clinicopathological variables carry independent prognostic and predictive values. We examined seven clinical variables and six previously described prognostic signatures on 228 tumors from patients who received homogeneous preoperative chemotherapy and had long-term follow-up information for survival. We used the area under the receiver operator characteristic curve (AUC) to compare predictors and also performed univariate and multivariate analyses including the genomic and clinical variables and plotted Kaplan-Meir survival curves. All genomic prognostic markers had statistically similar AUCs and sensitivity to predict 5-year progression-free survival (PFS, sensitivities ranged from 0.591 to 0.773, and AUCs: 0.599-0.673), overall survival (OS, sensitivities: 0.590-0.769, AUCs: 0.596-0.684) and pathologic complete response (pCR, sensitivities: 0.596-0.851, AUCs: 0.614-0.805). In multivariate analysis, the genomic markers were not independent from one another; however, estrogen receptor (Odds Ratio [OR] 7.63, P < 0.001) and HER2 status (OR: 0.37, P = 0.021) showed significant independent predictive values for pCR. Nodal status remained an independent prognostic, but not predictive, variable (OR for PFS: 2.77, P = 0.021, OR for OS: 3.62, P = 0.01). There was moderate to good agreement between different prediction results in pair-wise comparisons. First-generation prognostic-gene signatures predict both chemotherapy response and long-term survival. When multiple predictors are applied to the same case discordant risk prediction frequently occurs.

The goal of this study was to determine whether gene expression differences exist between inflammatory breast cancers (IBC) and T stage-matched non-IBC patients stratified by hormone receptor and HER2 status. We used Affymetrix GeneChips to analyze 82 tumor samples (25 T4d patients, and 57 T4a-c patients) of newly diagnosed breast cancers. Genes that were differentially expressed between the IBC and non-IBC specimens were identified using the t test, and differential expression of gene sets was assessed using gene set analysis. Three distinct clinical subtypes of IBC and non-IBC were compared: ER-positive/HER2-normal, HER2-amplified, and ER-negative/HER2-normal. When we compared expression data from all IBC with all non-IBC, we found no significant differences after adjusting for multiple testing. When IBC and non-IBC tumors were compared by clinical subtype, however, significant differences emerged. Complement and immune system-related pathways were overexpressed in ER-positive/HER2-normal IBC. Protein translation and mTOR signaling were overexpressed in HER2-amplified IBC. Apoptosis-, neural-, and lipid metabolism-related pathways were overexpressed in ER-negative/HER2-normal IBC compared with non-IBC of the same receptor phenotype. In this T stage-matched case-control study, the survival curves of patients with IBC and non-IBC were similar for all three clinical subtypes. IBC tumors can be divided into molecular and clinical subtypes similar to those of non-IBC. Clinical subtypes of IBC show molecular differences compared with similar subtypes of non-IBC.

The goal of this study was to develop pharmacogenomic predictors in response to standard chemotherapy drugs in breast cancer cell lines and test their predictive value in patients who received treatment with the same drugs. Nineteen human breast cancer cell lines were tested for sensitivity to paclitaxel (T), 5-fluorouracil (F), doxorubicin (A) and cyclophosphamide (C) in vitro. Baseline gene expression data were obtained for each cell line with Affymetrix U133A gene chips, and multigene predictors of sensitivity were derived for each drug separately. These predictors were applied individually and in combination to human gene expression data generated with the same Affymetrix platform from fine needle aspiration specimens of 133 stage I-III breast cancers. Tumor samples were obtained at baseline, and each patient received 6 months of preoperative TFAC chemotherapy followed by surgery. Cell line-derived prediction results were correlated with the observed pathologic response to chemotherapy. Statistically robust differentially expressed genes between sensitive and resistant cells could only be found for paclitaxel. False discovery rates associated with the informative genes were high for all other drugs. For each drug, the top 100 differentially expressed genes were combined into a drug-specific response predictor. When these cell line-based predictors were applied to patient data, there was no significant correlation between observed response and predicted response either for individual drug predictors or combined predictions. Cell line-derived predictors of response to four commonly used chemotherapy drugs did not predict response accurately in patients.

Purpose: We examined the correlation between HER2 expression and pathologic complete response (pCR) to paclitaxel/FAC (T/FAC) preoperative chemotherapy in breast cancer., Patients and Methods: Retrospective analysis of data including 534 patients treated with preoperative T/FAC was performed. Gene expression results were available from two datasets of 132 and 286 patients, and were used to examine the co-expression of HER2 and topoisomerase II alpha (TOP2A) and microtubule associated protein tau (MAP-Tau)., Results: Of the 534 patients, 105 (20%) had HER2-overexpressing breast cancer. The pCR rates were 33% and 15% for patients with HER2+ and HER2- tumors (P<0.001). The 5-year relapse-free survival rates were 94% and 70% in HER2+ tumors with and without pCR (P=0.009). HER2 overexpression (odds ratio 2.3, 95%CI: 1.3-3.9, P=0.004), estrogen receptor (ER) status, grade and weekly schedule of paclitaxel were each significantly and independently associated with pCR in multivariate analysis. When patients were stratified by ER status, the pCR rates were 50% for HER2+/ER-, 30% for HER2-/ER-, 19% for HER2+/ER+, and 6% for HER2-/ER+ tumors. HER2 overexpression was associated with lower expression of MAP-tau (P=0.001 and P<0.001) and higher expression of TOP2A mRNAs (P=0.048 and P=0.001) in patients with ER+ disease. ER- cancers had low MAP-tau expression regardless of HER-status., Conclusion: HER2 overexpression is associated with higher rate of pCR to preoperative T/FAC chemotherapy regardless of ER status. HER2 overexpression also correlates with increased TOP2A and decreased MAP-tau expression in ER-positive cancers.