Basal-like breast cancer defined by five biomarkers has superior prognostic value than triple-negative phenotype

Purpose: Basal-like breast cancer is associated with high grade, poor prognosis, and younger patient age. Clinically, a triple-negative phenotype definition [estrogen receptor, progesterone receptor, and human epidermal growth factor receptor (HER)-2, all negative] is commonly used to identify such cases. EGFR and cytokeratin 5/6 are readily available positive markers of basallike breast cancer applicable to standard pathology specimens. This study directly compares the prognostic significance between three- and five-biomarker surrogate panels to define intrinsic breast cancer subtypes, using a large clinically annotated series of breast tumors. Experimental Design: Four thousand forty-six invasive breast cancers were assembledinto tissuemicroarrays. Allhad staging, pathology, treatment, andoutcomeinformation;median follow-up was12.5 years. Cox regression analyses and likelihood ratio tests compared the prognostic significance for breast cancer death-specific survival (BCSS) of the twoimmunohistochemicalpanels. Results: Among3,744interpretable cases,17%werebasalusing the triple-negativedefinition(10- year BCSS, 6 7%) and 9% were basal using the five-marker method (10-year BCSS, 62%). Likelihood ratio tests ofmultivariable Coxmodelsincluding standard clinical variables show that the fivemarker panel is significantly more prognostic than the three-marker panel.The poor prognosis of triple-negative phenotype is conferred almost entirely by those tumors positive for basal markers. Among triple-negativepatients treatedwithadjuvant anthracycline-based chemotherapy, theadditionalpositive basalmarkersidentified a cohort of patients with significantly worse outcome. Conclusions:The expanded surrogate immunopanel of estrogen receptor, progesterone receptor, human HER-2, EGFR, and cytokeratin 5/6 provides a more specific definition of basal-like breast cancer that better predicts breast cancer survival

A comparison of PAM50 intrinsic subtyping with immunohistochemistry and clinical prognostic factors in tamoxifen-treated estrogen receptor-positive breast cancer

Purpose: To compare clinical, immunohistochemical (IHC), and gene expression models of prognosis applicable to formalin-fixed, paraffin-embedded blocks in a large series of estrogen receptor (ER)–positive breast cancers from patients uniformly treated with adjuvant tamoxifen. Experimental Design: Quantitative real-time reverse transcription-PCR (qRT-PCR) assays for 50 genes identifying intrinsic breast cancer subtypes were completed on 786 specimens linked to clinical (median follow-up, 11.7 years) and IHC [ER, progesterone receptor (PR), HER2, and Ki67] data. Performance of predefined intrinsic subtype and risk-of-relapse scores was assessed using multivariable Cox models and Kaplan-Meier analysis. Harrell's C-index was used to compare fixed models trained in independent data sets, including proliferation signatures. Results: Despite clinical ER positivity, 10% of cases were assigned to nonluminal subtypes. qRT-PCR signatures for proliferation genes gave more prognostic information than clinical assays for hormone receptors or Ki67. In Cox models incorporating standard prognostic variables, hazard ratios for breast cancer disease-specific survival over the first 5 years of follow-up, relative to the most common luminal A subtype, are 1.99 [95% confidence interval (CI), 1.09-3.64] for luminal B, 3.65 (95% CI, 1.64-8.16) for HER2-enriched subtype, and 17.71 (95% CI, 1.71-183.33) for the basal-like subtype. For node-negative disease, PAM50 qRT-PCR–based risk assignment weighted for tumor size and proliferation identifies a group with >95% 10-year survival without chemotherapy. In node-positive disease, PAM50-based prognostic models were also superior. Conclusion: The PAM50 gene expression test for intrinsic biological subtype can be applied to large series of formalin-fixed, paraffin-embedded breast cancers, and gives more prognostic information than clinical factors and IHC using standard cut points

Predicting Drug Responsiveness in Human Cancers Using Genetically Engineered Mice

To use genetically engineered mouse models (GEMMs) and orthotopic syngeneic murine transplants (OSTs) to develop gene-expression based predictors of response to anti-cancer drugs in human tumors. These mouse models offer advantages including precise genetics and an intact microenvironment/immune system

Race, Breast Cancer Subtypes, and Survival in the Carolina Breast Cancer Study

Context: Gene expression analysis has identified several breast cancer subtypes, including basal-like, human epidermal growth factor receptor-2 positive/estrogen receptor negative (HER2+/ER–), luminal A, and luminal B. Objectives: To determine population-based distributions and clinical associations for breast cancer subtypes. Design, Setting, and Participants: Immunohistochemical surrogates for each subtype were applied to 496 incident cases of invasive breast cancer from the Carolina Breast Cancer Study (ascertained between May 1993 and December 1996), a population based, case-control study that oversampled premenopausal and African American women. Subtype definitions were as follows: luminal A (ER+ and/or progesterone receptor positive [PR+], HER2−), luminal B (ER+ and/or PR+, HER2+), basal-like (ER−, PR−, HER2−, cytokeratin 5/6 positive, and/or HER1+), HER2+/ER− (ER−, PR−, and HER2+), and unclassified (negative for all 5 markers). Main Outcome Measures: We examined the prevalence of breast cancer subtypes within racial and menopausal subsets and determined their associations with tumor size, axillary nodal status, mitotic index, nuclear pleomorphism, combined grade, p53 mutation status, and breast cancer–specific survival. Results The basal-like breast cancer subtype was more prevalent among premenopausal African American women (39%) compared with postmenopausal African American women (14%) and non–African American women (16%) of any age (P<.001), whereas the luminal A subtype was less prevalent (36% vs 59% and 54%, respectively). The HER2+/ER− subtype did not vary with race or menopausal status (6%-9%). Compared with luminal A, basal-like tumors had more TP53 mutations (44% vs 15%, P<.001), higher mitotic index (odds ratio [OR], 11.0; 95% confidence interval [CI], 5.6-21.7), more marked nuclear pleomorphism (OR, 9.7; 95% CI, 5.3-18.0), and higher combined grade (OR, 8.3; 95% CI, 4.4-15.6). Breast cancer–specific survival differed by subtype (P<.001), with shortest survival among HER2+/ER− and basal-like subtypes. Conclusions: Basal-like breast tumors occurred at a higher prevalence among premenopausal African American patients compared with postmenopausal African American and non–African American patients in this population-based study. A higher prevalence of basal-like breast tumors and a lower prevalence of luminal A tumors could contribute to the poor prognosis of young African American women with breast cancer

Responsiveness of Intrinsic Subtypes to Adjuvant Anthracycline Substitution in the NCIC.CTG MA.5 Randomized Trial

Recent studies suggest that intrinsic breast cancer subtypes may differ in their responsiveness to specific chemotherapy regimens. We examined this hypothesis on NCIC.CTG MA.5, a clinical trial randomizing premenopausal women with node-positive breast cancer to adjuvant CMF (cyclophosphamide-methotrexate-fluorouracil) versus CEF (cyclophosphamide-epirubicin-fluorouracil) chemotherapy

Impact of duration of neoadjuvant aromatase inhibitors on molecular expression profiles in estrogen receptor positive breast cancers

BACKGROUND: Aromatase inhibitors (AI) treatment is the standard of care for post-menopausal women with primary estrogen receptor positive breast cancer (BC). The impact of duration of neoadjuvant endocrine therapy (NET) on molecular characteristics is still unknown. We evaluated and compared changes of gene expression profiles under short-term (2-week) versus longer-term neoadjuvant AI. METHODS: Global gene expression profiles from POETIC trial (137 received 2 weeks of AI and 47 notreatment) and targeted gene expression from 80 BC patients treated with NET for more than one-month (NeoAI) were assessed. Intrinsic subtyping, module-scores covering different cancer-pathways and immune-related genes were calculated for pre- and post-treated tumours. RESULTS: The differences in intrinsic subtypes after NET were comparable between the two cohorts, with most Luminal B (90.0% in POETIC and 76.3% in NeoAI) and 50.0% of HER2-enriched at baseline re-classified as Luminal A or Normal-like after NET. Downregulation of proliferative-related pathways was observed after two-weeks of AI. However, more changes in genes from cancer-signaling pathways such as MAPK and PI3K/AKT/mTOR and immune response/immune-checkpoint components that were associated with AI resistant tumours and differential outcome were observed in the NeoAI study. CONCLUSIONS: Tumour transcriptional profiles undergo bigger changes in response to longer NET. Changes in HER2-enriched and Luminal B subtypes are similar between the two cohorts, thus AI sensitive intrinsic subtype tumours associated with good survival might be identified after 2 weeks of AI. The changes of immune-checkpoint component expression in early AI resistance and its impact on survival outcome warrants careful investigation in clinical trials

Response and survival of breast cancer intrinsic subtypes following multi-agent neoadjuvant chemotherapy.

Background Predicting treatment benefit and/or outcome before any therapeutic intervention has taken place would be clinically very useful. Herein, we evaluate the ability of the intrinsic subtypes and the risk of relapse score at diagnosis to predict survival and response following neoadjuvant chemotherapy. In addition, we evaluated the ability of the Claudin-low and 7-TNBCtype classifications to predict response within triple-negative breast cancer (TNBC). Methods Gene expression and clinical-pathological data were evaluated in a combined dataset of 957 breast cancer patients, including 350 with TNBC, treated with sequential anthracycline and anti-microtubule-based neoadjuvant regimens. Intrinsic subtype, risk of relapse score based on subtype and proliferation (ROR-P), the Claudin-low subtype and the 7-TNBCtype subtype classification were evaluated. Logistic regression models for pathological complete response (pCR) and Cox models for distant relapse-free survival (DRFS) were used. Results Basal-like, Luminal A, Luminal B, and HER2-enriched subtypes represented 32.7 %, 30.6 %, 18.2 %, and 10.3 % of cases, respectively. Intrinsic subtype was independently associated with pCR in all patients, in hormone receptor-positive/HER2-negative disease, in HER2-positive disease, and in TNBC. The pCR rate of Basal-like disease was >35 % across all clinical cohorts. Neither the Claudin-low nor the 7-TNBCtype subtype classifications predicted pCR within TNBCs after accounting for intrinsic subtype. Finally, intrinsic subtype and ROR-P provided independent prognostic information beyond clinicopathological variables and type of pathological response. A 5-year DRFS of 97.5 % (92.8-100.0 %) was observed in these neoadjuvant-treated and clinically node-negative patients predicted to be low risk by ROR-P (i.e. 57.4 % of Luminal A tumors with clinically node-negative disease). Conclusions Intrinsic subtyping at diagnosis provides prognostic and predictive information for patients receiving neoadjuvant chemotherapy. Although we could not exclude a survival benefit of neoadjuvant chemotherapy in patients with early breast cancer with clinically node-negative and ROR-low disease at diagnosis, the absolute benefit of cytotoxic therapy in this group might be rather small (if any)

HER2-enriched subtype and novel molecular subgroups drive aromatase inhibitor resistance and an increased risk of relapse in early ER+/HER2+ breast cancer

BACKGROUND: Oestrogen receptor positive/ human epidermal growth factor receptor positive (ER+/HER2+) breast cancers (BCs) are less responsive to endocrine therapy than ER+/HER2- tumours. Mechanisms underpinning the differential behaviour of ER+HER2+ tumours are poorly characterised. Our aim was to identify biomarkers of response to 2 weeks’ presurgical AI treatment in ER+/HER2+ BCs. METHODS: All available ER+/HER2+ BC baseline tumours (n=342) in the POETIC trial were gene expression profiled using BC360™ (NanoString) covering intrinsic subtypes and 46 key biological signatures. Early response to AI was assessed by changes in Ki67 expression and residual Ki67 at 2 weeks (Ki67(2wk)). Time-To-Recurrence (TTR) was estimated using Kaplan-Meier methods and Cox models adjusted for standard clinicopathological variables. New molecular subgroups (MS) were identified using consensus clustering. FINDINGS: HER2-enriched (HER2-E) subtype BCs (44.7% of the total) showed poorer Ki67 response and higher Ki67(2wk) (p<0.0001) than non-HER2-E BCs. High expression of ERBB2 expression, homologous recombination deficiency (HRD) and TP53 mutational score were associated with poor response and immune-related signatures with High Ki67(2wk). Five new MS that were associated with differential response to AI were identified. HER2-E had significantly poorer TTR compared to Luminal BCs (HR 2.55, 95% CI 1.14–5.69; p=0.0222). The new MS were independent predictors of TTR, adding significant value beyond intrinsic subtypes. INTERPRETATION: Our results show HER2-E as a standardised biomarker associated with poor response to AI and worse outcome in ER+/HER2+. HRD, TP53 mutational score and immune-tumour tolerance are predictive biomarkers for poor response to AI. Lastly, novel MS identify additional non-HER2-E tumours not responding to AI with an increased risk of relapse. FUNDING: Cancer Research UK (CRUK/07/015)