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PURPOSE: There is currently no standardised definition for patients at high risk of recurrence of HER2-negative early breast cancer (eBC, stages 1–3) after surgery. Recognising that the assessment of high risk is often multifactorial, the aim of this modified Delphi panel was to establish expert UK consensus on this definition, separately considering HR-positive and triple-negative (TN) patients. METHODS: A total of 45 UK-based clinicians, including breast cancer oncologists and surgeons, were invited to participate. The number of respondents in each of three rounds was 29, 24 and 22 respectively. Statements were developed using the results from a targeted literature review and the guidance of a lead clinician, and comprised free-text, single-choice or numerical formats. The first round aimed to determine which factors are currently used in clinical practice to assess risk of recurrence in the populations of interest. In the subsequent rounds, the objective was to establish thresholds indicative of high risk in a 10-year timeframe for each of the factors retained in Round 1. Between each round, statements were refined, considering the distribution of responses and free-text notes provided by participants. Consensus for single-choice questions was set at a pre-defined threshold of ≥70% of respondents. RESULTS: Consensus was achieved on the need to assess age, tumour size, tumour grade, number of positive nodes, presence of inflammatory breast cancer and one or more risk prediction tools to define high risk of recurrence in all HER2-negative patients. In HR-positive patients, there was agreement on the use of one or more tumour profiling tests and biomarkers to define high risk of recurrence. However, there was no consensus on biomarker use in TN patients, and support for specific biomarkers (such as Ki-67) was conflicting for both sub-populations based on the analysis of free-text notes. Similarly, while there was consensus on the use of pCR status/residual disease to indicate high risk in TN patients, this factor failed to reach consensus for the HR-positive sub-population. Germline BRCA status and menopausal status were not considered to be key factors for risk of recurrence in either biological subtype. In the second and third rounds, thresholds indicative of high recurrence risk were agreed; it should be noted that the free-text responses provided by the participants frequently highlighted that many of the factors should be considered along a continuous scale when assessing the risk of individual patients. In HR-positive patients, these thresholds included: age < 35 years, tumour size >5 cm (each when considered independently from other risk factors); tumour grade 3 (independently or in combination with other factors); number of positive lymph nodes ≥4 when considered independently or ≥1 in combination with other factors. For patients with TN tumours, the following thresholds reached consensus, whether considered independently or in combination with other factors: tumour size >2 cm, tumour grade 3, number of positive lymph nodes ≥1. In several cases, however, no consensus could be reached on the appropriate threshold indicating high risk of recurrence. In the HR-positive sub-population, these included thresholds for age and tumour size, when considered in combination with other factors. In the TN sub-population, this included age, whether independently or in combination with other factors. CONCLUSIONS: The expert consensus reached in this panel highlights that an integrated model is important in assessing recurrence risk in eBC and that definitions of high risk differ according to biological subtype. The results may serve as a valuable reference point for clinicians to use in assessing risk of disease recurrence and in making treatment decisions after surgery in the HER2-negative eBC population. FUNDING: AstraZeneca UK Ltd. Writing support: Costello Medical. Citation Format: Ellen R. Copson, Jean E. Abraham, Jeremy P. Braybrooke, Stuart A. McIntosh, Caroline O. Michie, Carlo Palmieri, Rebecca Roylance, Saiqa Spensley. Expert consensus on the definition of high risk of recurrence in HER2-negative early breast cancer: a modified Delphi panel [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium; 2022 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2023;83(5 Suppl):Abstract nr P3-05-39.

Supplementary Materials (clean)

Hyperpolarized 13C-MRI is an emerging tool for probing tissue metabolism by measuring 13C-label exchange between intravenously injected hyperpolarized [1–13C]pyruvate and endogenous tissue lactate. Here, we demonstrate that hyperpolarized 13C-MRI can be used to detect early response to neoadjuvant therapy in breast cancer. Seven patients underwent multiparametric 1H-MRI and hyperpolarized 13C-MRI before and 7–11 days after commencing treatment. An increase in the lactate-to-pyruvate ratio of approximately 20% identified three patients who, following 5–6 cycles of treatment, showed pathological complete response. This ratio correlated with gene expression of the pyruvate transporter MCT1 and lactate dehydrogenase A (LDHA), the enzyme catalyzing label exchange between pyruvate and lactate. Analysis of approximately 2,000 breast tumors showed that overexpression of LDHA and the hypoxia marker CAIX was associated with reduced relapse-free and overall survival. Hyperpolarized 13C-MRI represents a promising method for monitoring very early treatment response in breast cancer and has demonstrated prognostic potential.Significance:Hyperpolarized carbon-13 MRI allows response assessment in patients with breast cancer after 7–11 days of neoadjuvant chemotherapy and outperformed state-of-the-art and research quantitative proton MRI techniques.

Background: Triple Negative Breast Cancers (TNBC) are a biologically diverse and aggressive subgroup lacking targeted therapy. Germline BRCA (gBRCA) breast cancer and TNBC share some phenotypic and molecular similarities, with 10%-20% of TNBC patients having gBRCA mutations. Homologous recombination deficient tumours are particularly sensitive to PARP inhibitors such as olaparib (Lynparza). It has been shown that adjuvant olaparib for patients with high-risk, HER2-negative early breast cancer and gBRCA pathogenic or likely pathogenic variants after adjuvant or neoadjuvant chemotherapy significantly improves 3-year invasive and distant disease-free survival compared to placebo (OlympiA). Aim: To establish if the addition of olaparib to neoadjuvant platinum based chemotherapy for basal TNBC and/or gBRCA breast cancer is safe and improves efficacy (pathological complete response (pCR) rate). Trial design: 3-stage open label randomised phase II/III trial of neoadjuvant paclitaxel and carboplatin +/- olaparib, followed by clinicians' choice of anthracycline regimen. Stage 1 and 2: Randomisation (1:1:1) to either control (3 weekly carboplatin AUC5/weekly paclitaxel 80mg/m2 for 4 cycles) or one of two research arms with the same chemotherapy regimen but with two different schedules of olaparib 150mg BD for 12 days. Stage 3: Randomisation (1:1) to either control arm or to the research arm selected in stage 2. End-points: Stage 1: Safety; Stage 2: Schedule selection using pCR rate and completion rate of olaparib using a “pick-the-winner” design. Stage 3: pCR rate. This trial includes an optional pathway (PARTNERING) aiming to establish if the addition of new agents (ATR inhibitor and PDL1 inhibitor) can improve response in those patients with evidence of residual disease before surgery. Eligibility criteria: Aged 16-70; histologically confirmed invasive breast cancer; ER-negative, HER2-negative with TNBC basal phenotype or gBRCA positive, HER2-negative irrespective of hormone status; clinical stage T1-4 N0-2; performance status 0-1; treatment commenced within 6 weeks of diagnostic biopsy; biomarker scores: TILs, CK 5/6, EGFR +/- AR. Statistical methods: The recruitment of TNBC non-gBRCA and gBRCA patients is independent. Enrichment design is applied with an overall significance level 0.05(α) and 80% power. A minimum of 780 patients will be included to detect an absolute improvement of 15% (all patients and the TNBC non-gBRCA cohort) and 20% (gBRCA patients) by adding olaparib to platinum based chemotherapy. It is planned to recruit a minimum of 188 gBRCA patients. A maximum of 15 patients will be allocated into each PARTNERING cohort. Present accrual: Recruitment commenced 27 May 2016 and 678 patients from 30 sites have been accrued to date. The IDSMC reviewed the trial after Stages 1 and 2 and recommended to continue the trial without change. Data analysis for Stage 2 revealed no safety concerns and research arm 2 (olaparib on day 3 to day 14) was selected. Stage 3 Phase I recruitment is in progress (recruiting TNBC non-gBRCA and gBRCA patients) and we anticipate moving to Phase II (recruiting gBRCA patients only) by early 2022. Four patients have been accrued to the PARTNERING optional pathway to date. The trial is open and enrolling patients to UK and international sites. Contact information: partner@addenbrookes.nhs.uk Citation Format: Lynsey M Drewett, Karen A Pinilla, Louise Grybowicz, Jerome Wulff, Alimu Dayimu, Nikolaos Demiris, Jessica Martin, Camila Maida de Pontes, Nicola Johnson, Caron Harvey, Erdem Demir, Kimberley St John Green, James Jones, Gemma Young, Anne-Laure Vallier, Wendi Qian, Andrea Machin, Karen McAdam, Rebecca Roylance, Ellen R Copson, Anne Armstrong, Nicola Levitt, Elena Provenzano, Marc Tischkowitz, Emma McMurtry, Helena Earl, Jean E Abraham. PARTNER: Randomised, phase II/III trial to evaluate the safety and efficacy of the addition of olaparib to platinum-based neoadjuvant chemotherapy in triple negative and/or germline BRCA mutated breast cancer patients [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 OT2-24-01.

Purpose: Associations between taxane-related sensory neuropathy (TRSN) and single-nucleotide polymorphisms (SNP) have previously been reported, but few have been replicated in large, independent validation studies. This study evaluates the association between previously investigated SNPs and TRSN, using genotype data from a study of chemotherapy-related toxicity in patients with breast cancer.Experimental Design: We investigated 73 SNPs in 50 genes for their contribution to TRSN risk, using genotype data from 1,303 European patients. TRSN was assessed using National Cancer Institute common toxicity criteria for adverse events classification. Unconditional logistic regression evaluated the association between each SNP and TRSN risk (primary analysis). Cox regression analysis assessed the association between each SNP and cumulative taxane dose causing the first reported moderate/severe TRSN (secondary analysis). The admixture likelihood (AML) test, which considers all SNPs with a prior probability of association with TRSN together, tested the hypothesis that certain SNPs are truly associated.Results: The AML test provided strong evidence for the association of some SNPs with TRSN (P = 0.023). The two most significantly associated SNPs were rs3213619(ABCB1) [OR = 0.47; 95% confidence interval (CI), 0.28–0.79; P = 0.004] and rs9501929(TUBB2A) (OR = 1.80; 95% CI, 1.20–2.72; P = 0.005). A further 9 SNPs were significant at P-value ≤ 0.05.Conclusion: This is currently the largest study investigating SNPs associated with TRSN. We found strong evidence that SNPs within genes in taxane pharmacokinetic and pharmacodynamic pathways contribute to TRSN risk. However, a large proportion of the inter-individual variability in TRSN remains unexplained. Further validated results from GWAS will help to identify new pathways, genes, and SNPs involved in TRSN susceptibility. Clin Cancer Res; 20(9); 2466–75. ©2014 AACR.

PDF file - 237KB, Supplementary Table 1: Published Studies of Putative Functional SNPs Supplementary Table 2a: Drug Regimens and Doses of Taxanes by Study Supplementary Table 2b: Comparison of Toxicity grades/rates by recruiting trial in PGSNPS included in Taxane Related Sensory Neuropathy Study Supplementary Table 3: PGSNPS Taxane Treated Patient Characteristics Supplementary Table 4: All Putative Functional SNPs Replicated in the PGSNPS dataset (phenotype: cumulative dose to TRSN) Supplementary Table 5: All Putative Functional SNPs Replicated in the PGSNPS dataset (phenotype: maximum TRSN) Supplementary Figure 1: Percentage of Patients with TRSN ≥ grade 2 by genotype, for three statistically significant SNPs that were genotyped in PGSNPS (maximum TRSN) Supplementary Figures 2a-c: Kaplan-Meier curves Kaplan-Meier curves: Shows for each SNP, by genotype, the probability of TRSN grade 0-1 (i.e., the probability of not experiencing moderate/severe TRSN) as the cumulative dose increases.

Supplementary Tables S1-S4 from Common Polymorphisms in the Prostaglandin Pathway Genes and Their Association with Breast Cancer Susceptibility and Survival

Purpose: There is evidence that genetic variation in the prostaglandin pathway affects cancer susceptibility and progression. Conflicting data from several studies exist for the association of PTGS2 (cyclooxygenase 2) polymorphisms with breast cancer risk. We investigated associations between common germ-line variations in seven genes in the prostaglandin pathway and breast cancer susceptibility and survival among women with invasive breast cancer in the SEARCH study.Experimental Design: DNA samples from 9,030 cases and controls were genotyped for 64 single nucleotide polymorphisms tagging known common variants (minor allele frequency > 0.05) in PTGS1, PTGS2, TBXAS1, PTGIS, PTGES, PTGDS, and PGDS with a two-stage case-control study design.Results: Four tagging single nucleotide polymorphisms showed modest association with breast cancer susceptibility. All four fit a recessive genetic model. Minor allele homozygotes for PTGISrs5602 [odds ratio (OR), 1.15; 95% confidence interval (95% CI), 1.04-1.27; P = 0.005], PTGISrs8183919 (OR, 1.22; 95% CI, 1.06-1.41; P = 0.006), and TBXASrs41727 (OR, 1.83; 95% CI, 1.22-2.73; P = 0.003) are associated with an increased risk compared with common allele carriers. For PTGISrs44627 minor allele homozygotes (OR, 0.66; 95% CI, 0.5-0.86; P = 0.002), a protective effect was observed.Conclusion: Specific PTGIS and TBXAS1 variants may affect breast cancer susceptibility, but common variants in PTGS1, PTGS2, PTGES, PTGDS, and PGDS have no major role in breast cancer susceptibility. None of the variants in the seven genes studied appear to affect survival. Further larger studies correlating clinical and genotypic data are required to establish if the clinical utility of prostaglandin-targeted therapies, as chemoprevention agents, is influenced by an individual's profile of genetic variants in key prostaglandin pathway genes.

Background: Previous studies have independently validated the prognostic relevance of residual cancer burden (RCB) after neoadjuvant chemotherapy. We used results from several independent cohorts in a pooled patient-level analysis to evaluate the relationship of RCB with long-term prognosis across different phenotypic subtypes of breast cancer, to assess generalisability in a broad range of practice settings. Methods: In this pooled analysis, 12 institutes and trials in Europe and the USA were identified by personal communications with site investigators. We obtained participant-level RCB results, and data on clinical and pathological stage, tumour subtype and grade, and treatment and follow-up in November, 2019, from patients (aged ≥18 years) with primary stage I–III breast cancer treated with neoadjuvant chemotherapy followed by surgery. We assessed the association between the continuous RCB score and the primary study outcome, event-free survival, using mixed-effects Cox models with the incorporation of random RCB and cohort effects to account for between-study heterogeneity, and stratification to account for differences in baseline hazard across cancer subtypes defined by hormone receptor status and HER2 status. The association was further evaluated within each breast cancer subtype in multivariable analyses incorporating random RCB and cohort effects and adjustments for age and pretreatment clinical T category, nodal status, and tumour grade. Kaplan-Meier estimates of event-free survival at 3, 5, and 10 years were computed for each RCB class within each subtype. Findings: We analysed participant-level data from 5161 patients treated with neoadjuvant chemotherapy between Sept 12, 1994, and Feb 11, 2019. Median age was 49 years (IQR 20–80). 1164 event-free survival events occurred during follow-up (median follow-up 56 months [IQR 0–186]). RCB score was prognostic within each breast cancer subtype, with higher RCB score significantly associated with worse event-free survival. The univariable hazard ratio (HR) associated with one unit increase in RCB ranged from 1·55 (95% CI 1·41–1·71) for hormone receptor-positive, HER2-negative patients to 2·16 (1·79–2·61) for the hormone receptor-negative, HER2-positive group (with or without HER2-targeted therapy; p

Breast cancers are complex ecosystems of malignant cells and the tumour microenvironment1. The composition of these tumour ecosystems and interactions within them contribute to responses to cytotoxic therapy2. Efforts to build response predictors have not incorporated this knowledge. We collected clinical, digital pathology, genomic and transcriptomic profiles of pre-treatment biopsies of breast tumours from 168 patients treated with chemotherapy with or without HER2 (encoded by ERBB2)-targeted therapy before surgery. Pathology end points (complete response or residual disease) at surgery3 were then correlated with multi-omic features in these diagnostic biopsies. Here we show that response to treatment is modulated by the pre-treated tumour ecosystem, and its multi-omics landscape can be integrated in predictive models using machine learning. The degree of residual disease following therapy is monotonically associated with pre-therapy features, including tumour mutational and copy number landscapes, tumour proliferation, immune infiltration and T cell dysfunction and exclusion. Combining these features into a multi-omic machine learning model predicted a pathological complete response in an external validation cohort (75 patients) with an area under the curve of 0.87. In conclusion, response to therapy is determined by the baseline characteristics of the totality of the tumour ecosystem captured through data integration and machine learning. This approach could be used to develop predictors for other cancers., Integration of pre-treatment tumour features in predictive models using machine learning could inform on response to therapy.

Purpose To compare hyperpolarized carbon 13 (13C) MRI with dynamic contrast material–enhanced (DCE) MRI in the detection of early treatment response in breast cancer. Materials and Methods In this institutional review board–approved prospective study, a woman with triple-negative breast cancer (age, 49 years) underwent 13C MRI after injection of hyperpolarized [1–carbon 13 {13C}]-pyruvate and DCE MRI at 3 T at baseline and after one cycle of neoadjuvant therapy. The 13C-labeled lactate-to-pyruvate ratio derived from hyperpolarized 13C MRI and the pharmacokinetic parameters transfer constant (Ktrans) and washout parameter (kep) derived from DCE MRI were compared before and after treatment. Results Exchange of the 13C label between injected hyperpolarized [1-13C]-pyruvate and the endogenous lactate pool was observed, catalyzed by the enzyme lactate dehydrogenase. After one cycle of neoadjuvant chemotherapy, a 34% reduction in the 13C-labeled lactate-to-pyruvate ratio resulted in correct identification of the patient as a responder to therapy, which was subsequently confirmed via a complete pathologic response. However, DCE MRI showed an increase in mean Ktrans (132%) and mean kep (31%), which could be incorrectly interpreted as a poor response to treatment. Conclusion Hyperpolarized 13C MRI enabled successful identification of breast cancer response after one cycle of neoadjuvant chemotherapy and may improve response prediction when used in conjunction with multiparametric proton MRI. Published under a CC BY 4.0 license.