Background

HR+/HER2+ BC is heterogeneous and there is a need to identify predictive biomarkers. We previously reported the ability of the PAM50-based CES to predict chemoendocrine sensitivity in HR+/HER2-negative BC beyond intrinsic subtype and risk of relapse (ROR) (Prat.CCR.2017). Here we evaluate the association of CES with pCR and DFS following different anti-HER2 combinations in HR+/HER2+ BC.

Methods

Intrinsic subtype and clinicopathologic data were obtained from 8 independent studies for a total of 485 HR+/HER2+ early BC. Patients (pts) were treated with anti-HER2 therapy either with endocrine therapy (PAMELA and PER-ELISA) or with chemotherapy (CHERLOB, OptiHER, LPT109096, ICO, HCB, PER-ELISA and CALGB 40601 [Alliance]). CES was evaluated as a continuous variable and categorically (CES-E [endocrine-sensitive], CES-U [uncertain] and CES-C [chemosensitive]) using previously reported cutoffs. We first performed statistical analyses in each dataset individually, and then all 8 combined. Multivariable analyses were used to test the association of the CES score with pCR and DFS.

Results

In the combined cohort, CES-E, CES-U and CES-C were identified in 16%, 22% and 62% of the pts, respectively. CES (continuous variable) was associated with higher pCR rates independent of clinical characteristics, treatment type, intrinsic subtype and study (adjusted Odd Ratio [OR]=0.42; p = 0.02). In the PER-ELISA trial, CES was also found associated with response (decrease in ki67) following 2 weeks of letrozole alone (OR=29.1, p 0.01). 295 pts (CHERLOB, ICO, HCB and CALGB40601) were analyzed for DFS with a median follow-up of 66 months (IQR 37-82). The adjusted DFS hazard ratio of the CES (continuous variable) was 0.13 (p < 0.01) independent of pCR, clinical characteristics, ROR and intrinsic subtype. In pts without pCR, disease recurrence occurred in 4% of CES-E, 19% of CES-U and 34% of CES-C pts (p < 0.01).

Conclusions

In HR+/HER+ BC, CES shows clinical validity for predicting chemoendocrine sensitivity in combination with anti-HER2 targeted therapies and is a good prognostic factor beyond intrinsic subtype and clinicopathologic characteristics.

Clinical trial identification

CALGB-40601: NCT00770809; Per-ELISA: NCT02411344; SOLTI-PAMELA: NCT01973660; SOLTI-Opti-HER:NCT01669239; LPT109096: NCT00524303; CHERLOB: NCT00429299.

Legal entity responsible for the study

Instituto de Investigaciones Biomédicas August Pi i Sunyer (IDIBAPS).

Funding

Becas FSEOM para Formación en Investigación en Centros de Referencia en el Extranjero 2018 (TP). Fundación SEOM, Becas FSEOM para Formación en Investigación en Centros de Referencia en el Extranjero 2016 (AF-M). Conquer Cancer Foundation -YIA in Breast Cancer 2019 (GG). BCRF, Susan G Komen, NCI SPORE (P50-CA58823), R01-CA229409 and Alliance U10CA180821(LAC, CMP). Instituto de Salud Carlos III - PI16/00904 (AP), Pas a Pas (AP), Save the Mama (AP), Breast Cancer Now - 2018NOVPCC1294 (AP).

Disclosure

M.V. Dieci: Honoraria (self): Genomic Health; Honoraria (self): Eli Lilly; Honoraria (self): Celgene. S. Pernas Simon: Travel/Accommodation/Expenses: Roche; Travel/Accommodation/Expenses: Novartis; Advisory/Consultancy: Polyphor; Advisory/Consultancy: TFS. J. Gavila Gregori: Honoraria (self), Advisory/Consultancy, Travel/Accommodation/Expenses: Roche; Honoraria (self), Advisory/Consultancy: Novartis; Honoraria (self), Advisory/Consultancy: Pfizer; Honoraria (self), Advisory/Consultancy: MSD Oncology. V. Guarneri: Honoraria (self): Eli Lilly; Honoraria (self): Roche/Genentech; Honoraria (self): Novartis. P. Villagrasa: Speaker Bureau/Expert testimony: NanoString Technologies. M.J. Vidal: Honoraria (self), Advisory/Consultancy, Travel/Accommodation/Expenses: Roche; Honoraria (self): Daiichi Sankyo; Honoraria (self), Advisory/Consultancy: Novartis; Honoraria (self), Travel/Accommodation/Expenses: Pfizer. M. Oliveira: Advisory/Consultancy, Research grant/Funding (institution): AstraZeneca; Research grant/Funding (institution): Philips Healthcare; Honoraria (self), Advisory/Consultancy, Research grant/Funding (institution), Travel/Accommodation/Expenses: Genentech/Roche; Honoraria (self), Research grant/Funding (institution), Travel/Accommodation/Expenses: Novartis; Research grant/Funding (institution): Immunomedics; Honoraria (self), Research grant/Funding (institution): Seattle Genetics; Advisory/Consultancy, Research grant/Funding (institution): GSK; Research grant/Funding (institution): Boehringer-Ingelheim; Advisory/Consultancy, Research grant/Funding (institution): PUMA Biotechnology; Research grant/Funding (institution): Zenith Epigenetics; Travel/Accommodation/Expenses: Pierre-Fabre; Travel/Accommodation/Expenses: GP Pharma; Travel/Accommodation/Expenses: Grünenthal; Travel/Accommodation/Expenses: Eisai. C.M. Perou: Advisory/Consultancy, Shareholder/Stockholder/Stock options: BioClassifier LLC; Licensing/Royalties: Breast PAM50 assay. A. Prat: Honoraria (self), Travel/Accommodation/Expenses: Daiichi Sankyo; Honoraria (self), Advisory/Consultancy, Research grant/Funding (self): Novartis; Honoraria (self), Advisory/Consultancy, Research grant/Funding (self): Roche; Honoraria (self), Advisory/Consultancy: Pfizer; Honoraria (self): MSD Oncology; Honoraria (self): Lilly; Advisory/Consultancy: NanoString Technologies; Advisory/Consultancy: Amgen; Advisory/Consultancy: Bristol-Myers Squibb. All other authors have declared no conflicts of interest.

Background

Changes in ctDNA levels may predict response to a variety of drugs, including CDK4/6i; however, the best assay and method are still to be defined.

Methods

This is a prospective single-center study in hormone receptor-positive/HER2-negative advanced breast cancer pts treated with CDK4/6i and endocrine therapy (ET). Paired plasma samples were collected at cycle 1 day 1 (C1) and cycle 2 day 1 (C2). Somatic alterations and variant allele fraction (VAF) were assessed using the 74-gene Guardant360 assay (Guardant Health). A VAF ratio (VAFR) was calculated for each alteration with a VAF of ≥ 0.4% at C1 or C2. Molecular response was defined for each patient as the mean of all VAFRs (mVAFR). Pts with VAFs < 0.4% at C1 and C2 were considered to have low-shedding tumors. Progression free survival (PFS) hazard ratios (HR) were calculated using a univariate Cox model. PAM50 subtypes and tumor infiltrating lymphocytes (TILs) were determined in a subset.

Results

48 pts treated with ET and palbociclib (89%) or ribociclib (11%) were analyzed with a median follow-up of 12.0 months (IQR 6.7-14.6). Clinical characteristics: 65% had visceral disease, 48% were treated as 1st-line, 35% as 2nd-line, 57% used fulvestrant and 33% an aromatase inhibitor. PAM50 subtype distribution (n=27): Luminal A (n=9), Luminal B (n=10), HER2-enriched (n=4), Normal (n=3) and Basal-like (n=1). ctDNA was detected in 96% of pts. mVAFR < 0.3 (high-ctDNA responders) (n=12) and low-shedding tumors (n=13) correlated with significantly improved PFS (HR=0.39, p=0.025), especially when compared to pts with ctDNA mVAFR > 1 (HR=0.27, p=0.010, n=12). Within PAM50 tested tumors, non-Luminal (n=5) were low-ctDNA responders (mVAFR > 0.3) (n=3) or low-shedding (n=2); Luminal A or B were high-ctDNA responders (n=8), low-ctDNA responders (n=7) and low-shedding (n=4). TILs were increased in low relative to high-ctDNA responders (mean 3.3% vs 1.8%).

Conclusions

ctDNA dynamics are an early surrogate of CDK4/6i + ET efficacy. The clinical utility of this biomarker should be tested in prospective clinical trials in which pts with unfavorable ctDNA responses are randomized to alternative treatment strategies.

Legal entity responsible for the study

The authors.

Funding

European Union’s Horizon 2020 Research and Innovation Programme under Grant agreement No. 847912.

Disclosure

M.J. Vidal: Honoraria (self), Travel/Accommodation/Expenses: Pfizer; Honoraria (self), Advisory/Consultancy: Novartis; Honoraria (self), Advisory/Consultancy, Travel/Accommodation/Expenses: Roche; Honoraria (self): Daiichi Sankyo. E.M. Ciruelos: Advisory/Consultancy: Roche; Advisory/Consultancy: Lilly; Advisory/Consultancy: Novartis; Advisory/Consultancy: Pfizer. A. Prat: Honoraria (self), Advisory/Consultancy, Research grant/Funding (institution), Full/Part-time employment, An Immediate Family Member: Novartis; Honoraria (self), Advisory/Consultancy: Pfizer; Honoraria (self), Advisory/Consultancy, Research grant/Funding (institution): Roche; Honoraria (self): MSD Oncology; Honoraria (self), Advisory/Consultancy: Amgen; Honoraria (self), Advisory/Consultancy: Daiichi Sankyo; Advisory/Consultancy: Bristol-Myers Squibb; Advisory/Consultancy: Boehringer; Advisory/Consultancy, Research grant/Funding (institution): PUMA; Advisory/Consultancy: Oncolytics Biotech; Advisory/Consultancy: AbbVie; Advisory/Consultancy: NanoString Technologies; Research grant/Funding (institution): Incyte. All other authors have declared no conflicts of interest.

Background

Resistance to CDK4/6i is inevitable. CTC count is prognostic in ABC, but its role in pts treated with CDK4/6i is not well defined. Genetic loss of RB1 is a known yet infrequent marker of CDK4/6i resistance. We assessed the prognostic role of CTC count and gene-expression (GE) levels of RB1 in CTCs in pts receiving P.

Methods

The TREnd trial (NCT02549430) randomized pts with endocrine resistant ABC to either P alone or P plus the endocrine therapy received in the prior line of treatment. In TREnd, blood samples were prospectively collected in CellSave® tubes before starting P (T0), after the first cycle (T1) and at disease progression (T2). CTCs were isolated and counted by CellSearch® System (CS) using CellSearch^TM Epithelial Cell kit. Samples with ≥5CTCs were sorted by DEPArray system® (DA). RNA extraction and retro-transcription for GE experiments were performed by Cell Lysis Two-Step RT-qPCR. RB1 and GAPDH GE levels were measured by ddPCR, with a multiplex assay with a sensitivity of 30-10 pg of cDNA, set up on three different cell lines sensitive and resistant to P.

Results

46 pts were suitable for CTC analysis. CTC count at T0 did not show significant prognostic value in terms of progression free survival (PFS). However, pts with at least 1 detectable CTC at T1 (n=26) had a worse PFS than those with 0 CTCs (n=16) (p=0.02). Similar results were observed with a cut-off of 5 CTCs (p=0.04). At T1, 7 out of 39 pts had an increase of at least 3 CTCs which proved prognostic (p=0.01). Pts with ≥5CTCs at T2 (n=6/23) who received chemotherapy as post-study treatment had a shorter time to treatment failure (p=0.02). DA sorting was conducted on 20/46 pts and GE data for RB1 were obtained from 19 pts. CTCs showed heterogeneous RB1 expression. Pts with detectable expression of RB1 in at least one time-point had better, but not significant, outcomes than those with undetectable levels.

Conclusions

Persistence or an increase in CTCs after one cycle of P may identify pts with worse outcome. High CTC counts at disease progression on P may indicate poor post-treatment prognosis. Measuring RB1 GE levels on CTCs by ddPCR is feasible, but its clinical significance is yet unclear.

Clinical trial identification

NCT02549430.

Legal entity responsible for the study

Fondazione Sandro Pitigliani per la Lotta Contro i Tumori.

Funding

Pfizer.

Disclosure

G. Curigliano: Advisory/Consultancy, Speaker Bureau/Expert testimony: Roche; Advisory/Consultancy, Speaker Bureau/Expert testimony: Seattle Genetics; Speaker Bureau/Expert testimony, writing engagement: Novartis; Advisory/Consultancy, Speaker Bureau/Expert testimony: Lilly; Advisory/Consultancy, Speaker Bureau/Expert testimony: Pfizer; Advisory/Consultancy, Speaker Bureau/Expert testimony: Foundation Medicine; Speaker Bureau/Expert testimony, Cosultancy: NanoString; Advisory/Consultancy, Speaker Bureau/Expert testimony: Samsung; Advisory/Consultancy, Speaker Bureau/Expert testimony: Celltrion; Advisory/Consultancy, scientific affairs group: Ellipsis; Speaker Bureau/Expert testimony, writing engagement: BMS; Speaker Bureau/Expert testimony: MSD; Advisory/Consultancy: Mylan. M. Benelli: Advisory/Consultancy: Novartis. L. Biganzoli: Honoraria (self), Advisory/Consultancy: AstraZeneca; Honoraria (self), Advisory/Consultancy, Research grant/Funding (self): Celgene; Honoraria (self), Advisory/Consultancy: Eisai; Honoraria (self), Advisory/Consultancy, Research grant/Funding (self): Genomic Health; Honoraria (self), Advisory/Consultancy: Ipsen; Honoraria (self), Advisory/Consultancy: Lilly; Honoraria (self), Advisory/Consultancy, Research grant/Funding (self): Novartis; Honoraria (self), Advisory/Consultancy: Pfizer; Honoraria (self), Advisory/Consultancy: Pierre Fabre; Honoraria (self), Advisory/Consultancy: Roche. A. Di Leo: Honoraria (self), Advisory/Consultancy: Amgen; Honoraria (self), Advisory/Consultancy: AstraZeneca; Honoraria (self), Advisory/Consultancy: Bayer; Honoraria (self), Advisory/Consultancy: Daiichi-Sankyo; Honoraria (self), Advisory/Consultancy: Eisai; Honoraria (self), Advisory/Consultancy: Genentech; Honoraria (self), Advisory/Consultancy: Genomic Health; Honoraria (self), Advisory/Consultancy: Lilly; Honoraria (self), Advisory/Consultancy: Novartis; Honoraria (self), Advisory/Consultancy: Pfizer; Honoraria (self), Advisory/Consultancy: Roche; Honoraria (self), Advisory/Consultancy: Seattle Genetics. L. Malorni: Advisory/Consultancy, Research grant/Funding (self): Novartis; Advisory/Consultancy, Research grant/Funding (self): Pfizer; Advisory/Consultancy: Lilly. All other authors have declared no conflicts of interest.

Background

Although the survival benefit of dual epidermal growth factor receptor 2 (HER2) blockade with trastuzumab and pertuzumab was definitely demonstrated in HER2-amplified early breast cancer, sufficient biomarkers are urgently required to explain the heterogeneous response to dual HER-2 blockade therapy. The prognostic significance of immune infiltration in TRYPHAENA trial was investigated to tailor treatment in current analysis.

Methods

Among the 225 HER2-amplified early breast cancer patients randomly assigned to trastuzumab/pertuzumab concurrently or sequentially with standard chemotherapy as neoadjuvant therapy in TRYPHAENA trial, 162 patients with available gene expression profile and complete follow-up data were enrolled. The normalized gene expression matrix (GSE109710) based on the NanoString nCounter array was downloaded from Gene Expression Omnibus database and further used to estimate the immune infiltration score (IIS) for each patient by the Immune Cell Abundance Identifier tool. A cut-off of IIS to stratify patients was determined by the R-based survminer package. Multivariable Cox proportional event-free survival (EFS) hazard ratios were preformed.

Results

Among the 162 women included in the analysis (median [range] age, 49.0 [27-81] years), the pathologic complete response (pCR) rate was 50.0% (21/42) in patients with a high IIS (>0.628) and 66.7% (80/120) in patients with a low SII (≤0.628). At a median follow-up of 4.7 years, the multivariable-adjusted hazard ratio for EFS was 2.933 (95%CI, 1.223-7.033) for the high IIS and 0.356 (95%CI, 0.127- 0.999) in patients who achieved pCR, respectively. Table: 7P

Cox regression for EFS

Conclusions

Our analysis demonstrates an independent prognostic value of IIS in patients receiving trastuzumab/pertuzumab-based neoadjuvant chemotherapy.

Clinical trial identification

NCT00976989.

Legal entity responsible for the study

The authors.

Funding

Has not received any funding.

Disclosure

All authors have declared no conflicts of interest.

Background

Despite its recognized role in breast cancer (BC), the complexity of immune microenvironment remains largely unexplored. Multiplex immunohistochemistry (mIHC) holds opportunity to more comprehensively assess BC immunity, potentially providing information to improve immunotherapy.

Methods

In the neoadjuvant phase II SOLTI-1114 PAMELA trial (NCT01973660), 151 HER2+ BC patients received lapatinib and trastuzumab, plus hormonal therapy if HR+. Baseline (BSL, n=66) and day-15 (D15, n=54) biopsies from 76 patients were analyzed using a custom mIHC 6-plex panel, including immune subtyping (CD3, CD4, CD8, FOXP3), localization (keratin for tumor mask), and activity (Ki67 for proliferation). Immune cell density (cells/mm²) and localization were determined by digital image analysis and classified in: intratumor (A), proximal peritumor (B - < 10um; C - 10 to 30um from tumor) and distal peritumor stroma (D). Intrinsic subtyping was determined at the same timepoints using the PAM50 predictor (nCounter).

Results

Both at BSL and D15, no significant difference in immune subpopulation densities was observed according to PAM50 subtype. At both timepoints, fraction of proliferating (Ki67+) immune cells (all subpopulations) differed significantly according to subtype (basal-like tumors showing the highest and luminal tumors showing the lowest fraction of proliferating cells, p varying from <0.001 to 0.031). Tumors achieving a pCR showed numerically higher densities of CD3+, CD8+ and FOXP3+ cells. Association with pCR was stronger at D15 and for immune cells intratumor/more proximal to tumor (Table). Overall, at D15, tumors achieving pCR showed higher CD3+ density (p=0.03) and higher ratio in Ki67+CD8+/Ki67+FOXP3+ (p=0.03). Table: 8P

Odds ratios (95% CI) for pCR for 1000 cells/mm2 increases in immune cell density according to subpopulation, timepoint, and localization

Conclusions

In early HER2+ BC, immune cells show differential proliferation patterns according to tumor biology. Number of immune cells spatially interacting with tumor after priming by anti-HER2 therapy was associated with pCR.

Clinical trial identification

NCT01973660.

Legal entity responsible for the study

The authors.

Funding

Vall d'Hebron Institute of Oncology (VHIO).

Disclosure

G. Griguolo: Travel/Accommodation/Expenses: Pfizer. A. Prat: Honoraria (self), Advisory/Consultancy: Pfizer; Honoraria (self), Advisory/Consultancy, Research grant/Funding (institution), immediate family member being employed by Novartis: Novartis; Honoraria (self), Advisory/Consultancy, Research grant/Funding (institution): Roche; Honoraria (self): MSD Oncology; Honoraria (self): Lilly; Honoraria (self), Travel/Accommodation/Expenses: Daiichi Sankyo; Advisory/Consultancy: NanoString Technologies; Advisory/Consultancy: Amgen; Advisory/Consultancy: Bristol-Myers Squibb. P. Nuciforo: Advisory/Consultancy: Bayer; Advisory/Consultancy, Speaker Bureau/Expert testimony: MSD Oncology; Advisory/Consultancy, Speaker Bureau/Expert testimony: Novartis. All other authors have declared no conflicts of interest.

Background

Breast cancer is the most common type of malignancy in pregnant women and it occurs in 1-4 per 10,000 pregnancies. The incidence of pregnancy associated breast cancer (PABC), accounting for up to 3.8% of all breast cancers, is expected to rise, especially in developed countries. Whether these cancers arise before or during pregnancy, and whether they are stimulated by the high hormonal environment of pregnancy, is currently unknown. This study assesses the histopathological profile of PABC in a large Dutch population-based cohort.

Methods

We identified 744 patients with PABC (defined as breast cancer diagnosed during or within six months after pregnancy), between 1988 and 2019, in the nationwide Dutch Pathology Registry (PALGA). An age-matched PALGA cohort of unselected breast cancer patients (≤ 45 years), diagnosed between 2013 and 2016, was used as a control (n=4,314). Histopathologic features of both cohorts were compared.

Results

Mean age at diagnosis of PABC patients was 34.5 years and most breast cancers were diagnosed during pregnancy (70.7%). As compared to age-matched controls, PABC patients had tumors of higher Bloom-Richardson grade (grade I: 1.2% vs. 17.9%, grade II: 14.7% vs. 35.3%, grade III: 71.9% vs. 31.1%). Furthermore, estrogen (ER) and progesterone-receptor (PR) expression was more often reported as negative (ER: 45.0% vs. 20.2%, PR: 48.8% vs. 29.4%), while a higher percentage of PABC patients was reported as overexpressing HER2 (22.0% vs. 15.1%). The most observed subtype in PABC was triple-negative breast cancer; 34.1% compared to 15.1%, and luminal subtypes represented only 17.2% v.s. 60.6% in the non-PABC cases. There were no differences in grade or hormone receptor-status between pregnant -and postpartum-PABC patients.

Conclusions

This study, based on a large population-based cohort of 744 PABC patients, underlines a different, more aggressive histopathologic profile compared to age-matched breast cancer patients ≤ 45 years. RNA-and DNA sequencing of breast tumors will be conducted to unravel the genetic background and find opportunities for prevention and optimal treatment (more targeted and less toxic).

Legal entity responsible for the study

University Medical Center Utrecht.

Funding

A Sister’s Hope for Breast Cancer Research.

Disclosure

All authors have declared no conflicts of interest.

Background

The recurrence score (RS), which is derived from the results of an assay of 21 genes, predicts the likelihood of recurrence in patients with breast cancer, thus potentially helping clinicians decide when to recommend chemotherapy. However, non-genomic clinicopathologic prognostic markers may also be able to distinguish patients with low, intermediate, and high risk of recurrence without the added cost of genetic testing.

Methods

We developed a novel non-genomic tool called predicted RS (pRS) and investigated the relationship between RS and pRS among patients with stage I estrogen receptor-positive, human epidermal growth factor receptor 2-negative (HER2) breast cancer. We reviewed the records of 1055 patients at The University of Texas MD Anderson Cancer Center with estrogen receptor-positive, HER2-negative stage I breast cancer who had RS results available. We used multivariable linear regression to develop pRS in this population. We then validated our models in a cohort of 242 patients from Anne Arundel Medical Center with the same characteristics.

Results

The pRS model is pRS = 26.089 – 0.071ER – 0.092PR + 0.132Ki67 + 1.08I[HG=II] + 7.129I[HG=III] where I is an indicator function. The pRS had a Pearson correlation coefficient of 0.7352 with RS in our validation cohort (p < 0.0001). Two (1.2%) of the 170 patients with low/intermediate RS (RS ≤25) were classified into the high pRS group (P-value <0.0001). None of the patients with a pRS >30 were considered low/intermediate risk (RS ≤ 25) as defined in the TAILORx trial. Table: 10P

Correlation between recurrence score (RS) and predicted RS (pRS) in the Anne Arundel Medical Center validation cohort using two risk categories∗

Conclusions

pRS accurately identified patients who had an RS >25 and thus were at high risk for recurrence. These patients could therefore be prescribed chemotherapy without first undergoing genetic testing.

Editorial acknowledgement

Department of Scientific Publications at The University of Texas MD Anderson Cancer Center for manuscript editing.

Legal entity responsible for the study

The authors.

Funding

90 National Cancer Institute (P30CA016672) for all MD Anderson investigators CRLCC Eugène Marquis for F.LE DU.

Disclosure

F. Le Du: Advisory/Consultancy: Myriad. N.T. Ueno: Research grant/Funding (institution): Genomic Health; Research grant/Funding (institution): Sysmex. All other authors have declared no conflicts of interest.

Background

BIOITALEE aims to study circulating tumor DNA (ctDNA) alterations, their evolution and association with clinical outcome in patients (pts) receiving ribociclib+letrozole as 1^st-line treatment for aBC. Here we report the analysis of baseline liquid biopsy (LB) and tumor tissue samples (TS), and their comparison.

Methods

287 postmenopausal pts with HR+, HER2– aBC were enrolled in 47 Italian centers. 271 pts were suitable for Next Generation Sequencing (NGS) on LB and 144 had a paired TS valid for NGS. LBs and TSs were analyzed by a Custom panel (average coverage 23000x). LBs were also analyzed by Oncomine Pan-Cancer Assay (Thermo Fisher Scientific). The agreement was determined by Cohen’s kappa statistic (K) and McNemar test (p).

Results

Of the 144 paired TSs, 116 (80.5%) were collected in the 6 months preceding study entry. In custom panel analysis, 72.9% TS and 44.4% LB, exhibited at least one alteration. The concordance was moderate (K=0.51, CI: 0.44-0.58, p<1e-4) mostly due to negative findings in LB. For PIK3CA, 21.5% of pts had TS+/LB- and discordant cases showed significantly lower allele frequencies (AFs) (Wilcoxon p<1e-4). The concordance for the 3 most frequently altered genes is detailed below: Table: 11P

25 distinct PIK3CA variants with different AFs were observed, suggesting both clonal and subclonal alterations. For LB, the concordance between Custom and Oncomine panel was good (K=0.70, CI: 0.64-0.76) (for PIK3CA, K=0.79, CI: 0.70-0.88).

Conclusions

In our study, mutations were more frequently found in TS rather than LB, supporting the strategy of querying the tissue to complement ctDNA results. The ultra-deep NGS of TS in this study, enabled improved comparison between TS and LB. LB+ findings with TS- results were infrequent. Discordancy in PIK3CA status is associated with lower AFs in TS, likely due to subclonal events. Further analyses are ongoing and will be presented.

Clinical trial identification

NCT03439046.

Legal entity responsible for the study

Novartis Farma SpA, Italy.

Funding

Novartis Farma SpA, Italy.

Disclosure

G. Bianchini: Advisory/Consultancy: Roche; Advisory/Consultancy: Novartis; Advisory/Consultancy: Eisai; Advisory/Consultancy: AstraZeneca; Advisory/Consultancy: Pfizer; Advisory/Consultancy: Lilly; Advisory/Consultancy: Genomic Health; Advisory/Consultancy: Amgen; Advisory/Consultancy: MSD; Advisory/Consultancy: Sanofi; Advisory/Consultancy: Daiichi Sankyo; Advisory/Consultancy: Chugai. M. De Laurentiis: Advisory/Consultancy, Speaker Bureau/Expert testimony: Pfizer; Advisory/Consultancy, Speaker Bureau/Expert testimony: Novartis; Advisory/Consultancy, Speaker Bureau/Expert testimony: Roche; Advisory/Consultancy, Speaker Bureau/Expert testimony: Celgene; Advisory/Consultancy, Speaker Bureau/Expert testimony: AstraZeneca; Advisory/Consultancy, Speaker Bureau/Expert testimony: Eisai; Advisory/Consultancy, Speaker Bureau/Expert testimony: Eli Lilly; Advisory/Consultancy, Speaker Bureau/Expert testimony: Amgen; Advisory/Consultancy: MSD; Advisory/Consultancy, Speaker Bureau/Expert testimony: Pierre Fabre. G. Arpino: Honoraria (self), Research grant/Funding (institution): Novartis; Honoraria (self), Research grant/Funding (institution): Roche; Honoraria (self): Lilly; Honoraria (self): AstraZeneca; Honoraria (self): MSD; Honoraria (self): Amgen; Honoraria (self), Research grant/Funding (institution): Eisai; Honoraria (self), Research grant/Funding (institution): Pfizer. A. Zambelli: Advisory/Consultancy: Novartis; Advisory/Consultancy: Roche; Advisory/Consultancy: AstraZeneca; Advisory/Consultancy: Pfizer; Advisory/Consultancy: Lilly; Advisory/Consultancy: Biogen; Advisory/Consultancy: Genomic Health. F. Puglisi: Research grant/Funding (institution): AstraZeneca; Research grant/Funding (institution): Eisai; Research grant/Funding (institution): Roche; Advisory/Consultancy: Novartis; Advisory/Consultancy: MSD; Advisory/Consultancy: Eli Lilly; Advisory/Consultancy: Roche; Advisory/Consultancy: Pfizer; Advisory/Consultancy: Pierre Fabre; Advisory/Consultancy: Eisai. L. Del Mastro: Honoraria (self): Roche; Honoraria (self): Pfizer; Honoraria (self): Ipsen; Honoraria (self): Eli Lilly; Honoraria (self): Novartis; Honoraria (self): Takeda; Honoraria (self): MSD; Honoraria (self): Genomic Health; Non-remunerated activity/ies: Celgene; Honoraria (self): Seattle Genetics. M.A. Colleoni: Advisory/Consultancy: AstraZeneca; Advisory/Consultancy: Pierre Fabre; Advisory/Consultancy: Pfizer; Honoraria (self): Novartis; Advisory/Consultancy: OBI Pharma; Advisory/Consultancy: Puma Biotechnology; Advisory/Consultancy: Celldex. F. Montemurro: Honoraria (self), Advisory/Consultancy, Speaker Bureau/Expert testimony, Travel/Accommodation/Expenses: Roche; Honoraria (self), Advisory/Consultancy, Speaker Bureau/Expert testimony: Novartis; Speaker Bureau/Expert testimony: Pfizer; Advisory/Consultancy: Pierre Fabre; Speaker Bureau/Expert testimony: Daiichi Sankyo. G.V. Bianchi: Advisory/Consultancy: Novartis; Speaker Bureau/Expert testimony: Eli Lilly. C. Zamagni: Honoraria (self), Advisory/Consultancy, Research grant/Funding (institution), Travel/Accommodation/Expenses, Non-remunerated activity/ies: Roche; Advisory/Consultancy, Research grant/Funding (institution): Eisai; Honoraria (self), Advisory/Consultancy, Research grant/Funding (institution), Travel/Accommodation/Expenses, Non-remunerated activity/ies: Novartis; Honoraria (self), Advisory/Consultancy, Research grant/Funding (institution), Non-remunerated activity/ies: AstraZeneca; Honoraria (self), Advisory/Consultancy, Research grant/Funding (institution), Travel/Accommodation/Expenses, Non-remunerated activity/ies: Pfizer; Advisory/Consultancy, Research grant/Funding (institution), Travel/Accommodation/Expenses: PharmaMar; Advisory/Consultancy, Research grant/Funding (institution), Travel/Accommodation/Expenses: Celgene; Advisory/Consultancy, Research grant/Funding (institution): Lilly; Honoraria (self), Advisory/Consultancy, Research grant/Funding (institution): Amgen; Honoraria (self), Advisory/Consultancy, Research grant/Funding (institution), Travel/Accommodation/Expenses: Tesaro; Honoraria (self), Advisory/Consultancy: QuintikesIMS; Research grant/Funding (institution), Travel/Accommodation/Expenses: Pierre Fabre; Research grant/Funding (institution), Travel/Accommodation/Expenses: Istituto Gentili; Research grant/Funding (institution): Takeda; Research grant/Funding (institution): Teva; Research grant/Funding (institution): Medivation; Research grant/Funding (institution): AbbVie; Research grant/Funding (institution): Array BioPharma; Research grant/Funding (institution): Morphotek; Research grant/Funding (institution): Synthon, Seattle Genetics. S. Bianchetti: Full/Part-time employment: Novartis. D. Castelletti: Full/Part-time employment: Novartis. M. Benelli: Honoraria (self): Novartis. L. Malorni: Advisory/Consultancy, Research grant/Funding (institution): Novartis; Advisory/Consultancy, Research grant/Funding (institution): Pfizer. All other authors have declared no conflicts of interest.

Background

In the CORALLEEN trial, R+L achieved similar response rates to multi-agent CT. We present a comprehensive gene expression analysis done before, during, and after therapy to fully characterize the biology behind the primary results of the trial.

Methods

CORALLEEN was a randomized study in postmenopausal women with stage I-IIIA hormone receptor positive (HR+)/HER2-negative Luminal B breast cancer by PAM50. Patients (pts) received either 6 cycles of R+L or 4 cycles of AC followed by 12 doses of paclitaxel. Primary endpoint was rate of PAM50 Risk of Relapse (ROR) low disease at surgery. Baseline, week 2, and surgical specimens were collected. Expression of 770 genes and 31 signatures were determined using the Breast360^TM nCounter-based codeset. Response was defined as ROR-low disease at surgery, relative/absolute changes in ROR between baseline/week 2 and surgery, RCB-0/I or levels of Ki67 at surgery. To identify genes associated with response, a significance of microarrays (SAM) analysis with a false discovery rate (FDR) <5% was performed.

Results

A total 297/318 (93.4%) samples were available. No genes or signatures at baseline, or week 2, were found to be associated with response at surgery in each arm. At week 2, 146 (14.6%) genes or signatures were found significantly up-regulated (n=47) and down-regulated (n=99) in the R+L arm compared to CT. R+L induced higher expression of genes related to DNA damage repair and immune activation (e.g. TP53, RAD52, GZMM and CD19) and lower expression of cell-cycle and hormone-related genes (e.g. PGR, CDK1 and MKI67). At surgery, 102 (10.2%) genes or signatures were found significantly up-regulated (n=4) and down-regulated (n=98) in the R+L arm compared to CT. R+L induced higher downregulation of estrogen- and proliferation-related genes and signatures (e.g. PGR, ER signaling, and MKI67).

Conclusions

No genes were able to predict response. Compared to CT, R+L induced higher downregulation of proliferation-related genes and signatures at week 2 and surgery. These results support the strategy to use the neoadjuvant setting to select patients who achieve a large molecular downstaging following CDK4/6 inhibition.

Legal entity responsible for the study

SOLTI Breast Cancer Research Group.

Funding

Novartis, Nanostring, Breast Cancer Research Foundation-AACR Career Development Award (to AP), PhD4MD grant (to NC), Fundación Científica Asociación Española Contra el Cáncer - Ayuda Postdoctoral AECC 2017 (to FB-M), This project has received funding from the European Union’s Horizon 2020 Research and Innovation Programme under Grant agreement No. 847912.

Disclosure

N. Chic: Travel/Accommodation/Expenses: Novartis. C. Saura: Advisory/Consultancy, Research grant/Funding (institution), Travel/Accommodation/Expenses: Puma biotechnology; Advisory/Consultancy, Research grant/Funding (institution), Travel/Accommodation/Expenses: Pfizer; Advisory/Consultancy, Travel/Accommodation/Expenses: Roche; Advisory/Consultancy, Travel/Accommodation/Expenses: AstraZeneca; Advisory/Consultancy, Travel/Accommodation/Expenses: Celgene; Advisory/Consultancy, Travel/Accommodation/Expenses: Daiichi-Sankyo; Advisory/Consultancy, Travel/Accommodation/Expenses: Eisai; Advisory/Consultancy, Travel/Accommodation/Expenses: Genomyc Health; Advisory/Consultancy, Research grant/Funding (institution), Travel/Accommodation/Expenses: Novartis; Advisory/Consultancy, Travel/Accommodation/Expenses: Pierre Fabre; Advisory/Consultancy, Research grant/Funding (institution), Travel/Accommodation/Expenses: Synthon biopharmaceuticals; Research grant/Funding (institution): Roche-Genentech; Research grant/Funding (institution): Macrogenics; Research grant/Funding (institution): Piqur; Research grant/Funding (institution): BMS. M. Muñoz: Speaker Bureau/Expert testimony, Research grant/Funding (institution): Novartis; Research grant/Funding (institution): Breast Cancer Research Foundation-AACR; Research grant/Funding (institution): Breast Cancer Now Career Catalyst; Travel/Accommodation/Expenses: Roche; Speaker Bureau/Expert testimony: Pfizer; Speaker Bureau/Expert testimony: Lilly. X. González-Farré: Travel/Accommodation/Expenses: Roche; Travel/Accommodation/Expenses: Eisai. M. Oliveira: Honoraria (self), Advisory/Consultancy, Travel/Accommodation/Expenses: Roche; Advisory/Consultancy: GlaxoSmithKline; Advisory/Consultancy: Puma Biotechnology; Research grant/Funding (institution): Philips Healthcare; Travel/Accommodation/Expenses: Grünenthal Group; Travel/Accommodation/Expenses: Novartis; Travel/Accommodation/Expenses: Pierre Fabre; Travel/Accommodation/Expenses: GP Pharm. M. Gil-Gil: Honoraria (self): Genentech; Honoraria (self): Novartis; Honoraria (self), Travel/Accommodation/Expenses: Pfizer; Honoraria (self), Travel/Accommodation/Expenses: Daiichi; Honoraria (self): Eisai; Travel/Accommodation/Expenses: Roche. E.M. Ciruelos: Advisory/Consultancy, Travel/Accommodation/Expenses: Roche; Advisory/Consultancy: Lilly; Advisory/Consultancy: Novartis; Advisory/Consultancy, Travel/Accommodation/Expenses: Pfizer. P. Villagrasa: Speaker Bureau/Expert testimony: NanoString. J. Gavila Gregori: Advisory/Consultancy, Research grant/Funding (institution): Novartis; Advisory/Consultancy, Research grant/Funding (institution): Pfizer; Advisory/Consultancy, Research grant/Funding (institution): Roche. A. Prat: Advisory/Consultancy, Research grant/Funding (institution): Novartis; Advisory/Consultancy, Research grant/Funding (institution): Pfizer; Advisory/Consultancy: Lilly; Advisory/Consultancy: NanoString; Advisory/Consultancy, Research grant/Funding (institution): Amgen; Advisory/Consultancy, Research grant/Funding (institution): Roche; Advisory/Consultancy: Oncolytics; Advisory/Consultancy: Daiichi; Advisory/Consultancy: Puma; Advisory/Consultancy: BMS. All other authors have declared no conflicts of interest.

Background

15-20% of breast cancers are HER2 over-expressing (IHC 3+), or over-amplified (IHC2+/ISH+) while 45% have lower levels of HER2 expression (IHC 2+/ISH- or IHC 1+); there are currently no approved HER2-targeted therapies for patients with low levels of HER2 expression. Measuring HER2 expression levels is critical in the management of patients with breast cancer yet IHC results are often confounded by multiple variables, including fixative conditions (pre-analytical) and staining procedures (analytical). In addition, results are often difficult to interpret since a number of cases show only moderate overexpression of the protein and the analysis of the IHC staining are subject to interobserver variability (post-analytical). Therefore, more sensitive and objective assays are needed to better identify patients who may benefit from anti-HER2therapies including those patients with lower levels of HER2. To address this gap, we evaluated non-antibody-based methods to quantify targets from FFPE tissue and liquid biopsy.

Methods

Here, we have analyzed 107 breast carcinomas for ERBB2 RNA and protein expression using, QRT-PCR (Fluidigm) and SRM-MS (mProbe) and compared between patients with HER2 expression levels of IHC 0(34.6%), 1+(15.9%), 2+(27.1 %) or 3+(22.4%) (ANOVA).

Results

ERBB2 RNA and protein expression were progressively increased according to HER2 IHC grouping (i.e. lowest concentration in HER2 0 samples, highest in HER2 3+ samples). ERBB2 RNA and protein levels were significantly elevated in 2+ vs. 0 samples (2-fold increase, p < 0.05). No significant trend was observed in 2+ vs. 1+ and in 1+ vs. 0. Moreover, no correlation was seen between plasma and tissue ERBB2 RNA expression or IHC status. In this work, SRM-MS revealed a 100-fold difference in HER2 expression between the HER2 IHC 0 versus IHC 3+ tumor tissue samples. PCR-based methods were not reliable enough to detect a similar range of expression.

Conclusions

These results are encouraging and favor SRM-MS profiling as a more sensitive method to detect HER2 protein levels from tumor tissue samples. Future studies will include comparative analysis of SRM-MS versus other methods to detect HER2 expression and require confirmation on a larger series of tumors, notably for the tissue samples expressing lower levels of HER2 (0, 1+ and 2+).

Legal entity responsible for the study

Translational Medicine.

Funding

AstraZeneca.

Disclosure

F. Cecchi, D. Carrolle, M. Gustavson, S. Sridhar, M. de los Reyes, S. Thyparambil, A. Bhalkikar, W-L. Liao, S. Coats, T. Hembrough: Full/Part-time employment, Employee of AstraZeneca.

Background

There are more pathological complete responses (pCR) after neoadjuvant treatment in breast cancer with predominance of tumor infiltrating lymphocytes (TILs). The objective is to analyze immunosuppressive (regulatory T) and cytotoxic (CD8+ T) TILs before and after neoadjuvant treatment and the pathological response achieved in breast carcinoma.

Methods

Translational study of 50 breast carcinoma patients with neoadjuvant treatment. Measurement of cytotoxic CD8 + and regulatory T lymphocytes (CD25H or FOXP3 +) was performed in peripheral blood (before, during and after treatment), and before (biopsy) and after (surgical specimens) neoadjuvant in tumor tissue. The pathological response was assessed according to Miller & Payne (M&P: G1: minimal changes, G2: <30%, G3: 30-90%, G4:> 90%, G5: pCR). Peripheral blood lymphocytes were measured by flow cytometry (cells/microliter) and lymphocytes from tissue were measured by immunohistochemistry using the Ladoire classification (G0: 0 cells in 5f/20x, G1: 1-5, G2: 5-15, G3: > 15).

Results

Peripheral blood CD8+ T lymphocytes decreased significantly after treatment in patients with a <30% tumor response (M&P grade 1-2), median of 239 cells/ul in cycle 1 (C1) vs 133 cells/ul in C6, p 0.041. However, they remained constant (200-300 cells/ul) in 30-90% tumor response (M&P grade 3-4) and in pCR (M&P grade 5). Median CD8+ T lymphocytes in M&P grades 1-2 vs 5 were 184 vs 258 cells/ul (p 0.044) in C4, 180 vs 276 cells/ul (p 0.023) in C5 and 133 vs 285 cells/ul (p 0.012) in C6. The percentage of CD8+ T from tissue in M&P grade 5 is focused on Ladoire grade 3, while M&P grade 1-2 highlights a lower gradation of CD8+ T (Ladoire grade 0-2). There are high levels of FOXP3+ from tissue both before and after treatment in M&P grade 1-2. However, a low FOXP3+ percentage is expressed in M&P grade 5, and even that percentage decreases drastically in Ladoire grade 2-3 after treatment. The peripheral blood regulatory T (CD25H) cells descrease in M&P grade 3-4 and do not vary in M&P grade 1.

Conclusions

There is a significant descent of CD8+ T cells in non-pCR patients, while remaining elevated in pCR. There are more FOXP3+ T cells in non-pCR. CD8+ T and regulatory T cells are potential predictive biomarkers in breast carcinoma.

Legal entity responsible for the study

Hospital Universitario Virgen Macarena, Seville, Spain.

Funding

Has not received any funding.

Disclosure

All authors have declared no conflicts of interest.