Background
The antibody–drug conjugate (ADC) trastuzumab emtansine (T-DM1) is composed of the anti-human epidermal growth factor receptor 2 (HER2) antibody trastuzumab linked to the cytotoxic agent DM1 through a stable, uncleavable linker [
1]. T-DM1 selectively delivers DM1 to HER2-positive tumor cells and retains the mechanisms of action of trastuzumab [
2]. Based on results from a randomized phase III study (EMILIA) [
3], T-DM1 was approved by the US Food and Drug Administration (FDA) in 2013 for the treatment of patients with HER2-positive metastatic breast cancer (mBC) who previously received trastuzumab and a taxane. T-DM1 is also FDA-approved as an adjuvant treatment in patients with HER2-positive early breast cancer (eBC) with residual invasive disease after neoadjuvant taxane and trastuzumab-based treatment, based on findings from the KATHERINE study [
4,
5].
Pertuzumab is an anti-HER2 antibody that differs from trastuzumab by blocking HER2 dimerization with other HER family members, thereby inhibiting ligand-dependent HER2 signaling [
6]. In combination with trastuzumab and docetaxel, pertuzumab is FDA-approved for the first-line treatment of HER2-positive mBC [
7] and in the neoadjuvant setting for patients with HER2-positive, locally advanced, inflammatory, or eBC based on demonstration of improvements in pathologic complete response (pCR) and invasive disease-free survival (iDFS) rates versus trastuzumab and chemotherapy [
5,
8]. In the phase III MARIANNE study, first-line treatment with T-DM1 alone or in combination with pertuzumab (T-DM1 + P) was associated with non-inferior efficacy but better tolerability than trastuzumab plus taxane in patients with HER2-positive mBC [
9]. T-DM1 + P was also assessed in patients with HER2-positive stage II/III breast cancer in KRISTINE, a phase III study that compared neoadjuvant T-DM1 + P with docetaxel, carboplatin, and trastuzumab plus pertuzumab (TCH + P) [
10,
11]. As reported previously, the pCR rate was higher in the TCH + P arm versus T-DM1 + P (55.7% vs. 44.4%; absolute difference − 11.3 percentage points, 95% confidence interval [CI] – 20.5 to – 2.0;
P = 0.016) [
10]. Event-free survival (EFS) at 3 years numerically favored TCH + P, with a higher number of locoregional progression events before surgery in patients treated with T-DM1 + P; iDFS after surgery was similar between arms [
11].
Biomarker analyses could potentially elucidate patient subgroups with better prognosis or with a higher likelihood of clinical benefit from treatment with specific HER2-targeted regimens (e.g., T-DM1 + P vs. TCH + P) in the adjuvant/neoadjuvant setting [
12]. Exploratory biomarker analyses from previous studies of HER2-targeted therapy have shown associations between the levels of HER2 amplification and/or expression and outcomes in both mBC [
13‐
15] and eBC [
16,
17]. Consistent with these data, the HER2-enriched (HER2-E) intrinsic breast cancer subtype has been associated with better responses [
18‐
21] and favorable long-term outcomes in patients treated with neoadjuvant HER2-targeted therapy [
18,
21,
22]. In addition, increased HER2 heterogeneity has been associated with reduced benefit from T-DM1 [
15]. Preclinical and clinical evidence suggests that mutated (vs. non-mutated) phosphatidylinositol-4,5-bisphosphate 3-kinase catalytic subunit alpha (
PIK3CA) confers resistance to HER2-targeted therapies [
17,
23]. Markers indicating an activated immune microenvironment, such as higher tumor-infiltrating lymphocytes (TILs) [
24‐
26] or higher expression of immune gene signatures, are associated with higher pCR rates [
19,
27] and better long-term outcomes in HER2-positive BC [
23,
28]. Other biomarkers have also been hypothesized to influence outcomes, such as the anti-apoptotic marker bcl-2 [
29] and expression of the MDR1/ABCB1 drug efflux pump, for which upregulation has been associated with resistance to T-DM1 and other therapeutics in breast cancer [
30‐
32]. Here, we report the results obtained from exploratory analyses designed to examine a variety of biomarkers and their association with clinical outcomes in patients who participated in the KRISTINE study.
Methods
Study design and patients
The KRISTINE study design and results from primary and secondary analyses have been reported elsewhere [
10,
11]. Briefly, KRISTINE (ClinicalTrials.gov #NCT02131064) was a randomized, multicenter, open-label, phase III study of treatment-naïve patients with HER2-positive, operable, stage II/III breast cancer. All tumors scored as HER2-positive according to local testing were confirmed by central testing. Patients were randomized (1:1) to receive six cycles (administered every 3 weeks) of neoadjuvant T-DM1 + P (T-DM1: 3.6 mg/kg; P: 840 mg loading dose, then 420 mg maintenance doses) or TCH + P (docetaxel: 75 mg/m
2; carboplatin: area under the concentration–time curve 6 mg/mL × min; trastuzumab: 8 mg/kg loading dose, then 6 mg/kg maintenance doses; P: 840 mg loading dose, then 420 mg maintenance doses). All drugs were administered intravenously. HER2-targeted therapy continued within 9 weeks after surgery for a maximum of 18 total cycles in the neoadjuvant/adjuvant settings. At the discretion of the treating physician, patients treated with neoadjuvant T-DM1 + P could initiate adjuvant chemotherapy.
The primary efficacy endpoint was locally determined pCR (ypT0/is, ypN0), assessed using samples taken at surgery following the completion of neoadjuvant therapy [
10]. Secondary endpoints included EFS (defined as the time from randomization to disease progression, disease recurrence, or death from any cause), iDFS, and overall survival. Exploratory biomarker analyses (both predefined and post hoc) were conducted to evaluate potential associations between tissue biomarkers and pCR in each treatment arm. The association of selected biomarkers of interest with EFS was also assessed, but using data pooled from both treatment arms due to the low event rate. The iDFS event rate was too low to enable any assessment of association with tissue biomarkers.
The KRISTINE study protocol, which included a description of preplanned exploratory biomarker analyses, received ethics approval from the institutional review board or ethics committee at each study site, and all patients provided written informed consent. The study was conducted in accordance with the International Conference on Harmonization Good Clinical Practice guidelines and the Declaration of Helsinki.
Biomarker assessments
Biomarker analyses were conducted on formalin-fixed paraffin-embedded tumor tissue collected at baseline for all markers (Additional file
1: Table S1) and at cycle 2 and surgery for selected markers. HER2 status used for study eligibility was centrally assessed at baseline at Targos Molecular Pathology GmbH (Kassel, Germany). HER2 positivity was defined as immunohistochemistry 3 + (IHC3+) (using PATHWAY anti-HER2/neu [4B5] assay, Ventana Medical Systems, Roche Diagnostics) and/or HER2/CEP17 gene ratio ≥ 2 by in situ hybridization (using ISH; INFORM HER2 Dual ISH assay, Ventana Medical Systems, Roche Diagnostics). As part of the central HER2 assessment, the percentage and intensity of HER2 staining was assessed manually by central laboratory pathologists and categorized as focal (< 30% of cells positive for HER2), heterogeneous (30–79%), or homogeneous (≥ 80%) in the subgroup of patients with HER2 IHC2+ or IHC3+ staining, as previously described [
15] (Additional file
1: Fig. S1). HER2 H-score was calculated as ((%IHC3+) × 3) + ((%IHC2+) × 2) + (%IHC1+) [
15,
33]. HER2 and HER3 messenger RNA (mRNA) expression were measured at baseline using quantitative reverse transcriptase polymerase chain reaction (qRT-PCR) using the cobas® z 480 analyzer (Roche Diagnostics).
PIK3CA mutation status was determined at baseline using the cobas®
PIK3CA Mutation Test on the cobas® z 480 analyzer (both Roche Diagnostics).
Expression of additional predefined single genes and signatures of interest were analyzed using a custom 800-gene codeset on the nCounter® platform (NanoString Technologies) from samples collected at baseline, cycle 2, and surgery. Genes of interest included HER2, programmed death ligand 1 (PD-L1), CD8, predefined immune signatures including 3-gene (PD-L1/IFNG/CXCL9), 5-gene (PD-L1/granzyme B/CD8/IFNG/CXCL9), T effector (Teff) signature (CD8/granzyme A/granzyme B/perforin/IFNG), chemokine signaling (ThCytokines signature, i.e., CXCL9/CXCL10/CXCL11), and checkpoint inhibitor signatures (PD-L1/PD-L2/IDO), as well as other markers of interest (complete listing available in Additional file
1: Table S2) based on knowledge of the immune signatures and TILs associated with pCR in HER2-positive eBC [
17,
19].
The Prediction Analysis of Microarray with the 50-gene classifier (PAM50) subtype prediction [
34] was carried out using the random-forest-based classifier [
35] and examined HER2-E, luminal A, luminal B, and basal-like as the major intrinsic breast cancer subtypes.
Expression of PD-L1 by IHC was assessed post hoc (Ventana SP142 assay, Roche Diagnostics) from samples collected at baseline, cycle 2, and surgery. PD-L1-positive disease was defined as tumor-infiltrating immune cell (IC) expression ≥ 1% of the tumor area (IC score 1, 2, or 3), while PD-L1-negative disease was defined as PD-L1 expression on IC < 1% of the tumor area (IC score 0) [
36]. Stromal TILs were assessed post hoc using hematoxylin and eosin images from tumor samples according to the International Immuno-oncology Biomarker Working Group on Breast Cancer guidelines [
25] from samples collected at baseline, cycle 2, and surgery. A predefined cutoff was used to define high- (> 10%) and low- (≤ 10%) infiltrated tumors.
Local hormone receptor status was assessed as a stratification factor, and centrally assessed hormone receptor status was used for the biomarker analyses. Hormone receptor-positive disease was defined as estrogen and/or progesterone receptor staining of ≥ 1% (Dako Omnis IHC assay, Agilent Technologies).
FcγR IIa (rs1801274), FcγR IIIa (s396991), ABCB1 polymorphisms (RS1045642), and ABCG2 polymorphisms (RS2231142) were analyzed based on whole blood samples collected at baseline or during the study. Polymorphisms were assessed using genotyping assays from ThermoFisher and TaqMan probe chemistry.
All biomarkers were analyzed for their correlation with pCR. In addition, specific biomarkers (HER2 IHC subgroups, PIK3CA mutation status, and PD-L1 status) were measured from baseline samples and evaluated for their correlation with EFS in a pooled analysis of both treatment arms. These biomarkers were selected for EFS analyses based on their potential as targets of possible combination therapies and the robustness of the assays.
Statistical methods
pCR rates by treatment arm were assessed across biomarker subgroups for HER2 IHC (IHC1+, IHC2+, or IHC3+), HER2/CEP17 gene ratio (≥ 2 to < 4 or ≥ 4), HER2 and HER3 mRNA expression (≤ median or > median), HER2 staining pattern (focal, heterogeneous, or homogeneous), PIK3CA mutation status (mutated or non-mutated), intrinsic breast cancer subtype (HER2-E, luminal A, luminal B, or basal-like), PD-L1 expression (IC 0 or IC 1, 2, or 3), stromal TILs (≤ 10% or > 10%), single genes of interest, and immune genes/signatures (≤ median or > median).
A multivariate analysis was carried out to identify biomarkers most prognostic for pCR, regardless of treatment. Univariate analysis based on a logistic model was conducted for all biomarkers assessed. Biomarkers showing at least a moderate potential association with pCR (< 0.15 significance level) were included in a multivariate logistic model in which backwards selection was applied. The final analysis model included randomized treatment plus the set of biomarker covariates selected based on the previous step.
An unstratified Cox proportional hazards model was used to estimate hazard ratios (HRs) between biomarker subgroups (preplanned: HER2 IHC subgroups [3+ versus 2+], PD-L1 IHC [IC 1/2/3 versus IC 0], and PIK3CA [mutated versus non-mutated]; post hoc: PAM50 subtype [HER2-E versus non-HER2-E]) and corresponding 95% CIs for the EFS endpoint. The Kaplan–Meier approach was used to estimate 3-year EFS rates and corresponding 95% CIs.
Changes in PAM50 subtype, PD-L1 IHC status, percentage of stromal TILs, and HER2 mRNA levels (NanoString) from baseline to cycle 2 and surgery were assessed by treatment arm.
As these were exploratory analyses, all gene expression levels, HRs, odds ratios, and 95% CIs should be considered descriptive and are included for illustrative purposes only. The clinical cutoff dates for the biomarker analyses were the same as those used for the primary and secondary endpoints: December 3, 2015, for the pCR analysis and May 29, 2018, for the final EFS analysis.
Discussion
Consistent with the analysis of pCR in the ITT population from KRISTINE [
10], pCR rates in this exploratory biomarker analysis were numerically lower in the T-DM1 + P versus TCH + P treatment arm for the majority of the assessed biomarkers. The only exception was the luminal A subgroup, which appeared to favor T-DM1 + P; however, the interpretation of these data is limited by the small sample sizes in this subgroup. Therefore, no subgroup of patients that clearly benefited from neoadjuvant T-DM1 + P versus TCH + P was identified. As expected, higher HER2 levels (based on mRNA and protein expression, gene amplification, and HER2-E intrinsic subtype) were associated with numerically higher pCR rates versus those observed with lower HER2 levels, irrespective of treatment arm. Additionally, immune activation factors, including PD-L1 positivity, higher immune gene expression, and higher TILs, were associated with higher pCR rates; this was especially notable in the TCH + P arm. These data are consistent with previous reports from neoadjuvant breast cancer studies of HER2-targeted therapy [
16,
24,
25,
27,
37,
38] and recently reported validation results from the HER2DX assay, which integrates HER2 subtype information, immune information, and ERBB2 levels into a single score [
39].
The multivariate analysis indicated that PAM50 HER2-E subtype, HER2 gene ratio ≥ 4, and PD-L1-positive IHC status positively influenced the pCR rate, while hormone receptor-negative status was not shown to be a covariate influencing the pCR rate. However, patients with hormone receptor-negative disease were more likely to be PD-L1-positive than patients with hormone receptor-positive disease. Similar to previous studies [
8,
40,
41], hormone receptor-negative status was associated with a higher pCR rate, but did not remain a significant factor after correcting for other factors. The reason for the difference in pCR rate between treatment arms in the PD-L1-negative versus PD-L1-positive subgroups within the HR subgroups is unclear. It should be noted that as these are small subsets within a subgroup analysis, no firm conclusions can be drawn.
Previous studies assessing the impact of
PIK3CA mutation status on HER2-targeted treatments for eBC appear to have been influenced by the study setting and/or treatments received. In the neoadjuvant eBC setting,
PIK3CA mutations have generally been associated with worse outcomes, including lower pCR rates, in patients treated with HER2-targeted therapies [
17,
42]. However, the impact of
PIK3CA mutations on long-term outcomes in the adjuvant setting is less clear [
43‐
45]. In our analysis of data from KRISTINE,
PIK3CA mutations were associated with a lower pCR rate in a univariate analysis, although this effect was mainly present in the T-DM1 + P arm. These results differ from previous studies in second-line mBC that did not show an association between
PIK3CA mutation and efficacy in T-DM1-treated patients with HER2-positive breast cancer, suggesting that T-DM1 treatment may overcome the prognostic value of
PIK3CA mutations [
13]. The differences between the current study and previous analyses may also be due to imbalances in other influencing factors—such as HER2 IHC or hormone receptor status—within these subgroups across treatment arms, as well as to differences in treatment lines and disease setting. Notably, the multivariate analysis did not confer a clear prognostic value for pCR rates for
PIK3CA mutations.
In addition, we observed that hormone receptor-positive disease was negatively associated with almost all HER2-related biomarkers with high levels of HER2 expression, and PIK3CA mutation showed a negative association with high HER2 H-score and mRNA. This may have contributed to the fact that PIK3CA and hormone receptor status were not included in the final multivariate model. Other explanations include the relatively small sample size and differences in the impact of the biomarker on pCR between the two treatment arms. The balloon plot further shows the independent presence of high HER2 and high immune markers in the tumors and may therefore explain the role of the HER2-E subtype, HER2 gene ratio, and PD-L1 as independent factors associated with pCR.
We observed alterations in “on-treatment” biomarkers from baseline to the time of surgery. The proportion of luminal A tumor subtypes, previously identified as predictive of resistance to anti-HER2 therapy [
46], increased in both “on-treatment” and “post-treatment” tumor samples. The increased proportion of the luminal A subtype and subsequent decreased proportion of the HER2-E subtype over time was predominantly observed in the TCH + P group; this suggests that there is a shift in tumor cells with characteristics that may be less sensitive to combination treatment with systemic chemotherapy and HER2-targeted therapy or that the increase in the prevalence of luminal A subtype is simply due to a more prominent reduction in the number of HER2-positive tumor cells within more heterogeneous tumors. The rapid shift to a higher proportion of luminal disease subtypes with dual HER2 blockade observed in this study was also reported in the CALGB and PAMELA trials, highlighting the fluidity of molecular subtyping under treatment pressure [
46,
47]. While a general conversion of subtypes was seen in 36% of patients who progressed from primary to metastatic disease in the AURORA study [
48], the change from HER2-E into luminal subtypes was rarely observed, suggesting that the HER2-E subtype may be more stable. Of note, the AURORA data were generated across breast cancer types, not only HER2-positive disease. Another explanation for the differences in subtype fluidity over time and disease settings may be the role of adjuvant endocrine treatment, which is absent in the neoadjuvant setting. An additional finding in KRISTINE was that in the TCH + P arm, the proportion of PD-L1-positive tumors was similar from baseline to cycle 2, but decreased from baseline to surgery. In contrast, PD-L1-positivity increased between baseline and cycle 2, as well as between cycle 2 and surgery, in the T-DM1 + P arm. Thus, while an overall increase in PD-L1-positivity was mainly seen in the T-DM1 + P arm, dynamic changes in PD-L1 status during treatment were observed in both treatment arms. The changes in PD-L1 expression likely represent increased immune activation resulting from therapy, but more data are needed on potential differences in immune stimulation relating to the type of chemotherapy used (DM1 versus docetaxel/carboplatin), the route of administration (systemic versus targeted delivery via an ADC), and the role of preexisting immunity [
49]. Overall, these data suggest that immune stimulation can be induced by both traditional chemotherapy and an ADC (i.e., T-DM1), perhaps as a result of antigen spreading induced by antigens released from dying tumor cells.
These changes in “on-treatment” biomarkers align with findings in the neoadjuvant setting, including studies of chemotherapy combined with HER2-targeted therapies [
46,
47]. In the TRIO-US B07 phase II trial, immune signature levels decreased at the time of surgery in patients with HER2-positive breast cancer treated with neoadjuvant trastuzumab and/or lapatinib plus chemotherapy [
37]. In a study of anti-HER2-based neoadjuvant treatment in HER2-positive breast cancer, stromal TILs consistently decreased at surgery in patients who achieved pCR, whereas most residual tumors remained inflamed at surgery [
50].
Our biomarker analysis has several limitations. The sample sizes for some subgroups were small, particularly for the breast cancer subtype, biomarker co-occurrence, subsets of subgroups, and post-baseline time points. The small number of EFS events and the receipt of other therapies (e.g., chemotherapy, hormonal therapy) following neoadjuvant treatment in some patients limit the potential impact of a biomarker analysis for this clinical outcome. A numerically higher rate of the HER2-E subtype in the TCH + P arm may have impacted overall results due to the association between HER2 subtype and increased pCR rate. Only three biomarkers of interest (HER2, PD-L1 IHC status, and
PIK3CA mutation) were pre-specified to be included in this analysis and were investigated following the pooling of data from both treatment arms. Therefore, no firm conclusions should be drawn. Of note, 15 EFS events were reported during the neoadjuvant period in the T-DM1 + P arm, and these were associated with low and heterogeneous HER2 expression [
11]. Additionally, interpretation is limited by the enrichment of patients without pCR in biomarker data derived from serial samples. Again, firm conclusions cannot be made regarding data reported for changes from baseline in PAM50 intrinsic subtypes, PD-L1 expression, TILs, and HER2 mRNA, as these may be biased by the fact that patients with residual disease were more likely to have tumor tissue available at cycle 2 as well as at surgery.
Declarations
Competing interests
SLdH is an employee of, and owns stock in, Roche. DJS owns stock in Pfizer, Amgen, Merck, Vertex, and Seattle Genetics; has received consulting fees from Novartis and Pfizer and research funding from Bayer and Novartis; and is a co-founder of 1200Pharma and TORL BioTherapeutics. MM has served as a consultant for F. Hoffmann-La Roche, Genentech, Novartis, and AstraZeneca. His institution has received research funding from Novartis and from Centro de Investigación Biomédica en Red in the thematic area of Breast Oncology (CIBERONC Breast), of the Instituto de Salud Carlos III (ISCIII). MFP has received research grants to his institution from Cepheid, Eli Lilly & Company, Novartis Pharmaceuticals, F. Hoffmann-La Roche Ltd, and Puma; has served as a consultant or advisor with honoraria for AstraZeneca, Biocartis SA, Cepheid, Eli Lilly & Company, Merck & Co, Puma Biotechnology, and Zymeworks Inc; has provided expert testimony for Amgen, Inc; and has private equity in TORL Biotherapeutics, LLA. GLP is an employee of Genentech and owns stock in Roche. CL is an employee of Roche. AP owns stock in Reveal Genomics; has received honoraria from Pfizer, Novartis, Roche, MSD Oncology, Lilly, Daiichi Sankyo, Amgen, and Guardant Health; has served as a consultant or advisor for Amgen, Roche, Novartis, Pfizer, Bristol-Myers Squibb, Boehringer, PUMA, Oncolytics Biotech, Daiichi Sankyo, AbbVie, AstraZeneca, and NanoString Technologies; has received research funding from Roche, Novartis, Incyte, and Puma Biotechnology; and has received royalties for patents/other intellectual property for PCT/EP2016/080056 (HER2 as a predictor of response to dual HER2 blockade in the absence of cytotoxic therapy), WO/2018/096191 (chemoendocrine score [CES] based on PAM50 for breast cancer with positive hormone receptors with an intermediate risk of recurrence), HER2DX filing, and US 63/023785 (methods for breast cancer treatment and prediction of therapeutic response. VL-V is an employee of, and owns stock in, Roche. TB is an employee from Parexel International GmbH contracted by F. Hoffmann-La Roche for statistical services in the conduct of the study. SAH has received travel support from F. Hoffmann-La Roche, Boehringer Ingelheim, Novartis, Lilly, Pfizer, and Bayer. Her institution has received research funding from Ambrx, AstraZeneca, Arvinas, Daiichi Sankyo, Dantari, G1-Therapeutics, Gilead, Immunomedics, MacroGenics, Pieris, Radius, Seattle Genetics, Zymeworks, Cytomx, Phoenix Molecular Designs, Ltd, F. Hoffmann-La Roche, Genentech, Novartis, GlaxoSmithKline, Boehringer Ingelheim, Sanofi, Pfizer, Amgen, OBI Pharma, Puma Biotechnology, Dignitana, Bayer, BioMarin, Lilly, and Merrimack.
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.