Patritumab deruxtecan in HR+HER2- advanced breast cancer: a phase 2 trial

Abstract

Antibody-drug conjugates have shown impressive clinical outcomes, particularly in metastatic breast cancer, but biomarkers to predict response and resistance remain unidentified. Here we report the results of ICARUS-BREAST01, a phase 2 study evaluating efficacy, safety and biomarkers of response and resistance to patritumab deruxtecan (HER3-DXd), in patients with HR⁺HER2^- metastatic breast cancer, who previously progressed on CDK4/6 inhibitors and one line of chemotherapy. From May 2021 to June 2023, 99 patients were enrolled to receive HER3-DXd 5.6 mg kg^-1 intravenously every 3 weeks. The study met its primary endpoint, showing an overall response rate of 53.5% (90% confidence interval [44.8-62.1%]). The most frequent adverse events were fatigue (83%), nausea (75%), diarrhea (53%) and alopecia (40%). Exploratory biomarker analysis of baseline tumor samples suggested preliminary associations between overall response rate and both HER3 spatial distribution and absence of estrogen receptor 1 (ESR1) mutations, as well as between progression-free survival and HER3 expression, pending further validation. Analysis of on-treatment tumor samples showed that treatment efficacy seems to be associated with antibody-drug conjugate intratumoral distribution and interferon response. Overall, HER3-DXd showed promising activity and manageable tolerability in patients with HR⁺HER2^- metastatic breast cancer who progressed on CDK4/6 inhibitors. These findings highlight the need for larger trials to define HER3-DXd efficacy relative to other drugs, including antibody-drug conjugates (ClinicalTrials.gov Identifier: NCT04965766 ).

Fig. 1. Study consort diagram.

CONSORT flowchart illustrating patient disposition throughout the study.

Fig. 2. Efficacy of HER3-DXd.

a, Waterfall plot showing the best percentage change in the sum of tumor diameters from BL. The bars colored green, blue, purple and red represent CR, PR, SD and PD, respectively. The response was determined by investigator assessment according to RECIST v.1.1 and required confirmation after the first observed response at least 4 weeks later. The Clopper–Pearson (exact) method was used for the CIs. b, Kaplan–Meier estimates of PFS as assessed by a local investigator (median 9.2 months (95% CI [8.0–12.8 months]). c, Kaplan–Meier estimates of duration of response as assessed by a local investigator (median 9.3 months (95% CI 8.2 months–N/A)). ^aPatients who developed new lesions; ^bClopper–Pearson (exact) method used for the 90% CI; ^ctwo patients not evaluable (NE) for ORR: one patient had only one tumor assessment with PR and then treatment discontinued due to clinical progression and a second patient had no evaluable global response-of-target lesions.

Fig. 3. HER3 expression and spatial mapping at BL and association with treatment response.

a, Box plot showing the proportion of HER3 1+, 2+ and 3+ TCs at BL and best overall treatment response. b, Kaplan–Meier estimates of PFS according to HER3-membrane 2+ and 3+ ≥50% of TCs (left) and according to HER3-membrane 1+, 2+ and 3+ in ≥75% of TCs (right) (for both n = 72 and no. of events = 46). c, Clusters of HER3 or neighborhood cell distribution. Digitized DAB-stained slides were overlapped with digitized H&E-stained slides. These regions were then segmented into eight different clusters. Box plots show the proportion of each cluster in 63 evaluable patients, according to treatment response: responders (CR, PR) and nonresponders (SD, PD). The box center lines, box ranges, whiskers and dots indicate the medians, quartiles, 1.5× the IQR and outliers, respectively. Our analysis revealed an association between treatment response and the percentage of cluster 0 (P = 0.040), with an odds ratio of 1.527 95% CI [1.020–2.287]. For all these analyses, using R v.4.1.2, we applied Dirichlet’s regression to identify which clusters were significantly associated with the objective response to treatment (statistical significance was assessed using Wald’s test based on Dirichlet-distributed parameters; the reported P values were unadjusted for multiple comparisons). d, H&E-stained slide showing the composition of cluster 0, characterized by a moderate number of TCs, surrounded by connective areas, with a few immune cells and no necrotic areas. e, Proportion of the different cell phenotypes (epithelial, connective, inflammatory, necrotic and neoplastic areas) across the identified clusters (n = 63). The box center lines, box ranges, whiskers and dots indicate the medians, quartiles, 1.5× the IQR and outliers, respectively.

Fig. 4. HER3-DXd intratumoral distribution and interaction with TCs.

a, Dynamics of HER3-DXd⁺ cells over the different time points. b, Mean tumor shrinkage in patients with ≥5% of HER3-DXd⁺ cells and those with <5% HER3-DXd⁺ cells at C1D3 (Student’s t-test, P = 0.0146). The 5% cut-off was chosen according to the minimal detectable percentage of HER3-DXd⁺ cells. The boxes represent the IQR and the whiskers extend to the minimum and maximum values within each group. c, Left: image of a tumor with HER3-DXd staining ≥5% of TCs at C1D3: intact-DXd⁺ cells 21% of the PANK⁺ cells. Right: image of a tumor with HER3-DXd staining <5% of TCs at C1D3: intact-DXd⁺ cells 0.25% of the PANK⁺ cells. PANK⁺ cells are shown in red and Intact-DXd⁺ cells in blue; similar staining patterns were observed across all analyzed samples (n = 20). d,e, Volcano plot of differentially expressed genes in paired on-T and BL tumor samples in responders (d) and nonresponders (e). The P values shown are from two-sided tests and were adjusted for multiple comparisons using the Benjamini–Hochberg method. f, Volcano plot of differentially expressed genes in on-treatment samples of HER3-DXd⁺ (≥5% TCs, n = 5) and HER3-DXd⁻ (<5% TCs, n = 7) tumors. The P values shown are from two-sided tests and were adjusted for multiple comparisons using the Benjamini–Hochberg method.

Extended Data Fig. 1. ORR and PFS according to HER3-membrane expression.

a. ORR and PFS according to HER3 membrane positivity as measured by overall membrane positivity at 10x and scored as < 25%, 25-75% and > 75% of tumor cells; b. ORR and PFS according to HER3 membrane positivity as measured by H-score 0-100, 100-200, ≥ 200; the 95% confidence interval was estimated using the Clopper–Pearson exact method.

Extended Data Fig. 2. Gene alterations at baseline with response to HER3-DXd.

(a) Oncoplot showing non-synonymous point mutations, indels, homozygous deletions, loss of heterozygosity (LOH) and low, medium, and high-level amplifications in the set of 73 genes of interest, according to treatment response: responders (confirmed CR, PR), n = 26; non-responders (SD, PD, NE), n = 17.Blood samples were available for all patients. (b) Oncoplot showing non-synonymous point mutations, indels, homozygous deletions, loss of heterozygosity (LOH) and low, medium, and high-level amplifications in the set of 73 genes of interest, according to CBR: CBR (confirmed CR, PR, SD > 6 months; n = 27; non CBR (unconfirmed PR, SD < 6 months, PD; n = 16). Blood samples were available for all patients.

Extended Data Fig. 3. HER3-DXd interactions with tumor cells.

(a, b) Pie chart showing the proportion of the different cell phenotypes among the HER3-DXd-positive cells at C1D3 in responders (a) and non-responders (b); (c) Dynamics of HER3-positive cells after 1 or 2 doses of HER3-DXd in responders and non-responders (n = 39), showing a greater reduction on-treatment of HER3-positive cells in responders as compared to non-responders (Mann-Whitney U test, p-value 0.011).

Extended Data Fig. 4. Genes and pathways modulated by HER3-DXd.

(a, b) Gene set enrichment analysis (GSEA), using the Hallmark gene set in the overall population (a) and in responders (b) showed upregulation of genes involved in immune response, particularly interferon alpha and gamma and complement signaling; (c) GSEA, using the Hallmark gene sets: Key activated/suppressed pathways in on treatment/baseline matched biopsies by comparing responders (n = 14 pairs) vs. non responders (n = 8 pairs), showing on-treatment activation of immune pathways in responders as compared non responders; (d) GSEA, using the Hallmark gene sets: Key activated/suppressed pathways in HER3-DXd-positive (HER3-DXd-positive cells ≥ 5%, n = 5) and HER3-DXd-negative tumors (HER3-DXd-positive cells < 5%, n = 7) on-treatment.

Extended Data Fig. 5. Interferon alpha and gamma signature and association with PFS.

(a) Kaplan-Meier curve estimating PFS according to up or stable/downregulation of interferon alfa (p-value = 0.258) (n = 22); (b) Kaplan-Meier curve estimating PFS according to up or stable/downregulation of interferon gamma (p-value = 0.045).

Extended Data Fig. 6. HER3-DXd interaction with the TME.

(a–d)Heatmaps showing density of CD4 + (a), CD8 + (b), C8 CD107a + (c) and CD8 GzmB+ cells (d) at baseline and on-treatment in matched samples of responders and non-responders; (e) Heatmaps showing density of CD68+ cells in responders and non-responders.