HER2 Amplicon Research Articles

Characterization of HER2-Low Breast Tumors among a Cohort of Colombian Women.

HER2-low tumors have shown promise in response to antibody-drug conjugates (ADCs) in recent clinical trials, underscoring the need to characterize this group's clinical phenotype. In this study, we aimed to explore the clinicopathological features, survival rates, and HER2 amplicon mRNA expression of women affected with HER2-low breast cancer, compared with HER2-negative and HER2-positive groups. We included 516 breast cancer patients from Colombia, for whom we compared clinicopathological features, mRNA expression of three HER2 amplicon genes (ERBB2, GRB7 and MIEN1), survival and risk of mortality between HER2-low cases (1+ or 2+ with negative in situ hybridization (ISH) result) with HER2-positive (3+ or 2+ with positive ISH test) and HER2-negative (0+) cases. A higher proportion of patients with better-differentiated tumors and a lower proliferation index were observed for HER2-low tumors compared to the HER2-positive group. Additionally, HER2-low tumors showed higher mRNA expression of the ERBB2 gene and longer overall survival rates compared to HER2-negative cases. Nonetheless, a Cox-adjusted model by ER status and clinical stage showed no statistically significant differences between these groups. Our results show differences in important clinicopathological features between HER2-low and both HER2-positive and negative tumors. Given this unique phenotype, it is crucial to evaluate the potential advantages of ADC therapies for this emerging subtype of breast cancer.

RNA-Seq based gene expression profiling of baseline and on-treatment breast tumors to predict response to HER2-directed therapy, without chemotherapy (TBCRC026).

530 Background: Robust biomarkers are needed to personalize treatment in early stage HER2-positive breast cancer. The TBCRC026 trial (n=83) demonstrated that early metabolic changes on FDG-PET/CT [>40% decline in SULmax at day 15 post treatment initiation (C1D15); C1D15 SULmax] were associated with response to neoadjuvant trastuzumab/pertuzumab (HP), without chemotherapy, in an ER-negative, HER2-positive cohort (NCT01937117). We investigated the association of RNA sequencing (RNAseq)-based gene expression signatures (GES) at baseline and on-treatment (C1D15), with early metabolic change on PET/CT and clinical outcomes. Methods: RNAseq (664 GES) was performed on baseline (n=56) and C1D15 (n=31) tumor biopsies (25 paired samples available). Association with pCR following HP (secondary), PET/CT parameters and survival (exploratory) was studied. Gene expression changes between baseline and C1D15 samples were tested by Wilcoxon signed-rank test. Association between GES and PET/CT parameters and GES with pCR were evaluated using logistic regression models. Cox regressions were performed to study the association between PET/CT SULmax at C1D15 and a B cell signature and relapse-free survival (RFS). The likelihood ratio test was used to compare the prognostic ability of two nested Cox models. Results: Both RNAseq and clinical outcomes were available in 53/83 patients. HER2-enriched (HER2-E) intrinsic subtype comprised 71% (40/56) of cases at baseline and 61% (19/31) at D15; basal subtype for 27% (15/56) and 39% (12/31), respectively. pCR rate was 19% (10/53) with all but one exhibiting HER2-E subtype. One basal-like sample underwent pCR, with downregulation of HER2 amplicon and IgG signatures slightly more prominent. Gene expression changes from baseline to C1D15 were analyzed; ERBB2was downregulated after HP (p = 0.007), B cell signatures, CD4, CD8, natural killer cells and Treg cells were significantly upregulated at C1D15. GES associated with 40% decline in SULmax at C1D15 included ERBB2 amplicon genes ( ERBB2, GRB7) and correlation to the HER2-E subtype, whereas basal-like signatures were significantly associated with lack of response on PET at C1D15. Univariate logistic regression analysis suggested that FOS-JUN, fibroblast and B cell GES at baseline were significantly associated with pCR (p=<0.05). Finally, the addition of a B cell signature improved the prognostic value of C1D15 SULmax on PET/CT for RFS (p < 0.05). Conclusions: In this unique cohort with ER-negative, HER2-positive breast cancer treated with neoadjuvant HP without chemotherapy, HER2-E tumors and those with increased immune signaling were more likely to respond to HER2-directed therapy. Combining C1D15 SULmax on PET/CT and a B cell signature provided improved prognostic information and should be further explored as candidate biomarkers in this setting. Clinical trial information: NCT01937117 .

Abstract PO2-01-06: Prognostic value of residual disease (RD) biology and gene expression changes during the neoadjuvant treatment in HER2+ early-breast cancer (EBC)

Abstract Title Prognostic value of residual disease (RD) biology and gene expression changes during the neoadjuvant treatment in HER2+ early-breast cancer (EBC). Background In HER2+ EBC, neoadjuvant trastuzumab-based therapy is the standard of care, with adjuvant therapy determined by whether residual disease (RD) is present. Patients (pts) with RD have significantly higher relapse rates than pts with pathologic complete response. Differences in tumor and immune biology between pre-treated and post-treated tumors after HER2-blockade have been described, but little is known about how these changes can affect long-term outcomes or can be leveraged to tailor adjuvant treatment. Here we evaluate the biology of RD using gene expression analyses of pre- and post-treated HER2+ tumors, and their prognostic value to predict event-free survival (EFS) in a pooled analysis of 4 neoadjuvant studies in which single-agent trastuzumab or combined with lapatinib was explored, with and without chemotherapy: CALGB 40601 (Alliance), PAMELA, NeoALTTO, and NSABP B-41. Methods Gene expression profiling by RNA sequencing was assessed on 497 pre-treated samples from pts with RD, and on pre-treated and RD in 171 tumor pairs. Intrinsic subtypes and 22 tumor and immune gene expression signatures (GESs) were evaluated. We studied and compared the association of gene expression biomarkers with EFS in different cohorts and time points, including when GESs were calculated at baseline (N=497), in the 171 paired baseline and RD samples, and the nature of biomarker changes during neoadjuvant therapy. Association between GESs and EFS was explored by uni- and multivariable Cox regression models adjusted by clinical parameters (i.e., study, treatment arm, hormone receptor status, clinical tumor size, and clinical node involvement), and the performance of the models was assessed by the c-index. Results In 497 baseline untreated samples from pts with RD after neoadjuvant therapy (N=497), intrinsic subtypes were significantly associated with EFS (log-rank [LR] P 0.007), with Luminal A showing the best prognosis and Basal-like the worst. Among 171 paired tumors, HER2-Enriched tumors were more common in baseline (50.3%) with change to Normal-like (49.7%) and Luminal A (18.7%) in RD (chi-square P < 0.001). This luminal phenotypic change was also confirmed by a significant reduction in the correlation to the HER2-Enriched centroid and a significant increase in the correlation to the Luminal A centroid between pre- and post-treated samples; a significant decrease in ERBB2 gene expression and the HER2 amplicon gene expression signature was also observed (Wilcoxon P < 0.001). At an immune GES level, we found a significant increase in B cell, CD8+ T cell, and NK cell signatures in RD specimens. In contrast, T reg GES was significantly downregulated (Wilcoxon P < 0.05). In uni- and multivariable models, immune GESs provided more prognostic information when assessed in RD samples. In contrast, subtype-related biomarkers provided more prognostic information at baseline. From all the multivariable models, the best (c-index= 0.78) included the IgG signature assessed in RD (adjusted hazard ratio 0.46, 95% CI 0.30-0.70, adjusted P 0.005). IgG signature levels (tertiles) in RD could also stratify pts into different groups based on prognostic information (EFS at 7 years: 69% in IgG low vs. 91% in IgG high, LR P 0.02). Conclusions In pts with HER2+ EBC and RD after neoadjuvant treatment with HER2-blockade, tumor-related biomarkers seem to provide more prognostic information when calculated at baseline, whereas immune biomarkers in the RD perform better for EFS prognostication. This finding could be relevant for implementing RD biomarkers in the clinic to stratify pts into different prognostic groups and tailor the post-operative treatment strategy. Supported in part by U10 CA180821, U10 CA180882, R01-CA229409 https://acknowledgments.alliancefound.org Citation Format: Aranzazu Fernandez-Martinez, Maki Tanioka, Sung Gwe Ahn, Paola Zagami, Tomás Pascual, Mattia Rediti, Gong Tang, Katherine A Hoadley, David Venet, Naim U. Rashid, Patty Spears, Judith Bliss, Jens Huober, Priya Rastogi, Md N. Islam, Javier Cortés, Antonio Llombart-Cussac, Sandra Swain, Christos Sotiriou, Aleix Prat, Charles M Perou, Lisa Carey. Prognostic value of residual disease (RD) biology and gene expression changes during the neoadjuvant treatment in HER2+ early-breast cancer (EBC) [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO2-01-06.

Abstract 5540: Single cell multiomic analysis of human brain metastasis reveals conserved dormancy population

Abstract This study explores the complex realm of brain metastasis, pivotal in crafting effective anti-tumor strategies. Leveraging single-cell multi-omics sequencing, we profiled the transcriptomes and chromatin accessibility landscapes of tumor cells and their surrounding microenvironment in human brain metastases that originated from across a spectrum of primary cancers. Our investigations have identified distinct, yet uniformly present, tumor cell subpopulations, each defined by unique gene expression patterns, chromatin accessibility, and the interactions between tumor and stromal cells. Notably, one such subpopulation exhibits a dormancy signature, characterized by enhanced interferon response, oxidative phosphorylation, and upregulated HLA class molecules, alongside alterations in circadian rhythms. Our trajectory analysis charts a course from these dormant cells to rapidly proliferating ones, with notable shifts in circadian rhythm genes, underscoring their potential role in brain metastasis. This aligns with recent findings that disruptions in circadian rhythms can modify stem cell characteristics in glioblastomas. This insight led us to focus on a specific circadian rhythm gene, highly active in the dormant cells and located on the HER2 amplicon—an area linked to high brain metastasis relapse rates in patients. We've developed inducible models for both overexpression and knockdown to scrutinize this gene's impact in her2 positive breast cancer cell lines, examining gene expression and proliferation in vitro. Complementing this, we are conducting spatial transcriptomic analysis to evaluate the microenvironmental regulation of tumor dormancy in human brain metastases. This multi-omics approach reveals a nuanced regulatory landscape of brain metastasis, highlighting a novel and often overlooked factor in metastasis progression and brain tumor relapse: the interplay between circadian rhythms and tumor dormancy. This discovery not only deepens our understanding of brain metastases but also opens potential new avenues for therapeutic interventions. Citation Format: Remi Klotz, Yiru Wang, Anu Sunkara, Frank Attenelo, Min Yu. Single cell multiomic analysis of human brain metastasis reveals conserved dormancy population [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 5540.

Abstract 963: Comprehensive epigenomic profiling from plasma to inform therapy selection: A proof-of-concept study in cancer

Abstract BACKGROUND: Analysis of genomic alterations in circulating tumor DNA is gaining traction in clinical oncology and can provide insights into tumor biology without the need for invasive tissue sampling. In addition to genetic alterations, epigenomic reprogramming leads to transcriptional dysregulation and drives cancer phenotypes including molecular subtypes, histologic subtypes, and mechanisms resistance. As current liquid biopsy assays fail to effectively capture transcriptional biology, new approaches are needed to examine the transcriptional status of therapeutic gene targets and pathways including those relevant to rapidly emerging classes such as antibody-drug conjugates (ADC) and radio-conjugates. METHODS: We developed a novel multimodal assay that reveals genome-wide transcriptional activity of promoters, enhancers from chromatin and surveys the DNA methylome using 1ml of patient plasma. We applied this assay to patient plasma samples from across 15 tumor types generating 7000 genome-wide transcriptional profiles. RESULTS: We confirmed a significant correlation between epigenomic signals of transcriptional activation and gene expression from RNA-seq (Promoter vs RNA-seq: ⍴ =0.95, p<0.05; DNA methylation vs RNA-seq: ⍴=-0.16, p<0.05). We identified transcriptional activation in cancer patient plasma of well-established cancer-associated biomarkers (e.g. MET, DLL3, PSMA) in a tumor-specific manner. Epigenomic profiling simultaneously inferred the expression of multiple pertinent ADC targets currently under investigation (MET, HER2, HER3, TROP2, B7H4 in breast cancer), and SLFN11, a known biomarker for sensitivity to these agents. Unlike targeted panels, the platform assesses transcriptional regulation genome-wide, enabling the assessment of transcriptional activity of select genes as well as related pathways. For example, a multimodal classifier robustly predicted HER2 status across metastatic breast cancer plasma samples based on features both within the HER2 amplicon as well as HER2-distal genes that are activated in HER2+ cancers (AUC = 0.93, 0.84-1.0 95% CI). The multimodal classifier out-performed individual analyte-based classifiers (AUCPromoter+Enhancer = 0.85, 0.72-0.98 95% CI; AUCDNA-methylation = 0.69, 0.48-0.90 95% CI). Epigenomic signatures were also used to delineate multiple mechanisms of resistance to androgen receptor signaling inhibition in prostate cancer, including reactivation of the androgen receptor, glucocorticoid signaling bypass, and histological transformation to a neuroendocrine subtype. CONCLUSION: This comprehensive epigenomic liquid biopsy assay provides a platform for simultaneous genome-wide transcriptional assessment of disease and therapy relevant genes and pathways, representing a paradigm shift in our ability to longitudinally monitor cancer in individual patients. Citation Format: Travis Clark, Ji-Heui Seo, Anthony D'Ippolito, Aparna Gorthi, Jonathan Beagan, Jamey Guess, Amy Donahue, Mandy Greene, Alyssa Lau, Fernando Ramirez, Kristian Cibulskis, Hyun-Hwan Jeong, Matthew Davidsohn, Gitanjali Lakshminarayanam, Michael Coyne, Baovy Tran, Tyrone Tamakloe, Hathairat Sawaengsri, Marc Eid, Karl Semaan, Brad Fortunato, Corrie A. Painter, Juliann Chmielecki, Toni K. Choueiri, J Carl Barrett, Geoff Otto, Matthew L. Freedman, Matthew L. Eaton, Sylvan C. Baca. Comprehensive epigenomic profiling from plasma to inform therapy selection: A proof-of-concept study in cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 963.

3MO HER2 expression and early response to patritumab deruxtecan (HER3-DXd) in early-stage hormone receptor-positive/HER2-negative (HR+/HER2-) breast cancer (BC): A correlative analysis from SOLTI-TOT-HER3 trial

HER3-DXd and trastuzumab deruxtecan (T-DXd) are antibody-drug-conjugates (ADCs) directed against HER3 and HER2, respectively. Both drugs have shown efficacy in patients (pt) with HR+/HER2- BC. Baseline HER3 protein or mRNA levels do not predict efficacy from HER3-DXd. Here, we aimed to evaluate the association of early response to HER3-DXd with HER2 levels. TOT-HER3 (NCT04610528), a window-of-opportunity trial, evaluated a single dose of HER3-DXd in 77 pts with untreated HR+/HER2- early BC in Part A (6.4 mg/kg) and 17 in Part B (5.6 mg/kg). Primary objective was CelTIL score [a surrogate of response that combines tumor cellularity and tumor-infiltrating lymphocytes] variation between baseline and day 21 tumor samples. Here, CelTIL response was defined as an absolute increase of 20 at day 21. HER2 expression was determined by immunohistochemistry (IHC). RNA and DNA were purified from baseline FFPE tumor samples and analyzed using the nCounter and the VHIO-300 NGS platforms, respectively. Logistic regression models and area under the ROC Curve (AUC) estimated the performance of HER2 IHC, mRNA or copy-number (CN) levels with CelTIL response. In TOT-HER3 Part A, HER2 IHC status was 32% HER2 0, 38% HER2 1+ and 30% HER2 2+. Distribution of high CelTIL responders was 40% in HER2 0, 45% in HER2 1+ and 13% in HER2 2+ (p=0.034). High ERBB2 mRNA and RNA-based HER2 amplicon signatures were significantly associated with low CelTIL response (ERBB2: Odds Ratio [OR]=0.34, p<0.001, AUC=0.71; and HER2 amplicon: OR=0.20, p=0.005, AUC=0.74). The association of ERBB2 mRNA with CelTIL response was independent of HER2 IHC expression (p=0.002), PAM50 subtype (p=0.001) or proliferation (p=0.003). High HER2 CN signal was found associated with low CelTIL response (p=0.005). The association of HER2 IHC and ERBB2 mRNA with CelTIL response will be independently validated in TOT-HER3 Part B. Low HER2 IHC, mRNA or CN levels in early-stage HR+/HER2- BC are associated with high response to HER3-DXd. HER3-DXd might be highly active in HR+ BC with very low HER2 levels, thereby offering a new therapeutic paradigm to this subset of patients.

15P Portraying HER2-positive breast cancer heterogeneity with spatial transcriptomics

HER2-positive breast cancer is a heterogeneous disease, presenting tumor and microenvironment features which can impact prognosis and treatment response. Here, we aimed at better understanding the heterogeneity of this disease by performing spatial transcriptomics (ST) on HER2-positive breast cancer samples. Spatial transcriptomics (Visium) was performed on 33 frozen HER2-positive breast cancer surgical samples, including 6 residual disease samples. H&E images of the ST slides were annotated for morphological structures at the single-cell/structure level (QuPath software). Clusters identified on integrated data (harmony R package) were characterized calculating gene expression signatures, including HER2DX gene modules, at the spot level, and by morphological annotation. Gene signatures were computed on pseudo-bulk RNA data as well. A total of 25 integrated clusters were identified (range 15-21 in each sample). As each spot/cluster represents a mixture of different cell types, using gene expression and morphological data we defined a total of 9 tumor-enriched clusters (of which 5 sample-specific), as well as 12 clusters mainly enriched for stroma, 3 for adipose tissue, and 1 for tumor-infiltrating lymphocytes. All samples presented more than 1 tumor cluster, in various proportions. Interestingly, when comparing tumor clusters, levels of HER2DX signatures depicting HER2 amplicon, luminal phenotype, proliferation, B cell infiltration, as well as signatures related to stroma activation, signaling pathways and metabolism differed, demonstrating heterogeneity in tumor-enriched areas. Of note, within the same sample, tumor clusters with high/low levels of the HER2DX modules and other signatures could co-exist, and samples presenting signature scores above/below the cohort median at the pseudo-bulk level (also influenced by the stroma composition) showed the co-presence of tumor clusters with high/low signature levels. Our findings highlight the heterogeneity of HER2-positive breast cancer. Spatial transcriptomics may help in refining gene expression signatures computed on bulk RNA, and these results open to further analyses aimed at better understanding the tumor microenvironment in this disease.

Abstract P6-01-46: Independent validation of the HER2DX genomic test in HER2-positive breast cancer treated with neoadjuvant docetaxel, carboplatin, trastuzumab +/- pertuzumab (TCH/TCHP): a correlative analysis from a multicenter academic study

Abstract Background: HER2DX (Prat et al. EBiomedicine 2022) is a 27-gene prognostic (risk-score) and predictive (pathological complete response [pCR]-score) assay in early-stage HER2+ breast cancer based on clinical data and the expression of 4 gene signatures (immune, proliferation, luminal differentiation and HER2 amplicon). Here, we aim to evaluate, for the first time, the ability of HER2DX to predict pCR following neoadjuvant TCH or TCHP in HER2+ disease. Methods: Standardized HER2DX was performed in a central lab on baseline pre-treatment FFPE tumor biopsies from the GOM-HGUGM-2018-05 study in Spain, a consecutive retrospective series of patients (pts) with newly diagnosed stage I-III HER2+ breast cancer eligible for neoadjuvant therapy. Pts received standard 6 cycles of docetaxel, carboplatin and trastuzumab (TCH) or TCH with pertuzumab (TCHP) regimens. Primary aim was to test the ability of HER2DX pCR score to predict pCR (ypT0/is ypN0). Secondary objectives were to test the ability of HER2DX pCR score to predict pCR independently of clinical-pathological variables and the PAM50 subtype (HER2-enriched versus not), and to evaluate the association of HER2DX pCR score with the HER2DX risk-score. Logistic regression and receiver-operator curve (ROC) analysis were assessed. Statistical analyses were performed in R code 4.0.5. Results: HER2DX was evaluated in 155 pts (97%) enrolled in the study with available RNA (as of June 2022). Mean age of pts was 50 (range 22-74) and 55.2% of pts (n=85) were pre-menopausal. Clinical T2-4 disease represented 77.4% of cases (n=120), clinical node-positive disease (cN1-3) represented 63.9% of cases (n=99), and 68.0% of tumors (n=105) were hormone receptor-positive. The overall pCR rate was 57.4% (95% confidence interval [CI] 50-65): 52.2% (95% CI 40-64) with TCH (n=67) and 61.4% (95% CI 50-72) with TCHP (n=88). The proportion of HER2DX low-, medium- and high-pCR groups was 34.2%, 34.8% and 31.0%, respectively. HER2DX pCR score (as a continuous variable from 0 to 100) was significantly associated with pCR (odd ratio [OR]=1.03, p=5.91e-07). The pCR rates in HER2DX pCR-high and pCR-low groups were 75.0% and 28.0% (OR=7.6, 95% CI 3.2-19.1, p=7.14e-06), respectively. In pts treated with TCHP, the pCR rates in HER2DX pCR-high and pCR-low groups were 85.7% and 27.3% (OR=16.0, 95% CI 4.3-59.01, p=3.2e-05), respectively. The AUC ROC of HER2DX pCR score (as a continuous variable) and pCR status was 0.746 (in all pts) and 0.812 (in pts treated with TCHP). HER2DX pCR score was significantly associated with pCR independently of hormone receptor status, Ki67, age, menopausal status, pertuzumab use, clinical stage and PAM50 HER2-enriched subtype. The proportion of HER2DX low- and high-risk of relapse disease was 32.0% and 68.0%, respectively. The correlation of HER2DX pCR score and HER2DX risk-score was weak (coefficient=-0.17), as previously described. Proportion of cases according to both HER2DX scores and absolute difference of pCR rates between TCHP and TCH in each combined group is shown in Table. Conclusion: The HER2DX genomic test predicts pCR following neoadjuvant TCH or TCHP regimens independently of clinical-pathological variables and intrinsic subtype. The combination of both HER2DX scores might help better tailor systemic therapy in patients with newly diagnosed stage I-III HER2+ breast cancer. Citation Format: Coralia Bueno-Muiño, Isabel Echavarria, Sara López-Tarruella, Roche-Molina Marta, María del Monte-Millán, Tatiana Massarrah, Yolanda Jerez Gilarranz, Blanca Herrero, Salvador Gámez, Iván Márquez-Rodas, María Cebollero-Presmanes, Nevado Santos Manuel, Pilar de la Morena Barrio, Francisco Ayala de la Peña, José Ángel García-Sáenz, Fernando Moreno Antón, Álvaro Rodríguez Lescure, Teresa Quintanar, Diego Malón-Giménez, Laura Rodriguez-Lajusticia, Ana Isabel Ballesteros García, Dulce Bañón Torres, Lucía Villarejo, Nerea Lobato, Ainhoa Arias, Inmaculada Ocaña, Enrique Álvarez, Laia Paré, Mercedes Marín-Aguilera, Patricia Galván, Fara Brasó-Maristany, Ana Vivancos, Patricia Villagrasa, Joel S Parker, Charles M. Perou, Aleix Prat, Miguel Martín. Independent validation of the HER2DX genomic test in HER2-positive breast cancer treated with neoadjuvant docetaxel, carboplatin, trastuzumab +/- pertuzumab (TCH/TCHP): a correlative analysis from a multicenter academic study [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 P6-01-46.

Abstract P4-02-30: Association between tumor infiltrating lymphocytes (TILs) and the HER2DX assay in early-stage of HER2-positive (HER2+) breast cancer

Abstract Background: The HER2DX assay is a genomic test in early-stage HER2-positive (HER2+) breast cancer that provides prognostic and predictive information. HER2DX is a supervised learning algorithm incorporating tumor size, nodal staging, and 4 gene expression signature scores (immune/IGG, tumor cell proliferation, luminal differentiation and the expression of the HER2 amplicon). Among them, the IGG signature is associated with both overall survival and probability of achieving a pathologic complete response (pCR). Here, we studied the association of percentage (%) of tumor infiltrating lymphocytes (TILs) with HER2DX scores, immune genes and other breast cancer-related genes. Methods: HER2DX and %TILs were evaluated in 670 formalin-fixed paraffin-embedded (FFPE) samples of HER2+ breast cancer, including in 3 clinical studies SHORTHER (n=437), PAMELA (n=86), a cohort of patients treated with anti-HER2 therapy plus chemotherapy at Hospital Clínic of Barcelona (n=147). The %TILs were quantified by histological evaluation with hematoxylin eosin staining according to International TILs Working Group guidelines. The nCounter platform determined the expression of 192 genes and HER2DX scores. Pearson correlations (Cor) and Significance Analysis of Microarrays (SAM) with a false-discovery rate (FDR) &amp;lt; 5% assessed the association between %TILs and the expression of individual genes or HER2DX signature scores. Results: A moderate correlation was observed between %TILs and the immune IGG signature (Cor=0.56, p&amp;lt; 0.001). Of note, 171 (25.52%) cases had low %TILs (&amp;lt; 30%) and high IGG score, while 1 (0.15%) case had high %TILs (≥30%) and low IGG score. The %TILs were significantly associated with the expression of immune genes, ERBB2, IGG signature and HER2 amplicon score, and negatively associated with the expression of luminal genes (i.e., ESR1, PRG and BCL2). An unclear relationship between TILs and proliferation genes was observed. Finally, moderate correlations were observed between %TILs and HER2DX pCR score (Cor=0.48, p&amp;lt; 0.001) and between %TILs and HER2DX risk score (Cor=0.33, p&amp;lt; 0.001). Conclusions: Important differences exist between the %TILs and the HER2DX IGG signature in early-stage HER2+ breast cancer. The %TILs should not be used to predict the HER2DX scores. Biologically, a higher %TILs indirectly capture a higher ERBB2 expression and a lower expression of luminal genes, both associated with response to anti-HER2 treatment. Citation Format: Esther Sanfeliu, Fara Brasó-Maristany, Maria Vittoria Dieci, Mercedes Marín-Aguilera, Blanca González-Farré, Gaia Griguolo, Tomas Pascual, Patricia Galván, Laura Angelats, Oleguer Castillo, Paula Blasco, Valeria Sirenko, Pedro Jares, Joan Antón Puig-Butillé, Laia Paré, Antonio Martínez, Antonio Llombart-Cussac, Javier Cortés, Ana Vivancos, Patricia Villagrasa, Joel S Parker, Charles M Perou, Aleix Prat, PierFranco Conte, Valentina Guarneri. Association between tumor infiltrating lymphocytes (TILs) and the HER2DX assay in early-stage of HER2-positive (HER2+) breast cancer [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 P4-02-30.

Abstract P1-04-05: Independent validation of the HER2DX genomic test in HER2-positive breast cancer treated with neoadjuvant paclitaxel, trastuzumab and pertuzumab (THP): a correlative analysis from the DAPHNe phase II clinical trial

Abstract Background: HER2DX is a 27-gene prognostic (risk-score) and predictive (pathological complete response [pCR]-score) assay in early-stage HER2+ breast cancer (BC) based on clinical data and the expression of 4 gene signatures (immune, proliferation, luminal differentiation, and HER2 amplicon). Here we aim to evaluate, for the first time, the ability of HER2DX to predict pCR following neoadjuvant THP in HER2+ BC. Methods: Standardized HER2DX was evaluated centrally on baseline pre-treatment FFPE tumor biopsies from the DAPHNe phase II trial (Waks et al. NPJ Breast 2022; NCT03716180), in which patients (pts) with newly diagnosed stage II-III HER2+ BC were treated with neoadjuvant weekly paclitaxel × 12 and HP every 3 weeks × 4. Primary aim was to test the ability of HER2DX pCR-score to predict pCR (ypT0/isN0). Secondary objectives were to test the ability of HER2DX pCR-score to predict pCR independent of clinical-pathological variables and PAM50 subtype (HER2-enriched vs not) and to evaluate the association of HER2DX pCR-score with HER2DX risk-score. Five patients who received additional neoadjuvant chemotherapy after THP were excluded from this analysis. Logistic regression and receiver-operator curve (ROC) analysis were assessed. Statistical analyses were performed in R code 4.0.5. Results: HER2DX was evaluated in 80 of 97 pts (82.5%) enrolled in the DAPHNe trial who received study treatment. Clinical T2-4 disease represented 81.3% of cases (n=65), clinical node-negative disease (cN0) represented 65.0% of cases (n=52), and 70.0% of tumors (n=56) were hormone receptor-positive. The overall pCR rate was 60.0% (95% confidence interval [CI] 49.3-70.7): 87.0% (95% CI 79.6-94.4) in hormone receptor-negative disease and 48.2% (95% CI 37.2-59.1) in hormone receptor-positive disease. The proportion of HER2DX low-, medium- and high-pCR groups was 38.8%, 27.5% and 33.7%, respectively. HER2DX pCR-score (as a continuous variable from 0 to 100) was significantly associated with pCR (odds ratio [OR]=1.05, p&amp;lt; 0.0001). In the overall population, the pCR rates in HER2DX pCR-high, pCR-med and pCR-low groups were 92.6%, 63.6% and 29.0% (pCR-high vs pCR-low OR=30.6, p&amp;lt; 0.0001), respectively. The AUC ROC of HER2DX pCR score (as a continuous variable) and pCR status was 0.835. In the ER-negative population, the pCR rates in HER2DX pCR-high, pCR-med and pCR-low groups were 94.7%, 66.7%, and 0%, respectively (Table 1). HER2DX pCR-score was significantly associated with pCR independent of hormone receptor status, HER2 immunohistochemistry (IHC) score, clinical stage, and PAM50 HER2-enriched subtype. The correlation between HER2DX pCR-score and HER2DX risk-score was weak (Pearson coefficient=-0.12), as previously described (Prat et al. EBiomedicine 2022). 51.3% of patients were categorized as HER2DX low-risk. Conclusion: The 27-gene HER2DX genomic test predicts pCR following neoadjuvant THP in newly diagnosed stage II-III HER2+ BC. Patients with HER2DX pCR-low score and HER2DX high-risk score, representing 22.5% of pts, warrant further attention in order to optimize therapeutic strategies in this subset. The combination of HER2DX pCR-score and risk-score might guide therapeutic decisions by identifying patients who are ideal candidates for de-escalated or escalated systemic and locoregional treatments. Table 1 Citation Format: Adrienne Waks, Esther R. Ogayo, Laia Paré, Mercedes Marín-Aguilera, Fara Brasó-Maristany, Patricia Galván, Oleguer Castillo, Olga Martínez-Sáez, Ana Vivancos, Patricia Villagrasa, Paolo Tarantino, Neelam Desai, Jennifer Guerriero, Otto Metzger, Nadine Tung, Ian Krop, Joel S Parker, Charles M. Perou, Aleix Prat, Eric Winer, Sara Tolaney, Elizabeth A. Mittendorf. Independent validation of the HER2DX genomic test in HER2-positive breast cancer treated with neoadjuvant paclitaxel, trastuzumab and pertuzumab (THP): a correlative analysis from the DAPHNe phase II clinical trial [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 P1-04-05.

Novel Therapies and Strategies to Overcome Resistance to Anti-HER2-Targeted Drugs.

Simple SummaryDrug resistance is the “Achilles’ heel” in current oncology. In this sense, the clinical management of HER2 breast carcinomas (tumors with overexpression/amplification of the ErbB2/HER2 oncogene) is still a challenge. Although a variety of anti-HER2 therapies (anti-HER2 antibodies, antibody–drug conjugates, and tyrosine kinase inhibitors) are available for these patients, the frequent appearance of innate and acquired tumor resistance to these treatments creates an urgent need to develop new and more effective therapeutic approaches. In this review, we discuss the most relevant clinical and pre-clinical advances in therapeutic strategies aimed at overcoming drug resistance in HER2 breast cancer patients in different stages of the disease.The prognosis and quality of life of HER2 breast cancer patients have significantly improved due to the crucial clinical benefit of various anti-HER2 targeted therapies. However, HER2 tumors can possess or develop several resistance mechanisms to these treatments, thus leaving patients with a limited set of additional therapeutic options. Fortunately, to overcome this problem, in recent years, multiple different and complementary approaches have been developed (such as antibody–drug conjugates (ADCs)) that are in clinical or preclinical stages. In this review, we focus on emerging strategies other than on ADCs that are either aimed at directly target the HER2 receptor (i.e., novel tyrosine kinase inhibitors) or subsequent intracellular signaling (e.g., PI3K/AKT/mTOR, CDK4/6 inhibitors, etc.), as well as on innovative approaches designed to attack other potential tumor weaknesses (such as immunotherapy, autophagy blockade, or targeting of other genes within the HER2 amplicon). Moreover, relevant technical advances such as anti-HER2 nanotherapies and immunotoxins are also discussed. In brief, this review summarizes the impact of novel therapeutic approaches on current and future clinical management of aggressive HER2 breast tumors.

140MO HER2DX genomic test in HER2-positive/hormone receptor-positive (HER2+/HR+) breast cancer (BC) treated with neoadjuvant trastuzumab (T) and pertuzumab (P): A correlative analysis from the PerELISA trial

HER2DX is a prognostic and predictive assay in early-stage HER2+ BC based on clinical data and the expression of 4 gene signatures (immune, proliferation, luminal differentiation and HER2 amplicon), including ERBB2 levels. Here, we evaluated the ability of HER2DX to predict efficacy of a de-escalated, chemotherapy (CT)-free neoadjuvant regimen in HER2+/HR+ BC.

153P HER2DX risk-score in the context of the PREDICT online-tool: A correlative analysis of the Short-HER clinical trial in early-stage HER2-positive (HER2+) breast cancer (BC)

PREDICT is an online tool (https://breast.predict.nhs.uk/) designed to help make informed decisions about treatment following surgery for early invasive BC and estimates overall survival (OS). HER2DX is a prognostic test that integrates clinical data and gene expression from immune, proliferation, luminal differentiation and HER2 amplicon processes. Here, we explored the prognostic ability of HER2DX beyond the PREDICT tool.

14-gene immunoglobulin (IGG) and proliferation signatures and association with overall survival across cancer-types.

2636 Background: The HER2DX prognostic assay in early-stage HER2-positive breast cancer integrates clinical variables and 4 gene expression signatures (GES) tracking IGG, tumor proliferation, luminal cell differentiation, and the expression of the HER2 amplicon. Here, we assessed the prognostic value across cancer-types of each of these four individual GES and a research-based version of the HER2DX risk-score. Methods: RSEM batch normalized RNA-sequencing gene expression data from The Cancer Genome Atlas (TCGA) project were downloaded from cBioPortal. The association between a research-based version of the HER2DX risk-score, and each GES, with overall survival (OS) was assessed as continuous variables using univariate Cox regression model. The research-based version of the HER2DX risk-score tested did not include clinical variables. The Cox model was applied to estimate hazard ratios (HR) with 95% confidence intervals. The threshold for statistical significance was set at p&lt; 0.05. Results: Gene expression data from 9,852 patients representing 30 different cancer-types were evaluated. The proliferation, IGG, luminal and HER2 amplicon GES were significantly associated with OS in 40.0%, 33.3%, 23.0% and 6.7% of the cancer-types tested, respectively. The IGG GES was found significantly associated with a favorable OS in breast cancer (HR: 0.73, p &lt; 0.001), cervical and head &amp; neck squamous cell carcinomas (HR: 0.75, p = 0.021 and HR: 0.78, p &lt; 0.001), lung adenocarcinoma (HR: 0.84, p = 0.020), skin melanoma (HR: 0.73, p &lt; 0.001) and sarcomas (HR: 0.78, p = 0.029). Conversely, association of IGG GES with unfavorable OS was observed in uveal melanoma (HR: 1.74, p = 0.008), kidney clear cell and papillary cell carcinomas (HR: 1.29, p &lt; 0.001 and HR: 1.44, p = 0.017, respectively), as well as brain low-grade gliomas (LGG) (HR: 1.56, p &lt; 0.001). Finally, the research-based HER2DX risk-score was found significantly associated with OS in 11 of 30 (36.7%) cancer-types, including breast (HR: 1.42, p &lt; 0.001) cervical and head &amp; neck squamous cells cancers (HR: 1.36, p = 0.018 and HR: 1.30, p &lt; 0.001), lung adenocarcinoma (HR: 1.34, p &lt; 0.001), skin melanoma (HR: 1.34, p &lt; 0.001), sarcomas (HR: 1.41, p = 0.003), adrenocortical carcinoma (HR: 2.31, p &lt; 0.001), endometrial carcinoma (HR: 1.36, p = 0.005), hepatocarcinoma (HR: 1.26, p = 0.012), LGG (HR: 1.37, p = 0.001) and mesothelioma (HR: 1.48, p = 0.005). Conclusions: The 14-gene IGG and proliferation signatures are strong prognostic biomarkers across cancer-types. The opposite association of IGG with OS depending on the cancer-type warrants further investigation.

Development and validation of the new HER2DX assay for predicting pathological response and survival outcome in early-stage HER2-positive breast cancer.

SummaryBackgroundBoth clinical and genomic data independently predict survival and treatment response in early-stage HER2-positive breast cancer. Here we present the development and validation of a new HER2DX risk score, and a new HER2DX pathological complete response (pCR) score, both based on a 27-gene expression plus clinical feature-based classifier.MethodsHER2DX is a supervised learning algorithm incorporating tumour size, nodal staging, and 4 gene expression signatures tracking immune infiltration, tumour cell proliferation, luminal differentiation, and the expression of the HER2 amplicon, into a single score. 434 HER2-positive tumours from the Short-HER trial were used to train a prognostic risk model; 268 cases from an independent cohort were used to verify the accuracy of the HER2DX risk score. In addition, 116 cases treated with neoadjuvant anti-HER2-based chemotherapy were used to train a predictive model of pathological complete response (pCR); two independent cohorts of 91 and 67 cases were used to verify the accuracy of the HER2DX pCR likelihood score. Five publicly available independent datasets with >1,000 patients with early-stage HER2-positive disease were also analysed.FindingsIn Short-HER, HER2DX variables were associated with good risk outcomes (i.e., immune, and luminal) and poor risk outcomes (i.e., proliferation, and tumour and nodal staging). In an independent cohort, continuous HER2DX risk score was significantly associated with disease-free survival (DFS) (p=0·002); the 5-year DFS in the low-risk group was 97·4% (94·4-100·0%). For the neoadjuvant pCR predictor training cohort, HER2DX variables were associated with pCR (i.e., immune, proliferation and HER2 amplicon) and non-pCR (i.e., luminal, and tumour and nodal staging). In both independent test set cohorts, continuous HER2DX pCR likelihood score was significantly associated with pCR (p<0·0001). A weak negative correlation was found between the HER2DX risk score versus the pCR score (correlation coefficient -0·19).InterpretationThe two HER2DX tests provide accurate estimates of the risk of recurrence, and the likelihood to achieve a pCR, in early-stage HER2-positive breast cancer.FundingThis study received funding from Reveal Genomics, IDIBAPS and the University of Padova.

Abstract P1-21-08: Application of machine learning to elucidate the biology predicting response in the I-SPY 2 neoadjuvant breast cancer trial

Abstract Background: Machine learning relies on algorithms that learn patterns in large, complex datasets to predict outcomes. The adaptive, neoadjuvant I-SPY 2 TRIAL evaluates novel agents added to standard therapy, and identifies their most responsive subtype. While previously proposed genes/signatures reflecting an agent’s mechanism of action predicted pathologic complete response (pCR) in some treatment arms/subtypes, not all arms had strong predictive biomarkers. We leverage machine learning to explore the limitations of using only known mechanisms of action in predicting pCR, and the extent to which biology outside known drug action improves response prediction in the first 10 arms of the trial. Methods: Our study involves 986 patients with pre-treatment gene expression and pCR data across 10 treatment arms including inhibitors of HER2: neratinib (N), pertuzumab (P), TDM1/P; AKT (MK-2206; M); IGF1R (ganitumab); HSP90 (ganetespib); PARP/DNA repair (veliparib/carboplatin; VC); ANG1/2 (AMG386); immune checkpoints (pembrolizumab; Pembro); and a shared control arm (Ctr). Each arm/receptor subtype group was evaluated independently for groups with at least 20 patients (n=19), with 25% of data held out as independent test sets. We implemented a 3-fold cross validation technique with 10 repeats using Random Forest ensemble algorithm with recursive feature elimination. In combination with clinical data, a three-pronged feature-selection approach was employed: (1) restricted to mechanism of action genes: AKT/PI3K/HER (m=10 genes), IGF1 (m=11), HSP90 (m=88), DNA repair (m=79), TIE1/2 (m=11), and immune (m=61), as well as HER2 amplicon genes; (2) expanded to include targeted pathways for all 10 agents/combinations plus ESR1 and proliferation genes (m=339); (3) an unbiased whole genome approach (m=17,990). Models were considered predictive if AUROC ≥ 0.75, Sensitivity ≥ 0.6 and Specificity ≥ 0.6 in cross validation and independent test sets. Results: Table 1 summarizes the results of our analysis (Yes=predictive; NA=no/insufficient data). Prediction of pCR using only genes reflecting the known mechanism of the drug succeeded in 5 subgroups, with DNA repair genes predicting VC response and immune genes predicting Pembro response in HR+HER2- and HR-HER2- subsets, and AKT/PI3K/HER + HER2 amplicon genes predicting (P) response in HR+HER2+ patients. Expansion of the feature set to include genes associated with all mechanisms of action of all drugs proved sufficient to produce good predictive models in 8 of 19 subgroups. Examples include DNA repair + immune genes predicting response to ganitumab in HR+HER2- and to (N) in HR+HER2+. An unbiased approach using all data yielded predictive power in 8 of 19 subgroups, including 5 with no predictive models from the first two approaches. Examples include HR-HER2- (N) predictors enriched for metabolic, cell division and membrane protein proteolytic processes; HR+HER2+ TDM1/P enriched for metabolic, stress response and cell cycle processes; and HR-HER2- MK-2206 predictors containing Ser/Thr kinases. In total, we identify predictive biomarkers in 14 of 19 subgroups across the three feature selection approaches. Conclusion: Our results suggests that hypothesis driven analysis restricted to assumed mechanisms of action of the experimental agents may be insufficient, and that exploration of possible off target effects may be needed to understand the underlying biology of response or resistance. Table 1. Model results across feature selection approachesHR+HER2-HR-HER2-HR+HER2+HR-HER2+Number of PatientsMechanism of ActionAll Mechanisms of ActionUnbiasedNumber of PatientsMechanism of ActionAll Mechanisms of ActionUnbiasedNumber of PatientsMechanism of ActionAll Mechanisms of ActionUnbiasedNumber of PatientsMechanism of ActionAll Mechanisms of ActionUnbiasedneratinib (pan anti-HER)NA32NoNoYes42NoYesYes23NoNoYespertuzumab (anti-HER2)NANA29YesYesNoNATDM1/Pertuzumab (anti-HER2)NANA35NoNoYesNAMK−2206 (AKT inhibitor)28NoNoNo32NoNoYesNANAganitumab (IGFR inhibitor)58NoYesNo48NoNoNoNANAganetespib (HSP90 inhibitor)48NoYesYes45NoNoNoNANAvelirapib/carboplatin (PARP inhibitor/DNA damage)33YesYesNo39YesYesNoNANAAMG386 (ANG1/2 inhibitor)62NoYesYes53NoNoNoNANApembrolizumab (immune checkpoint inhibitor)38YesYesNo29YesNoNoNANAHER2+ controlNANANANAHER2- control94NoNoYes84NoNoNoNANA Citation Format: Rosalyn W. Sayaman, Denise M. Wolf, Christina Yau, Julie Wulfkuhle, Emanuel Petricoin, Lamorna Brown-Swigart, Smita M. Asare, Gillian L. Hirst, Laura Sit, Nicholas O'Grady, Diane Hedistian, I-SPY 2 TRIAL Consortium, Laura J. Esserman, Mark A. LaBarge, Laura J van 't Veer. Application of machine learning to elucidate the biology predicting response in the I-SPY 2 neoadjuvant breast cancer trial [abstract]. In: Proceedings of the 2019 San Antonio Breast Cancer Symposium; 2019 Dec 10-14; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2020;80(4 Suppl):Abstract nr P1-21-08.

Abstract P4-10-02: HER2 signaling, ER, and proliferation biomarkers predict response to multiple HER2-targeted agents/combinations plus standard neoadjuvant therapy in the I-SPY 2 trial

Abstract Background: A variety of investigational HER2-inhibitor agents/combinations have been tested in I-SPY 2, including neratinib (N), TDM1 combined with pertuzumab (P) (TDM1/P), and trastuzumab (H) combined with pertuzumab (H/P; prior to this combination becoming standard of care), all with trastuzumab as control (Ctr). All three experimental arms graduated, showing improved efficacy over control in one or more receptor subsets (HR+HER2+, HR-HER2+, or/and HER2+). Here we assess 10 biomarkers in the HER2, ER/PR, and proliferation pathways on multiple levels of resolution (expression, protein, phospho-protein) as predictors of response in these four arms, hypothesizing that highly HER2-activated, proliferative tumors may be more sensitive to HER2-inhibition than those that are more luminal and quiescent. Methods: 192 HER2+ patients were considered in this analysis: (31 Ctr, 65 N, 52 TDM1/P, and 44 H/P). 10 biomarkers relating to HER2, ER, or proliferation were evaluated from pre-treatment biopsies: HER2 IHC (n=145), 3 expression signatures (n=192), BluePrint subtype (n=192), and 5 protein/phospho-protein analytes by RPPA (n=175). Each biomarker was tested for association with pCR in the whole population and within each arm using a logistic model. This analysis was adjusted for HR status and treatment arm as covariates, and performed within receptor subtypes. This analysis does not adjust for multiplicities of other biomarkers. Results: In the population as a whole, HER2 and HER2-signaling biomarkers, evaluated at multiple levels of resolution: IHC, total-/phospho-protein by RPPA, and mRNA (HER2 amplicon module) - are highly correlated (rho=0.8 [0.65-0.92]). Higher HER2 levels and activity are associated with response: HER2 IHC 3+ status (LR p=0.00032), total quantitative ERBB2 protein by RPPA (LR p=5.4E-09), ERBB2 activation levels (LR p=6.58E-06 (pERBB2 (Y1248)) and 9.95E-06 (pEGFR Y1173)), and the ERBB2 amplicon expression signature (LR p=2.38E-08). In contrast, higher average ER/PR expression associates with non-response to HER2-targeted therapy (LR p=4.28E-08). Both HER2 and ER/PR signaling phenotypes are captured by BluePrint subtyping; and consistent with the individual pathway markers, tumors classified Luminal-type had a lower pCR rate relative to those classified as Her2-type (or Basal-type) (LR p=4.84E-11). These associations all retain significance in a model adjusting for HR status and treatment arm, and in the HR+HER2+ subset. In addition, we quantitatively assessed proliferation markers at the total protein (RPPA: Ki67), phospho-protein (pAURKA) and mRNA (proliferation signature Module11_Prolif) levels. All three proliferation biomarkers predict response overall; but this association is strongest within the HR+HER2+ subset (LR p=0.0012 (Module11_prolif), 0.0036 (pAURK), and 0.045 (Ki67)). None of the biomarkers tested were associated with response in the HR-HER2+ subset. Numbers are small within individual arms. Within the HR+HER2+ subtype, higher HER2 and lower ER/PR is observed in responders in all experimental arms; but the proliferation markers Module11_Prolif (LR p=0.0031) and Ki67 total protein (LR p=0.0029) are associated with response to TDM1/P but not H/P or N. Conclusion: High HER2 signaling at the expression, protein, and phospho-protein levels, and low ER signaling, all predict response to HER2-inhibition across treatment arms. Proliferation markers may be useful for prioritizing therapies in the HR+HER2+ subset. Citation Format: Denise M Wolf, Christina Yau, Julia Wulfkuhle, Lamorna Brown-Swigart, Smita M. Asare, Gillian L. Hirst, Laura Sit, Jane Perlmutter, I-SPY 2 TRIAL Consortium, Minetta Liu, John Park, Angela DeMichele, Douglas Yee, Don Berry, Laura Esserman, Emanuel Petricoin, Laura van t' Veer. HER2 signaling, ER, and proliferation biomarkers predict response to multiple HER2-targeted agents/combinations plus standard neoadjuvant therapy in the I-SPY 2 trial [abstract]. In: Proceedings of the 2019 San Antonio Breast Cancer Symposium; 2019 Dec 10-14; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2020;80(4 Suppl):Abstract nr P4-10-02.

Selective Progesterone Receptor Modulators in Early-Stage Breast Cancer: A Randomized, Placebo-Controlled Phase II Window-of-Opportunity Trial Using Telapristone Acetate

Selective progesterone receptor modulators (SPRMs) show preclinical activity against hormone-sensitive breast cancer, but have not been tested in patients with early, treatment-naïve tumors. In a double-blind presurgical window trial of oral telapristone acetate (TPA) 12 mg daily versus placebo, 70 patients with early-stage breast cancer were randomized 1:1 (stratified by menopause) and treated for 2 to 10 weeks. The primary endpoint was change in Ki67 between diagnostic biopsy and surgical specimens. Gene expression pre- and posttherapy was assessed using RNA-sequencing and gene set enrichment analysis was performed to determine pathways enriched in response to TPA and placebo treatments. Among 61 evaluable women (29 placebo and 32 telapristone acetate), 91% of tumors were ER/PR positive. The mean Ki67 declined by 5.5% in all women treated with telapristone acetate (P = 0.003), and by 4.2% in all women treated with placebo (P = 0.04). After menopausal stratification, the Ki67 decline remained significant in 22 telapristone acetate-treated premenopausal women (P = 0.03). Differential gene expression analysis showed no significant modulation overall. However, in a subset of tumors that demonstrated ≥30% relative reduction in Ki67 in the telapristone acetate group, genes related to cell-cycle progression, and those in the HER2 amplicon were significantly downregulated. In contrast, no significantly enriched pathways were identified in the placebo group. Patients treated with telapristone acetate whose Ki67 decreased by ≥30% demonstrated a selective antiproliferative signal, with a potentially important effect on HER2 amplicon genes. Evaluation of SPRMs in a neoadjuvant trial is merited, with attention to predictors of response to SPRM therapy, and inclusion of pre- and postmenopausal women.

Molecular mechanisms of STARD3 addiction in HER2 tumors

Human Epidermal growth factor Receptor 2 (HER2) is overexpressed and amplified in approximately 15–20% of breast cancers. HER2 is a tyrosine kinase receptor belonging to the EGFR family. HER2 amplification and overexpression play a central role in initiation, progression and metastasis of common cancers like lung, breast and gastric cancer (Hynes and MacDonald, 2009). HER2 amplification is a marker of poor prognosis, especially in breast and gastric cancer (Slamon and Clark, 1988). Although anti‐HER2‐targeted therapies have shown significant clinical benefits, de novo and acquired resistance remain a considerable issue (Garrett and Arteaga, 2011). Genomic profiling has demonstrated that HER2 positive‐tumors have additional alterations, and more importantly they co‐amplify and co‐express several genes on the 17q12 locus (Bièche et al., 1996; Kauraniemi et al., 2001; Tomasetto et al., 1995). Among these genes co‐expressed with HER2, our team identified and characterized STARD3, a gene belonging to the HER2 amplicon (Alpy and Tomasetto, 2014).STARD3 is a lipid transfer protein belonging to the START domain protein family (Alpy et al., 2001). This protein has two domains: the MENTAL domain anchors the protein in late endosomes and the cytoplasmic START domain allows cholesterol transport. Moreover, an FFAT motif present at the interface between the two domains of STARD3 interacts with VAP or MOSPD2 proteins localized in the endoplasmic reticulum (ER) (Alpy et al., 2013; Mattia et al., 2018). Thus, this interaction creates a membrane contact site between late endosomes and the ER allowing then the transfer of cholesterol towards late endosomes (Alpy et al., 2013; Wilhelm et al., 2017). Also, STARD3 has been functionally implicated in the survival of HER2‐amplified cells. Indeed, inhibition of STARD3 expression by RNA interference limits cell growth only in HER2‐amplified cells (Alpy and Tomasetto, 2014; Sahlberg et al., 2013). Thus, STARD3 belongs to the HER2 smallest region of amplification and its expression suggests that it contributes to HER2 tumor growth. We think that STARD3 cooperates with HER2 for tumor growth through an indirect molecular mechanism. Our results suggest that STARD3 acts on cancer cells by altering the normal cholesterol distribution and modifying the lipid composition of cellular membranes.This abstract is from the Experimental Biology 2019 Meeting. There is no full text article associated with this abstract published in The FASEB Journal.

GRB7 dependent proliferation of basal-like, HER-2 positive human breast cancer cell lines is mediated in part by HER-1 signaling.

GRB7 gene encodes a multi-domain signal transduction molecule and is part of the core of the HER-2 amplicon. GRB7 is commonly co-amplified and overexpressed with HER-2 in human breast cancer. This study addresses the role of GRB7 in HER-2 positive human breast cancers resistant to HER-2 targeted therapy. HCC1954, 21MT1, and JIMT1 are basal like HER-2 positive breast cancer cell lines based on expression profiling. These three cell lines are resistant to trastuzumab and lapatinib treatment. Knockdown of GRB7 protein expression with siRNA transfection as well as lentiviral vector mediated shRNA over-expression decreased the growth of HCC1954, 21MT1, and JIMT1 cells in vitro and the growth of tumor xenografts these cells formed in animal models. When assayed by ki-67 staining and TUNEL assay, the mechanism of reduced tumor xenograft growth appeared to be distinct. Reduced proliferation and increased apoptosis were seen in 21MT1 cells, while reduced proliferation was seen in HCC1954 cells and increased apoptosis in JIMT1 cells. Phospho-proteome profiling found HER-1 tyrosine phosphorylation was reduced with GRB7 knock down in JIMT1 cells. Immuno-blotting and immuno-precipitation experiments found HER-1 phosphorylation was reduced with GRB7 knock down in all three cell lines. HER-1 knock down via siRNA transient transfection as well as blocking HER-1 function with panitumumab decreased proliferation of all three cell lines in vitro. Our study finds that GRB7 has an essential growth promoting function which is mediated in part by HER-1 activation. The potential of HER-1 targeting in therapy resistant HER-2 positive breast cancer merits further study.