Immune Effective Score as a Predictor of Response to Neoadjuvant Trastuzumab Therapy and a Prognostic Indicator for HER2-Positive Breast Cancer

Background: HER2-positive breast cancer (BC) is a highly aggressive phenotype. The role of the host immune features in predictive response to anti-HER2 therapies and prognosis in BC has already been suggested. We aimed to develop a predictive and prognostic model and examine its relevance to the clinical outcomes of patients with HER2-positive BC. Methods: Immune effective score (IES) was constructed using principal component analysis algorithms. A bioinformatic analysis using four independent cohorts (GSE66305, n = 88; GSE130786, n = 110; TCGA, n = 123; METABRIC, n = 236) established associations between IES and clinical outcomes. Results: Genes associated with neoadjuvant trastuzumab therapy response were enriched in pathways related to antitumor immune activities. IES was demonstrated to be a predictive biomarker to neoadjuvant trastuzumab therapy benefits (GSE66305: area under the curve (AUC) = 0.804; GSE130786: AUC = 0.704). In addition, IES was identified as an independent prognostic factor for overall survival (OS) in the TCGA cohort (p = 0.036, hazard ratio (HR): 0.66, 95% confidence interval (CI): 0.449–0.97) and METABRIC cohort (p = 0.037, HR: 0.9, 95% CI: 0.81–0.99). Conclusion: IES has a predictive value for response to neoadjuvant trastuzumab therapy and independent prognostic value for HER2-positive breast cancer.

A Randomized Trial Comparing 3- versus 4-Monthly Cardiac Monitoring in Patients Receiving Trastuzumab-Based Chemotherapy for Early Breast Cancer

Purpose: The optimal frequency for cardiac monitoring of left ventricular ejection fraction (LVEF) in patients receiving trastuzumab-based therapy for early breast cancer (EBC) is unknown. We conducted a randomized controlled trial comparing 3- versus 4-monthly cardiac monitoring. Patients and Method: Patients scheduled to receive trastuzumab-containing cancer therapy for EBC with normal (>53%) baseline LVEF were randomized to undergo LVEF assessments every 3 or 4 months. The primary outcome was the change in LVEF from baseline. Secondary outcomes included the rate of cardiac dysfunction (defined as a decrease in the LVEF of ≥10 percentage points, to a value <53%), delays in or discontinuation of trastuzumab therapy, and cardiology referral. Results: Of the 200 eligible and enrolled patients, 100 (50%) were randomized to 3-monthly and 100 (50%) to 4-monthly cardiac monitoring. Of these patients, 98 and 97 respectively underwent at least one cardiac scan. The estimated mean difference in LVEF from baseline was −0.94% (one-sided 95% lower bound: −2.14), which exceeded the pre-defined non-inferiority margin of −4%. There were also no significant differences between the two study arms for any of the secondary endpoints. The rate of detection of cardiac dysfunction was 16.3% (16/98) and 12.4% (12/97) in the 3- and 4-monthly arms, respectively (95% CI: 4.0 [−5.9, 13.8]). Conclusions: Cardiac monitoring every 4 months was deemed non-inferior to that every 3 months in patients with HER2-positive EBC being treated with trastuzumab-based therapy. Given its costs and inconvenience, cardiac monitoring every 4 months should be considered standard practice. Registration: NCT02696707, 18 February 2016.

Right Ventricular Function during Trastuzumab Therapy for Breast Cancer

PurposeCardiotoxicity (CDT) is the main adverse effect related to trastuzumab (TTZ) use, and the role of the right ventricle (RV) in this context is not clear. We aimed to evaluate the longitudinal changes in RV function during TTZ therapy and to determine the differences in RV function associated with subclinical CDT.MethodsPatients with breast cancer underwent echocardiograms at the beginning of TTZ treatment (Ex 1) and every 3 months during the first year (Ex 2, 3, 4). Subclinical CDT was defined as ≥ 12% relative reduction of left ventricle global longitudinal strain (LV GLS).ResultsTwenty-five women (52.1 ± 13.1 y-o) were included. We found a decrease in LV ejection fraction between the first and fourth exams and the LV GLS gradually decreased during follow-up (Ex1: -20.6 ± 2.0; Ex2: -19.4 ± 2.1; Ex3: -19.2 ± 1.8; Ex4: -19.0 ± 2.1, all p < 0.05). RV GLS changed from baseline to 3 month and to 6 month (Ex1: -23.9% ± 1.6; Ex2: -22.5% ± 2.1; Ex3: -22.5% ± 2.3, all p < 0.05), and the RV Fractional Area Change was lower in the third exam (Ex1: 44.3% ± 6.6 vs Ex3: 39.9% ± 6.0, p = 0.004). We found subclinical CDT in 13 patients (52%); changes in RV parameters had the same pattern of changing in the group with and without subclinical CDT.ConclusionIn this sample, the RV function decreased during TTZ therapy and the decrease was not associated to the observed LV cardiotoxicity.

Dermatomyositis following Biosimilar Trastuzumab in a Breast Cancer Patient: A Case Report

Trastuzumab, as a recombinant IgG1 kappa, is a humanized monoclonal antibody against human epidermal growth factor receptor 2. Accordingly, it is widely used in breast cancers at early and advanced stages. Dermatomyositis is a rare adverse event of trastuzumab therapy, which is not well documented yet. In this study, a patient was treated for invasive ductal carcinoma with some symptoms of rash and generalized fatigue. These symptoms started after the fifth cycle of trastuzumab, which were gradually deteriorating. This patient’s medical and family histories were unremarkable. The progression of the disease was ruled out as a possible cause of dermatomyositis, and the laboratory evaluation revealed a moderate increase in serum muscle protein (CPK). So, trastuzumab treatment was discontinued, and by passing 1 month from the start of prednisolone and hydroxychloroquine, the patient had no symptoms.

Caveolin-1 temporal modulation enhances trastuzumab and trastuzumab-drug conjugate efficacy in heterogeneous gastric cancer

Resistance mechanisms and heterogeneity in HER2-positive gastric cancers (GC) limit trastuzumab benefit in 32% of patients, and other targeted therapies have failed in clinical trials. Using genomic data from patient tissue, patient-derived xenografts (PDXs), partially humanized biological models, and HER2-targeted imaging we identified caveolin-1 (CAV1) as a complementary biomarker in GC selection for trastuzumab therapy. In retrospective analyses of samples from patients enrolled on trastuzumab trials, the CAV1-high profile was associated with low membrane HER2 density and reduced patient survival. We found a negative correlation between CAV1 tumoral protein levels - a major protein of cholesterol-rich membrane domains - and trastuzumab-drug conjugate TDM1 tumor uptake. Finally, CAV1 depletion using knockdown or pharmacologic approaches was shown to increase HER2-directed immunoPET uptake and TDM1 efficacy in GC with incomplete HER2 membranous reactivity. In support of these findings, background statin use in patients is associated with enhanced antibody efficacy. Together, this work provides mechanistic justification and clinical evidence that require prospective investigation of HER2-targeted therapies combined with statins to delay drug resistance in GC.

UCP-2 inhibitor enhanced the efficacy of trastuzumab against HER2 positive breast cancer cells

Purpose This study aimed to investigate the possibility of UCP-2 inhibitor in reducing acquired resistance of trastuzumab to improve the outcome of patients receiving trastuzumab therapy by exploring the relationship between UCP-2 expression and HER2 signaling pathway and examining whether UCP-2 expression was modulated by trastuzumab treatment. Methods 32 women diagnosed with primary HER2-positive breast cancer were recruited in this study. Needle biopsy was obtained from patients before they received at least four cycles neoadjuvant therapy containing trastuzumab in combination with chemotherapy. Surgical tumor biopsy was obtained during surgical procedure after the neoadjuvant therapy. Levels of HER2 phosphorylation and UCP-2 expression were detected by immunohistochemistry (IHC) and compared between tumor needle biopsy tissue and surgical tumor samples of these patients, as well as in BT474 breast cancer cells before and after trastuzumab treatment. HER2-selective phosphorylation/kinase activity inhibitor ONT-380 was used to identify the correlation between HER2 phosphorylation level and UCP-2 expression. UCP-2 inhibitor Genipin was then used to evaluate the apoptosis index in BT474 cells treated with trastuzumab. Results UCP-2 expression was significantly elevated in surgical tumor samples from breast cancer patients receiving trastuzumab in a neoadjuvant setting. We further confirmed our findings in HER2-positive BT474 cell line and found that trastuzumab treatment induced phosphorylation of HER2 and the overexpression of UCP-2, and the latter can be reversed by HER2 selective kinase inhibitor ONT-380. Moreover, UCP-2 inhibitor Genipin significantly enhanced the proliferation suppression effects of trastuzumab and markedly promoted apoptosis. Conclusion Taken together, our study identified UCP-2 as a novel therapeutic target for HER2 positive breast cancer and UCP-2 inhibitor may have great potential to enhance the response rate and efficacy of trastuzumab therapy.

Deep learning trained on H&E tumor ROIs predicts HER2 status and Trastuzumab treatment response in HER2+ breast cancer

The current standard of care for many patients with HER2-positive breast cancer is neoadjuvant chemotherapy in combination with anti-HER2 agents, based on HER2 amplification as detected by in situ hybridization (ISH) or protein immunohistochemistry (IHC). However, hematoxylin & eosin (H&E) tumor stains are more commonly available, and accurate prediction of HER2 status and anti-HER2 treatment response from H&E would reduce costs and increase the speed of treatment selection. Computational algorithms for H&E have been effective in predicting a variety of cancer features and clinical outcomes, including moderate success in predicting HER2 status. In this work, we present a novel convolutional neural network (CNN) approach able to predict HER2 status with increased accuracy over prior methods. We trained a CNN classifier on 188 H&E whole slide images (WSIs) manually annotated for tumor regions of interest (ROIs) by our pathology team. Our classifier achieved an area under the curve (AUC) of 0.90 in cross-validation of slide-level HER2 status and 0.81 on an independent TCGA test set. Within slides, we observed strong agreement between pathologist annotated ROIs and blinded computational predictions of tumor regions / HER2 status. Moreover, we trained our classifier on pre-treatment samples from 187 HER2+ patients that subsequently received trastuzumab therapy. Our classifier achieved an AUC of 0.80 in a five-fold cross validation. Our work provides an H&E-based algorithm that can predict HER2 status and trastuzumab response in breast cancer at an accuracy that is better than IHC and may benefit clinical evaluations.