Professor Charles E. Geyer: neoadjuvant therapy is becoming standard of care for HER2+ breast cancer

2016 ◽  
Vol 5 (5) ◽  
pp. 71-71
Author(s):  
Lucille L. Ye
Keyword(s):  
Breast Cancer ◽  
Neoadjuvant Therapy ◽  
Standard Of Care ◽  
Her2 Breast Cancer

The role of ado-trastuzumab emtansine in current clinical practice

2020 ◽  
pp. 107815522095186
Author(s):  
Alla Turshudzhyan
Keyword(s):  
Breast Cancer ◽  
Neoadjuvant Therapy ◽  
Early Breast Cancer ◽  
Bystander Effect ◽  
Residual Disease ◽  
Trastuzumab Emtansine ◽  
Her2 Positive ◽  
Post Surgery ◽  
Her2 Breast Cancer ◽  
Randomized Controlled Studies

Objective This review reflects the literature from 2019 to 2020 on ado-trastuzumab emtansine’s (T-DM1) therapeutic use, clinical controversies, and newest perspectives on use. Data sources: PubMed was used as a database. Search “ado-trastuzumab emtansine” on June 11th, 2020 resulted in 57 publications: 20 clinical trials, two metanalysis, six randomized controlled studies, 13 reviews, and two systematic reviews. Of the 57 publications, 34 were descriptive of the topic in question and were used for this review. Data summary: T-DM1 is now used for patients with HER2 breast cancer who have residual disease post surgery after neoadjuvant chemotherapy (KATHERINE trial). Initial success prompted KRISTINE trial, which investigated whether T-DM1 can be used as a neoadjuvant therapy. While it did have fewer adverse events, T-DM1 was inferior to chemotherapy in treating early breast cancer. Noted shortcomings of the drug were toxicity limited Cmax, slow rate of internalization, lack of payload bystander effects, and number of resistance mechanisms. Proposed solutions were pre-treatment with metformin to augment drug internalization by the cell, use of second generation anti-HER2 antibody-drug conjugates to overcome developing resistance, payload swapping to increase bystander effect. Conclusions While T-DM1 has fewer side-effects, it is inferior to chemotherapy in early breast cancer treatment. More research should be done to overcome resistance pathways, identify rate-limiting intracellular processing pathways, improve bystander, and enhance internalization of the drug. Until more research is done, T-DM1 will continue to be used in HER2 positive breast cancer as well as a few other HER2 expressing tumors that fail to respond to neoadjuvant therapy.

scholarly journals Automated Tumour Recognition and Digital Pathology Scoring Unravels New Role for PD-L1 in Predicting Good Outcome in ER-/HER2+ Breast Cancer

2018 ◽  
Vol 2018 ◽  
pp. 1-14 ◽  
Author(s):  
Matthew P. Humphries ◽  
Sean Hynes ◽  
Victoria Bingham ◽  
Delphine Cougot ◽  
Jacqueline James ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Clinical Significance ◽  
Digital Pathology ◽  
Scoring Systems ◽  
Standard Of Care ◽  
Inflammatory Cells ◽  
Predictive Biomarker ◽  
Current Standard ◽  
Her2 Breast Cancer ◽  
Biomarker Quantitation

The role of PD-L1 as a prognostic and predictive biomarker is an area of great interest. However, there is a lack of consensus on how to deliver PD-L1 as a clinical biomarker. At the heart of this conundrum is the subjective scoring of PD-L1 IHC in most studies to date. Current standard scoring systems involve separation of epithelial and inflammatory cells and find clinical significance in different percentages of expression, e.g., above or below 1%. Clearly, an objective, reproducible and accurate approach to PD-L1 scoring would bring a degree of necessary consistency to this landscape. Using a systematic comparison of technologies and the application of QuPath, a digital pathology platform, we show that high PD-L1 expression is associated with improved clinical outcome in Triple Negative breast cancer in the context of standard of care (SoC) chemotherapy, consistent with previous findings. In addition, we demonstrate for the first time that high PD-L1 expression is also associated with better outcome in ER- disease as a whole including HER2+ breast cancer. We demonstrate the influence of antibody choice on quantification and clinical impact with the Ventana antibody (SP142) providing the most robust assay in our hands. Through sampling different regions of the tumour, we show that tumour rich regions display the greatest range of PD-L1 expression and this has the most clinical significance compared to stroma and lymphoid rich areas. Furthermore, we observe that both inflammatory and epithelial PD-L1 expression are associated with improved survival in the context of chemotherapy. Moreover, as seen with PD-L1 inhibitor studies, a low threshold of PD-L1 expression stratifies patient outcome. This emphasises the importance of using digital pathology and precise biomarker quantitation to achieve accurate and reproducible scores that can discriminate low PD-L1 expression.

The relationship between treatment intensity and characteristics of patients with early-stage breast cancer.

2020 ◽  
Vol 38 (29_suppl) ◽  
pp. 125-125
Author(s):  
Jeffrey Franks ◽  
Nicole Caston ◽  
Courtney Williams ◽  
Andres Azuero ◽  
Monica S. Aswani ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Clinical Trials ◽  
High Intensity ◽  
Early Stage ◽  
Standard Of Care ◽  
Early Stage Breast Cancer ◽  
Treatment Intensity ◽  
Low Intensity ◽  
Her2 Breast Cancer ◽  
To Receive

125 Background: Clinical trials are used to generate standard-of-care, yet often do not reflect patient populations treated in real-world settings. Elderly patients or patients of color who are often underrepresented in trials, which may impact what types of treatments are prescribed. This study examines how patient characteristics are associated with treatment intensity in early stage breast cancer. Methods: This retrospective cross-sectional study included women with a stage I-III breast cancer from American Society of Clinical Oncology’s CancerLinQ database treated by chemotherapy from 2005-2019. Seven standard-of-care regimens were characterized by intensity. For patients with ER+/- HER2- breast cancer, low-intensity regimens were Taxol and Cyclophosphamide or Adriamycin and Cyclophosphamide; while Taxol, Adriamycin, and Cyclophosphamide was considered high intensity. For patients with HER2+ breast cancer, the low intensity regimen was Taxol and Herceptin; while Adriamycin and Cyclophosphamide followed by Taxol and Herceptin; Taxol, Carboplatin, and Herceptin; or Taxol, Carboplatin, Herceptin, and Pertuzumab were considered high intensity. A model estimating the likelihood of intensity was calculated using log-binomial regression, in order to produce relative risks. The models were adjusted for patient demographics and cancer stage. Results: Of 24,383 patients, 51% had ER+HER2-, 20% ER-HER2-, and 29% HER2+ breast cancer. Most patients were White (60%), age 40-69 (80%), had stage II breast cancer (39%), and received higher intensity treatment (65%). Adjusted for the other covariates, patient who were Black were more likely to receive high-intensity treatment than patients who were White (61% vs 58%; RR 1.05, 95%CI 1.02-1.06. Additionally, older adults were more likely to receive low-intensity treatment, with 42% of patients over 70 receiving low intensity treatment, and 29% of patients between the ages 40 and 69 received low intensity treatment (RR 1.5, 95% CI 1.44 -1.54). Conclusions: Differences in treatment intensity were observed for patients with differing demographic characteristics. Further research is needed to determine lack of representation in clinical trials impacts on prescribing patterns, regimen intensity, and survival.

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

2021 ◽  
Author(s):  
saman farahmand ◽  
Aileen Fernandez ◽  
Fahad Shabbir Ahmed ◽  
David Rimm ◽  
Jeffrey H Chuang ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Treatment Response ◽  
Cross Validation ◽  
Area Under The Curve ◽  
Standard Of Care ◽  
Her2 Status ◽  
Current Standard ◽  
Her2 Positive ◽  
Trastuzumab Therapy ◽  
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.

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