Impact of timing of trastuzumab initiation on long-term outcome of patients with early-stage HER2-positive breast cancer: the "one thousand HER2 patients" project

Factors delaying non-metastatic breast cancer adjuvant therapy and impact on prognosis in a cohort of Brazilian women

OBJECTIVE

To identify factors associated with delays in beginning adjuvant therapy and prognosis impacts on non-metastatic breast cancer patients.

METHODS

This assessment comprised a prospective cohort study concerning breast cancer patients treated at a public oncology centre. A time interval of ≥60 days between surgery and the beginning of the first adjuvant treatment was categorised as a delay. Factors associated with delays were evaluated through logistic regression analysis and the prognosis effects were assessed by a Cox regression analysis.

RESULTS

The median time interval between surgery and the first adjuvant treatment for the 401 women included in this study was of 57.0 days (37.0-93.0). Independent factors associated with delays comprised not presenting an overexpression of the HER-2 protein, not having undergone neoadjuvant chemotherapy, and having undergone chemotherapy or other therapeutic modalities other than hormone therapy and chemotherapy as the first adjuvant treatment. Delays did not affect recurrence, distant metastasis, or death risks. Factors associated with recurrence and distant metastasis risks comprised a clinical staging ≥2B, having undergone neoadjuvant chemotherapy, presenting the luminal molecular subtype B and triple-negative tumours, and having children. Factors associated with death comprised triple-negative molecular tumours and neoadjuvant chemotherapy.

CONCLUSION

Delays in beginning adjuvant treatment did not affect the prognosis of non-metastatic breast cancer patients. Clinical and treatment-related factors, on the other hand, were associated with delays, and recurrence, distant metastasis, and death risks.

Evaluation of HER2 immunohistochemistry expression in non-standard solid tumors from a Single-Institution Prospective Cohort

Aim

Human epidermal growth factor receptor-2 (HER2) is a well-established prognostic and predictive biomarker. It is an FDA-approved therapeutic target for HER2 positive breast, gastroesophageal, and more recently, lung and colon cancers. It is an emerging biomarker in biliary tract, bladder, cervical, endometrial, ovarian, and pancreatic cancers. The emergence of new indications warrants further characterization of HER2 expression in diverse cancer populations. This study investigated HER2 expression in solid tumour samples and the feasibility of obtaining these results.

Methods

Prospective consent was obtained at a Canadian tertiary academic cancer center from adult oncology patients who were referred for molecular genetic testing of malignant tissue samples. Standard HER2-targeted malignancies were considered breast and gastroesophageal, and were excluded from this study. Between July 2020 and November 2023, 499 samples of solid tumors underwent immunohistochemistry (IHC) HER2 staining. A median turnaround time (TAT) of 14 days would be considered feasible for clinical decision making.

Results

The mean age (± SD) of participants was 67 ± 12.5 years, with 270 (54%) male and 229 (46%) female. HER2 protein expression was measured in 42 unique cancer types. IHC levels of 0, 1+, 2+, and 3+ were reported and were 43%, 12%, 35%, and 10% of all analyzable samples respectively (tissue inadequate in 3% of samples). The median TAT for HER2 expression results from time of request to result in release was 18 (interquartile range, 11 to 30) days.

Conclusions

HER2 protein expression varies widely between different cancer types. TAT for HER2 IHC results was a median of 18 days, which is close to our feasibility cut-off.

Prognostic Factors and Survival Outcomes of Patients With Early HER2+ Breast Cancer Treated With Trastuzumab in a Brazilian Public Reference Center: A Real-World Study

PURPOSE

Trastuzumab was introduced into the Brazilian public health care service for early breast cancer (BC) in 2012. This study describes the survival outcomes and prognostic factors related to early HER2+ BC treatment in a Brazilian reference cancer center.

PATIENTS AND METHODS

This were a retrospective, single-center, observational study of early HER2+ BC patients treated with trastuzumab in the (neo)adjuvant setting between 2012 and 2018 at Hospital Pérola Byington. Demographic, clinical, disease-free survival (DFS) and overall survival (OS) data were evaluated. Multivariate analysis was performed to assess independent prognostic factors.

RESULTS

One hundred seventy-six and 353 patients treated in the neoadjuvant and adjuvant setting were included, respectively. The 3- and 5-year OS rates were 79% and 56% for the neoadjuvant group and 97% and 92% for the adjuvant group, respectively. Node positivity at diagnosis predicted poor OS for both groups. In the neoadjuvant group, stage III disease at diagnosis, delayed surgery, and lack of pathological complete response (pCR) predicted poor prognosis. The 3- and 5-year DFS rates were 67% and 46% in the neoadjuvant group and 91% and 86% in the adjuvant group, respectively. Histological grade 2, stage III disease at diagnosis, and lack of pCR predicted poor DFS for the neoadjuvant group. For the adjuvant group, node positivity at diagnosis predicted poor DFS.

CONCLUSION

Our results reveal multiple clinical parameters affecting survival outcomes according to the treatment setting. Patients treated with neoadjuvant therapy have a poor prognosis since they present with more advanced disease, indicating the importance of early diagnosis and optimized treatment.

Predictive modelling of response to neoadjuvant therapy in HER2+ breast cancer

HER2-positive (HER2+) breast cancer accounts for 20-25% of all breast cancers. Predictive biomarkers of neoadjuvant therapy response are needed to better identify patients with early stage disease who may benefit from tailored treatments in the adjuvant setting. As part of the TCHL phase-II clinical trial (ICORG10-05/NCT01485926) whole exome DNA sequencing was carried out on normal-tumour pairs collected from 22 patients. Here we report predictive modelling of neoadjuvant therapy response using clinicopathological and genomic features of pre-treatment tumour biopsies identified age, estrogen receptor (ER) status and level of immune cell infiltration may together be important for predicting response. Clonal evolution analysis of longitudinally collected tumour samples show subclonal diversity and dynamics are evident with potential therapy resistant subclones detected. The sources of greater pre-treatment immunogenicity associated with a pathological complete response is largely unexplored in HER2+ tumours. However, here we point to the possibility of APOBEC associated mutagenesis, specifically in the ER-neg/HER2+ subtype as a potential mediator of this immunogenic phenotype.

Optimizing combination therapy in a murine model of HER2+ breast cancer

Human epidermal growth factor receptor 2 positive (HER2+) breast cancer is frequently treated with drugs that target the HER2 receptor, such as trastuzumab, in combination with chemotherapy, such as doxorubicin. However, an open problem in treatment design is to determine the therapeutic regimen that optimally combines these two treatments to yield optimal tumor control. Working with data quantifying temporal changes in tumor volume due to different trastuzumab and doxorubicin treatment protocols in a murine model of human HER2+ breast cancer, we propose a complete framework for model development, calibration, selection, and treatment optimization to find the optimal treatment protocol. Through different assumptions for the drug-tumor interactions, we propose ten different models to characterize the dynamic relationship between tumor volume and drug availability, as well as the drug-drug interaction. Using a Bayesian framework, each of these models are calibrated to the dataset and the model with the highest Bayesian information criterion weight is selected to represent the biological system. The selected model captures the inhibition of trastuzumab due to pre-treatment with doxorubicin, as well as the increase in doxorubicin efficacy due to pre-treatment with trastuzumab. We then apply optimal control theory (OCT) to this model to identify two optimal treatment protocols. In the first optimized protocol, we fix the maximum dosage for doxorubicin and trastuzumab to be the same as the maximum dose delivered experimentally, while trying to minimize tumor burden. Within this constraint, optimal control theory indicates the optimal regimen is to first deliver two doses of trastuzumab on days 35 and 36, followed by two doses of doxorubicin on days 37 and 38. This protocol predicts an additional 45% reduction in tumor burden compared to that achieved with the experimentally delivered regimen. In the second optimized protocol we fix the tumor control to be the same as that obtained experimentally, and attempt to reduce the doxorubicin dose. Within this constraint, the optimal regimen is the same as the first optimized protocol but uses only 43% of the doxorubicin dose used experimentally. This protocol predicts tumor control equivalent to that achieved experimentally. These results strongly suggest the utility of mathematical modeling and optimal control theory for identifying therapeutic regimens maximizing efficacy and minimizing toxicity.

Real-world Evidence of Diagnostic Testing and Treatment Patterns in US Patients With Breast Cancer With Implications for Treatment Biomarkers From RNA Sequencing Data

OBJECTIVE/BACKGROUND

We performed a retrospective analysis of longitudinal real-world data (RWD) from patients with breast cancer to replicate results from clinical studies and demonstrate the feasibility of generating real-world evidence. We also assessed the value of transcriptome profiling as a complementary tool for determining molecular subtypes.

METHODS

De-identified, longitudinal data were analyzed after abstraction from records of patients with breast cancer in the United States (US) structured and stored in the Tempus database. Demographics, clinical characteristics, molecular subtype, treatment history, and survival outcomes were assessed according to strict qualitative criteria. RNA sequencing and clinical data were used to predict molecular subtypes and signaling pathway enrichment.

RESULTS

The clinical abstraction cohort (n = 4000) mirrored the demographics and clinical characteristics of patients with breast cancer in the US, indicating feasibility for RWE generation. Among patients who were human epidermal growth factor receptor 2-positive (HER2+), 74.2% received anti-HER2 therapy, with ∼70% starting within 3 months of a positive test result. Most non-treated patients were early stage. In this RWD set, 31.7% of patients with HER2+ immunohistochemistry (IHC) had discordant fluorescence in situ hybridization results recorded. Among patients with multiple HER2 IHC results at diagnosis, 18.6% exhibited intra-test discordance. Through development of a whole-transcriptome model to predict IHC receptor status in the molecular sequenced cohort (n = 400), molecular subtypes were resolved for all patients (n = 36) with equivocal HER2 statuses from abstracted test results. Receptor-related signaling pathways were differentially enriched between clinical molecular subtypes.

CONCLUSIONS

RWD in the Tempus database mirrors the overall population of patients with breast cancer in the US. These results suggest that real-time, RWD analyses are feasible in a large, highly heterogeneous database. Furthermore, molecular data may aid deficiencies and discrepancies observed from breast cancer RWD.

Management of early-stage breast cancer patients during the coronavirus disease 2019 (COVID-19) pandemic: The experience in China from a surgical standpoint

Breast cancer is the most common malignant tumor in women globally. Currently, due to limited data, there are no international guidelines for addressing the management of a large group of patients during infectious disease pandemics. Coronavirus disease 2019 (COVID-19), declared as a pandemic by the World Health Organization (WHO), has rapidly spread globally. The COVID-19 pandemic changed our daily routines and forced us to rethink the management of breast cancer patients. Clinicians need to take into account multiple factors such as the timing and delivery of cancer care, epidemic prevention and control, and the allocation of medical resources. Determining ways to reasonably adjust the treatment strategy is a real challenge. In this review, we aim to discuss particular challenges associated with managing breast cancer patients during the COVID-19 pandemic, share experience from Chinese oncologists and surgeons and propose some practical approaches to the management of early-stage breast cancer patients from a surgical standpoint.