Evaluation of Therapeutic Target Gene Expression Based on Residual Cancer Burden Classification After Neoadjuvant Chemotherapy for HER2-Negative Breast Cancer

Dynamic changes in intrinsic subtype, immunity status, and risk score before and after neoadjuvant chemo- and HER2-targeted therapy without pCR in HER2-positive breast cancers: A cross-sectional analysis

Very few studies have been done in HER2 positive patients without complete pathological response (pCR) after combined neoadjuvant chemo- and HER2-target therapy to investigate changes in intrinsic subtype, risk of recurrence (ROR) score, and immunity status before and after treatment. Patients with nonmetastatic HER2-positive breast cancer failed to achieve pCR after neoadjuvant chemotherapy plus trastuzumab were included in current study. We examined the distribution of PAM50 subtypes, ROR score and immunity score in 25 paired baseline and surgical samples. The Miller-Payne grading system was used to evaluate the efficacy of the neoadjuvant therapy. It was observed that the distribution of intrinsic subtype, ROR category and immunity subgroup varied according to hormone receptor (HR) status. HER2-enriched and basal-like subtypes, median-high ROR categories and immunity-weak subgroup were dominant in baseline tumors. Compared to baseline samples, conversion of intrinsic subtype, ROR categories and immunity subgroups were found in 15 (60.0%), 13(52.0%), and 11(44.0%) surgical samples, respectively. The PAM50 subtype, ROR category, and immunity subgroup were concordant between baseline and surgical samples where nonluminal subtypes, median-high ROR categories and i-weak subgroup were still common. In conclusion, the HER2-positive breast cancer is highly heterogeneous with a distribution of 72-gene expression varying according to HR co-expression. The dynamics of the 72-gene expression pre- and posttreatment may become novel biomarker for guiding adjuvant therapy and hence warrant further investigation.

Gene-expression signatures to inform neoadjuvant treatment decision in HR+/HER2- breast cancer: Available evidence and clinical implications

Over the last few years, the indication for chemotherapy use in HR+/HER2- early BC has been significantly modified by the introduction of gene-expression profiling. In the adjuvant setting, several gene-expression signatures have been validated to discriminate early stage HR+/HER2- BC with different prognosis and to identify patients for which adjuvant chemotherapy can be spared. Considering their ability to optimize the choice of adjuvant treatment and the increasing use of neoadjuvant approach in early BC, the potential use of gene-expression signatures to discriminate patients to be candidate to neoadjuvant chemotherapy or endocrine treatment appears particularly appealing. Indeed, the San Gallen Consensus Conference panel recently endorsed the use of genomic assays on core biopsies as a potential strategy for choosing the type of neoadjuvant treatment (chemotherapy or endocrine therapy) in selected patients. In this context, we here review evidence supporting the use of most common commercially available gene-expression signatures (Oncotype DX, MammaPrint, PAM50, EndoPredict and Breast Cancer Index) in patients receiving neoadjuvant therapy for HR+/HER2- BC. Data on the association of gene expression signatures and response to neoadjuvant chemotherapy or neoadjuvant endocrine therapy will be reviewed and the clinical implications of this data to guide the clinical decision-making process in early HR+/HER2- BC will be discussed.

Resistance to Neoadjuvant Treatment in Breast Cancer: Clinicopathological and Molecular Predictors

Neoadjuvant Chemotherapy (NAC) in Breast Cancer (BC) has proved useful for the reduction in tumor burden prior to surgery, allowing for a more extensive breast preservation and the eradication of subjacent micrometastases. However, the impact on prognosis is highly dependent on the establishment of Pathological Complete Response (pCR), in particular for Triple Negative (TN) and Hormonal Receptor negative/Human Epidermal growth factor Receptor 2 positive (HR-/HER2+) subtypes. Several pCR predictors, such as PAM50, Integrative Cluster (IntClust), mutations in PI3KCA, or the Trastuzumab Risk model (TRAR), are useful molecular tools for estimating response to treatment and are prognostic. Major evolution events during BC NAC that feature the Residual Disease (RD) are the loss of HR and HER2, which are prognostic of bad outcome, and stemness and immune depletion-related gene expression aberrations. This dynamic nature of the determinants of response to BC NAC, together with the extensive heterogeneity of BC, raises the need to discern the individual and subtype-specific determinants of resistance. Moreover, refining the current approaches for a comprehensive monitoring of tumor evolution during treatment, RD, and eventual recurrences is essential for identifying new actionable alterations and the integral best management of the disease.