Comparison of the Response to Neoadjuvant Therapy Between Immunohistochemistry HER2 (3+) and HER2 (2+)/ISH+ Early-Stage Breast Cancer: A Retrospective Multicenter Cohort Study.

BACKGROUND: According to the American Society of Clinical Oncology/College of American Pathologists (ASCO/CAP) criteria, both immunohistochemical HER2 (3+) and HER2 (2+)/in situ hybridization (ISH) amplified [HER2 (2+)/ISH+] breast cancers (BCs) fall under the HER2-positive BC category. However, there is a lack of studies exploring the difference of neoadjuvant therapeutic response between patients with HER2 (3+) and HER2 (2+)/ISH+ early BC. We aimed to evaluate the neoadjuvant therapeutic response, long-term outcome, and intrinsic subtype heterogeneity between HER2 (3+) and HER2 (2+)/ISH+ BC. METHODS: We examined 2 distinct cohorts. Cohort 1 (C1) encompassed 2648 patients with HER2-positive early BC diagnoses, and they received neoadjuvant therapy (NT) and surgery between January 1, 2009 and December 31, 2022, from the Shanghai Jiao Tong University Breast Cancer Data Base. Cohort 2 (C2) comprised 135 patients with early-stage HER2-positive BC who underwent NT and surgery at Henan Cancer Hospital from January 1, 2021, to December 31, 2022. These patients had available genomic and transcriptomic data at their disposal. C1 and C2 were further categorized into 2 patient cohorts as follows: (1) patients with IHC HER2 (3+) early BC [HER2 (3+) group], (2) patients with HER2 (2+)/ISH+ early BC [HER2 (2+)/ISH+ group]. Among those excluded from the analysis were patients < 18 years or >80 years of age. Clinicopathological parameters, long-term outcomes, and intrinsic subtypes were analyzed. RESULTS: In the C1 population, 83.7% had HER2 (3+) BC, while 16.3% had HER2 (2+)/ISH+ BC. Patients with HER2 (3+) had a significantly higher pathological complete response (PCR) rate (38.9%) than patients with HER2 (2+)/ISH+ (18.1%; P < .001), but the disease-free survival (DFS) was comparable after a median follow-up of 29 months (P = .556). The addition of trastuzumab or trastuzumab plus pertuzumab to neoadjuvant chemotherapy (NAC) improved PCR rates and DFS in HER2 (3+) BC but not in HER2 (2+)/ISH+ BC. In the C2 population, 97.75% HER2 (3+) and 52.17% HER2 (2+)/ISH+ were HER2 enriched (HER2E) subtype (P < .001). HER2E showed increased PCR rates compared to non-HER2E (P = .004). CONCLUSIONS: Compared to HER2 (3+) BC, the limited effectiveness of neoadjuvant trastuzumab and pertuzumab therapy for HER2 (2+)/ISH+ BC is due to subtype heterogeneity. Reassessment of targeted therapy efficacy in patients with HER2 (2+)/ISH+ BC is essential.

The use of longitudinal CT-based radiomics and clinicopathological features predicts the pathological complete response of metastasized axillary lymph nodes in breast cancer.

BACKGROUND: Accurate assessment of axillary status after neoadjuvant therapy for breast cancer patients with axillary lymph node metastasis is important for the selection of appropriate subsequent axillary treatment decisions. Our objectives were to accurately predict whether the breast cancer patients with axillary lymph node metastases could achieve axillary pathological complete response (pCR). METHODS: We collected imaging data to extract longitudinal CT image features before and after neoadjuvant chemotherapy (NAC), analyzed the correlation between radiomics and clinicopathological features, and developed models to predict whether patients with axillary lymph node metastasis can achieve axillary pCR after NAC. The clinical utility of the models was determined via decision curve analysis (DCA). Subgroup analyses were also performed. Then, a nomogram was developed based on the model with the best predictive efficiency and clinical utility and was validated using the calibration plots. RESULTS: A total of 549 breast cancer patients with metastasized axillary lymph nodes were enrolled in this study. 42 independent radiomics features were selected from LASSO regression to construct a logistic regression model with clinicopathological features (LR radiomics-clinical combined model). The AUC of the LR radiomics-clinical combined model prediction performance was 0.861 in the training set and 0.891 in the testing set. For the HR + /HER2 - , HER2 + , and Triple negative subtype, the LR radiomics-clinical combined model yields the best prediction AUCs of 0.756, 0.812, and 0.928 in training sets, and AUCs of 0.757, 0.777 and 0.838 in testing sets, respectively. CONCLUSIONS: The combination of radiomics features and clinicopathological characteristics can effectively predict axillary pCR status in NAC breast cancer patients.

Identification potential biomarkers for diagnosis, and progress of breast cancer by using high-pressure photon ionization time-of-flight mass spectrometry.

BACKGROUND: In this study, exhaled breath testing has been considered a promising method for the detection and monitoring of breast cancer (BC). METHODS: A high-pressure photon ionization time-of-flight mass spectrometry (HPPI-TOFMS) platform was used to detect volatile organic compounds (VOCs) in breath samples. Then, machine learning (ML) models were constructed on VOCs for the diagnosis of BC and its progression monitoring. Ultimately, 1981 women with useable breath samples were included in the study, of whom 937 (47.3 %) had been diagnosed with BC. VOC panels were used for ML model construction for BC detection and progression monitoring. RESULTS: On the blinded testing cohort, this VOC-based model successfully differentiated patients with and without BC with sensitivity, specificity, and area under receiver operator characteristic curve (AUC) values of 85.9 %, 90.4 %, and 0.946. The corresponding AUC values when differentiating between patients with and without lymph node metastasis (LNM) or between patients with tumor-node-metastasis (TNM) stage 0/I/II or III/IV disease were 0.840 and 0.708, respectively. While developed VOC-based models exhibited poor performance when attempting to differentiate between patients based on pathological patterns (Ductal carcinoma in situ (DCIS) vs Invasive BC (IBC)) or molecular subtypes (Luminal vs Human epidermal growth factor receptor 2 (HER2+) vs Triple-negative BC (TNBC)) of BC. CONCLUSION: Collectively, the HPPI-TOFMS-based breathomics approaches may offer value for the detection and progression monitoring of BC. Additional research is necessary to explore the fundamental mechanisms of the identified VOCs.

Axillary lymph node dissection in triple-negative or HER2-positive breast cancer patients with clinical N2 achieving pathological complete response after neoadjuvant therapy: Is it necessary?

AIM: This study aims to identify suitable candidates for axillary sentinel lymph node biopsy (SLNB) or targeted axillary dissection (TAD) among clinical N2 (cN2) triple-negative (TN) or HER2 positive (HER2+）breast cancer patients following neoadjuvant therapy（NAT）. BACKGROUND: Despite the substantial axillary burden in cN2 breast cancer patients, high pathological response rates can be achieved with NAT in TN or HER2+ subtypes, thus enabling potential downstaging of axillary surgery. METHODS: A retrospective analysis was conducted on data from the CSBrS-012 study, screening 709 patients with initial cN2, either HER2+ or TN subtype, from January 1, 2010 to December 31, 2020. The correlation between axillary pathologic complete response (pCR) (yPN0) and breast pCR was examined. RESULTS: Among the 177 cN2 patients who achieved breast pCR through NAT, 138 (78.0 %) also achieved axillary pCR. However, in the 532 initial clinical N2 patients who did not achieve breast pCR, residual axillary lymph node metastasis persisted in 77.4 % (412/532) of cases. The relative risk of residual axillary lymph node metastasis in patients who did not achieve breast pCR was 12.4 (8.1-19.1), compared to those who did achieve breast pCR, P < 0.001. CONCLUSION: For cN2 TN or HER2+ breast cancer patients who achieve breast pCR following NAT, consideration could be given to downstaging and performing an axillary SLNB or TAD.