Biomedical subjects

Sonya Reid

Publications and source records attributed to Sonya Reid.

2 recordsLinked to original sources

PubMed2026

Efficacy and Genomic Analysis of HER2-Mutant Metastatic Triple-Negative Breast Cancer Treated with Neratinib Alone or with Trastuzumab in the SUMMIT Basket Trial.

PURPOSE: Human epidermal growth factor receptor 2 (HER2) mutations occur in 1% to 3% of triple-negative breast cancers (TNBC), representing a novel target for biomarker-directed treatment. In the SUMMIT basket trial (NCT01953926), patients with HER2-mutant, metastatic TNBC received neratinib (240 mg/day) or neratinib + trastuzumab (N + T; neratinib 240 mg/day, intravenous trastuzumab 8 mg/kg initially and then 6 mg/kg every 3 weeks). We report final results from the neratinib and N + T TNBC cohorts. PATIENTS AND METHODS: Primary endpoint: investigator-assessed objective response rate at first postbaseline tumor assessment (ORRfirst); secondary endpoints included confirmed ORR by investigator, clinical benefit rate (CBR), and progression-free survival (PFS); exploratory endpoint included circulating tumor DNA (ctDNA) collected at baseline, during treatment, and at the end of treatment. RESULTS: Twenty-seven patients were enrolled between July 2014 and September 2021. Confirmed ORRs were 40% [95% confidence interval (CI), 12.2-73.8] for neratinib (n = 10) and 35.3% (95% CI, 14.2-61.7) for N + T (n = 17). CBRs were 40% (95% CI, 12.2-73.8) and 47.1% (95% CI, 23-72.2), respectively; median PFS times were 2.89 (95% CI, 0.95-5.52) and 6.24 months (95% CI, 2.10-8.18), respectively. HER2 mutation variant allele frequencies in ctDNA from patients with response or stable disease decreased upon treatment and increased upon progression. Serial ctDNA sequencing revealed emergence or increase in on-pathway (ERBB3) and off-pathway (KRAS and TP53) mutations. The most common treatment-emergent adverse events were diarrhea, nausea, and constipation. CONCLUSIONS: N + T in patients with HER2-mutant metastatic TNBC seemed to prolong responses versus neratinib alone, representing a novel approach for patients with biomarker-defined metastatic TNBC. Based on these and previously published data, neratinib-based combinations are endorsed by the National Comprehensive Cancer Network guidelines for patients with hormone receptor-positive or -negative metastatic breast cancer with activating HER2 mutations. See related commentary by Lloyd et al., p. 3715.

Adult↗

PubMed2025

Breast Cancer Risk Stratification in Black Women: Current Status and Potential Solutions to Improve Accuracy.

Breast cancer risk stratification models identify individuals at increased risk, allowing earlier screening than for those at average risk and potentially improving health outcomes. Due to the increasing rates of breast cancer in individuals aged <40 years, especially among Black females, the American College of Radiology now recommends all females initiate breast cancer risk assessment by age 25 years. Several breast cancer risk prediction models are readily available, including the Gail Model, Breast Cancer Surveillance Consortium Risk Calculator, BOADICEA, and Tyrer-Cuzick Model. However, because these models were primarily developed using data from White women of European ancestry, they may underestimate risk in Black women. Indeed, current evidence suggests that these models underpredict breast cancer risk among Black women, particularly those of African ancestry. Although cancer risk prediction models typically incorporate personal characteristics, family history of cancer, and hormonal and lifestyle factors, inherited breast cancer genes can also increase risk for breast cancer. Beyond monogenic inherited breast cancer genes that increase breast cancer risk, emerging data suggest that single nucleotide polymorphisms identified through genome-wide association studies (GWAS) may be used to generate polygenic risk scores, which may further refine breast cancer risk. However, GWAS data are also primarily gathered from European ancestry females, further reducing the ability to accurately stratify breast cancer risk in non-European ancestry populations. Current data highlight the importance of ensuring representation from all populations in developing cancer risk prediction models, conducting genomics research, and designing effective implementation strategies to enhance the use of these models in routine clinical care. Although new analytic methods and models are being developed to improve breast cancer risk stratification across populations, it remains critical to assess the utility and calibration of existing and new models to ensure applicability across non-European ancestry populations.

Humans↗