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Biomedical subjects

Alastair M Thompson

Publications and source records attributed to Alastair M Thompson.

3 recordsLinked to original sources

Exploration of body mass index and circulating metabolic factors as predictors of metformin benefit in the Canadian Cancer Trials Group MA.32.

BACKGROUND: In the MA.32 randomized adjuvant breast cancer trial, metformin (vs placebo) did not impact invasive disease-free survival or overall survival in estrogen and/or progesterone receptor-positive or -negative breast cancer; exploratory analyses suggested a benefit in HER2-positive breast cancer. We investigated whether body mass index (BMI) and obesity-associated blood variables predicted metformin benefit in immunohistochemically defined breast cancer subtypes (luminal [estrogen/progesterone receptor positive, HER2 negative], triple-negative breast cancer [estrogen receptor, progesterone receptor, HER2 negative], HER2 positive). METHODS: A total of 3649 nondiabetic patients with high risk T1-3, N0-3, M0 breast cancer were randomly assigned. Baseline fasting plasma was assayed for insulin, glucose, leptin, and C-reactive protein; Homeostasis Model Assessment was calculated. For each breast cancer subtype and each outcome (distant recurrence free survival, overall survival, invasive disease-free survival), Cox models examined interactions of BMI and blood variables with metformin vs placebo outcomes. RESULTS: Mean age was 51.1-53.0 years; mean BMI was 27.3-27.5 kg/m2. Most cancers were T2, N0, or N1 and grade 2-3; 2104 (57.7%) were luminal, 925 (25.3%) TN, and 620 (17.0%) HER2 positive. Median follow-up was 95.9 months. In luminal breast cancer, statistically significant interactions were identified for leptin, insulin, and Homeostasis Model Assessment on distant recurrence-free survival, and in triple-negative breast cancer, a statistically significant interaction was identified for glucose on distant recurrence-free survival, with potential adverse effects of metformin at lower levels of each variable. In those with HER2-positive breast cancer, there was no variable that predicted metformin benefit. CONCLUSIONS: Body mass index and blood variables did not identify subgroups with luminal or triple-negative breast cancer who benefited from metformin or those with HER2-positive breast cancer who did not benefit. CLINICAL TRIAL REGISTRATION NUMBER: ClinicalTrials.gov NCT01101438: 2010-04-09.

Female

An Annotated Biobank of Triple-Negative Breast Cancer Patient-Derived Xenografts Features Treatment-Naïve and Longitudinal Samples during Neoadjuvant Chemotherapy.

UNLABELLED: Triple-negative breast cancer (TNBC) that fails to respond to neoadjuvant chemotherapy (NACT) can be lethal. Developing effective strategies to eradicate chemoresistant disease requires experimental models that recapitulate the heterogeneity characteristic of TNBC. To that end, we established a biobank of 92 orthotopic patient-derived xenograft (PDX) models of TNBC from the tumors of 75 patients enrolled in A Robust TNBC Evaluation fraMework to Improve Survival clinical trial (ARTEMIS, NCT02276443), including 12 longitudinal sets generated from serial patient biopsies collected throughout NACT treatment and from metastatic disease. Models were established from both chemosensitive and chemoresistant tumors, and nearly 30% of the PDX models were capable of metastasizing to the lungs. Comprehensive molecular profiling demonstrated conservation of genomes and transcriptomes between patient and corresponding PDX tumors, with representation of all major transcriptional subtypes. Transcriptional changes observed in the longitudinal PDX models highlighted dysregulation in pathways associated with DNA integrity, extracellular matrix interactions, the ubiquitin-proteasome system, epigenetics, and inflammatory signaling. These alterations revealed a complex network of adaptations associated with chemoresistance. Overall, this PDX biobank provides a valuable tool for tackling the most pressing issues facing the clinical management of TNBC. SIGNIFICANCE: The development of a patient-derived xenograft biobank that comprehensively captures the genomic and transcriptional diversity of triple-negative breast cancer promises to be a robust resource to investigate and overcome chemoresistance and metastasis.

Animals

Coalescing single-cell genomes and transcriptomes to decode breast cancer progression.

Understanding epithelial lineages of breast cancer and genotype-phenotype relationships requires direct measurements of the genome and transcriptome of the same single cells at scale. To achieve this, we developed wellDR-seq, a high-genomic-resolution, high-throughput method to simultaneously profile the genome and transcriptome of thousands of single cells. We profiled 33,646 single cells from 12 estrogen-receptor-positive breast cancers and identified ancestral subclones in multiple patients that showed a luminal hormone-responsive lineage, indicating a potential cell of origin. In contrast to bulk studies, wellDR-seq enabled the study of subclone-level gene-dosage relationships, which showed near-linear correlations in large chromosomal segments and extensive variation at the single-gene level. We identified dosage-sensitive and dosage-insensitive genes, including many breast cancer genes as well as sporadic copy-number aberrations in non-cancer cells. Overall, these data reveal complex relationships between copy number and gene expression in single cells, improving our understanding of breast cancer progression.

Breast Neoplasms