Biology subjects

Sawyer, E.

Publications and source records attributed to Sawyer, E..

5 recordsLinked to original sources

bioRxiv2025

SMART: A Spatio-Molecular Atlas of Response Trajectories in Triple-Negative Breast Cancer

A major challenge in treating Triple-Negative Breast Cancer (TNBC) lies in its molecular, morphological and clinical heterogeneity, which hampers accurate prediction of responses to neoadjuvant treatment. To address this, we introduce SMART: Spatio-Molecular Atlas of Response Trajectories, a comprehensive, multimodal resource compiled from 129 TNBC samples across 89 patients, obtained before, during, and after neoadjuvant chemotherapy (NACT). SMART comprises of 5,096 high quality manually selected spatial transcriptomic profiles enriched for epithelial, immune, or stromal compartments; paralleled with histological annotations, imagebased network analysis and protein expression. Seven novel spatial epithelial archetypes (EAs), seven tumour-immune microenvironments (TIMEs) and their co-localisation patterns were defined, revealing an opposing prevalence of functionally divergent EAs between response groups and the prognostic significance of B-cell enriched TIMEs, in particular those surrounding histologically normal epithelium adjacent to the tumour. The SMART dataset and analytical tools are publicly available via the PharosAI platform, providing the research community with the most comprehensive, manually annotated spatio-molecular transcriptomics atlas of NACT-treated TNBC to date.

cancer biology↗

bioRxiv2025

The Effects of Intraspecies and Interspecies Competition on Genetic Device Construction and Performance

Future genetic devices expressed in microbes need to be tested in complex environments containing multiple organisms to expand their usability. We sought to determine if genetic parts designed for monoculture are predictable when used in co-culture by testing constitutive Anderson promoters driving expression of chromoproteins from a plasmid. In Escherichia coli monoculture a high copy number origin of replication causes stochastic expression regardless of promoter strength, and high Anderson promoter strength leads to selection for inactivating mutations, resulting in inconsistent chromoprotein expression. Medium and low strength Anderson promoters function more predictably in E. coli monoculture but experience an increase in inactivating mutations when grown in co-culture over many generations with Pseudomonas aeruginosa. Expression from native promoters instead of Anderson promoters can lead to stable expression in a complex wastewater culture. Overall, we show intraspecies selection for inactivating mutations due to a competitive growth advantage for E. coli that do not express the genetic device compared to their peers that retain the functional device. We show additional interspecies selection against the functional device when E. coli is co-cultured with another organism. Together, these two selection pressures create a significant barrier to genetic device function in microbial communities that we overcome by utilize a native E. coli promoter. Future strategies for genetic device design in microorganisms that need to function in a complex microbial environment should focus on native promoters and/or strategies that give the microorganism carrying the device a selective or growth advantage. ImportanceFirst generation biotechnology focused on genetic devices designed for use in monoculture conditions. Next generation biotechnology devices will need to function in complex ecosystems with other organisms, so we sought to create conditions where the genetic device retained function when the organism carrying it is in co-culture with other organisms. We discovered that when the genetic device is a significant resource burden on the organism carrying the device mutations will be selected for due to intraspecies and interspecies selection pressures and the device will be rendered non-functional. Therefore, genetic device design for complex ecosystems in next generation biotechnology needs to balance functionality of the genetic device with the need to reduce resource burden on the organism carrying it.

synthetic biology↗

bioRxiv2024

Development of a Deep Learning model Tailored for HER2 Detection in Breast Cancer to aid pathologists in interpreting HER2-Low cases

IntroductionOver 50% of breast cancer cases are "Human epidermal growth factor receptor 2 (HER2) low breast cancer (BC)", characterized by HER2 immunohistochemistry (IHC) scores of 1+ or 2+ alongside no amplification on fluorescence in situ hybridization (FISH) testing. The development of new anti-HER2 antibody-drug conjugates (ADCs) for treating HER2-low breast cancers illustrates the importance of accurately assessing HER2 status, particularly HER2-low breast cancer. In this study, we evaluated the performance of a deep learning (DL) model for the assessment of HER2, including an assessment of the causes of discordances of HER2-Null between a pathologist and the DL model. We specifically focussed on aligning the DL model rules with the ASCO/CAP guidelines, including stained cells staining intensity and completeness of membrane staining. MethodsWe trained a DL model on a multi-centric cohort of breast cancer cases with HER2- immunohistochemistry scores (n=299). The model was validated on 2 independent multi- centric validation cohorts (n=369 and n=92), with all cases reviewed by 3 senior breast pathologists. All cases underwent a thorough review by three senior breast pathologists, with the ground truth determined by a majority consensus on the final HER2 score among the pathologists. In total, 760 breast cancer cases were utilized throughout the training and validation phases of the study. ResultsThe models concordance with the ground truth (ICC = 0.77 [0.68 - 0.83]; Fisher P = 1.32e-10) is higher than the average agreement among the 3 senior pathologists (ICC = 0.45 [0.17 - 0.65]; Fisher P = 2e-3). In the two validation cohorts, the DL model identifies 95% [93%- 98%] and 97% [91% - 100%] of HER2-low and HER2-positive tumors respectively. Discordant results were characterized by morphological features such as extended fibrosis, a high number of tumor-infiltrating lymphocytes, and necrosis, whilst some artifacts such as non- specific background cytoplasmic stain in the cytoplasm of tumor cells also cause discrepancy. ConclusionDeep learning can support pathologists interpretation of difficult HER2-low cases. Morphological variables and some specific artifacts can cause discrepant HER2-scores between the pathologist and the DL Model.

pathology↗

bioRxiv2021

Define protein variant functions with high-complexity mutagenesis libraries and enhanced mutation detection software

Pooled variant expression libraries can test the phenotypes of thousands of variants of a gene in a single multiplexed experiment. In a library encoding all single-amino-acid substitutions of a protein, each variant differs from its reference only at a single codon-position located anywhere along the coding sequence. Consequently, accurately identifying these variants by sequencing is a major technical challenge. A popular but expensive brute-force approach is to divide the pool of variants into multiple smaller sub-libraries that each contains variants of a small region and that must each be constructed and screened individually, but that can then be PCR-amplified and fully sequenced with a single read to allow direct readout of variant abundance. Here we present an approach to screen very large variant libraries with mutations spanning a wide region in a single pool, including library design criteria and mutant-detection algorithms that permit reliable calling and counting of variants from large-scale sequencing data.

systems biology↗

bioRxiv2018

Developmental Regulation of an Organelle Tether Coordinates Mitochondrial Remodeling in Meiosis

Cellular differentiation involves remodeling cellular architecture to transform one cell type to another. By investigating mitochondrial dynamics during meiotic differentiation in budding yeast, we sought to understand how organelle morphogenesis is developmentally controlled in a system where regulators of differentiation as well as organelle architecture are known, but the interface between them remains unexplored. We found that mitochondria abruptly detach from the cell cortex shortly before segregating into gametes. Mitochondrial detachment is enabled by the programmed destruction of the mitochondria-endoplasmic reticulum-cortex anchor (MECA), an organelle tether that forms contact sites between mitochondria and the plasma membrane. MECA regulation is governed by a meiotic transcription factor, Ndt80, which promotes the activation of a conserved kinase, Ime2. We found that MECA undergoes Ime2-dependent phosphorylation. Furthermore, Ime2 promotes MECA degradation in a temporally controlled manner. Our study defines a key mechanism that coordinates mitochondrial morphogenesis with the landmark events of meiosis and demonstrates that cells can developmentally regulate tethering to induce organelle remodeling.

cell biology↗