Biology subjects

Yates, M.

Publications and source records attributed to Yates, M..

7 recordsLinked to original sources

bioRxiv2026

Novel transplantable mouse cell line model recapitulates invasive lobular breast carcinoma (ILC) phenotype and immune microenvironment.

Invasive lobular breast carcinoma (ILC) is the most common special histological subtype of breast cancer, which accounts for 10-15% of all cases. To study the phenotype characteristics, metastatic growth kinetic and immune microenvironment of ILC, we developed an orthotopically transplantable cell line model from the spontaneous mammary fat pad tumor of CDH1-PTEN dual knockout C57BL/6 mouse with Cre-loxP system, designated CPT6. CPT6 recapitulates single-file growth pattern of human ILC, with pleomorphic features and a high mitotic index. RNA sequencing together with whole exome sequencing reveals a luminal A subtype with targetable driver mutations such as Kras G12C. As a novel orthotopically transplantable ILC model in immune competent mice, CPT6 shows robust in vivo growth and metastatic rate, and has moderate immunogenicity which appears to be T-cell independent. We also profiled the immune microenvironment of CPT6, revealing a myeloid-rich environment with dominant M2-macrophage population, which is concordant with human ILC. In summary, this model recapitulates human ILC phenotype and represents a valuable preclinical platform for evaluating immunotherapy and other therapeutic strategies for invasive lobular breast carcinoma.

cancer biology↗

bioRxiv2026

Robust Regularization Enables Automated, Real-Time Square-Wave Voltammetry Signal Quantification

Square-wave voltammetry (SWV) is widely used for electrochemical biosensing because it enables sensitive, temporally resolved measurement of redox reporter signals. However, automated quantification of SWV signal remains challenging for long duration and in vivo measurements, where voltammograms can exhibit changing baselines, heterogeneous noise, peak drift, outliers, and interfering faradaic processes. Here, we introduce the Adaptive Square-Wave Voltammetry Iterative Fitting Toolkit (ASWIFT), an automated method for robust SWV signal extraction based on iteratively reweighted regularized smoothing. ASWIFT is available as both an open-source Python package and a downloadable desktop application. The method adaptively estimates the baseline, selects regularization strengths, fits the redox peak, and reports peak height without trace-specific parameter tuning. Across simulated datasets spanning diverse baseline, peak, noise, and concentration-response conditions, ASWIFT produced less systematic bias and more consistent signal estimates than existing methods. We further evaluated ASWIFT using in vitro doxorubicin measurements and in vivo DNA-based kanamycin sensor measurements collected in rat blood and interstitial fluid, demonstrating agreement with established methods. These results support ASWIFT as a robust framework for automated SWV analysis in real-time electrochemical biosensing.

bioengineering↗

bioRxiv2025

Identification and Credentialing of Patient Derived Xenograft Models of Invasive Lobular Breast Carcinoma using Multi-omics and Histopathology assessment

Breast cancer is a heterogeneous disease with numerous histological subtypes. Invasive lobular cancer (ILC) is the most common special subtype, accounting for 10-15% of all breast cancers. The pathognomonic feature of ILC is the loss of E-cadherin (CDH1), which leads to a unique single-file growth pattern of discohesive cells. Although ILCs show better prognostic factors than the most common No Special Type (NST) of breast cancer, patients with ILC have worse long-term outcomes, which is not well understood. In this study, we aimed to identify and characterize Patient-Derived Xenograft (PDX) models of ILC based upon the presence of truncating CDH1 mutations and/or low CDH1 mRNA expression among 128 human breast cancer PDX models. We selected 8 PDX models for validation using Immunohistochemical (IHC) analysis for E-Cadherin, p120, ER, PR, and HER2. We confirmed that seven of these PDX models are indeed ILC while one was identified as mixed NST-ILC PDX. Molecular analysis of the confirmed ILC PDX models showed enrichment of truncating CDH1 mutations, significantly lower levels of CDH1 mRNA expression and predominantly luminal subtypes compared to NST PDX models, in line with the molecular characteristics of human ILC disease. The commonly altered genes in the ILC PDX models included PIK3CA (57%), CDH1 (57%) and TP53 (57%) among others. Our study confirms and characterizes new ILC PDX models, offering valuable tools to advance our understanding of human ILC biology and support the development of innovative treatment strategies.

cancer biology↗

bioRxiv2025

Oncogene SETDB1s Dual Role in Endometrial Cancer: Driving Tumor Progression and Immune Escape

Oncogene SETDB1, an H3K9 methyltransferase, drives tumorigenesis in various cancers. Using endometrial cancer (EC) as a model, we discovered SETDB1s dual mechanisms in driving EC tumorigenesis and mediating immune evasion. SETDB1 knockout (SETDB1-/-) tumor-bearing mice exhibited prolonged survival of up to 100 days. Transcriptomic profiling of SETDB1-/- EC cells revealed decreased expression of oncogenes (POLR2A, MSH6, FLNA) and increased expression of tumor suppressor genes (PGR, RERG, ZNF582), which indicates that SETDB1 intrinsically promotes EC tumor proliferation by regulating these downstream genes. SETDB1 repressed repeat elements and the interferon pathway, mediating immune evasion extrinsically by inhibiting anti-tumor macrophage infiltration. ChIP-seq analysis showed SETDB1 binding at pericentromeric regions on many chromosomes and numerous ZNFs. Loss of SETDB1 resulted in abnormal cell division. SETDB1-/- tumors displayed reduced proliferation markers (Ki67, pHH3) and increased macrophage infiltration. Mechanistically, SETDB1 promotes CD47 (a dont-eat-me signal) and represses CCL5 and CXCL9 (macrophage and T-cell recruiting chemokines), contributing to immune evasion. M1-like macrophages killed more SETDB1-/- cells in co-culture. Additionally, SETDB1 knockout in mouse EC cells reduced tumor growth in C57BL/6 mice, with increased macrophage and CD4+ T-cell infiltration. Our results indicates that elevated SETDB1 and its target genes can predict higher tumor grade and worse survival, suggesting that targeting SETDB1 could be a promising therapeutic strategy for EC.

cancer biology↗

bioRxiv2021

Pre-trial predictors of conflict response efficacy in human dorsolateral prefrontal cortex

The ability to perform motor actions depends, in part, on the brains initial state, that is, the ensemble firing rate pattern prior to the initiation of action. We hypothesized that the same principle would apply to cognitive functions as well. To test this idea, we examined a unique set of single unit data collected in human dorsolateral prefrontal (dlPFC) cortex. Data were collected in a conflict task that interleaves Simon (motor-type) and Eriksen (flanker-type) conflict trials. In dlPFC, variability in pre-trial firing rate predicted the ability to resolve conflict, as inferred from reaction times. Ensemble patterns that predicted faster Simon reaction times overlapped slightly with those predicting Erikson performance, indicating that the two conflict types are associated with near-orthogonal initial states, and suggesting that there is a weak abstract or amodal conflict preparatory state in this region. These codes became fully orthogonalized in the response state. We interpret these results in light of the initial state hypothesis, arguing that the firing patterns in dlPFC immediately preceding the start of a task predispose it for the efficient implementation of cognitive action.

neuroscience↗

bioRxiv2021

Water as a reactant in the first step of triosephosphate isomerase catalysis

The enzyme triosephosphate isomerase (TIM) performs a crucial role in the extraction of energy from glucose, doing so by converting dihydroxyacetone phosphate (DHAP) into glyceraldehyde phosphate, thereby doubling the yield of ATP molecules during glycolysis. The initial step of the mechanism is the seemingly unlikely abstraction of the pro-R methylene hydrogen from C1 by a conserved glutamate (Glu165), an assignment that has been both universally accepted yet a much-studied phenomenon for decades. In this work we introduce an alternative mechanism in which water as a strong general base abstracts the carbon proton acting effectively as hydroxide. We posit that strong electric fields associated with the substrate phosphate promote facile autoionization of water trapped near the phosphate dianion of DHAP and Glu165, an example of substrate assisted catalysis. Classical molecular dynamics simulations assert that the closest water oxygen atom is consistently closer to the pro-R H than the carboxylate oxygen atoms of the accepted base Glu165. Our proposal is further supported by quantum computations that confirm the implausibility of abstraction of the methylene hydrogen by glutamate and the ease with which it is abstracted by hydroxide. The necessity of Glu165 for efficient catalysis is attributed to its crucial involvement in trapping the vital water in an environment of high electric fields which promote ionization far more rapidly than in bulk solvent.

biophysics↗

bioRxiv2020

Human dorsal anterior cingulate neurons signal conflict by amplifying task-relevant information

Hemodynamic activity in dorsal anterior cingulate cortex (dACC) correlates with conflict, suggesting it contributes to conflict processing. This correlation could be explained by multiple neural processes that can be disambiguated by population firing rates patterns. We used targeted dimensionality reduction to characterize activity of populations of single dACC neurons as humans performed a task that manipulates two forms of conflict. Although conflict enhanced firing rates, this enhancement did not come from a discrete population of domain-general conflict-encoding neurons, nor from a distinct conflict-encoding response axis. Nor was it the epiphenomenal consequence of simultaneous coactivation of action plans. Instead, conflict amplified the task-relevant information encoded across the neuronal population. Effects of conflict were weaker and more heterogeneous in the dorsolateral prefrontal cortex (dlPFC), suggesting that dACCs role in conflict processing may be somewhat specialized. Overall, these results support the theory that conflict biases competition between sensorimotor transformation processes occurring in dACC.

neuroscience↗