Biology subjects

Gillette, M. A.

Publications and source records attributed to Gillette, M. A..

6 recordsLinked to original sources

bioRxiv2025

Gliomas phenocopy an inborn error of metabolism to drive neuronal activity and tumor growth

The metabolic hallmarks of high-grade glioma (HGG) are not fully understood. Human brain tissue metabolomics revealed that the creatine synthesis pathway intermediate guanidinoacetate (GAA) accumulated [~]100-fold in HGGs relative to controls, which was caused by imbalanced activities of enzymes in this pathway. Glioma cells secreted GAA rather than using it to produce creatine, implicating an unexpected function. GAA accumulates in GAMT deficiency, an inborn error of metabolism, and elevates neuronal excitability. Neuronal excitability is also increased in glioma and drives tumor growth through neuron-glioma interactions. We hypothesized that glioma-generated GAA excites surrounding neurons. Indeed, GAA induced neuronal hyperactivity by activating GABAA receptors and causing depolarizing GABA currents in glioma-associated neurons with dysregulated chloride homeostasis. Depleting tumoral GAA decreased electrochemical activity, neuron-glioma interactions, and tumor aggressiveness. Our findings unveil a new mechanism linking cancer metabolism with cancer neuroscience and leverage human genetics to nominate GAA synthesis as a target in gliomas.

cancer biology↗

bioRxiv2025

Microscaled Cell Surface Proteomics for Cryo-preserved and Tissue Samples

Cell surface proteins (CSPs) regulate key cellular functions and represent valuable targets for diagnostics and therapeutics. Despite advances in proteomic workflows, CSP analysis from cryopreserved or low-input clinical samples remains limited by technical constraints, including reduced membrane integrity, inefficient labeling, and high background. To address these challenges, we optimized and benchmarked two complementary surface enrichment strategies compatible with low-input applications (fewer than 1 million cells) and real-world sample types, including fresh, viably cryopreserved, and dissociated solid tissues. We systematically compared oxidation-based N-glycoprotein capture and WGA-HRP-mediated proximity labeling across a range of input amounts using both solid tumor (A549) and hematologic cancer (KMS-12-BM) cell lines. The N-glycopeptide method yielded superior specificity in low-input contexts, while WGA-HRP captured complementary CSP subsets. Together, the methods identified more than 700 CSPs, with approximately 175 unique identifications per protocol. Both workflows detected dynamic EGFR internalization following EGF stimulation and maintained high reproducibility (Pearson correlation greater than 0.9) between fresh and cryopreserved preparations. To extend these findings to tissue-derived samples, we optimized dissociation protocols for healthy endometrium and applied the N-glycopeptide method to cryopreserved dissociated endometrium from three healthy donors. Enzymatic dissociation enabled accurate CSP profiling from fewer than 1 to 2 million cells. This study provides a systematic comparison of two leading surface proteomics approaches, validates their performance on cryopreserved and low-input specimens, and demonstrates applicability to clinically relevant tissues. Our optimized workflows enable robust surfaceome characterization in translational settings where sample quantity and preservation methods are often limiting, opening new avenues for biomarker discovery and patient stratification.

cell biology↗

bioRxiv2024

High-throughput proteomic and phosphoproteomic analysis of formalin-fixed paraffin-embedded tissue

Formalin-fixed, paraffin-embedded (FFPE) patient tissues are a valuable resource for proteomic studies with the potential to associate the derived molecular insights with clinical annotations and outcomes. Here we present an optimized, partially automated workflow for FFPE proteomics combining pathology-guided macro-dissection, Adaptive Focused Acoustics (AFA) sonication for lysis and decrosslinking, S-Trap digestion to peptides, and liquid chromatography-tandem mass spectrometry (LC-MS/MS) analysis using Orbitrap, Astral or timsTOF HT instrumentation. The workflow enables analysis of up to 96 dissected FFPE tissue samples or 10 {micro}m scrolls, identifying 8,000-10,000 unique proteins per sample with median CVs <20%. Key optimizations include improved tissue lysis strategies, protein quantification for normalization, and peptide cleanup prior to LC-MS/MS analysis. Application to lung adenocarcinoma (LUAD) FFPE blocks confirms the platforms effectiveness in processing complex, clinically relevant samples, achieving deep proteome coverage and quantitative robustness comparable to TMT-based methods. Using the newly released Orbitrap Astral with short, 24-minute gradients, the workflow identifies up to [~]10,000 unique proteins and [~]11,000 localized phosphosites in LUAD FFPE tissue. This high-throughput, scalable workflow advances biomarker discovery and proteomic research in archival tissue samples.

systems biology↗

bioRxiv2021

MONTE enables serial immunopeptidome, ubiquitylome, proteome, phosphoproteome, acetylome analyses of sample-limited tissues

Serial multiomic analyses of proteome, phosphoproteome and acetylome provides functional insights into disease pathology and drug effects while conserving precious human material. To date, ubiquitylome and HLA peptidome analyses have required separate samples for parallel processing each using distinct protocols. Here we present MONTE, a highly-sensitive multi-omic native tissue enrichment workflow that enables serial, deepscale analysis of HLA-I and HLA-II immunopeptidome, ubiquitylome, proteome, phosphoproteome and acetylome from the same tissue samples. We demonstrate the capabilities of MONTE in a proof-of-concept study of primary patient lung adenocarcinoma(LUAD) tumors. Depth of coverage and quantitative precision at each of the omes is not compromised by serialization, and the addition of HLA immunopeptidomics enables identification of putative immunotherapeutic targets such as cancer/testis antigens and neoantigens. MONTE can provide insights into disease-specific changes in antigen presentation, protein expression, protein degradation, cell signaling, cross-talk and epigenetic pathways involved in disease pathology and treatment.

cancer biology↗

bioRxiv2020

Biomarkers to distinguish bacterial from viral pediatric clinical pneumonia in a malaria endemic setting

BACKGROUNDDifferentiating the etiology of acute febrile respiratory illness in children is a challenge in low-income, malaria-endemic settings because the main pathogens responsible (viruses, bacteria, and malaria parasites) overlap in clinical presentation and frequently occur together as mixed infections. The critical task is to rapidly identify bacterial pneumonia to enable appropriate antibiotic treatment, ideally at point of care. Current diagnostic tests are insufficient and there is a need for the discovery and development of new tools. Here we report the identification of a unique biomarker signature that can be identified in blood samples. METHODSBlood samples from 195 pediatric Mozambican patients with clinical pneumonia were analyzed with an aptamer-based high dynamic range assay to quantify [~]1200 proteins. For discovery of new biomarkers, we identified a training set of patient samples in which the underlying etiology of the pneumonia was established as bacterial, viral or malaria. Proteins whose abundances varied significantly between patients with verified etiologies (FDR<0.01) formed the basis for predictive diagnostic models that were created using machine learning techniques (Random Forest, Elastic Net). These models were validated on a dedicated test set of samples. RESULTS219 proteins had significantly different abundances between bacterial and viral infections, and 151 differed between bacterial infections and a mixed pool of viral and malaria infections. Predictive diagnostic models achieved >90% sensitivity and >80% specificity, regardless of whether one or two pathogen classes were present. Bacterial pneumonia was strongly associated with markers of neutrophil activity, in particular neutrophil degranulation. Degranulation markers included HP, LCN2, LTF, MPO, MMP8, PGLYRP1, RETN, SERPINA1, S100A9, and SLPI. CONCLUSIONBlood protein signatures highly associated with neutrophil biology reliably differentiated bacterial pneumonia from other causes. With appropriate technology, these markers could provide the basis for a rapid diagnostic for field-based triage for antibiotic treatment of pediatric pneumonia.

genomics↗

bioRxiv2019

Microscaled Proteogenomic Methods for Precision Oncology

Cancer proteogenomics integrates genomics, transcriptomics and mass spectrometry (MS)-based proteomics to gain insights into cancer biology and treatment efficacy. A proteogenomics approach was therefore developed for frozen core biopsies using tissue-sparing specimen processing with a \"microscaled\" proteomics workflow. For technical proof-of-principle, biopsies from ERBB2 positive breast cancers before and 48-72 hours after the first dose of neoadjuvant trastuzumab-based chemotherapy were analyzed. ERBB2 protein and phosphosite levels, as well as mTOR target phosphosites, were significantly more suppressed upon treatment in cases associated with pathological complete response, suggesting MS-based pharmacodynamics is achievable. Furthermore, integrated analyses indicated potential causes of treatment resistance including the absence of ERBB2 amplification (false-ERBB2 positive) and insufficient ERBB2 activity for therapeutic sensitivity despite ERBB2 amplification (pseudo-ERBB2 positive). Candidate resistance features in true-ERBB2+ cases, including androgen receptor signaling, mucin expression and an inactive immune microenvironment were observed. Thus, proteogenomic analysis of needle core biopsies is feasible and clinical utility should be investigated.

cancer biology↗