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🧪 Clinical Proteomics & Metabolomics Track 4 Workshop Days • 12 Modular Chapters LC-MS/MS • Orbitrap DDA/DIA • MSFragger LFQ • XCMS • PLS-DA • Skyline MRM/PRM
• Mass Spectrometry • Untargeted Metabolomics • Machine Learning Panels • Targeted MRM/PRM • WHO CNS5 Glioma

Clinical Proteomics & Metabolomics in Precision Oncology: LC-MS/MS Biomarker Discovery, Machine Learning Panels & Targeted MRM/PRM Validation

End-to-End High-Resolution Mass Spectrometry: DDA/DIA Discovery, Label-Free Quantification, Metabolite Peak Alignment, PLS-DA/Random Forest Classification, Skyline Targeted Assay Design & WHO CNS5 Brain Tumor Translation

Bridge functional biochemistry and clinical decision-making. Move beyond genomic DNA variants into active proteomic phenotypes and metabolic rewiring. Master high-resolution Orbitrap and Q-TOF mass spectrometry, execute discovery workflows across Data-Dependent (DDA) and Data-Independent (DIA) acquisition, compute rigorous peptide-spectrum match FDRs and Label-Free Quantification (LFQ) via MSFragger and Philosopher, align untargeted metabolic features with XCMS 3, engineer machine learning classification panels using PLS-DA and Random Forests with nested cross-validation, design targeted MRM/PRM assays in Skyline, and navigate FDA/CLIA regulatory pathways (LDT vs. IVD) anchored in a 2021 WHO CNS5 Adult-Type Diffuse Glioma clinical benchmark.

Start Day 1 Module 1 → Precision Cancer Genomics (MTB) → Long-Read Genomics & SVs → 12 Comprehensive Modules • Day 1 to Day 4 • Open Access

🧠 Three Translational Pillars: From Discovery Mass Spec to Clinical Bedside

Translational Oncology Pipeline
Pillar 1 • Molecular Stratification

WHO CNS5 Glioma Integrated Subtyping

Integrating proteomic phosphorylation signatures and metabolomic D-2-hydroxyglutarate (D-2HG) accumulation to classify Astrocytoma IDH-mutant, Oligodendroglioma 1p/19q-codeleted, and Glioblastoma IDH-wildtype.

Pillar 2 • Targeted Assay Design

Skyline MRM & PRM Multiplex Verification

Transitioning from untargeted discovery into targeted clinical assays: transition selection, heavy isotope-labeled internal standards (AQUA), collision energy optimization, and lower limit of quantification (LLOQ) validation.

Pillar 3 • Regulatory Translation

LDT vs. IVD & Molecular Tumor Board

Overcoming pre-analytical cold ischemia drift, achieving CLIA/CAP analytical validity (precision, linearity, recovery), and synthesizing multi-omics findings into actionable molecular tumor board recommendations.

12 Modular Curriculum Chapters

Comprehensive practical manuals covering Orbitrap DDA/DIA mass spec, MSFragger LFQ, XCMS 3 metabolomics, machine learning biomarker panels, Skyline targeted PRM/MRM, and WHO CNS5 translation.

12 Hands-On Modules
Module 1 Day 1 • Molecular Discovery

Module 1: Beyond the Genome: The Functional Proteome, Metabolome & PTM Landscape in Oncology

Biological rationale for clinical mass spectrometry: why genomic DNA mutations alone fail to predict phenotype, kinase post-translational modifications (PTMs), oncometabolites, Warburg rewiring, and intratumoral heterogeneity.

Explore Module 1 →
Module 2 Day 1 • Instrumentation

Module 2: Clinical Mass Spectrometry Foundations: LC-MS/MS Instrumentation, Orbitraps & DDA vs. DIA

Principles of high-resolution mass spectrometry: nanoflow electrospray ionization (nanoESI), quadrupole mass filters, Orbitrap and Time-of-Flight (TOF) analyzers, and Data-Dependent Acquisition (DDA) vs. Data-Independent Acquisition (DIA/SWATH).

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Module 3 Day 1 • Clinical Case Study

Module 3: Clinical Study Design, Biospecimen Quality Control & WHO CNS5 Brain Tumor Cohort Mapping

Pre-analytical biospecimen variables in translational oncology: cold ischemia impact, freeze-thaw cycles, biobanking SOPs, and the 2021 WHO CNS5 classification of adult-type diffuse gliomas.

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Module 4 Day 2 • Proteomics Discovery

Module 4: Proteomics Identification & Quantification: Database Searching, Target-Decoy FDR & LFQ

Computational identification of peptide spectra: cross-correlation scoring, false discovery rate (FDR) target-decoy benchmarking, protein parsimony inference, and label-free quantification (LFQ).

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Module 5 Day 2 • Metabolomics Discovery

Module 5: Untargeted Metabolomics Processing: Peak Picking, Alignment & MSI Spectral Identification

High-throughput untargeted metabolomics data processing: XCMS feature detection, retention time alignment, adduct deconvolution, and Metabolomics Standards Initiative (MSI) confidence levels.

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Module 6 Day 2 • Statistical Prioritization

Module 6: Statistical Preprocessing & Cancer Signatures: Imputation, ComBat & Volcano Prioritization

Defensive biostatistics for mass spectrometry: Left-censored missing value imputation, ComBat batch adjustment, linear modeling with limma/MSstats, and pathway enrichment in cancer metabolism.

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Module 7 Day 3 • Candidate Prioritization

Module 7: The Biomarker Attrition Funnel: Translating Discovery Omics Lists into Diagnostic Panels

Overcoming the biomarker translational gap: the clinical attrition funnel from 5,000 discovery features to 5-10 validated markers, biological plausibility filtering, secretome dynamics, and stability assays.

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Module 8 Day 3 • Machine Learning Panels

Module 8: Machine Learning for Biomarker Panels: PLS-DA, Random Forests & Overfitting Prevention

Designing multi-marker clinical classifier panels using supervised machine learning: Partial Least Squares Discriminant Analysis (PLS-DA), Random Forest Boruta selection, nested cross-validation, and ROC/AUC metrics.

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Module 9 Day 3 • Targeted Assays

Module 9: Targeted Mass Spectrometry: SRM/MRM, PRM Assays & Skyline Workspace Design

Transition from discovery to targeted clinical assays: Triple Quadrupole Selected Reaction Monitoring (SRM/MRM), Orbitrap Parallel Reaction Monitoring (PRM), stable isotope-labeled internal standards (SIL/AQUA), and Skyline assay design.

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Module 10 Day 4 • Clinical Validation

Module 10: Analytical & Clinical Validation Rigor: Calibration, LOD/LOQ & Diagnostic PPV/NPV

Rigorous analytical assay qualification following FDA bioanalytical guidelines: standard calibration curves, lower limit of detection (LOD), lower limit of quantification (LOQ), matrix effects, and ROC-derived clinical cut-offs.

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Module 11 Day 4 • Regulatory & Implementation

Module 11: Regulatory Landscapes & Clinical Implementation: LDT vs. IVD, CLIA/CAP & Reimbursement

Navigating clinical adoption: Laboratory Developed Tests (LDTs) under CLIA/CAP vs. FDA In Vitro Diagnostics (IVD), companion diagnostics (CDx) co-development with targeted therapeutics, and health economic CPT coding.

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Module 12 Day 4 • Multi-Omics Synthesis

Module 12: Integrative Multi-Omics Case Studies: WHO CNS5 Glioma Subtyping & Therapy Monitoring

Hands-on clinical synthesis: integrating quantitative D-2-hydroxyglutarate (D-2HG) oncometabolite profiling with targeted IDH1-R132H PRM assays, longitudinal liquid biopsy monitoring, and Molecular Tumor Board reporting.

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