Episode 70: AIMS vs. LC-MS for Cancer Diagnostics: ccRCC Metabolomics with Rachel Wood | Queen's University episode artwork

EPISODE · Jul 20, 2026 · 23 MIN

Episode 70: AIMS vs. LC-MS for Cancer Diagnostics: ccRCC Metabolomics with Rachel Wood | Queen's University

from Concentrating on Chromatography · host David Oliva

What if you could assess a tumor's metastatic potential — without extensive sample prep — directly from tissue? Rachel Wood is working on exactly that.Rachel Wood is a PhD candidate at Queen's University (Kingston, Ontario), working jointly in the labs of Dr. Richard Oleschuk (Chemistry) and Dr. Chris Nicoll (Pathology & Molecular Medicine). Her research applies Ambient Ionization Mass Spectrometry — specifically the Liquid Microjunction Surface Sampling Probe (LMJ-SSP) and Desorption Electrospray Ionization (DESI) — to profile the metabolomics of non-metastatic and metastatic clear cell Renal Cell Carcinoma (ccRCC) cell lines. The long-term goal: a rapid, minimally invasive MS-based prognostic tool for kidney cancer.This is the first reported use of LMJ-SSP to assess metastatic status in ccRCC — and early PCA results are already showing distinct separation between cell line profiles.In this episode, David and Rachel cover:→ Why ccRCC is such a resistant biomarker problem despite active genomic, proteomic, and metabolomic research→ The clinical stakes of "diagnosed by accident" — and what a prognostic biomarker actually needs to do for a clinician→ How AIMS complements (not replaces) LC-MS in a discovery-phase cancer workflow→ LMJ-SSP vs. DESI: what each technique sees that the other misses, including spatial resolution differences (~1mm vs. ~50µm)→ Why Rachel runs LMJ-SSP on both a triple quad and a Q-TOF — and what each instrument contributes to the same research question→ How her lab repurposed a 3D printer as a custom automated XYZ sampling stage with 50µm movement precision→ Managing high-dimensional metabolomics data across two polarities, two cell lines, and two mass analyzers — the pipeline explained→ What unsupervised machine learning (PCA) showed in early results→ The path from cell lines to excised tumor tissue to, ultimately, liquid biopsies→ Advice for analytical chemists considering work at the chemistry–oncology interface🔗 CONNECT WITH RACHEL WOODLinkedIn: https://www.linkedin.com/in/rachel-wood-7b64492a2/Queen's University – Oleschuk Lab: https://oleschuklab.ca/📬 CONCENTRATING ON CHROMATOGRAPHYWebsite: https://concentratingonchromatography.com/Organomation: https://www.organomation.com🔬 ABOUT ORGANOMATIONOrganomation manufactures nitrogen blowdown evaporators, nitrogen generators, and sample concentration instruments for analytical laboratories worldwide#MassSpectrometry #AmbientIonization #Metabolomics #KidneyCancer #ccRCC #DESI #AIMS #CancerResearch #AnalyticalChemistry #Chromatography #Biomarkers #LiquidBiopsy #ReanalCellCarcinoma #MachineLearning #PCA #LabScience #GradSchool #Queen'sUniversity #Oncology #SamplePreparation

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Episode 70: AIMS vs. LC-MS for Cancer Diagnostics: ccRCC Metabolomics with Rachel Wood | Queen's University

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