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Oncometabolites Analysis Service

Unlock cancer metabolic reprogramming with a targeted oncometabolite LC–MS/MS service built for mechanistic studies. Our panel quantifies core oncometabolites and central-carbon nodes, including validated chiral separation of D- and L-2-hydroxyglutarate (2-HG) to distinguish IDH-driven D-2-HG from hypoxia-associated L-2-HG in complex tumor microenvironments.

Designed for studies involving IDH1/2, SDH, or FH alterations, we provide absolute quantification for key targets using calibration curves and isotope-labeled internal standards, with optional ¹³C-tracer workflows for mass isotopologue distribution (MID) reporting (RUO).

Key Advantages:

  • Chiral Specificity: Baseline separation of oncogenic D-2-HG from hypoxia-induced L-2-HG using specialized columns.
  • Pathway Depth: Quantify 50+ targets including labile intermediates (Succinate, Fumarate, OAA) often lost in standard panels.
  • High Sensitivity: Reliable detection of trace oncometabolites in limited samples (<106 cells) or interstitial fluids.
  • Flux Ready: Seamlessly upgrade from static concentration to metabolic flux analysis with ¹³C-tracers.
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What is Oncometabolites Analysis and Why It Matters?

Oncometabolites Analysis is a specialized Targeted Metabolomics approach designed to quantify specific metabolites that accumulate to supraphysiological levels due to cancer-associated mutations (e.g., IDH1/2, SDH, FH) or enzyme dysregulation.

Unlike general metabolic profiling, this service focuses on absolute quantification and chiral separation of molecules that directly drive tumorigenesis, epigenetic remodeling, and immune suppression. It is the gold standard for confirming whether a genetic mutation (e.g., IDH1 R132H) translates into a functional metabolic phenotype (e.g., D-2-HG production).

Overcoming Key Challenges in Cancer Metabolism Research

Resolving Isomer Ambiguity (D- vs L-2-HG)

Challenge: Standard LC-MS methods cannot distinguish oncogenic D-2-HG (from IDH mutations) from L-2-HG (produced under hypoxia/acidosis), leading to false positives.

Solution: We employ validated chiral chromatography to achieve baseline separation of enantiomers, ensuring your data reflects true mutation status, not just hypoxic stress.

Capturing Labile Pathway Intermediates

Challenge: Critical TCA intermediates like Succinate, Fumarate, and Oxaloacetate turn over rapidly and degrade within seconds of sampling.

Solution: Our protocol includes optimized quenching steps and cold-chain extraction with isotope-labeled internal standards to "freeze" the metabolic state instantly.

Profiling the Heterogeneous TME

Challenge: Tumors are spatially heterogeneous; obtaining signal from necrotic cores or interstitial fluid is technically demanding.

Solution: We offer high-sensitivity assays validated for complex matrices, including 3D spheroids, organoids, and scarce Tumor Interstitial Fluid (TIF).

Service Scope: Targeted Quantification and Optional Flux Analysis

We provide a modular workflow aligned to your study stage, sample type, and pathway hypothesis:

  • Targeted Oncometabolite Quantification: Absolute or relative quantification for selected targets (e.g., 2-HG, lactate/pyruvate, TCA intermediates) using calibration curves with internal standards (target-dependent).
  • Chiral 2-HG Resolution Assay: Dedicated chiral LC–MS/MS workflow to quantify D-2-HG and L-2-HG and report the D/L balance.
  • Optional Metabolic Flux Analysis (MFA): Add ¹³C-glucose or ¹³C-glutamine tracing and quantify mass isotopologue distributions (MID) to support pathway activity interpretation (see Metabolic Flux Analysis Service).
  • Tumor Microenvironment (TME) Metabolic Nodes: Quantify key TME-relevant nodes, including nutrient utilization (e.g., glucose/glutamine) and secretion readouts (e.g., lactate/pyruvate). Kynurenine/tryptophan modules are available as optional add-ons.

Analyte Coverage: Core Oncometabolites and Central Carbon Nodes

Our panel covers core cancer-relevant metabolites, with optional pathway and cofactor add-ons depending on study design and extraction requirements.

Metabolite Class Representative Analytes Research Relevance Availability Notes
Oncometabolites D-2-HG, L-2-HG Mechanism-focused readout for IDH-associated metabolic rewiring Core (chiral separation supported)
TCA Cycle Intermediates Citrate, isocitrate, α-KG, succinate, fumarate, malate, oxaloacetate* Central carbon status; SDH/FH-linked accumulation patterns Core, some labile targets are method-dependent
Glycolysis / Warburg Nodes Glucose, G6P, pyruvate, lactate Aerobic glycolysis readouts and carbon routing Core (matrix-dependent)
Anaplerotic Amino Acids Glutamine, glutamate, aspartate, serine, glycine TCA replenishment and carbon/nitrogen balance Core / Optional (panel configuration)
Energy & Redox Cofactors NAD+, NADH, NADPH, ATP, ADP Energy/redox status Optional add-on (requires specific extraction protocol)

*Note: Final target list is confirmed at project setup and reported in the methods appendix.

Why Choose Our Oncometabolites Profiling Service?

  • True Chiral Precision: We don't just measure "Total 2-HG." We separate D- and L-forms to confirm IDH mutation status versus general hypoxic response, a distinction critical for high-impact publications.
  • Absolute Quantification Standard: We utilize isotope-labeled internal standards (e.g., 13C5-2-HG, 13C4-Succinate) for every class, providing concrete concentration data (e.g., μM or ng/mg) rather than relative peak areas.
  • Broad Dynamic Range: Our methods are optimized to quantify metabolites across 4-5 orders of magnitude, accurately measuring both trace intracellular signals and high-abundance media nutrients in a single run.
  • Flux-Ready Platform: Our methods are inherently compatible with stable isotope tracers. You can upgrade any study from "static pool size" to "dynamic flux" without changing the core analytical platform.

Project Workflow: Step-by-Step Analysis

1

Study Consultation

Define targets (e.g., IDH, Warburg), sample types, and whether flux labeling is required.

2

Sample Collection

Guidance on standardized quenching protocols (e.g., liquid N2 flash freezing) to preserve unstable metabolites.

3

Metabolite Extraction

Optimized cold organic extraction spiked with isotope-labeled internal standards to correct for recovery losses.

4

LC-MS/MS Acquisition

Targeted quantitation is performed via LC–MRM on Sciex QTRAP platforms, with optional high-resolution accurate-mass confirmation and isotopologue analysis on Thermo Orbitrap systems.

5

Data Processing

Rigorous peak integration, chiral resolution verification, and quantification calculation.

6

Comprehensive Reporting

Final report includes standard curves, QC performance data, and biological visualization plots.

Vertical workflow diagram for targeted oncometabolomics: quenching, isotope-labeled extraction, LC–MRM, QC, reporting.

Stepwise oncometabolite workflow from study design and quenching to isotope-dilution LC–MS/MS, data processing, and reporting.

Analytical Platforms & Quality Control Standards

We utilize industry-leading instrumentation to ensure data integrity and reproducibility.

Instrumentation:

  • Sciex QTRAP 6500+: Selected for its unmatched sensitivity in targeted quantitation (MRM mode), ideal for low-abundance oncometabolites.
  • Thermo Orbitrap Exploris 480: Used for high-resolution confirmation and complex flux analysis (mass isotopologue distribution).

Quality Control Specs:

  • Linearity: Calibration curves with R2 ≥ 0.99 for all quantified analytes.
  • Precision: Technical replicate RSD < 15% for quality control samples.
  • Carryover: Strict blank monitoring between samples to prevent cross-contamination.

Sample Types & Submission Requirements

Sample Type Recommended Input Preparation & Shipping Notes
Cell Pellet / Cell Lysate ~0.5–2 × 106 cells (typical) Remove media quickly; rinse briefly if needed; quench/freeze immediately. Avoid repeated freeze–thaw. For adherent cells, plate-quenching is acceptable if applied consistently. Ship on dry ice (sealed tubes + secondary containment).
Tumor Tissue / Biopsy ~10–30 mg (typical) Minimize ischemia time; snap-freeze as quickly as possible. Record tissue weight and handling time. Avoid thawing during aliquoting—prepare multiple frozen pieces if needed. Ship on dry ice (labeled cryovials).
Plasma / Serum ~100–200 µL (typical) Separate plasma/serum promptly after collection; avoid hemolysis when possible. Record tube type and processing time. Aliquot to reduce freeze–thaw cycles. Ship on dry ice (leak-proof vials).
Culture Media (Spent / Baseline) ~100–300 µL (typical) Collect at defined time points; clarify by brief centrifugation if needed. Provide matching blank media controls when possible (same formulation). Ship on dry ice.
Tumor Interstitial Fluid (TIF) / Low-Input Fluids As available Keep cold during collection; freeze immediately. Note collection method and volume. Low-input feasibility is matrix-dependent—consult prior to shipment. Ship on dry ice.

Packaging checklist: Dry ice in an insulated container; sample inventory sheet; clearly labeled tubes; secondary containment to prevent leakage.

Deliverables: Publication-Ready Data Package

We provide a comprehensive data package designed for direct inclusion in manuscripts.

Data Report:

  • Concentration tables (Excel/CSV).
  • Calibration curve parameters and QC performance report.

Representative Data Visualization:

  • Chiral 2-HG Chromatogram: Baseline separation of D- and L-2-Hydroxyglutarate.
  • Differential Volcano Plot: Identifying significant metabolic shifts in mutant tumors.
  • TCA Cycle Heatmap: Visualizing metabolic bottlenecks in the TCA cycle.
  • Drug Response Bar Chart: Assessing drug efficacy on oncometabolite levels.

(Need advanced data interpretation? See our Metabolomics Data Analysis services).

Chiral LC–MS/MS chromatogram showing baseline separation of D-2-HG and L-2-HG for IDH mutation studies.

Chiral LC–MS/MS resolves D-2-HG from L-2-HG, enabling confident IDH-associated oncometabolite readouts.

Validation figure for isotope-dilution LC–MS/MS: calibration curve, QC precision (RSD), and carryover blank check.

Isotope-dilution LC–MS/MS delivers absolute quantification with linear calibration, tight precision, and carryover control.

Heatmap of TCA and glycolysis metabolites across WT, IDH/SDH/FH models, highlighting oncometabolic signatures.

Central carbon profiling reveals mutation-linked TCA signatures, capturing succinate/fumarate shifts and glycolysis nodes.

13C-glucose tracing figure with MID stacked bars for TCA metabolites, showing altered labeling patterns after treatment.

13C-glucose tracing MID reports pathway activity, linking glycolysis-to-TCA carbon flow with flux-ready evidence.

Applications in Oncology Research

IDH Mutation Verification

Distinguishing IDH-mutant tumors by quantifying the specific accumulation of D-2-HG relative to L-2-HG and α-KG to confirm functional mutation status.

TCA Cycle Dysregulation

Detecting "orphan" metabolite accumulation (e.g., Succinate, Fumarate) in hereditary cancers caused by SDH or FH deficiency, or identifying breaks in the Krebs cycle.

Immunometabolism (TME)

Mapping the "nutrient tug-of-war" (Glucose/Lactate/Arginine) between tumor cells and T-cells to understand how metabolic exhaustion drives immune evasion.

Oncometabolite-Driven Epigenetics

Investigating how high levels of 2-HG, Succinate, or Fumarate competitively inhibit α-KG-dependent dioxygenases (e.g., TETs, KDMs), leading to DNA and histone hypermethylation.

Therapy Resistance Mechanisms

Uncovering metabolic adaptations (e.g., a shift from Glycolysis to OXPHOS, or reliance on Glutaminolysis) that enable tumor cells to survive chemotherapy or targeted inhibition.

Metastasis & EMT Profiling

Tracking metabolic signatures associated with Epithelial-to-Mesenchymal Transition (EMT), such as Fumarate accumulation, which promotes invasion and colonization of distant niches.

Can you distinguish between D-2-HG and L-2-HG?

Yes. We use specialized chiral chromatography columns to achieve baseline separation of the two enantiomers. This is critical because L-2-HG can be produced under hypoxia in wild-type cells, whereas D-2-HG is the specific marker for IDH mutations.

What is the difference between this panel and general targeted metabolomics?

This panel is specifically optimized for cancer-associated metabolites. It utilizes extraction protocols that prioritize the stability of TCA intermediates (like Oxaloacetate) and includes isomer separation (D/L-2-HG) that general panels typically lack.

Can I add isotope tracing (Flux) to this panel?

Yes. Our platform is fully compatible with ¹³C-Glucose or ¹³C-Glutamine tracers. We can report mass isotopologue distributions (MIDs) to tell you not just the concentration, but the metabolic rate (flux) through the TCA cycle.

Do you provide absolute concentration values?

Yes. For the key oncometabolites, we use isotope-labeled internal standards to construct standard curves. This allows us to report absolute quantification (e.g., ng/mL or pmol/cell), which is essential for comparing results across different studies or batches.

Is this service suitable for drug screening?

Absolutely. It is widely used to determine the IC50 of metabolic inhibitors (e.g., IDH1 inhibitors, Glutaminase inhibitors) by measuring the dose-dependent reduction of specific oncometabolites in cell or animal models.

Can you detect trace oncometabolites in limited samples like tumor spheroids or interstitial fluid?

Yes. Our platform utilizes high-sensitivity instruments (e.g., Sciex 6500+) optimized for low-input samples. We can reliably quantify metabolites from as few as 106 cells or small volumes of Tumor Interstitial Fluid (TIF), making it ideal for rare samples or 3D models.

Macrophage-Associated Lipin-1 Promotes β-Oxidation in Response to Proresolving Stimuli

Schilke, R. M., Blackburn, C. M. R., Rao, S., Krzywanski, D. M., Finck, B. N., & Woolard, M. D.

Journal: ImmunoHorizons

Year: 2020

DOI: https://doi.org/10.4049/immunohorizons.2000047

YAP mediates compensatory cardiac hypertrophy through aerobic glycolysis

Kashihara, T., Mukai, R., Oka, S. I., Zhai, P., Nakada, Y., Yang, Z., ... & Sadoshima, J.

Journal: The Journal of Clinical Investigation

Year: 2022

DOI: https://doi.org/10.1172/JCI150595

The Mechanism of Action of a New Class of Nucleoside Analogues Targeting Gastrointestinal Tumours

Collins, L.

Journal: University of Ottawa (Thesis)

Year: 2019

DOI: https://ruor.uottawa.ca/bitstream/10393/38845/3/Collins_Laura_2019_thesis.pdf

A personalized probabilistic approach to ovarian cancer diagnostics based on serum metabolic profiles

Ban, D., Housley, S. N., Matyunina, L. V., McDonald, L. D., Bae-Jump, V. L., Benigno, B. B., ... & McDonald, J. F.

Journal: Gynecologic Oncology

Year: 2024

DOI: https://doi.org/10.1016/j.ygyno.2023.12.030

MS CETSA deep functional proteomics uncovers DNA repair programs leading to gemcitabine resistance

Nordlund, P., Liang, Y. Y., Khalid, K., Van Le, H., Teo, H. M., Raitelaitis, M., ... & Prabhu, N.

Journal: Research Square (Preprint)

Year: 2024

DOI: https://doi.org/10.21203/rs.3.rs-4820265/v1

For Research Use Only. Not for use in diagnostic procedures.
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