Evidence map›Paper›PMID 24280026›Full record

ArticleCancer & metabolism2013

Monitoring metabolic responses to chemotherapy in single cells and tumors using nanostructure-initiator mass spectrometry (NIMS) imaging.

Peter J O'Brien, Michelle Lee, Mary E Spilker, Cathy C Zhang, Zhengming Yan, Timothy C Nichols, Wenlin Li, Caroline H Johnson, Gary J Patti, Gary Siuzdak

Open access · goldAbstract read
In one paragraph

Article in Cancer & metabolism, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
23citing papers in PubMed, 1 pooled it
3.2field-weighted citation impact, top 8% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

23 citing papers in PubMed, 1 synthesis or guideline pooled it, 49 citations in OpenAlex.

  1. Molecular imaging of bacterial biofilms-a systematic review.Critical reviews in microbiology · 2024
    Pooled it
  2. Metabolomics of healthy hematopoietic stem cells and leukemic stem cells.Journal of clinical and translational research · 2025
    Article
  3. Review
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  7. Article
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  10. The Application of Single-Cell Technologies in Cardiovascular Research.Frontiers in cell and developmental biology · 2021
    Review
  11. Review
  12. Review
  13. Applications of metabolomics to study cancer metabolism.Biochimica et biophysica acta. Reviews on cancer · 2018
    Review
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors at 3 institutions in 1 country.

Peter J O'BrienPfizer Worldwide Research and Development, La Jolla Laboratories, La Jolla, CA, USA. peter.obrien2@pfizer.com.
Michelle Lee
Mary E Spilker
Cathy C Zhang
Zhengming Yan
Timothy C Nichols
Wenlin Li
Caroline H Johnson
Gary J Patti
Gary Siuzdak
Pfizer (United States) · USScripps (United States) · USWashington University in St. Louis · US

Funding

Normalizing Breast Cancer Metabolism to Prevent Progression and Recurrence (PQ21)R01CA170737 · NCI · SCRIPPS RESEARCH INSTITUTE, THE · PI FELDING, BRUNIE H. · 2012 to 2015
$2.1M
DEVELOPING THE UNTARGETED METABOLOMIC WORKFLOW FOR HIGH-THROUGHPUT ANALYSESR01ES022181 · NIEHS · WASHINGTON UNIVERSITY · PI PATTI, GARY J · 2012 to 2016
$1.8M
NCI NIH HHS R01 CA170737NIEHS NIH HHS R01 ES022181
6 · The paper itself

Abstract

backgroundTissue imaging of treatment-induced metabolic changes is useful for optimizing cancer therapies, but commonly used methods require trade-offs between assay sensitivity and spatial resolution. Nanostructure-Initiator Mass Spectrometry imaging (NIMS) permits quantitative co-localization of drugs and treatment response biomarkers in cells and tissues with relatively high resolution. The present feasibility studies use NIMS to monitor phosphorylation of 3'-deoxy-3'-fluorothymidine (FLT) to FLT-MP in lymphoma cells and solid tumors as an indicator of drug exposure and pharmacodynamic responses.

methodsNIMS analytical sensitivity and spatial resolution were examined in cultured Burkitt's lymphoma cells treated briefly with Rapamycin or FLT. Sample aliquots were dispersed on NIMS surfaces for single cell imaging and metabolic profiling, or extracted in parallel for LC-MS/MS analysis. Docetaxel-induced changes in FLT metabolism were also monitored in tissues and tissue extracts from mice bearing drug-sensitive tumor xenografts. To correct for variations in FLT disposition, the ratio of FLT-MP to FLT was used as a measure of TK1 thymidine kinase activity in NIMS images. TK1 and tumor-specific luciferase were measured in adjacent tissue sections using immuno-fluorescence microscopy.

resultsNIMS and LC-MS/MS yielded consistent results. FLT, FLT-MP, and Rapamycin were readily detected at the single cell level using NIMS. Rapid changes in endogenous metabolism were detected in drug-treated cells, and rapid accumulation of FLT-MP was seen in most, but not all imaged cells. FLT-MP accumulation in xenograft tumors was shown to be sensitive to Docetaxel treatment, and TK1 immunoreactivity co-localized with tumor-specific antigens in xenograft tumors, supporting a role for xenograft-derived TK1 activity in tumor FLT metabolism.

conclusionsNIMS is suitable for monitoring drug exposure and metabolite biotransformation with essentially single cell resolution, and provides new spatial and functional dimensions to studies of cancer metabolism without the need for radiotracers or tissue extraction. These findings should prove useful for in vitro and pre-clinical studies of cancer metabolism, and aid the optimization of metabolism-based cancer therapies and diagnostics.

Identifiers

PMID24280026
PMCPMC3834492
OpenAlexW2152997281

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.