Evidence map›Paper›PMID 33806757›Full record

ArticleCancers2021

Tracking the Progression of Triple Negative Mammary Tumors over Time by Chemometric Analysis of Urinary Volatile Organic Compounds.

Mark Woollam, Luqi Wang, Paul Grocki, Shengzhi Liu, Amanda P Siegel, Maitri Kalra, John V Goodpaster, Hiroki Yokota, Mangilal Agarwal

Open access · goldAbstract read
In one paragraph

Article in Cancers, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
1.3field-weighted citation impact, top 23% 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

9 citing papers in PubMed, 20 citations in OpenAlex.

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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

9 authors at 2 institutions in 1 country.

Mark WoollamDepartment of Chemistry and Chemical Biology, Indiana University-Purdue University, Indianapolis, IN 46202, USA.
Luqi WangIntegrated Nanosystems Development Institute, Indiana University-Purdue University, Indianapolis, IN 46202, USA.
Paul GrockiDepartment of Chemistry and Chemical Biology, Indiana University-Purdue University, Indianapolis, IN 46202, USA.
Shengzhi LiuIntegrated Nanosystems Development Institute, Indiana University-Purdue University, Indianapolis, IN 46202, USA.
Amanda P SiegelDepartment of Chemistry and Chemical Biology, Indiana University-Purdue University, Indianapolis, IN 46202, USA.
Maitri KalraHematology and Oncology, Ball Memorial Hospital, Indiana University Health, Muncie, IN 47303, USA.
John V GoodpasterDepartment of Chemistry and Chemical Biology, Indiana University-Purdue University, Indianapolis, IN 46202, USA.
Hiroki YokotaIntegrated Nanosystems Development Institute, Indiana University-Purdue University, Indianapolis, IN 46202, USA.ORCID 0000-0002-7881-8959
Mangilal AgarwalDepartment of Chemistry and Chemical Biology, Indiana University-Purdue University, Indianapolis, IN 46202, USA.
Indiana University – Purdue University Indianapolis · USIndiana University Health · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Previous studies have shown that volatile organic compounds (VOCs) are potential biomarkers of breast cancer. An unanswered question is how urinary VOCs change over time as tumors progress. To explore this, BALB/c mice were injected with 4T1.2 triple negative murine tumor cells in the tibia. This typically causes tumor progression and osteolysis in 1-2 weeks. Samples were collected prior to tumor injection and from days 2-19. Samples were analyzed by headspace solid phase microextraction coupled to gas chromatography-mass spectrometry. Univariate analysis identified VOCs that were biomarkers for breast cancer; some of these varied significantly over time and others did not. Principal component analysis was used to distinguish Cancer (all Weeks) from Control and Cancer Week 1 from Cancer Week 3 with over 90% accuracy. Forward feature selection and linear discriminant analysis identified a unique panel that could identify tumor presence with 94% accuracy and distinguish progression (Cancer Week 1 from Cancer Week 3) with 97% accuracy. Principal component regression analysis also demonstrated that a VOC panel could predict number of days since tumor injection (

Indexed as

breast cancer biomarkersgas chromatography (GC)headspace solid phase microextraction (HS-SPME)linear discriminant analysis (LDA)mass spectrometry (MS)principal component analysis (PCA)principal component regression (PCR)volatile organic compounds (VOCs)

Identifiers

PMID33806757
PMCPMC8004946
OpenAlexW3137434041

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.