Evidence map›Paper›PMID 33267867›Full record

Observational studyBreast cancer research : BCR2020

Shotgun proteomics coupled to nanoparticle-based biomarker enrichment reveals a novel panel of extracellular matrix proteins as candidate serum protein biomarkers for early-stage breast cancer detection.

Claudia Fredolini, Khyatiben V Pathak, Luisa Paris, Kristina M Chapple, Kristine A Tsantilas, Matthew Rosenow, Tony J Tegeler, Krystine Garcia-Mansfield, Davide Tamburro, Weidong Zhou and 9 more

Open access · goldAbstract readObservational Study
In one paragraph

Observational study in Breast cancer research : BCR, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.

0numbers the graph read from it
0cells of the map it votes in
20citing papers in PubMed
1.6field-weighted citation impact, top 18% 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

20 citing papers in PubMed, 36 citations in OpenAlex.

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  19. Combinatorial Power of cfDNA, CTCs and EVs in Oncology.Diagnostics (Basel, Switzerland) · 2022
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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

19 authors at 6 institutions in 2 countries.

Claudia FredoliniCenter for Applied Proteomics & Molecular Medicine, George Mason University, Manassas, VA, USA.
Khyatiben V PathakCollaborative Center for Translational Mass Spectrometry, Translational Genomics Research Institute, 445 N 5th St, Phoenix, AZ, 85004, USA.
Luisa ParisCenter for Applied Proteomics & Molecular Medicine, George Mason University, Manassas, VA, USA.
Kristina M ChappleCollaborative Center for Translational Mass Spectrometry, Translational Genomics Research Institute, 445 N 5th St, Phoenix, AZ, 85004, USA.
Kristine A TsantilasCollaborative Center for Translational Mass Spectrometry, Translational Genomics Research Institute, 445 N 5th St, Phoenix, AZ, 85004, USA.
Matthew RosenowCollaborative Center for Translational Mass Spectrometry, Translational Genomics Research Institute, 445 N 5th St, Phoenix, AZ, 85004, USA.
Tony J TegelerCollaborative Center for Translational Mass Spectrometry, Translational Genomics Research Institute, 445 N 5th St, Phoenix, AZ, 85004, USA.
Krystine Garcia-MansfieldCollaborative Center for Translational Mass Spectrometry, Translational Genomics Research Institute, 445 N 5th St, Phoenix, AZ, 85004, USA.
Davide TamburroCenter for Applied Proteomics & Molecular Medicine, George Mason University, Manassas, VA, USA.
Weidong ZhouCenter for Applied Proteomics & Molecular Medicine, George Mason University, Manassas, VA, USA.
Paul RussoCenter for Applied Proteomics & Molecular Medicine, George Mason University, Manassas, VA, USA.
Samuele MassarutDepartment of Surgical Oncology, Centro di Riferimento Oncologico di Aviano (CRO) IRCCS, 33081, Aviano, PN, Italy.
Francesco FacchianoDipartimento di Oncologia e Medicina Molecolare, Istituto Superiore di Sanità, Rome, Italy.
Claudio BellucoDepartment of Surgical Oncology, Centro di Riferimento Oncologico di Aviano (CRO) IRCCS, 33081, Aviano, PN, Italy.
Ruggero De MariaIstituto di Patologia Generale, Università Cattolica del Sacro Cuore, 00168, Rome, Italy.
Enrico GaraciUniversity San Raffaele and Istituto di Ricovero e Cura a Carattere Scientifico San Raffaele, Rome, Italy.
Lance LiottaCenter for Applied Proteomics & Molecular Medicine, George Mason University, Manassas, VA, USA.
Emanuel F PetricoinCenter for Applied Proteomics & Molecular Medicine, George Mason University, Manassas, VA, USA.
Patrick PirrotteCollaborative Center for Translational Mass Spectrometry, Translational Genomics Research Institute, 445 N 5th St, Phoenix, AZ, 85004, USA. ppirrotte@tgen.org.ORCID 0000-0003-1360-6039
George Mason University · USTranslational Genomics Research Institute · USCentro di Riferimento Oncologico · ITIstituti di Ricovero e Cura a Carattere Scientifico · ITIstituto Superiore di Sanità · ITUniversità Cattolica del Sacro Cuore · IT

Funding

Transgenic Mouse FacilityP30CA033572 · NCI · CITY OF HOPE/BECKMAN RESEARCH INSTITUTE · PI XIWEI WU · 1985 to 2026
$86.3M
NCI NIH HHS P30 CA033572
6 · The paper itself

Abstract

backgroundThe lack of specificity and high degree of false positive and false negative rates when using mammographic screening for detecting early-stage breast cancer is a critical issue. Blood-based molecular assays that could be used in adjunct with mammography for increased specificity and sensitivity could have profound clinical impact. Our objective was to discover and independently verify a panel of candidate blood-based biomarkers that could identify the earliest stages of breast cancer and complement current mammographic screening approaches.

methodsWe used affinity hydrogel nanoparticles coupled with LC-MS/MS analysis to enrich and analyze low-abundance proteins in serum samples from 20 patients with invasive ductal carcinoma (IDC) breast cancer and 20 female control individuals with positive mammograms and benign pathology at biopsy. We compared these results to those obtained from five cohorts of individuals diagnosed with cancer in organs other than breast (ovarian, lung, prostate, and colon cancer, as well as melanoma) to establish IDC-specific protein signatures. Twenty-four IDC candidate biomarkers were then verified by multiple reaction monitoring (LC-MRM) in an independent validation cohort of 60 serum samples specifically including earliest-stage breast cancer and benign controls (19 early-stage (T1a) IDC and 41 controls).

resultsIn our discovery set, 56 proteins were increased in the serum samples from IDC patients, and 32 of these proteins were specific to IDC. Verification of a subset of these proteins in an independent cohort of early-stage T1a breast cancer yielded a panel of 4 proteins, ITGA2B (integrin subunit alpha IIb), FLNA (Filamin A), RAP1A (Ras-associated protein-1A), and TLN-1 (Talin-1), which classified breast cancer patients with 100% sensitivity and 85% specificity (AUC of 0.93).

conclusionsUsing a nanoparticle-based protein enrichment technology, we identified and verified a highly specific and sensitive protein signature indicative of early-stage breast cancer with no false positives when assessing benign and inflammatory controls. These markers have been previously reported in cell-ECM interaction and tumor microenvironment biology. Further studies with larger cohorts are needed to evaluate whether this biomarker panel improves the positive predictive value of mammography for breast cancer detection.

Indexed as

AdultAgedBiomarkers, TumorBiopsyBreastBreast NeoplasmsCarcinoma, Ductal, BreastCase-Control StudiesCohort StudiesEarly Detection of CancerExtracellular Matrix ProteinsFemaleHumansMaleMammographyMiddle AgedBiomarkers, TumorExtracellular Matrix ProteinsInvasive ductal carcinomaMammographyMultiple reaction monitoringNanoparticlesProtein enrichmentSerum

Identifiers

PMID33267867
PMCPMC7709252
OpenAlexW3110232732

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

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.