Evidence map›Paper›PMID 27381847›Full record

ArticleTechnology in cancer research & treatment2017

Label-Free Raman Imaging to Monitor Breast Tumor Signatures.

Felicia S Manciu, John D Ciubuc, Karla Parra, Marian Manciu, Kevin E Bennet, Paloma Valenzuela, Emma M Sundin, William G Durrer, Luis Reza, Giulio Francia

Open access · greenAbstract read
In one paragraph

Article in Technology in cancer research & treatment, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
4.0field-weighted citation impact, top 7% 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

13 citing papers in PubMed, 29 citations in OpenAlex.

  1. Identifying Molecular Changes inDiagnostics (Basel, Switzerland) · 2025
    Article
  2. Article
  3. Article
  4. Article
  5. Assessment of Drug Activities againstPathogens (Basel, Switzerland) · 2024
    Article
  6. Article
  7. Article
  8. Article
  9. Review
  10. Article
  11. Article
  12. Review
  13. Article
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 2 institutions in 1 country.

Felicia S Manciu1 Department of Physics, University of Texas at El Paso, El Paso, TX, USA.
John D Ciubuc1 Department of Physics, University of Texas at El Paso, El Paso, TX, USA.
Karla Parra3 Department of Biological Sciences, University of Texas at El Paso, El Paso, TX, USA.
Marian Manciu1 Department of Physics, University of Texas at El Paso, El Paso, TX, USA.
Kevin E Bennet4 Division of Engineering, Mayo Clinic, Rochester, MN, USA.
Paloma Valenzuela3 Department of Biological Sciences, University of Texas at El Paso, El Paso, TX, USA.
Emma M Sundin1 Department of Physics, University of Texas at El Paso, El Paso, TX, USA.
William G Durrer1 Department of Physics, University of Texas at El Paso, El Paso, TX, USA.
Luis Reza1 Department of Physics, University of Texas at El Paso, El Paso, TX, USA.
Giulio Francia2 Border Biomedical Research Center, University of Texas at El Paso, El Paso, TX, USA.
The University of Texas at El Paso · USMayo Clinic · US

Funding

TCCG12MD007592 · NIMHD · UNIVERSITY OF TEXAS EL PASO · PI KIRKEN, ROBERT A. · 2012 to 2018
$19.4M
RISE Scholars Program at UTEPR25GM069621 · NIGMS · UNIVERSITY OF TEXAS EL PASO · PI AGUILERA, RENATO J · 2004 to 2021
$11.2M
NIGMS NIH HHS R25 GM069621NIMHD NIH HHS G12 MD007592
6 · The paper itself

Abstract

Although not yet ready for clinical application, methods based on Raman spectroscopy have shown significant potential in identifying, characterizing, and discriminating between noncancerous and cancerous specimens. Real-time and accurate medical diagnosis achievable through this vibrational optical method largely benefits from improvements in current technological and software capabilities. Not only is the acquisition of spectral information now possible in milliseconds and analysis of hundreds of thousands of data points achieved in minutes, but Raman spectroscopy also allows simultaneous detection and monitoring of several biological components. Besides demonstrating a significant Raman signature distinction between nontumorigenic (MCF-10A) and tumorigenic (MCF-7) breast epithelial cells, our study demonstrates that Raman can be used as a label-free method to evaluate epidermal growth factor activity in tumor cells. Comparative Raman profiles and images of specimens in the presence or absence of epidermal growth factor show important differences in regions attributed to lipid, protein, and nucleic acid vibrations. The occurrence, which is dependent on the presence of epidermal growth factor, of new Raman features associated with the appearance of phosphothreonine and phosphoserine residues reflects a signal transduction from the membrane to the nucleus, with concomitant modification of DNA/RNA structural characteristics. Parallel Western blotting analysis reveals an epidermal growth factor induction of phosphorylated Akt protein, corroborating the Raman results. The analysis presented in this work is an important step toward Raman-based evaluation of biological activity of epidermal growth factor receptors on the surfaces of breast cancer cells. With the ultimate future goal of clinically implementing Raman-guided techniques for the diagnosis of breast tumors (e.g., with regard to specific receptor activity), the current results just lay the foundation for further label-free optical tools to diagnose the disease.

Indexed as

Biomarkers, TumorBreast NeoplasmsErbB ReceptorsFemaleHumansMCF-7 CellsMicroscopy, ConfocalSpectrum Analysis, RamanStaining and LabelingBiomarkers, TumorEGFR protein, humanErbB ReceptorsDNA denaturationEGF overexpressionMCF-7 cellsRaman spectroscopyRNA

Identifiers

PMID27381847
PMCPMC5557097
OpenAlexW814005048

What OpenQuestion holds

Textmetadata
LicenceTDM
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.