Evidence map›Paper›PMID 31316139›Full record

ArticleScientific reports2019

Proteogenomic Analysis of Protein Sequence Alterations in Breast Cancer Cells.

Iulia M Lazar, Arba Karcini, Shreya Ahuja, Carly Estrada-Palma

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
1.9field-weighted citation impact, top 16% 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

7 citing papers in PubMed, 19 citations in OpenAlex.

  1. Article
  2. Statistical Methodology for Ribosomal Frameshift Detection.ACM-BCB ... ... : the ... ACM Conference on Bioinformatics, Computational Biology and Biomedicine. ACM Conference on Bioinformatics, Computational Biology and Biomedicine · 2022
    Article
  3. Article
  4. Metagenomic-Metabolomic Mining ofFrontiers in microbiology · 2022
    Article
  5. Article
  6. Article
  7. 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

4 authors at 1 institution in 1 country.

Iulia M LazarDepartment of Biological Sciences, Virginia Tech 1981 Kraft Drive, Blacksburg, VA, 24061, USA. malazar@vt.edu.ORCID http://orcid.org/0000-0001-7746-7889
Arba KarciniDepartment of Biological Sciences, Virginia Tech 1981 Kraft Drive, Blacksburg, VA, 24061, USA.
Shreya AhujaDepartment of Biological Sciences, Virginia Tech 1981 Kraft Drive, Blacksburg, VA, 24061, USA.
Carly Estrada-PalmaDepartment of Biochemistry, Virginia Tech 1981 Kraft Drive, Blacksburg, VA, 24061, USA.
Virginia Tech · US

Funding

Microfluidic Chip for the Analysis of Cell-Surface ProteinsR01GM121920 · NIGMS · VIRGINIA POLYTECHNIC INST AND ST UNIV · PI LAZAR, MARIA IULIANA · 2017 to 2021
$1.9M
NIGMS NIH HHS R01 GM121920
6 · The paper itself

Abstract

Cancer evolves as a result of an accumulation of mutations and chromosomal aberrations. Developments in sequencing technologies have enabled the discovery and cataloguing of millions of such mutations. The identification of protein-level alterations, typically by using reversed-phase protein arrays or mass spectrometry, has lagged, however, behind gene and transcript-level observations. In this study, we report the use of mass spectrometry for detecting the presence of mutations-missense, indels and frame shifts-in MCF7 and SKBR3 breast cancer, and non-tumorigenic MCF10A cells. The mutations were identified by expanding the database search process of raw mass spectrometry files by including an in-house built database of mutated peptides (XMAn-v1) that complemented a minimally redundant, canonical database of Homo sapiens proteins. The work resulted in the identification of nearly 300 mutated peptide sequences, of which ~50 were characterized by quality tandem mass spectra. We describe the criteria that were used to select the mutated peptide sequences, evaluate the parameters that characterized these peptides, and assess the artifacts that could have led to false peptide identifications. Further, we discuss the functional domains and biological processes that may be impacted by the observed peptide alterations, and how protein-level detection can support the efforts of identifying cancer driving mutations and genes. Mass spectrometry data are available via ProteomeXchange with identifier PXD014458.

Indexed as

Amino Acid SequenceBreast NeoplasmsDatabases, ProteinHumansMass SpectrometryPeptidesProteogenomicsSequence Analysis, ProteinTandem Mass SpectrometryPeptides

Identifiers

PMID31316139
PMCPMC6637242
OpenAlexW2956329239

What OpenQuestion holds

Textmetadata
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.