Evidence map›Paper›PMID 36275472›Full record

ArticlePeerJ2022

Proteomic analysis of IgM antigens from mammary tissue under pre- and post-cancer conditions using the MMTV-PyVT mouse model.

Ricardo Hernández Ávila, Mariana Díaz-Zaragoza, Pedro Ostoa-Saloma

Open access · goldAbstract read
In one paragraph

Article in PeerJ, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact, top 81% 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

0 citing papers in PubMed, 0 citations in OpenAlex.

No citing paper in PubMed yet.

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

3 authors at 2 institutions in 1 country.

Ricardo Hernández ÁvilaDepartamento de Inmunología, Instituto de Investigaciones Biomédicas, Universidad Nacional Autonoma de México, Ciudad de México, CdMx, México.
Mariana Díaz-ZaragozaLaboratorio de Sistemas Biológicos, Departamento de Ciencias de la Salud. Centro Universitario de los Valles, Universidad de Guadalajara, Ameca, Jalisco, México.
Pedro Ostoa-SalomaDepartamento de Inmunología, Instituto de Investigaciones Biomédicas, Universidad Nacional Autonoma de México, Ciudad de México, CdMx, México.
Universidad Nacional Autónoma de México · MXUniversidad de Guadalajara · MX

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

We analyzed the recognition of tumor antigens by IgM in transgenic MMTV-PyVT mice. PyVT female mice are a model of breast cancer that simulates its counterpart in humans. The PyVT model allows studying antigen recognition in two conditions: before and during tumor expression. We attempted to identify by sequence, the antigens recognized by IgM that are expressed or disappear in the membrane of breast transgenic tissue during the transition "No tumor-Tumor". 2D immunoblots were obtained of isolated membranes from the breast tissue in the fifth, sixth, and seventh week (transition point). Proteins recognized by IgM were sequenced in duplicate by MALDI-TOF. In the transition, we observed the disappearance of antigens in transgenic mice with respect to non-transgenic ones. We believe that in the diagnosis of cancer in its early stages, the expression of early antigens is as important as their early delocalization, with the latter having the advantage that, under normal conditions, we can know which proteins should be present at a given time. Therefore, we could consider that also the absence of antigens could be considered as a biomarker of cancer in progress.

Indexed as

Mammary Neoplasms, ExperimentalAnimalsAntigens, NeoplasmFemaleHumansImmunoglobulin MMiceMice, TransgenicProteomicsAntigens, NeoplasmImmunoglobulin MBreast cancerIgMPyVT miceTumor antigens

Identifiers

PMID36275472
PMCPMC9586126
OpenAlexW4306679337

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.