Evidence map›Paper›PMID 37969199›Full record

ArticleAmerican journal of translational research2023

Comprehensive multi-level expression profiling of key biomarkers in breast cancer patients.

Tayyaba Zia, Liu Bangfan, Amun Nadeem, Abid Hussain, Mostafa A Abdel-Maksoud, Adel M Zakri, Muhammad Kazim Bashir, Mubarak Ali, Norina Jabeen, Muhammad Jamil and 2 more

Open access · greenAbstract read
PubMed Full text at PMC
In one paragraph

Article in American journal of translational research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.3field-weighted citation impact, top 34% 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

1 citing paper in PubMed, 1 citations in OpenAlex.

  1. 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

12 authors at 7 institutions in 3 countries.

Tayyaba ZiaSchool of Public Management, Yanshan University Qinhuangdao 066000, Hebei, China.
Liu BangfanSchool of Public Administration, Yanshan University Qinhuangdao 066000, Hebei, China.
Amun NadeemDepartment of Pathology, Gujranwala Medical College Teaching Hospital and DHQ Teaching Hospital Gujranwala 52250, Punjab, Pakistan.
Abid HussainAPMO Nishter Hospital Multan 60000, Punjab, Pakistan.
Mostafa A Abdel-MaksoudDepartment of Botany and Microbiology, College of Science, King Saud University P.O. Box 2455, Riyadh 11451, Saudi Arabia.
Adel M ZakriDepartment of Plant Production, College of Food and Agricultural Sciences, King Saud University Saudi Arabia.
Muhammad Kazim BashirShaukat Khanum Memorial Cancer Hospital and Research Centre Lahore 13014, Punjab, Pakistan.
Mubarak AliAnimal Science Institute, National Agricultural Research Center Islamabad 54000, Pakistan.
Norina JabeenDepartment of Rural Sociology, University of Agriculture Faisalabad Faisalabad 38000, Punjab, Pakistan.
Muhammad JamilPARC Arid Zone Research Centre Dera Ismail Khan 29050, Pakistan.
Wahidah H Al-QahtaniDepartment of Food Sciences & Nutrition, College of Food and Agricultural Sciences, King Saud University Saudi Arabia.
Taghreed N AlmanaaDepartment of Botany and Microbiology, College of Science, King Saud University P.O. Box 2455, Riyadh 11451, Saudi Arabia.
King Saud University · SAPakistan Agricultural Research Council · PKYanshan University · CNGIFT University · PKNishtar Medical College and Hospital · PKShaukat Khanum Memorial Cancer Hospital and Research Center · PKUniversity of Faisalabad · PK

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesIn this comprehensive breast cancer (BC) study, we aimed to identify, validate, and characterize key biomarkers with significant implications in BC diagnosis, prognosis, and as therapeutic targets.

methodsOur research strategy involved a multi-level methodology, combining bioinformatic analysis with experimental validation.

resultsInitially, we conducted an extensive literature search to identify BC biomarkers, selecting those with reported accuracies exceeding 20% in specificity and sensitivity. This yielded nine candidate biomarkers, which we subsequently analyzed using Cytoscape to identify a few key biomarkers. Based on the degree method, we denoted four key biomarkers, including progesterone receptor (PGR), epidermal growth factor receptor (EGFR), estrogen receptor 1 (ESR1), and Erb-B2 Receptor Tyrosine Kinase 2 (ERBB2). Expression analysis using The Cancer Genome Atlas (TCGA) dataset revealed that PGR and EGFR exhibited significant (

conclusionOur study gives valuable insight into BC biomarkers, for diagnosis and prognosis. These findings have implications for BC management using personalized and targeted therapeutic approaches for BC patients.

Indexed as

biomarkerBreast cancerdiagnosisprognosis

Identifiers

PMID37969199
PMCPMC10641354
OpenAlexW4388737006

What OpenQuestion holds

Textmetadata
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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.