Evidence map›Paper›PMID 39296438›Full record

ArticleJournal of medicine and life2024

Analysis of molecular marker expression in cutaneous lesions and cervical carcinoma associated with HPV infection.

Laura Maghiar, Liliana Sachelarie, Anca Carmen Huniadi

Abstract read
In one paragraph

Article in Journal of medicine and life, 2024. 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
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1 · What the graph read from it

What it found

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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.

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.

Laura MaghiarDepartment of Dental Medicine, Faculty of Medicine and Pharmacy, University of Oradea, Oradea, Romania.
Liliana SachelarieDepartment of Preclinical Discipline, Apollonia University, Iasi, Romania.
Anca Carmen HuniadiDepartment of Dental Medicine, Faculty of Medicine and Pharmacy, University of Oradea, Oradea, Romania.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The study sought to systematically compare the expression of molecular markers in benign cutaneous lesions and squamous cell cervical carcinoma associated with HPV infection to better understand the pathophysiological mechanisms involved in HPV-related lesions and their progression to malignancy. We included 200 patients recruited from a gynecological clinic divided into two groups: 100 patients with positive HPV tests presenting with cutaneous lesions and 100 patients diagnosed with squamous cell cervical carcinoma and testing positive for HPV. The participants were selected to ensure diverse ethnic and demographic representation. The study utilized different statistical analyses, including Chi-square tests to assess associations between categorical variables and logistic regression to evaluate factors influencing lesion progression and compare marker expressions across different lesion types. The results indicated significant differences in the expression of specific molecular markers between cutaneous lesions and cervical carcinomas, highlighting distinct molecular pathways involved in HPV-related lesion development. Notably, markers such as p16, p53, and E-cadherin showed varying expression, suggesting their potential role in distinguishing between benign and malignant lesions. The findings emphasize the significance of molecular marker profiling in improving diagnostic and therapeutic strategies for HPV-related lesions. The differential expression of molecular markers can offer valuable insights into the pathogenesis of HPV-induced lesions and help develop targeted interventions to prevent malignant transformation. Further research is necessary to validate these markers in larger cohorts and diverse populations.

Indexed as

Biomarkers, TumorPapillomavirus InfectionsUterine Cervical NeoplasmsAdultCadherinsCarcinoma, Squamous CellFemaleHumansMiddle AgedPapillomaviridaeSkin NeoplasmsBiomarkers, TumorCadherinsHPV infectionmalignant transformationmolecular markers

Identifiers

PMID39296438
PMCPMC11407498

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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.