Evidence map›Paper›PMID 38737450›Full record

ArticleCellular and molecular bioengineering2024

Pathological Features of Colorectal Adenocarcinoma Patients Related to MLH1.

Alexandru Adrian Bratei, Raluca-Ioana Stefan-van Staden

Abstract read
In one paragraph

Article in Cellular and molecular bioengineering, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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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

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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

2 authors.

Alexandru Adrian BrateiFaculty of Chemical Engineering and Biotechnologies, National University of Science and Technology POLITEHNICA Bucharest, Bucharest, Romania.
Raluca-Ioana Stefan-van StadenFaculty of Chemical Engineering and Biotechnologies, National University of Science and Technology POLITEHNICA Bucharest, Bucharest, Romania.ORCID 0000-0001-8244-2483

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: MLH1, one of the MMR proteins, is linked to DNA replication, its role being to repair the incorrect DNA sequences and to replace them with proper ones. The loss of the MLH1 gene expression is part of Lynch syndrome which can lead to a series of cancers like colorectal and endometrial ones. The aim of this paper is to correlate the levels of MLH1 in four different bio-logical fluids with clinicopathological features in colorectal cancer patients in order to predict them with high probability. Therefore, a mathematical model with given code in Matlab has been proposed to get the clinicopathological features with high probability by only introducing the values for MLH1 concentrations. All these data can be obtained in a very short time even before surgery which can be very helpful the surgeon and the oncologist. Methods: Four types of samples (whole blood, saliva, urine and tissue) were analyzed using stochastic microsensors; concentrations of MLH1 were determined and compared with different macroscopic and micro-scopic pathological features to obtain mathematical models for early, non-invasive diagnostic of colorectal adenocarcinoma. Results: There have been established criteria and mathematical models for tumor location, TNM grading system, depth of the tumor, lymphatic, vascular and perineural invasions and the presence of mucus in the tumoral mass. Conclusions: By using whole blood, saliva and urine samples, the location can be approximated. The proposed mathematical models aimed to allow a minim/noninvasive characterization of the tumor and its location which can help the surgeon and the oncologist to choose faster the personalized treatment.

Indexed as

Colorectal cancerMLH1Stochastic sensors

Identifiers

PMID38737450
PMCPMC11082117

What OpenQuestion holds

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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.