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Universal Markers Unveil Metastatic Cancerous Cross-Sections at Nanoscale

SIMPLE SUMMARY: We propose the use of two universal morphometric indices whose synergetic potency leads to the classification of a cancerous tissue of a few nanometers in size as metastatic or non-metastatic. The method is label-free, operates on conventional histological cross-sections, recording s...

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Autores principales: Bakalis, Evangelos, Ferraro, Angelo, Gavriil, Vassilios, Pepe, Francesco, Kollia, Zoe, Cefalas, Alkiviadis-Constantinos, Malapelle, Umberto, Sarantopoulou, Evangelia, Troncone, Giancarlo, Zerbetto, Francesco
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9367376/
https://www.ncbi.nlm.nih.gov/pubmed/35954392
http://dx.doi.org/10.3390/cancers14153728
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author Bakalis, Evangelos
Ferraro, Angelo
Gavriil, Vassilios
Pepe, Francesco
Kollia, Zoe
Cefalas, Alkiviadis-Constantinos
Malapelle, Umberto
Sarantopoulou, Evangelia
Troncone, Giancarlo
Zerbetto, Francesco
author_facet Bakalis, Evangelos
Ferraro, Angelo
Gavriil, Vassilios
Pepe, Francesco
Kollia, Zoe
Cefalas, Alkiviadis-Constantinos
Malapelle, Umberto
Sarantopoulou, Evangelia
Troncone, Giancarlo
Zerbetto, Francesco
author_sort Bakalis, Evangelos
collection PubMed
description SIMPLE SUMMARY: We propose the use of two universal morphometric indices whose synergetic potency leads to the classification of a cancerous tissue of a few nanometers in size as metastatic or non-metastatic. The method is label-free, operates on conventional histological cross-sections, recording surface height–height roughness by AFM, and detects nanoscale changes associated with the progress of carcinogenesis which are the output of combined statistical approaches, namely multifractal analysis and the generalized moments method. The benefit of this approach is at least two-fold. On the one hand, its application in the context of early diagnosis can increase the life expectancy of patients, and on the other hand, differentiation between metastatic and non-metastatic tissues at the singular cell level can lead to new methodologies to treat cancer biology and therapies. ABSTRACT: The characterization of cancer histological sections as metastatic, M, or not-metastatic, NM, at the cellular size level is important for early diagnosis and treatment. We present timely warning markers of metastasis, not identified by existing protocols and used methods. Digitized atomic force microscopy images of human histological cross-sections of M and NM colorectal cancer cells were analyzed by multifractal detrended fluctuation analysis and the generalized moments method analysis. Findings emphasize the multifractal character of all samples and accentuate room for the differentiation of M from NM cross-sections. Two universal markers emphatically achieve this goal performing very well: (a) the ratio of the singularity parameters (left/right), which are defined relative to weak/strong fluctuations in the multifractal spectrum, is always greater than 0.8 for NM tissues; and (b) the index of multifractality, used to classify universal multifractals, points to log-normal distribution for NM and to log-Cauchy for M tissues. An immediate large-scale screening of cancerous sections is doable based on these findings.
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spelling pubmed-93673762022-08-12 Universal Markers Unveil Metastatic Cancerous Cross-Sections at Nanoscale Bakalis, Evangelos Ferraro, Angelo Gavriil, Vassilios Pepe, Francesco Kollia, Zoe Cefalas, Alkiviadis-Constantinos Malapelle, Umberto Sarantopoulou, Evangelia Troncone, Giancarlo Zerbetto, Francesco Cancers (Basel) Article SIMPLE SUMMARY: We propose the use of two universal morphometric indices whose synergetic potency leads to the classification of a cancerous tissue of a few nanometers in size as metastatic or non-metastatic. The method is label-free, operates on conventional histological cross-sections, recording surface height–height roughness by AFM, and detects nanoscale changes associated with the progress of carcinogenesis which are the output of combined statistical approaches, namely multifractal analysis and the generalized moments method. The benefit of this approach is at least two-fold. On the one hand, its application in the context of early diagnosis can increase the life expectancy of patients, and on the other hand, differentiation between metastatic and non-metastatic tissues at the singular cell level can lead to new methodologies to treat cancer biology and therapies. ABSTRACT: The characterization of cancer histological sections as metastatic, M, or not-metastatic, NM, at the cellular size level is important for early diagnosis and treatment. We present timely warning markers of metastasis, not identified by existing protocols and used methods. Digitized atomic force microscopy images of human histological cross-sections of M and NM colorectal cancer cells were analyzed by multifractal detrended fluctuation analysis and the generalized moments method analysis. Findings emphasize the multifractal character of all samples and accentuate room for the differentiation of M from NM cross-sections. Two universal markers emphatically achieve this goal performing very well: (a) the ratio of the singularity parameters (left/right), which are defined relative to weak/strong fluctuations in the multifractal spectrum, is always greater than 0.8 for NM tissues; and (b) the index of multifractality, used to classify universal multifractals, points to log-normal distribution for NM and to log-Cauchy for M tissues. An immediate large-scale screening of cancerous sections is doable based on these findings. MDPI 2022-07-31 /pmc/articles/PMC9367376/ /pubmed/35954392 http://dx.doi.org/10.3390/cancers14153728 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Bakalis, Evangelos
Ferraro, Angelo
Gavriil, Vassilios
Pepe, Francesco
Kollia, Zoe
Cefalas, Alkiviadis-Constantinos
Malapelle, Umberto
Sarantopoulou, Evangelia
Troncone, Giancarlo
Zerbetto, Francesco
Universal Markers Unveil Metastatic Cancerous Cross-Sections at Nanoscale
title Universal Markers Unveil Metastatic Cancerous Cross-Sections at Nanoscale
title_full Universal Markers Unveil Metastatic Cancerous Cross-Sections at Nanoscale
title_fullStr Universal Markers Unveil Metastatic Cancerous Cross-Sections at Nanoscale
title_full_unstemmed Universal Markers Unveil Metastatic Cancerous Cross-Sections at Nanoscale
title_short Universal Markers Unveil Metastatic Cancerous Cross-Sections at Nanoscale
title_sort universal markers unveil metastatic cancerous cross-sections at nanoscale
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9367376/
https://www.ncbi.nlm.nih.gov/pubmed/35954392
http://dx.doi.org/10.3390/cancers14153728
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