Integrating digital pathology with transcriptomic and epigenomic tools for predicting metastatic uterine tumor aggressiveness

dc.contributor.authorSonzini, Giorgia
dc.contributor.authorGranados Aparici, Sofia
dc.contributor.authorSanegre, Sabina
dc.contributor.authorDiaz Lagares, Ángel
dc.contributor.authorDiaz Martin, Juan
dc.contributor.authorAndrea, Carlos de
dc.contributor.authorEritja, Núria
dc.contributor.authorBao Caamano, Aida
dc.contributor.authorCosta Fraga, Nicolás
dc.contributor.authorGarcía Ros, David
dc.contributor.authorSalguero Aranda, Carmen
dc.contributor.authorDavidson, Ben
dc.contributor.authorLópez López, Rafael
dc.contributor.authorMelero, Ignacio
dc.contributor.authorNavarro, Samuel
dc.contributor.authorRamon y Cajal, Santiago
dc.contributor.authorAlava, Enrique de
dc.contributor.authorMatias-Guiu, Xavier, 1958-
dc.contributor.authorNoguera, Rosa
dc.date.accessioned2023-02-23T16:32:33Z
dc.date.available2023-02-23T16:32:33Z
dc.date.issued2022-11-18
dc.date.updated2023-02-23T14:13:20Z
dc.description.abstractThe incidence of new cancer cases is expected to increase significantly in the future, posing a worldwide problem. In this regard, precision oncology and its diagnostic tools are essential for developing personalized cancer treatments. Digital pathology (DP) is a particularly key strategy to study the interactions of tumor cells and the tumor microenvironment (TME), which play a crucial role in tumor initiation, progression and metastasis. The purpose of this study was to integrate data on the digital patterns of reticulin fiber scaffolding and the immune cell infiltrate, transcriptomic and epigenetic profiles in aggressive uterine adenocarcinoma (uADC), uterine leiomyosarcoma (uLMS) and their respective lung metastases, with the aim of obtaining key TME biomarkers that can help improve metastatic prediction and shed light on potential therapeutic targets. Automatized algorithms were used to analyze reticulin fiber architecture and immune infiltration in colocalized regions of interest (ROIs) of 133 invasive tumor front (ITF), 89 tumor niches and 70 target tissues in a total of six paired samples of uADC and nine of uLMS. Microdissected tissue from the ITF was employed for transcriptomic and epigenetic studies in primary and metastatic tumors. Reticulin fiber scaffolding was characterized by a large and loose reticular fiber network in uADC, while dense bundles were found in uLMS. Notably, more similarities between reticulin fibers were observed in paired uLMS then paired uADCs. Transcriptomic and multiplex immunofluorescence-based immune profiling showed a higher abundance of T and B cells in primary tumor and in metastatic uADC than uLMS. Moreover, the epigenetic signature of paired samples in uADCs showed more differences than paired samples in uLMS. Some epigenetic variation was also found between the ITF of metastatic uADC and uLMS. Altogether, our data suggest a correlation between morphological and molecular changes at the ITF and the degree of aggressiveness. The use of DP tools for characterizing reticulin scaffolding and immune cell infiltration at the ITF in paired samples together with information provided by omics analyses in a large cohort will hopefully help validate novel biomarkers of tumor aggressiveness, develop new drugs and improve patient quality of life in a much more efficient way.
dc.format.extent20 p.
dc.format.mimetypeapplication/pdf
dc.identifier.issn2296-634X
dc.identifier.pmid36467415
dc.identifier.urihttps://hdl.handle.net/2445/194054
dc.language.isoeng
dc.publisherFrontiers Media SA
dc.relation.isformatofReproducció del document publicat a: https://doi.org/10.3389/fcell.2022.1052098
dc.relation.ispartofFrontiers in Cell and Developmental Biology, 2022, vol. 10, num. 1052098
dc.relation.urihttps://doi.org/10.3389/fcell.2022.1052098
dc.rightscc by (c) Sonzini, Giorgia et al., 2022
dc.rights.accessRightsinfo:eu-repo/semantics/openAccess
dc.rights.urihttp://creativecommons.org/licenses/by/3.0/es/*
dc.sourceArticles publicats en revistes (Institut d'lnvestigació Biomèdica de Bellvitge (IDIBELL))
dc.subject.classificationCàncer d'úter
dc.subject.classificationMetàstasi
dc.subject.classificationEpigenètica
dc.subject.otherUterine cancer
dc.subject.otherMetastasis
dc.subject.otherEpigenetics
dc.titleIntegrating digital pathology with transcriptomic and epigenomic tools for predicting metastatic uterine tumor aggressiveness
dc.typeinfo:eu-repo/semantics/article
dc.typeinfo:eu-repo/semantics/publishedVersion

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