Evidence map›Paper›PMID 36467415›Full record

ArticleFrontiers in cell and developmental biology2022

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

Giorgia Sonzini, Sofia Granados-Aparici, Sabina Sanegre, Angel Diaz-Lagares, Juan Diaz-Martin, Carlos de Andrea, Núria Eritja, Aida Bao-Caamano, Nicolás Costa-Fraga, David García-Ros and 9 more

Open access · goldAbstract read
In one paragraph

Article in Frontiers in cell and developmental biology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.2field-weighted citation impact, top 44% 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

2 citing papers in PubMed, 2 citations in OpenAlex.

  1. Article
  2. 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

19 authors at 10 institutions in 2 countries.

Giorgia SonziniDepartment of Pathology, Medical School, University of Valencia-INCLIVA, Valencia, Spain.
Sofia Granados-ApariciDepartment of Pathology, Medical School, University of Valencia-INCLIVA, Valencia, Spain.
Sabina SanegreDepartment of Pathology, Medical School, University of Valencia-INCLIVA, Valencia, Spain.
Angel Diaz-Lagares2 Cancer CIBER (CIBERONC), Madrid, Spain.
Juan Diaz-Martin2 Cancer CIBER (CIBERONC), Madrid, Spain.
Carlos de Andrea2 Cancer CIBER (CIBERONC), Madrid, Spain.
Núria Eritja2 Cancer CIBER (CIBERONC), Madrid, Spain.
Aida Bao-CaamanoEpigenomics Unit, Cancer Epigenomics, Translational Medical Oncology Group (Oncomet), Health Research Institute of Santiago (IDIS), University Clinical Hospital of Santiago (CHUS/SERGAS), Santiago de Compostela, Spain.
Nicolás Costa-FragaEpigenomics Unit, Cancer Epigenomics, Translational Medical Oncology Group (Oncomet), Health Research Institute of Santiago (IDIS), University Clinical Hospital of Santiago (CHUS/SERGAS), Santiago de Compostela, Spain.
David García-RosClínica Universidad de Navarra, University of Navarra, Pamplona, Spain.
Carmen Salguero-Aranda2 Cancer CIBER (CIBERONC), Madrid, Spain.
Ben DavidsonInstitute of Clinical Medicine, Faculty of Medicine, University of Oslo, Oslo, Norway.
Rafael López-López2 Cancer CIBER (CIBERONC), Madrid, Spain.
Ignacio Melero2 Cancer CIBER (CIBERONC), Madrid, Spain.
Samuel NavarroDepartment of Pathology, Medical School, University of Valencia-INCLIVA, Valencia, Spain.
Santiago Ramon Y Cajal2 Cancer CIBER (CIBERONC), Madrid, Spain.
Enrique de Alava2 Cancer CIBER (CIBERONC), Madrid, Spain.
Xavier Matias-Guiu2 Cancer CIBER (CIBERONC), Madrid, Spain.
Rosa NogueraDepartment of Pathology, Medical School, University of Valencia-INCLIVA, Valencia, Spain.
Centro de Investigación Biomédica en Red de Cáncer · ESClinica Universidad de Navarra · ESUniversitat de València · ESInstituto de Investigación Sanitaria de Santiago · ESInstituto de Biomedicina de Sevilla · ESServicio Gallego de Salud · ESUniversitat Autònoma de Barcelona · ESUniversitat de Barcelona · ESUniversitat de Lleida · ESUniversity of Oslo · NO

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The 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.

Indexed as

digital pathologyinvasive tumor frontlung metastasismethylomicsmultiplex immunofluorescencetranscriptomicsuterine adenocarcinomauterine leiomyosarcoma

Identifiers

PMID36467415
PMCPMC9716026
OpenAlexW4309457661

What OpenQuestion holds

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LicenceCC BY
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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.