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image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao ZENODOarrow_drop_down
image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
ZENODO
Dataset . 2023
Data sources: Datacite
image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
ZENODO
Dataset . 2023
Data sources: Datacite
ZENODO
Dataset . 2023
Data sources: ZENODO
ZENODO
Dataset . 2023
Data sources: ZENODO
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Dataset related to article "Definition of a multi-omics signature for Esophageal Adenocarcinoma prognosis prediction "

Authors: Luca Lambroia; Carola Conca Dioguardi; Simone Puccio; Andrea Pansa; Giorgia Alvisi; Gianluca Basso; Javier Cibella; +3 Authors

Dataset related to article "Definition of a multi-omics signature for Esophageal Adenocarcinoma prognosis prediction "

Abstract

This record contains raw data related to article “Definition of a multi-omics signature for Esophageal Adenocarcinoma prognosis prediction " Abstract: Esophageal cancer is a highly lethal malignancy that accounts for 5% of all cancer deaths. The two main sub-types of the disease are esophageal squamous-cell carcinoma (ESCC) and esophageal adenocarcinoma (EAC). To date, most studies focused on analysing the transcriptional profile in ESCC only a few studies analysed EAC for transcriptional signatures that might be associated with diagnosis and/or prognosis. In this work we performed a single-cell RNA sequencing (scRNAseq) analysis of the CD45+ cells enriched from from tumor and matched non-tumor tissues obtained from 3 therapy-naïve patients to identify all the types of immune cells present in the tumor's immune infiltrate and their transcriptomic profiles, moreover we have analysed the whole transcriptome in a cohort of 23 patients from whom tissue biopsies were taken from tumor and matched non-tumor tissues. The transcriptional signatures derived from both types of analyses were then used to stratify a larger cohort of TCGA EAC patients showing a strong association with their prognosis. The transcriptional signatures here described have therefore proved capable of being able to predict the clinical outcome of patients and could be used to better define the prognosis in EAC after surgery and to direct patients towards effective therapies.

Keywords

EAC, scRNAseq

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
views
OpenAIRE UsageCountsViews provided by UsageCounts
0
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14
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