Evidence map›Paper›PMID 31454993›Full record

ArticleCancers2019

Gastric Normal Adjacent Mucosa Versus Healthy and Cancer Tissues: Distinctive Transcriptomic Profiles and Biological Features.

Sabino Russi, Giovanni Calice, Vitalba Ruggieri, Simona Laurino, Francesco La Rocca, Elena Amendola, Cinzia Lapadula, Debora Compare, Gerardo Nardone, Pellegrino Musto and 3 more

Open access · goldAbstract read
In one paragraph

Article in Cancers, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers.

0numbers the graph read from it
0cells of the map it votes in
31citing papers in PubMed
4.7field-weighted citation impact, top 4% 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

31 citing papers in PubMed, 53 citations in OpenAlex.

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  11. The occurrence, progression and development of four types of gastric mucosal atrophic lesions and their histopathological characteristics.Gastric cancer : official journal of the International Gastric Cancer Association and the Japanese Gastric Cancer Association · 2023
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  18. How DoesInfection and drug resistance · 2022
    Article
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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

13 authors at 4 institutions in 1 country.

Sabino RussiLaboratory of Preclinical and Translational Research, IRCCS-Referral Cancer Center of Basilicata (CROB), 85028 Rionero in Vulture (PZ), Italy.
Giovanni CaliceLaboratory of Preclinical and Translational Research, IRCCS-Referral Cancer Center of Basilicata (CROB), 85028 Rionero in Vulture (PZ), Italy.
Vitalba RuggieriLaboratory of Preclinical and Translational Research, IRCCS-Referral Cancer Center of Basilicata (CROB), 85028 Rionero in Vulture (PZ), Italy.
Simona LaurinoLaboratory of Preclinical and Translational Research, IRCCS-Referral Cancer Center of Basilicata (CROB), 85028 Rionero in Vulture (PZ), Italy.
Francesco La RoccaLaboratory of Preclinical and Translational Research, IRCCS-Referral Cancer Center of Basilicata (CROB), 85028 Rionero in Vulture (PZ), Italy.
Elena AmendolaDepartment of Biology, University of Naples Federico II, 80138 Naples, Italy.
Cinzia LapadulaPathology Unit, IRCCS, Referral Cancer Center of Basilicata (CROB), 85028, Rionero in Vulture, Italy.
Debora CompareDepartment of Clinical Medicine and Surgery, University of Naples Federico II, 80131 Naples, Italy.
Gerardo NardoneDepartment of Clinical Medicine and Surgery, University of Naples Federico II, 80131 Naples, Italy.
Pellegrino MustoUnit of Hematology and Stem Cell Transplantation, IRCCS–Referral Cancer Center of Basilicata (CROB), 85028 Rionero in Vulture, Italy.
Mario De FeliceIstituto per l’Endocrinologia e l’Oncologia Sperimentale “Gaetano Salvatore” (IEOS), Consiglio Nazionale delle Ricerche (CNR), 80131 Naples, Italy.
Geppino FalcoDepartment of Biology, University of Naples Federico II, 80138 Naples, Italy.
Pietro ZoppoliLaboratory of Preclinical and Translational Research, IRCCS-Referral Cancer Center of Basilicata (CROB), 85028 Rionero in Vulture (PZ), Italy.
Centro di Riferimento Oncologico della Basilicata · ITUniversity of Naples Federico II · ITBiogem · ITInstitute for Experimental Endocrinology and Oncology · IT

Funding

IRCCS CROB ricerca corrente
6 · The paper itself

Abstract

Gastric cancer (GC) is a leading cause of cancer-related deaths in the world. Molecular heterogeneity is a major determinant for the clinical outcomes and an exhaustive tumor classification is currently missing. Histologically normal tissue adjacent to the tumor (NAT) is commonly used as a control in cancer studies, nevertheless a recently published paper described the unique characteristics of the NAT in several tumor types. Little is known about the global gene expression profile of gastric NAT (gNAT) which could be an effective tool for a more realistic definition of GC molecular signature. Here, we integrated data of 512 samples from the Genotype-Tissue Expression project (GETx) and The Cancer Genome Atlas (TCGA) to analyze the transcriptome of healthy gastric tissues, gNAT, and GC samples. We validated TCGA-GETx data mining through inHouse gNAT and GC expression dataset. Differential gene expression together with pathway enrichment analyses, indeed, led to different results when using the gNAT or the healthy tissue as control. Based on our analyses, gNAT showed a peculiar gene signature and biological features, like the estrogen receptor pathways activation, suggesting a molecular behavior partially different from both healthy and GC tissues. Therefore, using gNAT as healthy control tissue in the characterization of tumor associated biological processes and pathways could lead to suboptimal results.

Indexed as

gastric cancergene expression profilenormal tissue adjacent to the tumor

Identifiers

PMID31454993
PMCPMC6769942
OpenAlexW2969604738

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.