Evidence map›Paper›PMID 37958406›Full record

ReviewCancers2023

Defining Tumor Microenvironment as a Possible Target for Effective GEP-NENs Immunotherapy-A Systematic Review.

Paulina Chmiel, Paulina Rychcik-Pazyrska, Rafał Stec

Open access · goldAbstract readReview
In one paragraph

Review in Cancers, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
1.7field-weighted citation impact, top 14% 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

10 citing papers in PubMed, 8 citations in OpenAlex.

  1. 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

3 authors at 1 institution in 1 country.

Paulina ChmielDepartment of Oncology, Medical University of Warsaw, 02-097 Warsaw, Poland.
Paulina Rychcik-PazyrskaDepartment of Oncology, Medical University of Warsaw, 02-097 Warsaw, Poland.
Rafał StecDepartment of Oncology, Medical University of Warsaw, 02-097 Warsaw, Poland.ORCID 0000-0002-3291-6422
Medical University of Warsaw · PL

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Neuroendocrine neoplasms (NENs) are a heterogenous and recurrent group of malignancies originating from neuroendocrine secretory cells diffused on all parts of the human body. Gastro-entero-pancreatic neuroendocrine tumors (GEP-NETs) account for most NENs. Considering the abundance of possible origins, locations, and tumor specifications, there is still no consensus about optimal treatment options for these neoplasms. In light of the escalating immunotherapeutic approaches, it is crucial to define indications for such therapy in GEP-NETs. Bearing in mind the significance of pathophysiological mechanisms and tumor microenvironment (TME) impact on carcinogenesis, defining TME structure and correlation with the immune system in GEP-NETs appears essential. This paper aimed to assess the characterization of the tumor immune microenvironment for a better understanding of the possible therapeutic options in GEP-NETS. The authors performed a systematic review, extracting papers from the PubMed, Web of Science, and Scopus databases according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Among 3800 articles identified through database searching, 292 were assessed for eligibility. Ultimately, 28 articles were included in the qualitative synthesis. This paper sums up the research on the immune cell infiltrates, immune checkpoint expression, cytokine profile, neoangiogenesis, and microbiome in the TME of GEP-NETs.

Indexed as

GEP-NECsGEP-NETsimmunotherapyneuroendocrine tumorsPD-1/PD-L1TME

Identifiers

PMID37958406
PMCPMC10648089
OpenAlexW4388048792

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.