Evidence map›Paper›PMID 35216378›Full record

ReviewInternational journal of molecular sciences2022

Clinical Application Perspectives of Lung Cancers 3D Tumor Microenvironment Models for In Vitro Cultures.

Irena Wieleba, Kamila Wojas-Krawczyk, Paweł Krawczyk, Janusz Milanowski

Abstract readReview
In one paragraph

Review in International journal of molecular sciences, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
–field-weighted citation impact
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

7 citing papers in PubMed.

  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

4 authors.

Irena WielebaPneumonology, Oncology and Allergology Department, Medical University of Lublin, 20-059 Lublin, Poland.ORCID 0000-0002-6009-039X
Kamila Wojas-KrawczykPneumonology, Oncology and Allergology Department, Medical University of Lublin, 20-059 Lublin, Poland.ORCID 0000-0001-9947-5169
Paweł KrawczykPneumonology, Oncology and Allergology Department, Medical University of Lublin, 20-059 Lublin, Poland.
Janusz MilanowskiPneumonology, Oncology and Allergology Department, Medical University of Lublin, 20-059 Lublin, Poland.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Despite the enormous progress and development of modern therapies, lung cancer remains one of the most common causes of death among men and women. The key element in the development of new anti-cancer drugs is proper planning of the preclinical research phase. The most adequate basic research exemplary for cancer study are 3D tumor microenvironment in vitro models, which allow us to avoid the use of animal models and ensure replicable culture condition. However, the question tormenting the scientist is how to choose the best tool for tumor microenvironment research, especially for extremely heterogenous lung cancer cases. In the presented review we are focused to explain the key factors of lung cancer biology, its microenvironment, and clinical gaps related to different therapies. The review summarized the most important strategies for in vitro culture models mimicking the tumor-tumor microenvironmental interaction, as well as all advantages and disadvantages were depicted. This knowledge could facilitate the right decision to designate proper pre-clinical in vitro study, based on available analytical tools and technical capabilities, to obtain more reliable and personalized results for faster introduction them into the future clinical trials.

Indexed as

AnimalsCell Culture TechniquesHumansLung NeoplasmsOrganoidsSpheroids, CellularTumor Microenvironmentlung cancerorganoidsspheroidtumor microenvironmenttumor-on-chip

Identifiers

PMID35216378
PMCPMC8876687

What OpenQuestion holds

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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.