Evidence map›Paper›PMID 33672435›Full record

ReviewCancers2021

The Revolutionary Roads to Study Cell-Cell Interactions in 3D In Vitro Pancreatic Cancer Models.

Donatella Delle Cave, Riccardo Rizzo, Bruno Sainz, Giuseppe Gigli, Loretta L Del Mercato, Enza Lonardo

Abstract readReview
In one paragraph

Review in Cancers, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.

0numbers the graph read from it
0cells of the map it votes in
20citing 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

20 citing papers in PubMed.

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  7. Emerging Therapeutic Options in Pancreatic Cancer Management.International journal of molecular sciences · 2024
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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

6 authors.

Donatella Delle CaveInstitute of Genetics and Biophysics "A. Buzzati-Traverso", National Research Council (CNR-IGB), Via Pietro Castellino 111, 80131 Naples, Italy.ORCID 0000-0002-4019-2778
Riccardo RizzoInstitute of Nanotechnology, National Research Council (CNR-NANOTEC), c/o Campus Ecotekne, via Monteroni, 73100 Lecce, Italy.ORCID 0000-0002-5716-9195
Bruno SainzDepartment of Cancer Biology, Instituto de Investigaciones Biomedicas "Alberto Sols" (IIBM), CSIC-UAM, 28029 Madrid, Spain.ORCID 0000-0003-4829-7651
Giuseppe GigliInstitute of Nanotechnology, National Research Council (CNR-NANOTEC), c/o Campus Ecotekne, via Monteroni, 73100 Lecce, Italy.
Loretta L Del MercatoInstitute of Nanotechnology, National Research Council (CNR-NANOTEC), c/o Campus Ecotekne, via Monteroni, 73100 Lecce, Italy.
Enza LonardoInstitute of Genetics and Biophysics "A. Buzzati-Traverso", National Research Council (CNR-IGB), Via Pietro Castellino 111, 80131 Naples, Italy.

Funding

Associazione Italiana per la Ricerca sul Cancro 20206European Research Council 759959POR Campania FESR 2014/2020 SATIN"Tecnopolo per la medicina di precisione" (TecnoMed Puglia) - Regione Puglia 2117
6 · The paper itself

Abstract

Pancreatic cancer, the fourth most common cancer worldwide, shows a highly unsuccessful therapeutic response. In the last 10 years, neither important advancements nor new therapeutic strategies have significantly impacted patient survival, highlighting the need to pursue new avenues for drug development discovery and design. Advanced cellular models, resembling as much as possible the original in vivo tumor environment, may be more successful in predicting the efficacy of future anti-cancer candidates in clinical trials. In this review, we discuss novel bioengineered platforms for anticancer drug discovery in pancreatic cancer, from traditional two-dimensional models to innovative three-dimensional ones.

Indexed as

3D culturesfluorescent microscopynanotechnologypancreatic cancerpredictive modelstumor microenvironment

Identifiers

PMID33672435
PMCPMC7926501

What OpenQuestion holds

Textmetadata
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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.