Evidence map›Paper›PMID 30898166›Full record

ReviewJournal of experimental & clinical cancer research : CR2019

3D models in the new era of immune oncology: focus on T cells, CAF and ECM.

Francesca Di Modugno, Cristina Colosi, Paola Trono, Giuseppe Antonacci, Giancarlo Ruocco, Paola Nisticò

Abstract readReview
In one paragraph

Review in Journal of experimental & clinical cancer research : CR, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 58 papers.

0numbers the graph read from it
0cells of the map it votes in
58citing 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

58 citing papers in PubMed.

  1. Review
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  14. Tumor-to-stroma cd8Journal of cancer research and clinical oncology · 2024
    Article
  15. Imaging actin organisation and dynamics in 3D.Journal of cell science · 2024
    Article
  16. 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

6 authors.

Francesca Di ModugnoUnit of Tumor Immunology and Immunotherapy, Department of Research, Advanced Diagnostics, and Technological Innovation, Translational Research Area, IRCCS-Regina Elena National Cancer Institute, via Elio Chianesi 53, 00144, Rome, Italy. francesca.dimodugno@ifo.gov.it.
Cristina ColosiCenter for Life Nano Science@Sapienza, Istituto Italiano di Tecnologia, Viale Regina Elena 291, 00161, Rome, Italy.
Paola TronoUnit of Tumor Immunology and Immunotherapy, Department of Research, Advanced Diagnostics, and Technological Innovation, Translational Research Area, IRCCS-Regina Elena National Cancer Institute, via Elio Chianesi 53, 00144, Rome, Italy.
Giuseppe AntonacciCenter for Life Nano Science@Sapienza, Istituto Italiano di Tecnologia, Viale Regina Elena 291, 00161, Rome, Italy.
Giancarlo RuoccoCenter for Life Nano Science@Sapienza, Istituto Italiano di Tecnologia, Viale Regina Elena 291, 00161, Rome, Italy.
Paola NisticòUnit of Tumor Immunology and Immunotherapy, Department of Research, Advanced Diagnostics, and Technological Innovation, Translational Research Area, IRCCS-Regina Elena National Cancer Institute, via Elio Chianesi 53, 00144, Rome, Italy.

Funding

Associazione Italiana per la Ricerca sul Cancro 5×1000, 12182Associazione Italiana per la Ricerca sul Cancro IG 15224
6 · The paper itself

Abstract

Immune checkpoint inhibitor therapy has changed clinical practice for patients with different cancers, since these agents have demonstrated a significant improvement of overall survival and are effective in many patients. However, an intrinsic or acquired resistance frequently occur and biomarkers predictive of responsiveness should help in patient selection and in defining the adequate treatment options. A deep analysis of the complexity of the tumor microenvironment is likely to further advance the field and hopefully identify more effective combined immunotherapeutic strategies. Here we review the current knowledge on tumor microenvironment, focusing on T cells, cancer associated fibroblasts and extracellular matrix. The use of 3D cell culture models to resemble tumor microenvironment landscape and to screen immunomodulatory drugs is also reviewed.

Indexed as

Models, BiologicalCancer-Associated FibroblastsExtracellular MatrixHumansNeoplasmsPrinting, Three-DimensionalSpheroids, CellularTissue ScaffoldsT-LymphocytesTumor Microenvironment3D culture modelsCancer associated fibroblastsExtracellular matrixImmune oncologyT cellsTumor microenvironment

Identifiers

PMID30898166
PMCPMC6429763

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.