Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 265

The DOI matches its Crossref record; 112 of the 112 references it cites were found in a registry or an index.

Clinical development of therapies targeting TGFβ: current knowledge and future perspectives

Open access
Ciardiello, D., Elez, E., Tabernero, J., Seoane, J.·2020·Annals of Oncology

Abstract

Transforming growth factor beta (TGFβ) is a pleiotropic cytokine that plays a key role in both physiologic and pathologic conditions, including cancer. Importantly, TGFβ can exhibit both tumor-suppressive and oncogenic functions. In normal epithelial cells TGFβ acts as an antiproliferative and differentiating factor, whereas in advanced tumors TGFβ can act as an oncogenic factor by creating an immune-suppressive tumor microenvironment, and inducing cancer cell proliferation, angiogenesis, invasion, tumor progression, and metastatic spread. A wealth of preclinical findings have demonstrated that targeting TGFβ is a promising means of exerting antitumor activity. Based on this rationale, several classes of TGFβ inhibitors have been developed and tested in clinical trials, namely, monoclonal, neutralizing, and bifunctional antibodies; antisense oligonucleotides; TGFβ-related vaccines; and receptor kinase inhibitors. It is now >15 years since the first clinical trial testing an anti-TGFβ agent was engaged. Despite the promising preclinical studies, translation of the basic understanding of the TGFβ oncogenic response into the clinical setting has been slow and challenging. Here, we review the conclusions and status of all the completed and ongoing clinical trials that test compounds that inhibit the TGFβ pathway, and discuss the challenges that have arisen during their clinical development. With none of the TGFβ inhibitors evaluated in clinical trials approved for cancer therapy, clinical development for TGFβ blockade therapy is primarily oriented toward TGFβ inhibitor combinations. Immune checkpoint inhibitors are considered candidates, albeit with efficacy anticipated to be restricted to specific populations. In this context, we describe current efforts in the search for biomarkers for selecting the appropriate cancer patients who are likely to benefit from anti-TGFβ therapies. The knowledge accumulated during the last 15 years of clinical research in the context of the TGFβ pathway is crucial to design better, innovative, and more successful trials.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1016/j.annonc.2020.07.009

Cites

112 of 112 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Show all 112 references

Cited by

See all 265

Metadata

Authors
Ciardiello, D., Elez, E., Tabernero, J., & Seoane, J.
Venue
Annals of Oncology
Publisher
Elsevier BV
Published
2020-10
Volume
31
Issue
10
Pages
1336-1349
ISSN
0923-7534 (ISSN-L)
OpenAlex
W3044762644
Cited by
265
References
112
FWCI
10.23
Type
journal article
Language
en
Open access
hybrid

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: Clinical development of therapies targeting TGFβ: current knowledge and future perspectives. https://app.cochat.ai/papers/10.1016/j.annonc.2020.07.009
The paper
Ciardiello, D., Elez, E., Tabernero, J., & Seoane, J. (2020). Clinical development of therapies targeting TGFβ: current knowledge and future perspectives. Annals of Oncology. https://doi.org/10.1016/j.annonc.2020.07.009

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.