Cited by 355Growth Hormone and Insulin-like Growth FactorsBreast Cancer Treatment StudiesTGF-β signaling in diseases

IGF-I induced genes in stromal fibroblasts predict the clinical outcome of breast and lung cancer patients

Open access
Rajski, Michal, Zanetti-Dällenbach, Rosanna, Vogel, Brigitte, Herrmann, Richard, Rochlitz, Christoph, Buess, Martin·2010·BMC Medicine

Abstract

Background: Insulin-like growth factor-1 (IGF-I) signalling is important for cancer initiation and progression. Given the emerging evidence for the role of the stroma in these processes, we aimed to characterize the effects of IGF-I on cancer cells and stromal cells separately. Methods: We used an ex vivo culture model and measured gene expression changes after IGF-I stimulation with cDNA microarrays. In vitro data were correlated with in vivo findings by comparing the results with published expression datasets on human cancer biopsies. Results: Upon stimulation with IGF-I, breast cancer cells and stromal fibroblasts show some common and other distinct response patterns. Among the up-regulated genes in the stromal fibroblasts we observed a significant enrichment in proliferation associated genes. The expression of the IGF-I induced genes was coherent and it provided a basis for the segregation of the patients into two groups. Patients with tumours with highly expressed IGF-I induced genes had a significantly lower survival rate than patients whose tumours showed lower levels of IGF-I induced gene expression (P = 0.029 - Norway/Stanford and P = 7.96e-09 - NKI dataset). Furthermore, based on an IGF-I induced gene expression signature derived from primary lung fibroblasts, a separation of prognostically different lung cancers was possible (P = 0.007 - Bhattacharjee and P = 0.008 - Garber dataset). Conclusion: Expression patterns of genes induced by IGF-I in primary breast and lung fibroblasts accurately predict outcomes in breast and lung cancer patients. Furthermore, these IGF-I induced gene signatures derived from stromal fibroblasts might be promising predictors for the response to IGF-I targeted therapies. See the related commentary by Werner and Bruchim: http://www.biomedcentral.com/1741-7015/8/2

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 · 10.1186/1741-7015-8-1

Cites

77 of 77 references verified0 citation errors · 0 not checkable

Statistics

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

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • Brief psychological interventions either using a CBT or ACT approach have demonstrated similar effects of reducing a range of mental health presentations.

    “Brief psychological interventions either using a CBT or ACT approach have demonstrated similar effects of reducing a range of mental health presentations.86 87”

    From Acceptance and commitment therapy for mild traumatic brain injury (ACTion-mTBI): a quasiexperimental feasibility study (2025) · cites this paper as [86]

    The Results section on IGF-I effects and the Discussion address gene expression and cancer outcomes, not psychological interventions. Searches for the quoted claim and for CBT, ACT, and mental-health interventions found no passage comparing their effects. (LLM, conf=0.79)

    Experimental — accuracy not yet measured

Self-check

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

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

Cites

1 retracted

Flagged first, then by citations

Research works printed but not linked: 1

  1. Classification of Human Lung Carcinomas by mRNA Expression Profiling Reveals Distinct Adenocarcinoma Sub-classes 2001 http://www.broad.mit.edu/mpr/lung/ PMC61120 11707567

Cited by

Sorted by citations

Authors
Rajski, M., Zanetti-Dällenbach, R., Vogel, B., Herrmann, R., Rochlitz, C., & Buess, M.
Affiliations
University of Basel (CH)
Corresponding author
Buess, Martin
Venue
BMC Medicine
Published
2010-01-05
Volume
8
Issue
1
Pages
1-1
ISSN
1741-7015 (ISSN-L)
OpenAlex
W2050096609
Cited by
355
References
76
Citations by year
2026: 5 · 2025: 8 · 2024: 17 · 2023: 2 · 2022: 7 · 2021: 43 · 2020: 21 · 2019: 23 · 2018: 32 · 2017: 65 · 2016: 44 · 2015: 18 · 2014: 15 · 2013: 16 · 2012: 18
FWCI
13.03
Type
journal article
Language
en
Open access
Locations
  • BMC Medicine (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
Funders
  • National Science Foundation
  • Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung (112794, 320000)
  • Oncosuisse
Topics
  • Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Growth Hormone and Insulin-like Growth Factors
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Cancer Research › Breast Cancer Treatment Studies
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › TGF-β signaling in diseases
Keywords
insulin-like growth factor I, tumor stroma, stromal fibroblasts, breast cancer, lung cancer, prognostic gene signature, patient survival prediction, tumor cell proliferation
MeSH terms
Breast Neoplasms, Female, Fibroblasts, Humans, Insulin-Like Growth Factor I, Lung Neoplasms, Prognosis, Stimulation, Chemical, Signal Transduction, Up-Regulation, Gene Expression Regulation, Neoplastic, Cluster Analysis, Stromal Cells, Oligonucleotide Array Sequence Analysis, Gene Expression Profiling, Databases, Genetic, Cell Line, Tumor, Cell Growth Processes, Kaplan-Meier Estimate

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