Hormonal Receptor Status Determines Prognostic Significance of FGFR2 in Invasive Breast Carcinoma.
Marcin BraunDominika PiaseckaBartlomiej TomasikKamil MieczkowskiKonrad StawiskiAleksandra ZielinskaJanusz KopczynskiDariusz NejcRadzislaw KordekRafał SądejHanna M RomanskaPublished in: Cancers (2020)
Interaction between fibroblast growth factor receptor 2 (FGFR2) and estrogen/progesterone receptors (ER/PR) affects resistance to anti-ER therapies, however the prognostic value of FGFR2 in breast cancer (BCa) remains largely unexplored. We have recently showed in vitro that FGFR2-mediated signaling alters PR activity and response to anti-ER treatment. Herein, prognostic significance of FGFR2 in BCa was evaluated in relation to both ER/PR protein status and a molecular signature designed to reflect PR transcriptional activity. FGFR2 was examined in 353 BCa cases using immunohistochemistry and Nanostring-based RNA quantification. FGFR2 expression was higher in ER+PR+ and ER+PR- compared to ER-PR- cases (p < 0.001). Low FGFR2 was associated with higher grade (p < 0.001), higher Ki67 proliferation index (p < 0.001), and worse overall and disease-free survival (HR = 2.34 (95% CI: 1.26-4.34), p = 0.007 and HR = 2.22 (95% CI: 1.25-3.93), p = 0.006, respectively). The poor prognostic value of low FGFR2 was apparent in ER+PR+, but not in ER+PR- patients, and it did not depend on the expression level of PR-dependent genes. Despite the functional link between FGFR2 and ER/PR revealed by preclinical studies, the data showed a link between FGFR2 expression and poor prognosis in BCa patients.
Keyphrases
- poor prognosis
- estrogen receptor
- endoplasmic reticulum
- breast cancer cells
- end stage renal disease
- newly diagnosed
- ejection fraction
- free survival
- gene expression
- magnetic resonance
- genome wide
- prognostic factors
- adipose tissue
- dna methylation
- machine learning
- peritoneal dialysis
- mesenchymal stem cells
- patient reported
- young adults
- cell therapy
- diffusion weighted imaging
- artificial intelligence
- big data
- childhood cancer
- combination therapy
- case control