A monotonic and prognostic genomic signature from fibroblasts for colorectal cancer initiation, progression, and metastasis

• Published in: Molecular cancer research Vol. 12; no. 9; pp. 1254 - 1266
• Main Authors: Berdiel-Acer, Mireia, Cuadras, Daniel, Díaz-Maroto, Natalia Guillén, Sanjuan, Xavier, Serrano, Teresa, Berenguer, Antoni, Moreno, Victor, Gonçalves-Ribeiro, Samuel, Salazar, Ramon, Villanueva, Alberto, Molleví, David G
• Format: Journal Article
• Language: English
• Published: United States 01.09.2014
• Subjects: Carcinogenesis - genetics; Colorectal Neoplasms - diagnosis; Colorectal Neoplasms - genetics; Colorectal Neoplasms - pathology; Fibroblasts - metabolism; Fibroblasts - pathology; Gene Expression Regulation, Neoplastic; Genome, Human; Humans; Neoplasm Metastasis; Neoplasm Recurrence, Local - genetics; Neoplasm Recurrence, Local - pathology; Prognosis; Transcriptome
• ISSN: 1541-7786; 1557-3125
• DOI: 10.1158/1541-7786.mcr-14-0121

The differential gene expression patterns between normal colonic fibroblasts (NCF), carcinoma-associated fibroblasts from primary tumors (CAF-PT), and CAFs from hepatic metastasis (CAF-LM) are hypothesized to be useful for predicting relapse in primary tumors. A transcriptomic profile of NCF (n = 9), CAF-PT (n = 14), and CAF-LM (n = 11) was derived. Prediction Analysis of Microarrays (PAM) was used to obtain molecular details for each fibroblast class, and differentially expressed transcripts were used to classify patients according to recurrence status. A number of transcripts (n = 277) were common to all three types of fibroblasts and whose expression level was sequentially deregulated according to the transition: NCF→CAF-PT→CAF-LM. Importantly, the gene signature was able to accurately classify patients with primary tumors according to their prognosis. This capacity was exploited to obtain a refined 19-gene classifier that predicted recurrence with high accuracy in two independent datasets of patients with colorectal cancer and correlates with fibroblast migratory potential. The prognostic power of this genomic signature is strong evidence of the link between the tumor-stroma microenvironment and cancer progression. Furthermore, the 19-gene classifier was able to identify low-risk patients very accurately, which is of particular importance for stage II patients, who would benefit from the omission of chemotherapy, especially T4N0 patients, who are clinically classified as being at high risk. A defined stromal gene expression signature predicts relapse in patients with colorectal cancer.