Clinical Research Papers:

ColoLipidGene: signature of lipid metabolism-related genes to predict prognosis in stage-II colon cancer patients

Teodoro Vargas _, Juan Moreno-Rubio, Jesús Herranz, Paloma Cejas, Susana Molina, Margarita González-Vallinas, Marta Mendiola, Emilio Burgos, Cristina Aguayo, Ana B. Custodio, Isidro Machado, David Ramos, Meritxell Gironella, Isabel Espinosa-Salinas, Ricardo Ramos, Roberto Martín-Hernández, Alberto Risueño, Javier De Las Rivas, Guillermo Reglero, Ricardo Yaya, Carlos Fernández-Martos, Jorge Aparicio, Joan Maurel, Jaime Feliu and Ana Ramírez de Molina

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Oncotarget. 2015; 6:7348-7363. https://doi.org/10.18632/oncotarget.3130

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Teodoro Vargas1, Juan Moreno-Rubio2,3, Jesús Herranz4, Paloma Cejas2,5, Susana Molina1, Margarita González-Vallinas1, Marta Mendiola2, Emilio Burgos5,6, Cristina Aguayo5,7, Ana B. Custodio5,7, Isidro Machado5,8, David Ramos5,9, Meritxell Gironella5,10, Isabel Espinosa-Salinas1, Ricardo Ramos11, Roberto Martín-Hernández4, Alberto Risueño12, Javier De Las Rivas12, Guillermo Reglero1, Ricardo Yaya5,13, Carlos Fernández-Martos5,13, Jorge Aparicio5,14, Joan Maurel5,15, Jaime Feliu5,7, Ana Ramírez de Molina1

1Molecular Oncology, IMDEA-Food Institute, CEI UAM+CSIC, Madrid (Spain)

2Translational Oncology Laboratory, La Paz University Hospital (IdiPAZ), Madrid (Spain)

3Precision Oncology Laboratory (POL), Infanta Sofía University Hospital, Madrid (Spain)

4Biostatistics and Bioinformatics Unit, IMDEA-Food Institute, CEI UAM+CSIC, Madrid (Spain)

5Grupo Español Multidisciplinar en Cáncer Digestivo (GEMCAD)

6Pathology Department, La Paz University Hospital (IdiPAZ), Madrid (Spain)

7Medical Oncology, La Paz University Hospital (IdiPAZ), Madrid (Spain)

8Pathology Department, Oncologic Institute of Valencia (IVO), Valencia (Spain)

9Molecular Pathology, La Fe University Hospital, Valencia (Spain)

10Gastrointestinal and Pancreatic Oncology, Centro de Investigación Biomédica en Red de Enfermedades Hepáticas y Digestivas (CIBEREHD), Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Hospital Clínic, Barcelona (Spain)

11Genomics Unit, Science Park, Madrid (Spain)

12Bioinformatics and Functional Genomics Research Group, Cancer Research Center (CSIC-USAL), Salamanca (Spain)

13Medical Oncology, Oncologic Institute of Valencia (IVO), Valencia (Spain)

14Medical Oncology, La Fe University Hospital, Valencia (Spain)

15Medical Oncology and Translational Genomics Group and Targeted Therapeutics, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Hospital Clínic, Barcelona (Spain)

Correspondence to:

Ana Ramírez de Molina, e-mail: [email protected]

Keywords: colon cancer, lipid metabolism, biomarker, prognosis

Received: December 22, 2014     Accepted: January 09, 2015     Published: February 06, 2015


Lipid metabolism plays an essential role in carcinogenesis due to the requirements of tumoral cells to sustain increased structural, energetic and biosynthetic precursor demands for cell proliferation. We investigated the association between expression of lipid metabolism-related genes and clinical outcome in intermediate-stage colon cancer patients with the aim of identifying a metabolic profile associated with greater malignancy and increased risk of relapse. Expression profile of 70 lipid metabolism-related genes was determined in 77 patients with stage II colon cancer. Cox regression analyses using c-index methodology was applied to identify a metabolic-related signature associated to prognosis. The metabolic signature was further confirmed in two independent validation sets of 120 patients and additionally, in a group of 264 patients from a public database. The combined analysis of these 4 genes, ABCA1, ACSL1, AGPAT1 and SCD, constitutes a metabolic-signature (ColoLipidGene) able to accurately stratify stage II colon cancer patients with 5-fold higher risk of relapse with strong statistical power in the four independent groups of patients. The identification of a group of 4 genes that predict survival in intermediate-stage colon cancer patients allows delineation of a high-risk group that may benefit from adjuvant therapy, and avoids the toxic and unnecessary chemotherapy in patients classified as low-risk group.

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