Combination of a six microRNA expression profile with four clinicopathological factors for response prediction of systemic treatment in patients with advanced colorectal cancer

Autor: Tineke E. Buffart, Jan Hein T.M. van Waesberghe, Henk M.W. Verheul, Jan Dirk Burggraaf, Gerrit A. Meijer, Daoud Sie, Maarten Neerincx, Nicole C.T. van Grieken, Cornelis Verhoef, Bauke Ylstra, Ram C. Shankaraiah, Paul P. Eijk, Mark A. van de Wiel, Floor S.W. Van Der Wolf-De Lijster, Dennis Poel
Přispěvatelé: Gastroenterology and hepatology, Medical oncology, AGEM - Re-generation and cancer of the digestive system, Human genetics, CCA - Imaging and biomarkers, Pathology, Radiology and nuclear medicine, Epidemiology and Data Science, Amsterdam Neuroscience - Cellular & Molecular Mechanisms, NCA - Brain mechanisms in health and disease, Internal medicine, Surgery, Mathematics, Amsterdam Neuroscience - Complex Trait Genetics
Jazyk: angličtina
Rok vydání: 2018
Předmět:
Male
0301 basic medicine
Oncology
Molecular biology
Colorectal cancer
Cancer Treatment
lcsh:Medicine
Logistic regression
Biochemistry
Cohort Studies
Sequencing techniques
Mathematical and Statistical Techniques
0302 clinical medicine
Medicine and Health Sciences
DNA sequencing
lcsh:Science
Aged
80 and over

Multidisciplinary
Genomics
MicroRNA Expression Profile
Middle Aged
Prognosis
Tumor Resection
Gene Expression Regulation
Neoplastic

Surgical Oncology
Real-time polymerase chain reaction
Area Under Curve
030220 oncology & carcinogenesis
Physical Sciences
Cohort
Disease Progression
Female
Colorectal Neoplasms
Transcriptome Analysis
Statistics (Mathematics)
Research Article
Adult
Next-Generation Sequencing
Clinical Oncology
medicine.medical_specialty
Antineoplastic Agents
Surgical and Invasive Medical Procedures
03 medical and health sciences
SDG 3 - Good Health and Well-being
Internal medicine
Biomarkers
Tumor

Genetics
medicine
Adjuvant therapy
Humans
Clinical significance
Statistical Methods
Differentiated Tumors
Aged
Colorectal Cancer
Surgical Resection
business.industry
lcsh:R
Cancers and Neoplasms
Biology and Life Sciences
Computational Biology
Genome Analysis
medicine.disease
Research and analysis methods
MicroRNAs
Molecular biology techniques
030104 developmental biology
ROC Curve
Metastatic Tumors
lcsh:Q
Clinical Medicine
business
Biomarkers
Mathematics
Progressive disease
Forecasting
Zdroj: PLoS ONE, Vol 13, Iss 8, p e0201809 (2018)
PLoS ONE, 13(8). Public Library of Science
PLoS One (online), 13(8):e0201809. Public Library of Science
PLoS ONE
PLoS ONE, 13(8):e0201809, 1-20. Public Library of Science
Neerincx, M, Poel, D, Sie, D L S, van Grieken, N C T, Shankaraiah, R C, Van Der Wolf-De Lijster, F S W, van Waesberghe, J H T M, Burggraaf, J D, Eijk, P P, Verhoef, C, Ylstra, B, Meijer, G A, van de Wiel, M A, Buffart, T E & Verheul, H M W 2018, ' Combination of a six microRNA expression profile with four clinicopathological factors for response prediction of systemic treatment in patients with advanced colorectal cancer ', PLoS ONE, vol. 13, no. 8, e0201809, pp. 1-20 . https://doi.org/10.1371/journal.pone.0201809
Neerincx, M, Poel, D, Sie, D L S, van Grieken, N C T, Shankaraiah, R C, van der Wolf-de Lijster, F S W, van Waesberghe, J-H T M, Burggraaf, J-D, Eijk, P P, Verhoef, C, Ylstra, B, Meijer, G A, van de Wiel, M A, Buffart, T E & Verheul, H M W 2018, ' Combination of a six microRNA expression profile with four clinicopathological factors for response prediction of systemic treatment in patients with advanced colorectal cancer ', PLoS ONE, vol. 13, no. 8, pp. e0201809 . https://doi.org/10.1371/journal.pone.0201809
ISSN: 1932-6203
DOI: 10.1371/journal.pone.0201809
Popis: BACKGROUND: First line chemotherapy is effective in 75 to 80% of patients with metastatic colorectal cancer (mCRC). We studied whether microRNA (miR) expression profiles can predict treatment outcome for first line fluoropyrimidine containing systemic therapy in patients with mCRC.METHODS: MiR expression levels were determined by next generation sequencing from snap frozen tumor samples of 88 patients with mCRC. Predictive miRs were selected with penalized logistic regression and posterior forward selection. The prediction co-efficients of the miRs were re-estimated and validated by real-time quantitative PCR in an independent cohort of 81 patients with mCRC.RESULTS: Expression levels of miR-17-5p, miR-20a-5p, miR-30a-5p, miR-92a-3p, miR-92b-3p and miR-98-5p in combination with age, tumor differentiation, adjuvant therapy and type of systemic treatment, were predictive for clinical benefit in the training cohort with an AUC of 0.78. In the validation cohort the addition of the six miR signature to the four clinicopathological factors demonstrated a significant increased AUC for predicting treatment response versus those with stable disease (SD) from 0.79 to 0.90. The increase for predicting treatment response versus progressive disease (PD) and for patients with SD versus those with PD was not significant. in the validation cohort. MiR-17-5p, miR-20a-5p and miR-92a-3p were significantly upregulated in patients with treatment response in both the training and validation cohorts.CONCLUSION: A six miR expression signature was identified that predicted treatment response to fluoropyrimidine containing first line systemic treatment in patients with mCRC when combined with four clinicopathological factors. Independent validation demonstrated added predictive value of this miR-signature for predicting treatment response versus SD. However, added predicted value for separating patients with PD could not be validated. The clinical relevance of the identified miRs for predicting treatment response has to be further explored.
Databáze: OpenAIRE
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