bioRxivGenomicsPreprint
Copy-number intratumor heterogeneity contributes to predict relapse in chemotherapy-naive stage II colon cancer
Sara LahoziD, Iván ArchillaiD, Elena AsensioiD, Eva Hernández‐IllániD, Queralt Ferrer, Sandra López‐PradesiD, Ferran NadeuiD, Javier del ReyiD, Rebeca Sanz PamplonaiD, Juan José LozanoiD, Antoni CastellsiD, Míriam CuatrecasasiD, Jordi CampsiD
Abstract
Optimal selection of high-risk patients with stage II colon cancer is crucial to ensure clinical benefit of adjuvant chemotherapy after surgery. Here, we investigate the prognostic and predictive value of genomic intratumor heterogeneity and aneuploidy for disease recurrence. We combined SNP arrays, targeted next-generation sequencing, fluorescence in situ hybridization and inmunohistochemistry on a retrospective cohort of 84 untreated stage II colon cancer patients. We assessed the subclonality of copy-number alterations (CNAs) and mutations, CD8+ lymphocyte infiltration and their association with time to recurrence (TTR). Prognostic factors were included in machine learning analysis to evaluate their ability to predict individual relapse risk. Tumors from recurrent patients (N = 38) exhibited greater proportion of CNAs compared with non-recurrent (N = 46) (mean 31.3% vs. 23%, respectively; P = 0.014), which was confirmed in an independent cohort. Candidate chromosome-specific aberrations included the gain of the chromosome arm 13q (P = 0.02; HR, 2.67) and loss of heterozygosity at 17q22-q24.3 (P = 0.05; HR, 2.69), both associated with shorter TTR. CNA load positively correlated with intratumor heterogeneity (R = 0.52; P < 0.0001), indicating ongoing chromosomal instability. Consistently, subclonal copy-number heterogeneity was associated with elevated risk of relapse (P = 0.028; HR, 2.20), which we did not observe for subclonal mutations. The clinico-genomic model rated an area under the curve of 0.83, achieving a 10% incremental gain compared to clinicopathological markers. In conclusion, tumor aneuploidy and copy-number heterogeneity were predictive of a poor outcome in early-stage colon cancer, and improved discriminative performance in comparison to clinicopathological data.
- organism: human
- assay: bulk RNA-seq
- research focus: differential expression
- approach: machine learning (classical)
- Citations
- 2
Reproducibility ledger
Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.
Sign in to file a reproducibility report.
Related papers
- Spatial tumour gene signature discriminates neoplastic from non-neoplastic compartments in colon cancer: unravelling predictive biomarkers for relapse
K. Sallinger, M. Gruber, … A. El-Heliebi·bioRxiv·Sep 27, 2022
- Molecular subtyping improves prognostication of Stage 2 colorectal cancer
R. V. Purcell, S. Schmeier, … F. A. Frizelle·bioRxiv·Jun 20, 2019
- Lymph Node Morphology in Stage II Colorectal Cancer
A. Greenwood, J. Keating, … K. Danielson·bioRxiv·Apr 21, 2020
- Negative selection may cause grossly altered but broadly stable karyotypes in metastatic colorectal cancer
W. Cross, S. Nowinski, … Wat·bioRxiv·Mar 26, 2020
- Loss of cyclin A2 in murine colonic epithelial cells disrupts colon homeostasis by triggering DNA damage and dysplasia and high cyclin A2 expression is a good-prognosis factor in patients with colorectal cancer
- Bcl-xL as a poor prognostic biomarker and predictor of response to adjuvant chemotherapy specifically in BRAF-mutant stage II and III colon cancer
P. D. Dunne, H. G. Coleman, … M. Lawler·bioRxiv·Oct 23, 2017