Tumor Heterogeneity Predicts Metastatic Potential in Colorectal Cancer

Purpose: Tumors continuously evolve to maintain growth; secondary mutations facilitate this process, resulting in high tumor heterogeneity. In this study, we compared mutations in paired primary and metastatic colorectal cancer tumor samples to determine whether tumor heterogeneity can predict tumor metastasis. Experimental Design: Somatic variations in 46 pairs of matched primary-liver metastatic tumors and 42 primary tumors without metastasis were analyzed by whole-exome sequencing. Tumor clonality was estimated from single-nucleotide and copy-number variations. The correlation between clinical parameters of patients and clonal heterogeneity in liver metastasis was evaluated. Results: Tumor heterogeneity across colorectal cancer samples was highly variable; however, a high degree of tumor heterogeneity was associated with a worse disease-free survival. Highly heterogeneous primary colorectal cancer was correlated with a higher rate of liver metastasis. Recurrent somatic mutations in APC, TP53, and KRAS were frequently detected in highly heterogeneous colorectal cancer. The variant allele frequency of these mutations was high, while somatic mutations in other genes such as PIK3CA and NOTCH1 were low. The number and distribution of primary colorectal cancer subclones were preserved in metastatic tumors. Conclusions: Heterogeneity of primary colorectal cancer tumors can predict the potential for liver metastasis and thus, clinical outcome of patients. Clin Cancer Res; 23(23); 7209–16. ©2017 AACR.

[1]  Steven J. M. Jones,et al.  Comprehensive molecular characterization of human colon and rectal cancer , 2012, Nature.

[2]  A. Bouchard-Côté,et al.  PyClone: statistical inference of clonal population structure in cancer , 2014, Nature Methods.

[3]  B. Giusti,et al.  EXCAVATOR: detecting copy number variants from whole-exome sequencing data , 2013, Genome Biology.

[4]  Vladimir Vacic,et al.  Comparative sequencing analysis reveals high genomic concordance between matched primary and metastatic colorectal cancer lesions , 2014, Genome Biology.

[5]  Noemi Andor,et al.  EXPANDS: expanding ploidy and allele frequency on nested subpopulations , 2013, Bioinform..

[6]  N. Dubrawsky Cancer statistics , 1989, CA: a cancer journal for clinicians.

[7]  B. Taylor,et al.  deconstructSigs: delineating mutational processes in single tumors distinguishes DNA repair deficiencies and patterns of carcinoma evolution , 2016, Genome Biology.

[8]  Richard Durbin,et al.  Sequence analysis Fast and accurate short read alignment with Burrows – Wheeler transform , 2009 .

[9]  A. Jemal,et al.  Cancer statistics, 2014 , 2014, CA: a cancer journal for clinicians.

[10]  Obi L. Griffith,et al.  SciClone: Inferring Clonal Architecture and Tracking the Spatial and Temporal Patterns of Tumor Evolution , 2014, PLoS Comput. Biol..

[11]  C. Meijer,et al.  Somatic mutation in PIK3CA is a late event in cervical carcinogenesis , 2015, The journal of pathology. Clinical research.

[12]  Yu Cao,et al.  Intratumor heterogeneity in localized lung adenocarcinomas delineated by multiregion sequencing , 2014, Science.

[13]  E. Mroz,et al.  Intra-tumor Genetic Heterogeneity and Mortality in Head and Neck Cancer: Analysis of Data from The Cancer Genome Atlas , 2015, PLoS medicine.

[14]  G Smith,et al.  The prognostic significance of K-ras, p53, and APC mutations in colorectal carcinoma , 2005, Gut.

[15]  L. Foroni,et al.  Notch-1 Mutations Are Secondary Events in Some Patients with T-Cell Acute Lymphoblastic Leukemia , 2007, Clinical Cancer Research.

[16]  Y. Samuels,et al.  Oncogenic mutations of PIK3CA in human cancers. , 2004, Current topics in microbiology and immunology.

[17]  Z. Szallasi,et al.  Spatial and temporal diversity in genomic instability processes defines lung cancer evolution , 2014, Science.

[18]  M. DePristo,et al.  The Genome Analysis Toolkit: a MapReduce framework for analyzing next-generation DNA sequencing data. , 2010, Genome research.

[19]  A. McKenna,et al.  Evolution and Impact of Subclonal Mutations in Chronic Lymphocytic Leukemia , 2012, Cell.

[20]  Y. Cho,et al.  Animal models of colorectal cancer with liver metastasis. , 2017, Cancer letters.

[21]  David T. W. Jones,et al.  Signatures of mutational processes in human cancer , 2013, Nature.

[22]  M. D'Angelica,et al.  Meeting the biologic challenge of colorectal metastases , 2012, Clinical & Experimental Metastasis.

[23]  C. Curtis,et al.  A Big Bang model of human colorectal tumor growth , 2015, Nature Genetics.

[24]  Céline Lefebvre,et al.  Comparative analysis of primary tumour and matched metastases in colorectal cancer patients: evaluation of concordance between genomic and transcriptional profiles. , 2015, European journal of cancer.

[25]  Xinbing Sui,et al.  Use of Metformin Alone Is Not Associated with Survival Outcomes of Colorectal Cancer Cell but AMPK Activator AICAR Sensitizes Anticancer Effect of 5-Fluorouracil through AMPK Activation , 2014, PloS one.

[26]  N. McGranahan,et al.  Inferring mutational timing and reconstructing tumour evolutionary histories. , 2015, Biochimica et biophysica acta.

[27]  T. Efferth,et al.  Tumor Heterogeneity, Single-Cell Sequencing, and Drug Resistance , 2016, Pharmaceuticals.