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Multi-regional sequencing provides new opportunities to investigate genetic heterogeneity within or between common tumors from an evolutionary perspective. Several state-of-the-art methods have been proposed for reconstructing cancer evolutionary trees based on multi-regional sequencing data to develop models of cancer evolution. However, there have been few studies on comparisons of a set of cancer evolutionary trees. We propose a clustering method (phyC) for cancer evolutionary trees, in which sub-groups of the trees are identified based on topology and edge length attributes. For interpretation, we also propose a method for evaluating the sub-clonal diversity of trees in the clusters, which provides insight into the acceleration of sub-clonal expansion. Simulation showed that the proposed method can detect true clusters with sufficient accuracy. Application of the method to actual multi-regional sequencing data of clear cell renal carcinoma and non-small cell lung cancer allowed for the detection of clusters related to cancer type or phenotype. phyC is implemented with R(≥3.2.2) and is available from https://github.com/ymatts/phyC.

miR-146a plays important roles in cancer as it directly targets NUMB, an inhibitor of Notch signaling. miR-146a is reportedly regulated by a G>C polymorphism (SNP; rs2910164). This polymorphism affects various cancers, including colorectal cancer (CRC). However, the clinical significance of miR-146a polymorphism in CRC remains unclear. A total of 59 patients with CRC were divided into 2 groups: a CC/CG genotype (n = 32) and a GG genotype (n = 27), based on the miR-146a polymorphism. cDNA microarray analysis was performed using 59 clinical samples. Significantly enriched gene sets in each genotype were extracted using GSEA. We also investigated the association between miR-146a polymorphism and miR-146a, NUMB expression or migratory response in CRC cell lines. The CC/CG genotype was associated with significantly more synchronous liver metastasis (p = 0.007). A heat map of the two genotypes showed that the expression profiles were clearly stratified. GSEA indicated that Notch signaling and JAK/STAT3 signaling were significantly associated with the CC/CG genotype (p = 0.004 and p = 0.023, respectively). CRC cell lines with the pre-miR-146a/C revealed significantly higher miR-146a expression (p = 0.034) and higher NUMB expression and chemotactic activity. In CRC, miR-146a polymorphism is involved in liver metastasis. Identification of this polymorphism could be useful to identify patients with a high risk of liver metastasis in CRC., Competing Interests: The authors have declared that no competing interests exist.

Understanding intratumor heterogeneity is clinically important because it could cause therapeutic failure by fostering evolutionary adaptation. To this end, we profiled the genome and epigenome in multiple regions within each of nine colorectal tumors. Extensive intertumor heterogeneity is observed, from which we inferred the evolutionary history of the tumors. First, clonally shared alterations appeared, in which C>T transitions at CpG site and CpG island hypermethylation were relatively enriched. Correlation between mutation counts and patients' ages suggests that the early-acquired alterations resulted from aging. In the late phase, a parental clone was branched into numerous subclones. Known driver alterations were observed frequently in the early-acquired alterations, but rarely in the late-acquired alterations. Consistently, our computational simulation of the branching evolution suggests that extensive intratumor heterogeneity could be generated by neutral evolution. Collectively, we propose a new model of colorectal cancer evolution, which is useful for understanding and confronting this heterogeneous disease.

Background: Few driver genes have been well established in esophageal squamous cell carcinoma (ESCC). Identification of the genomic aberrations that contribute to changes in gene expression profiles can be used to predict driver genes., Methods: We searched for driver genes in ESCC by integrative analysis of gene expression microarray profiles and copy number data. To narrow down candidate genes, we performed survival analysis on expression data and tested the genetic vulnerability of each genes using public RNAi screening data. We confirmed the results by performing RNAi experiments and evaluating the clinical relevance of candidate genes in an independent ESCC cohort., Results: We found 10 significantly recurrent copy number alterations accompanying gene expression changes, including loci 11q13.2, 7p11.2, 3q26.33, and 17q12, which harbored CCND1, EGFR, SOX2, and ERBB2, respectively. Analysis of survival data and RNAi screening data suggested that GRB7, located on 17q12, was a driver gene in ESCC. In ESCC cell lines harboring 17q12 amplification, knockdown of GRB7 reduced the proliferation, migration, and invasion capacities of cells. Moreover, siRNA targeting GRB7 had a synergistic inhibitory effect when combined with trastuzumab, an anti-ERBB2 antibody. Survival analysis of the independent cohort also showed that high GRB7 expression was associated with poor prognosis in ESCC., Conclusion: Our integrative analysis provided important insights into ESCC pathogenesis. We identified GRB7 as a novel ESCC driver gene and potential new therapeutic target.