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Understanding cancer evolution provides a clue to tackle therapeutic difficulties in colorectal cancer. In this review, together with related works, we will introduce a series of our studies, in which we constructed an evolutionary model of colorectal cancer by combining genomic analysis and mathematical modeling. In our model, multiple subclones were generated by driver mutation acquisition and subsequent clonal expansion in early-stage tumors. Among the subclones, the one obtaining driver copy number alterations is endowed with malignant potentials to constitute a late-stage tumor in which extensive intratumor heterogeneity is generated by the accumulation of neutral mutations. We will also discuss how to translate our understanding of cancer evolution to a solution to the problem related to therapeutic resistance: mathematical modeling suggests that relapse caused by acquired resistance could be suppressed by utilizing clonal competition between sensitive and resistant clones. Considering the current rate of technological development, modeling cancer evolution by combining genomic analysis and mathematical modeling will be an increasingly important approach for understanding and overcoming cancer.

Seishi Ogawa, Atsushi Natsume and colleagues report analyses of large sets of sequence data of grade II and III gliomas. They find three distinct subtypes of grade II and III gliomas characterized by discrete mutation profiles and distinct clinical behaviors. Grade II and III gliomas are generally slowly progressing brain cancers, many of which eventually transform into more aggressive tumors. Despite recent findings of frequent mutations in IDH1 and other genes, knowledge about their pathogenesis is still incomplete. Here, combining two large sets of high-throughput sequencing data, we delineate the entire picture of genetic alterations and affected pathways in these glioma types, with sensitive detection of driver genes. Grade II and III gliomas comprise three distinct subtypes characterized by discrete sets of mutations and distinct clinical behaviors. Mutations showed significant positive and negative correlations and a chronological hierarchy, as inferred from different allelic burdens among coexisting mutations, suggesting that there is functional interplay between the mutations that drive clonal selection. Extensive serial and multi-regional sampling analyses further supported this finding and also identified a high degree of temporal and spatial heterogeneity generated during tumor expansion and relapse, which is likely shaped by the complex but ordered processes of multiple clonal selection and evolutionary events.

Cancer is composed of multiple cell populations with different genomes. This phenomenon called intratumor heterogeneity (ITH) is supposed to be a fundamental cause of therapeutic failure. Therefore, its principle‐level understanding is a clinically important issue. To achieve this goal, an interdisciplinary approach combining genome analysis and mathematical modeling is essential. For example, we have recently performed multiregion sequencing to unveil extensive ITH in colorectal cancer. Moreover, by employing mathematical modeling of cancer evolution, we demonstrated that it is possible that this ITH is generated by neutral evolution. In this review, we introduce recent advances in a research field related to ITH and also discuss strategies for exploiting novel findings on ITH in a clinical setting. In this review, we introduce recent findings on intratumor heterogeneity (ITH) revealed by genome analysis and mathematical modeling and also discuss treatment strategies based upon ITH in a clinical setting.

Seishi Ogawa and colleagues report an integrated genomics analysis of more than 100 clear-cell renal carcinoma samples. They analyze whole genomes or exomes, RNA sequences and DNA methylation in ∼100 paired specimens and perform SNP array-based copy number analysis for 240 specimens. They identify new recurrently mutated pathways and new associations between DNA methylation, mutations, gene expression and copy number profiles. Clear-cell renal cell carcinoma (ccRCC) is the most prevalent kidney cancer and its molecular pathogenesis is incompletely understood. Here we report an integrated molecular study of ccRCC in which ≥100 ccRCC cases were fully analyzed by whole-genome and/or whole-exome and RNA sequencing as well as by array-based gene expression, copy number and/or methylation analyses. We identified a full spectrum of genetic lesions and analyzed gene expression and DNA methylation signatures and determined their impact on tumor behavior. Defective VHL-mediated proteolysis was a common feature of ccRCC, which was caused not only by VHL inactivation but also by new hotspot TCEB1 mutations, which abolished Elongin C–VHL binding, leading to HIF accumulation. Other newly identified pathways and components recurrently mutated in ccRCC included PI3K-AKT-mTOR signaling, the KEAP1-NRF2-CUL3 apparatus, DNA methylation, p53-related pathways and mRNA processing. This integrated molecular analysis unmasked new correlations between DNA methylation, gene mutation and/or gene expression and copy number profiles, enabling the stratification of clinical risks for patients with ccRCC.

An essential step in the analysis of agent-based simulation is sensitivity analysis, which namely examines the dependency of parameter values on simulation results. Although a number of approaches have been proposed for sensitivity analysis, they still have limitations in exhaustivity and interpretability. In this study, we propose a novel methodology for sensitivity analysis of agent-based simulation, MASSIVE (Massively parallel Agent-based Simulations and Subsequent Interactive Visualization-based Exploration). MASSIVE takes a unique paradigm, which is completely different from those of sensitivity analysis methods developed so far, By combining massively parallel computation and interactive data visualization, MASSIVE enables us to inspect a broad parameter space intuitively. We demonstrated the utility of MASSIVE by its application to cancer evolution simulation, which successfully identified conditions that generate heterogeneous tumors. We believe that our approach would be a de facto standard for sensitivity analysis of agent-based simulation in an era of evergrowing computational technology. All the results form our MASSIVE analysis are available at https://www.hgc.jp/~niiyan/massive.

Clonal hematopoiesis (CH) in apparently healthy individuals is implicated in the development of hematological malignancies (HM) and cardiovascular diseases. Previous studies of CH analyzed either single-nucleotide variants and indels (SNVs/indels) or copy number alterations (CNAs), but not both. Here, using a combination of targeted sequencing of 23 CH-related genes and array-based CNA detection of blood-derived DNA, we have delineated the landscape of CH-related SNVs/indels and CNAs in 11,234 individuals without HM from the BioBank Japan cohort, including 672 individuals with subsequent HM development, and studied the effects of these somatic alterations on mortality from HM and cardiovascular disease, as well as on hematological and cardiovascular phenotypes. The total number of both types of CH-related lesions and their clone size positively correlated with blood count abnormalities and mortality from HM. CH-related SNVs/indels and CNAs exhibited statistically significant co-occurrence in the same individuals. In particular, co-occurrence of SNVs/indels and CNAs affecting DNMT3A , TET2 , JAK2 and TP53 resulted in biallelic alterations of these genes and was associated with higher HM mortality. Co-occurrence of SNVs/indels and CNAs also modulated risks for cardiovascular mortality. These findings highlight the importance of detecting both SNVs/indels and CNAs in the evaluation of CH. Analysis of single-nucleotide variants and copy number alterations gives a more complete picture of clonal hematopoiesis and its impact on hematological malignancy and cardiovascular disease.

The quiescent (G0) phase of the cell cycle is the reversible phase from which the cells exit from the cell cycle. Due to the difficulty of defining the G0 phase, quiescent cells have not been well characterized. In this study, a fusion protein consisting of mVenus and a defective mutant of CDK inhibitor, p27 (p27K − ) was shown to be able to identify and isolate a population of quiescent cells and to effectively visualize the G0 to G1 transition. By comparing the expression profiles of the G0 and G1 cells defined by mVenus-p27K − , we have identified molecular features of quiescent cells. Quiescence is also an important feature of many types of stem cells and mVenus-p27K − -transgenic mice enabled the detection of the quiescent cells with muscle stem cell markers in muscle in vivo. The mVenus-p27K − probe could be useful in investigating stem cells as well as quiescent cells.

MicroRNAs (miRNAs) are key post-transcriptional regulators of gene expression and commonly deregulated in carcinogenesis. To explore functionally crucial tumor-suppressive (TS)-miRNAs in hepatocellular carcinoma (HCC), we performed integrative function- and expression-based screenings of TS-miRNAs in six HCC cell lines. The screenings identified seven miRNAs, which showed growth-suppressive activities through the overexpression of each miRNA and were endogenously downregulated in HCC cell lines. Further expression analyses using a large panel of HCC cell lines and primary tumors demonstrated four miRNAs, miR-101, -195, -378 and -497, as candidate TS-miRNAs frequently silenced in HCCs. Among them, two clustered miRNAs miR-195 and miR-497 showed significant growth-suppressive activity with induction of G1 arrest. Comprehensive exploration of their targets using Argonute2-immunoprecipitation-deep-sequencing (Ago2-IP-seq) and genome-wide expression profiling after their overexpression followed by pathway analysis, revealed a significant enrichment of cell cycle regulators. Among the candidates, we successfully identified CCNE1, CDC25A, CCND3, CDK4, and BTRC as direct targets for miR-497 and miR-195. Moreover, target genes frequently upregulated in HCC in a tumor-specific manner, such as CDK6, CCNE1, CDC25A and CDK4, showed an inverse correlation in the expression of miR-195 and miR-497, and their targets. These results suggest the molecular pathway regulating cell cycle progression to be integrally altered by downregulation of miR-195 and miR-497 expression, leading to the aberrant cell proliferation in hepatocarcinogenesis.

Considering the cost and invasiveness of monitoring postoperative minimal residual disease (MRD) of colorectal cancer (CRC) after adjuvant chemoradiotherapy (ACT), we developed a favorable approach based on methylated circulating tumor DNA to detect MRD after radical resection. Analyzing the public database, we identified the methylated promoter regions of the genes FGD5, GPC6, and MSC. Using digital polymerase chain reaction (dPCR), we termed the “amplicon of methylated sites using a specific enzyme” assay as “AMUSE.” We examined 180 and 114 pre‐ and postoperative serial plasma samples from 28 recurrent and 19 recurrence‐free pathological stage III CRC patients, respectively. The results showed 22 AMUSE‐positive of 28 recurrent patients (sensitivity, 78.6%) and 17 AMUSE‐negative of 19 recurrence‐free patients (specificity, 89.5%). AMUSE predicted recurrence 208 days before conventional diagnosis using radiological imaging. Regarding ACT evaluation by the reactive response, 19 AMUSE‐positive patients during their second or third blood samples showed a significantly poorer prognosis than the other patients (p = 9E‐04). The AMUSE assay stratified four groups by the altered patterns of tumor burden postoperatively. Interestingly, only 34.8% of cases tested AMUSE‐negative during ACT treatment, indicating eligibility for ACT. The AMUSE assay addresses the clinical need for accurate MRD monitoring with universal applicability, minimal invasiveness, and cost‐effectiveness, thereby enabling the timely detection of recurrences. This assay can effectively evaluate the efficacy of ACT in patients with stage III CRC following curative resection. Our study strongly recommends reevaluating the clinical application of ACT using the AMUSE assay. We developed a method called AMUSE, utilizing methylated circulating tumor DNA, to detect minimal residual disease (MRD) in colorectal cancer (CRC) patients after treatment. The AMUSE assay displayed high sensitivity and specificity in predicting cancer recurrence earlier than traditional imaging methods and also evaluated the efficacy of adjuvant chemoradiotherapy in these patients. The study highlights the potential of the AMUSE assay for noninvasive, cost‐effective MRD monitoring and suggests reconsidering chemoradiotherapy application using this method.

Advanced colorectal cancer harbors extensive intratumor heterogeneity shaped by neutral evolution; however, intratumor heterogeneity in colorectal precancerous lesions has been poorly studied. We perform multiregion whole-exome sequencing on ten early colorectal tumors, which contained adenoma and carcinoma in situ. By comparing with sequencing data from advanced colorectal tumors, we show that the early tumors accumulate a higher proportion of subclonal driver mutations than the advanced tumors, which is highlighted by subclonal mutations in KRAS and APC . We also demonstrate that variant allele frequencies of subclonal mutations tend to be higher in early tumors, suggesting that the subclonal mutations are subject to selective sweep in early tumorigenesis while neutral evolution is dominant in advanced ones. This study establishes that the evolutionary principle underlying intratumor heterogeneity shifts from Darwinian to neutral evolution during colorectal tumor progression. Advanced colorectal cancers are characterised by intra-tumour heterogeneity dictated by neutral evolution. Here the authors analyse early colorectal tumours by whole-exome sequencing and find that Darwinian evolution determines the fate of early lesions in colorectal adenoma and carcinoma in situ.