| Literature DB >> 30238073 |
Koshi Mimori1, Tomoko Saito1, Atsushi Niida2, Satoru Miyano3.
Abstract
Undoubtedly, intratumor heterogeneity (ITH) is one of the causes of the intractability of cancers. Recently, technological innovation in genomics has promoted studies on ITH in solid tumors and on the pattern and level of diversity, which varies among malignancies. We profiled the genome in multiple regions of nine colorectal cancer (CRC) cases. The most impressive finding was that in the late phase, a parental clone branched into numerous subclones. We found that minor mutations were dominant in advanced CRC named neutral evolution; that is, driver gene aberrations were observed with high proportion in the early-acquired phase, but low in the late-acquired phase. Then, we validated that neutral evolution could cause ITH in advanced CRC by super-computational analysis. According to the clinical findings, we explored a branching evolutionary process model in cancer evolution, which assumes that each tumor cell has cellular automaton. According to the model, we verified factors to foster ITH with neutral evolution in advanced CRC. In this review, we introduce recent advances in the field of ITH including the general component of ITH, clonal selective factors that consolidate the evolutionary process, and a representative clinical application of ITH.Entities:
Keywords: The ratio between the rate of non‐synonymous substitutions per non‐synonymous site and the rate of synonymous substitutions per synonymous site; cellular automaton; intratumor heterogeneity; variant allele frequency; whole‐exome sequencing
Year: 2018 PMID: 30238073 PMCID: PMC6139712 DOI: 10.1002/ags3.12182
Source DB: PubMed Journal: Ann Gastroenterol Surg ISSN: 2475-0328
Achievements in the field of intratumor heterogeneity and evolutions of solid cancers
| Objectives | Journal | YearRef. | |
|---|---|---|---|
| Brain | 425 Glioma from 54 cases | Nat Genet | 2015 |
| 33 Medulloblastoma samples | Nature | 2016 | |
| 114 Cases of glioblastoma | Nat Genet | 2016 | |
| Breast | 100 Cells from 2 cases | Nature | 2011 |
| 303 Samples from 50 cases | Nat Med | 2015 | |
| 1000 Single cells from 12 cases | Nat Genet | 2016 | |
| 3 ER+HER2‐, 1 TN | PLoS Med | 2016 | |
| 10 Autopsied cases | Nat Commun | 2017 | |
| Colon | 349 Glands from 15 cases | Nat Genet | 2015 |
| 306 Polyps (6–9 mm) | Gut | 2017 | |
| 75 Samples from 10 cases | PLoS Genet | 2016 | |
| Esophagus | 40 Samples from 8 cases | Cancer Discov | 2015 |
| 25 Barrett's from 5 cases | Nat Genet | 2015 | |
| 51 Samples from 13 cases | Nat Genet | 2016 | |
| Head and neck | 1 HNC and 2 nodes | Neoplasia | 2013 |
| Liver | 23 Cases of HCC | Proc Natl Acad Sci USA | 2015 |
| 120 Samples from 23 cases | Clin Cancer Res | 2015 | |
| 43 Samples from 10 HCC | Gastroenterology | 2016 | |
| Lung | 25 Samples from 7 NSCLC | Science | 2014 |
| 11 Lung adenocarcinomas | Science | 2014 | |
| 100 From the TRACERx cohort | Nature | 2017 | |
| 100 Early‐stage NSCLC | N Engl J Med | 2017 | |
| Melanoma | 41 biopsies from 8 cases | Cancer Res | 2016 |
| Ovary | 135 Samples from 14 cases | PLoS Med | 2015 |
| Pancreas | 7 Autopsies | Nature | 2010 |
| 214 Samples | Nature | 2016 | |
| Prostate | 7 Distant metastases | J Clin Invest | 2013 |
| 57 Tumors | Cell | 2013 | |
| 5 Cases for methylation | Cell Rep | 2014 | |
| 10 Cases for resistant to TX | Nature | 2015 | |
| Kidney | 9 Samples from 1 case | N Engl J Med | 2012 |
| 10 Cases for signature | Nat Genet | 2014 | |
| Urothelium | 72 Samples from 16 cases | Nat Genet | 2016 |
Figure 1Branching evolutionary process (BEP) model. A, A cell has n genes, d of which are driver genes. In a unit time step, a cell divides and dies with probabilities p and q, respectively. A cell division mutates each gene with a probability r. One driver mutation increases p by f‐fold. In this model, f indicates strength of the driver genes. B, Population entropy depends on parameters d and f. The division probability increases per driver mutation. Red area indicates negentropy or syntropy, whereas white area indicates entropy. C, Existence of strong driver genes leads to a homogenous tumor. D, Multiple driver genes of moderate strength generate intratumor heterogeneity
Figure 2A, Implementation of environmental selection (n, number of genes; d, number of driver genes). If mutation has occurred in each quadrant of the tumor, selective driver genes increase growth rate. B, Existence of environmental selection can also enhance intratumor heterogeneity, which looks close to the actual heterogenous tumor