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Mechanisms and clinical implications of tumor heterogeneity and convergence on recurrent phenotypes

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Abstract

Tumor heterogeneity has been identified at various -omic levels. The tumor genome, transcriptome, proteome, and phenome can vary widely across cells in patient tumors and are influenced by tumor cell interactions with heterogeneous physical conditions and cellular components of the tumor microenvironment. Here, we explore the concept that while variation exists at multiple -omic levels, changes at each of these levels converge on the same pathways and lead to convergent phenotypes in tumors that can provide common drug targets. These phenotypes include cellular growth and proliferation, sustained oncogenic signaling, and immune avoidance, among others. Tumor heterogeneity complicates treatment of patient cancers as it leads to varied response to therapies. Identification of convergent cellular phenotypes arising in patient cancers and targeted therapies that reverse them has the potential to transform the way clinicians treat these cancers and to improve patient outcome.

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References

  1. Nowell PC (1976) The clonal evolution of tumor cell populations. Science 194:23–28

    Article  CAS  PubMed  Google Scholar 

  2. Bedard PL, Hansen AR, Ratain MJ, Siu LL (2013) Tumour heterogeneity in the clinic. Nature 501:355–364

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  3. Jamal-Hanjani M, Quezada SA, Larkin J, Swanton C (2015) Translational implications of tumor heterogeneity. Clin Cancer Res:Off J Am Assoc Cancer Res 21:1258–1266

    Article  CAS  Google Scholar 

  4. Sottoriva A, Spiteri I, Piccirillo SGM, Touloumis A, Collins VP, Marioni JC, Curtis C, Watts C, Tavaré S (2013) Intratumor heterogeneity in human glioblastoma reflects cancer evolutionary dynamics. Proc Natl Acad Sci 110:4009–4014

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  5. Turtoi A, Blomme A, Debois D, Somja J, Delvaux D, Patsos G, Di Valentin E, Peulen O, Mutijima EN, De Pauw E et al (2014) Organized proteomic heterogeneity in colorectal cancer liver metastases and implications for therapies. Hepatology 59:924–934

    Article  CAS  PubMed  Google Scholar 

  6. Brocks D, Assenov Y, Minner S, Bogatyrova O, Simon R, Koop C, Oakes C, Zucknick M, Lipka Daniel B, Weischenfeldt J et al (2014) Intratumor DNA methylation heterogeneity reflects clonal evolution in aggressive prostate cancer. Cell Rep 8:798–806

    Article  CAS  PubMed  Google Scholar 

  7. Gorges TM, Kuske A, Röck K, Mauermann O, Müller V, Peine S, Verpoort K, Novosadova V, Kubista M, Riethdorf S et al (2016) Accession of tumor heterogeneity by multiplex transcriptome profiling of single circulating tumor cells. Clin Chem 62:1504

    Article  CAS  PubMed  Google Scholar 

  8. Li S, Garrett-Bakelman FE, Chung SS, Sanders MA, Hricik T, Rapaport F, Patel J, Dillon R, Vijay P, Brown AL et al (2016) Distinct evolution and dynamics of epigenetic and genetic heterogeneity in acute myeloid leukemia. Nat Med 22:792–799

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Schwarz RF, Ng CKY, Cooke SL, Newman S, Temple J, Piskorz AM, Gale D, Sayal K, Murtaza M, Baldwin PJ et al (2015) Spatial and temporal heterogeneity in high-grade serous ovarian cancer: a phylogenetic analysis. PLoS Med 12:e1001789

    Article  PubMed  PubMed Central  Google Scholar 

  10. Hao J-J, Lin D-C, Dinh HQ, Mayakonda A, Jiang Y-Y, Chang C, Jiang Y, Lu C-C, Shi Z-Z, Xu X et al (2016) Spatial intratumor heterogeneity of genetic, epigenetic alterations and temporal clonal evolution in esophageal squamous cell carcinoma. Nat Genet 48:1500–1507

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Swanton C (2012) Intratumour heterogeneity: evolution through space and time. Cancer Res 72:4875–4882

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Sveen A, Løes IM, Alagaratnam S, Nilsen G, Høland M, Lingjærde OC, Sorbye H, Berg KCG, Horn A, Angelsen J-H et al (2016) Intra-patient inter-metastatic genetic heterogeneity in colorectal cancer as a key determinant of survival after curative liver resection. PLoS Genet 12:e1006225

    Article  PubMed  PubMed Central  Google Scholar 

  13. Tellez-Gabriel M, Ory B, Lamoureux F, Heymann M-F, Heymann D (2016) Tumour heterogeneity: the key advantages of single-cell analysis. Int J Mol Sci 17:2142

    Article  PubMed Central  Google Scholar 

  14. Winge Ö (1930) Zytologische Untersuchungen über die Natur maligner Tumoren. Z Zellforsch Mikrosk Anat 10:683–735

    Article  Google Scholar 

  15. Levan A (1956) Chromosomes in cancer tissue. Ann N Y Acad Sci 63:774–792

    Article  CAS  PubMed  Google Scholar 

  16. Schilsky RL (1987) Clinical implications of tumor heterogeneity. In: Neth R, Gallo RC, Greaves MF, Kabisch H (eds) Modern trends in human leukemia VII: new results in clinical and biological research including pediatric oncology. Springer Berlin Heidelberg, Berlin, Heidelberg, pp 278–282

    Chapter  Google Scholar 

  17. Trainer AH, Lewis CR, Tucker K, Meiser B, Friedlander M, Ward RL (2010) The role of BRCA mutation testing in determining breast cancer therapy. Nat Rev Clin Oncol 7:708–717

    Article  CAS  PubMed  Google Scholar 

  18. Cagle PT, Allen TC (2012) Lung cancer genotype-based therapy and predictive biomarkers: present and future. Arch Pathol Lab Med 136:1482–1491

    Article  CAS  PubMed  Google Scholar 

  19. Jekunen A (2014) Clinicians’ expectations for gene-driven cancer therapy. Clin Med Insights Oncol 8:159–164

    Article  PubMed  PubMed Central  Google Scholar 

  20. Campbell PJ, Pleasance ED, Stephens PJ, Dicks E, Rance R, Goodhead I, Follows GA, Green AR, Futreal PA, Stratton MR (2008) Subclonal phylogenetic structures in cancer revealed by ultra-deep sequencing. Proc Natl Acad Sci U S A 105:13081–13086

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Shah SP, Morin RD, Khattra J, Prentice L, Pugh T, Burleigh A, Delaney A, Gelmon K, Guliany R, Senz J et al (2009) Mutational evolution in a lobular breast tumour profiled at single nucleotide resolution. Nature 461:809–813

    Article  CAS  PubMed  Google Scholar 

  22. Boutros PC, Fraser M, Harding NJ, de Borja R, Trudel D, Lalonde E, Meng A, Hennings-Yeomans PH, McPherson A, Sabelnykova VY et al (2015) Spatial genomic heterogeneity within localized, multifocal prostate cancer. Nat Genet 47:736–745

    Article  CAS  PubMed  Google Scholar 

  23. Hardiman KM, Ulintz PJ, Kuick RD, Hovelson DH, Gates CM, Bhasi A, Rodrigues Grant A, Liu J, Cani AK, Greenson JK et al (2016) Intra-tumor genetic heterogeneity in rectal cancer. Lab Investig 96:4–15

    Article  CAS  PubMed  Google Scholar 

  24. Ling S, Hu Z, Yang Z, Yang F, Li Y, Lin P, Chen K, Dong L, Cao L, Tao Y et al (2015) Extremely high genetic diversity in a single tumor points to prevalence of non-Darwinian cell evolution. Proc Natl Acad Sci U S A 112:E6496–E6505

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Morrissy AS, Cavalli FMG, Remke M, Ramaswamy V, Shih DJH, Holgado BL, Farooq H, Donovan LK, Garzia L, Agnihotri S et al (2017) Spatial heterogeneity in medulloblastoma. Nat Genet 49:780–788

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. Werner B, Traulsen A, Sottoriva A, Dingli D (2017) Detecting truly clonal alterations from multi-region profiling of tumours. Sci Rep 7:44991

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. Lin D-C, Mayakonda A, Dinh HQ, Huang P, Lin L, Liu X, L-w D, Wang J, Berman BP, Song E-W et al (2017) Genomic and epigenomic heterogeneity of hepatocellular carcinoma. Cancer Res 77:2255–2265

    Article  CAS  PubMed  Google Scholar 

  28. Aihara K, Mukasa A, Nagae G, Nomura M, Yamamoto S, Ueda H, Tatsuno K, Shibahara J, Takahashi M, Momose T et al (2017) Genetic and epigenetic stability of oligodendrogliomas at recurrence. Acta Neuropathol Commun 5:18

    Article  PubMed  PubMed Central  Google Scholar 

  29. Savas P, Teo ZL, Lefevre C, Flensburg C, Caramia F, Alsop K, Mansour M, Francis PA, Thorne HA, Silva MJ et al (2016) The subclonal architecture of metastatic breast cancer: results from a prospective community-based rapid autopsy program “CASCADE”. PLoS Med 13:e1002204

    Article  PubMed  PubMed Central  Google Scholar 

  30. Ng CKY, Bidard F-C, Piscuoglio S, Geyer FC, Lim RS, de Bruijn I, Shen R, Pareja F, Berman SH, Wang L et al (2017) Genetic heterogeneity in therapy-naïve synchronous primary breast cancers and their metastases. Clin Cancer Res. https://doi.org/10.1158/1078-0432.ccr-16-3115

  31. Castellarin M, Milne K, Zeng T, Tse K, Mayo M, Zhao Y, Webb JR, Watson PH, Nelson BH, Holt RA (2013) Clonal evolution of high-grade serous ovarian carcinoma from primary to recurrent disease. J Pathol 229:515–524

    Article  CAS  PubMed  Google Scholar 

  32. Patch A-M, Christie EL, Etemadmoghadam D, Garsed DW, George J, Fereday S, Nones K, Cowin P, Alsop K, Bailey PJ et al (2015) Whole-genome characterization of chemoresistant ovarian cancer. Nature 521:489–494

    Article  CAS  PubMed  Google Scholar 

  33. De Mattos-Arruda L, Weigelt B, Cortes J, Won HH, Ng CKY, Nuciforo P, Bidard FC, Aura C, Saura C, Peg V et al (2014) Capturing intra-tumor genetic heterogeneity by de novo mutation profiling of circulating cell-free tumor DNA: a proof-of-principle. Ann Oncol 25:1729–1735

    Article  PubMed  Google Scholar 

  34. Frenel JS, Carreira S, Goodall J, Roda D, Perez-Lopez R, Tunariu N, Riisnaes R, Miranda S, Figueiredo I, NavaRodrigues D et al (2015) Serial next generation sequencing of circulating cell free DNA evaluating tumour clone response to molecularly targeted drug administration. Clin Cancer Res:Off J Am Assoc Cancer Res 21:4586–4596

    Article  CAS  Google Scholar 

  35. Murtaza M, Dawson S-J, Pogrebniak K, Rueda OM, Provenzano E, Grant J, Chin S-F, Tsui DWY, Marass F, Gale D et al (2015) Multifocal clonal evolution characterized using circulating tumour DNA in a case of metastatic breast cancer. Nat Commun 6:8760

  36. Abbosh C, Birkbak NJ, Wilson GA, Jamal-Hanjani M, Constantin T, Salari R, Le Quesne J, Moore DA, Veeriah S, Rosenthal R et al (2017) Phylogenetic ctDNA analysis depicts early-stage lung cancer evolution. Nature 545:446–451

    Article  CAS  PubMed  Google Scholar 

  37. Bulfoni M, Turetta M, Del Ben F, Di Loreto C, Beltrami AP, Cesselli D (2016) Dissecting the heterogeneity of circulating tumor cells in metastatic breast cancer: going far beyond the needle in the haystack. Int J Mol Sci 17:1775

    Article  PubMed Central  Google Scholar 

  38. Chabon JJ, Simmons AD, Lovejoy AF, Esfahani MS, Newman AM, Haringsma HJ, Kurtz DM, Stehr H, Scherer F, Karlovich CA et al (2016) Circulating tumour DNA profiling reveals heterogeneity of EGFR inhibitor resistance mechanisms in lung cancer patients. Nat Commun 7:11815

  39. Han X, Wang J, Sun Y (2017) Circulating tumor DNA as biomarkers for cancer detection. Genomics Proteomics & Bioinformatics 15:59–72

    Article  Google Scholar 

  40. Navin NE (2015) The first five years of single-cell cancer genomics and beyond. Genome Res 25:1499–1507

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  41. Ross EM, Markowetz F (2016) OncoNEM: inferring tumor evolution from single-cell sequencing data. Genome Biol 17:69

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  42. Navin N, Kendall J, Troge J, Andrews P, Rodgers L, McIndoo J (2011) Tumour evolution inferred by single-cell sequencing. Nature 472:90–94

  43. Wang Y, Waters J, Leung ML, Unruh A, Roh W, Shi X (2014) Clonal evolution in breast cancer revealed by single nucleus genome sequencing. Nature 512:155–160

  44. Li C, Wu S, Yang Z, Zhang X, Zheng Q, Lin L, Niu Z, Li R, Cai Z, Li L (2017) Single-cell exome sequencing identifies mutations in KCP, LOC440040, and LOC440563 as drivers in renal cell carcinoma stem cells. Cell Res 27:590–593

    Article  CAS  PubMed  Google Scholar 

  45. Welch JS, Ley TJ, Link DC, Miller CA, Larson DE, Koboldt DC, Wartman LD, Lamprecht TL, Liu F, Xia J et al (2012) The origin and evolution of mutations in acute myeloid leukemia. Cell 150:264–278

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  46. Watson IR, Takahashi K, Futreal PA, Chin L (2013) Emerging patterns of somatic mutations in cancer. Nat Rev Genet 14:703–718

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  47. Xu X, Hou Y, Yin X, Bao L, Tang A, Song L (2012) Single-cell exome sequencing reveals single-nucleotide mutation characteristics of a kidney tumor. Cell 148(5):886–895

  48. Hou Y, Song L, Zhu P, Zhang B, Tao Y, Xu X (2012) Single-cell exome sequencing and monoclonal evolution of a JAK2-negative myeloproliferative neoplasm. Cell 148(5):873–85

  49. Qiu P, Simonds EF, Bendall SC, Gibbs KD Jr, Bruggner RV, Linderman MD, Sachs K, Nolan GP, Plevritis SK (2011) Extracting a cellular hierarchy from high-dimensional cytometry data with SPADE. Nat Biotech 29:886–891

    Article  CAS  Google Scholar 

  50. Anchang B, Hart TDP, Bendall SC, Qiu P, Bjornson Z, Linderman M, Nolan GP, Plevritis SK (2016) Visualization and cellular hierarchy inference of single-cell data using SPADE. Nat Protocols 11:1264–1279

    Article  CAS  PubMed  Google Scholar 

  51. Saadatpour A, Lai S, Guo G, Yuan G-C (2015) Single-cell analysis in cancer genomics. Trends Genet: TIG 31:576–586

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  52. Patel AP, Tirosh I, Trombetta JJ, Shalek AK, Gillespie SM, Wakimoto H, Cahill DP, Nahed BV, Curry WT, Martuza RL et al (2014) Single-cell RNA-seq highlights intratumoral heterogeneity in primary glioblastoma. Science 344:1396–1401

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  53. Tirosh I, Venteicher AS, Hebert C, Escalante LE, Patel AP, Yizhak K, Fisher JM, Rodman C, Mount C, Filbin MG et al (2016) Single-cell RNA-seq supports a developmental hierarchy in human oligodendroglioma. Nature 539:309–313

    Article  PubMed  Google Scholar 

  54. Zhang X, Zhang M, Hou Y, Xu L, Li W, Zou Z, Liu C, Xu A, Wu S (2016) Single-cell analyses of transcriptional heterogeneity in squamous cell carcinoma of urinary bladder. Oncotarget 7:66069–66076

    PubMed  PubMed Central  Google Scholar 

  55. Chung W, Eum HH, Lee H-O, Lee K-M, Lee H-B, Kim K-T, Ryu HS, Kim S, Lee JE, Park YH et al (2017) Single-cell RNA-seq enables comprehensive tumour and immune cell profiling in primary breast cancer. Nat Commun 8:15081

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  56. Ahmed N, Greening D, Samardzija C, Escalona RM, Chen M, Findlay JK, Kannourakis G (2016) Unique proteome signature of post-chemotherapy ovarian cancer ascites-derived tumor cells. Scientific Reports 6:30061

  57. Kim M-S, Zhong Y, Yachida S, Rajeshkumar NV, Abel ML, Marimuthu A, Mudgal K, Hruban RH, Poling JS, Tyner JW et al (2014) Heterogeneity of pancreatic cancer metastases in a single patient revealed by quantitative proteomics. Mol Cell Proteomics: MCP 13:2803–2811

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  58. Edmondson R, Broglie JJ, Adcock AF, Yang L (2014) Three-dimensional cell culture systems and their applications in drug discovery and cell-based biosensors. Assay Drug Dev Technol 12:207–218

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  59. Giesen C, Wang HAO, Schapiro D, Zivanovic N, Jacobs A, Hattendorf B, Schuffler PJ, Grolimund D, Buhmann JM, Brandt S et al (2014) Highly multiplexed imaging of tumor tissues with subcellular resolution by mass cytometry. Nat Meth 11:417–422

    Article  CAS  Google Scholar 

  60. Sood A, Miller AM, Brogi E, Sui Y, Armenia J, McDonough E, Santamaria-Pang A, Carlin S, Stamper A, Campos C et al (2016) Multiplexed immunofluorescence delineates proteomic cancer cell states associated with metabolism. JCI Insight 1:e87030

    Article  PubMed  PubMed Central  Google Scholar 

  61. Gupta Piyush B, Fillmore Christine M, Jiang G, Shapira Sagi D, Tao K, Kuperwasser C, Lander Eric S (2011) Stochastic state transitions give rise to phenotypic equilibrium in populations of cancer cells. Cell 146:633–644

    Article  CAS  PubMed  Google Scholar 

  62. Nichol D, Robertson-Tessi M, Jeavons P, Anderson ARA (2016) Stochasticity in the genotype-phenotype map: implications for the robustness and persistence of bet-hedging. Genetics 204:1523–1539

    Article  PubMed  PubMed Central  Google Scholar 

  63. Hanahan D, Weinberg Robert A (2011) Hallmarks of cancer: the next generation. Cell 144:646–674

    Article  CAS  PubMed  Google Scholar 

  64. Chen H, He X (2016) The convergent cancer evolution toward a single cellular destination. Mol Biol Evol 33:4–12

    Article  CAS  PubMed  Google Scholar 

  65. Chen H, Lin F, Xing K, He X (2015) The reverse evolution from multicellularity to unicellularity during carcinogenesis. Nat Commun 6:6367

  66. Cunningham JJ, Brown JS, Vincent TL, Gatenby RA (2015) Divergent and convergent evolution in metastases suggest treatment strategies based on specific metastatic sites. Evol Med Public Health 2015:76–87

    Article  PubMed  PubMed Central  Google Scholar 

  67. Gerlinger M, Rowan AJ, Horswell S, Larkin J, Endesfelder D, Gronroos E, Martinez P, Matthews N, Stewart A, Tarpey P et al (2012) Intratumor heterogeneity and branched evolution revealed by multiregion sequencing. N Engl J Med 366:883–892

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  68. Voss MH, Hakimi AA, Pham CG, Brannon AR, Chen Y-B, Cunha LF, Akin O, Liu H, Takeda S, Scott SN et al (2014) Tumor genetic analyses of patients with metastatic renal cell carcinoma and extended benefit from mTOR inhibitor therapy. Clin Cancer Res 20:1955–1964

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  69. Wei EY, Hsieh JJ (2015) A river model to map convergent cancer evolution and guide therapy in RCC. Nat Rev Urol 12:706–712

    Article  CAS  PubMed  Google Scholar 

  70. Chen J, Lee H-J, Wu X, Huo L, Kim S-J, Xu L, Wang Y, He J, Bollu LR, Gao G et al (2015) Gain of glucose-independent growth upon metastasis of breast cancer cells to the brain. Cancer Res 75:554–565

    Article  CAS  PubMed  Google Scholar 

  71. Juric D, Castel P, Griffith M, Griffith OL, Won HH, Ellis H, Ebbesen SH, Ainscough BJ, Ramu A, Iyer G et al (2015) Convergent loss of PTEN leads to clinical resistance to a PI(3)K[agr] inhibitor. Nature 518:240–244

    Article  CAS  PubMed  Google Scholar 

  72. Shaffer SM, Dunagin MC, Torborg SR, Torre EA, Emert B, Krepler C, Beqiri M, Sproesser K, Brafford PA, Xiao M et al (2017) Rare cell variability and drug-induced reprogramming as a mode of cancer drug resistance. Nature 546:431–435

    Article  CAS  PubMed  Google Scholar 

  73. Hata AN, Niederst MJ, Archibald HL, Gomez-Caraballo M, Siddiqui FM, Mulvey HE, Maruvka YE, Ji F, Bhang H-eC, Krishnamurthy Radhakrishna V et al (2016) Tumor cells can follow distinct evolutionary paths to become resistant to epidermal growth factor receptor inhibition. Nat Med 22:262–269

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  74. Williams MJ, Werner B, Barnes CP, Graham TA, Sottoriva A (2016) Identification of neutral tumor evolution across cancer types. Nat Genet 48:238–244

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  75. Stayton CT (2008) Is convergence surprising? An examination of the frequency of convergence in simulated datasets. J Theor Biol 252:1–14

    Article  PubMed  Google Scholar 

  76. Park ES, Kim SJ, Kim SW, Yoon S-L, Leem S-H, Kim S-B, Kim SM, Park Y-Y, Cheong J-H, Woo HG et al (2011) Cross-species hybridization of microarrays for studying tumor transcriptome of brain metastasis. Proc Natl Acad Sci 108:17456–17461

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  77. Jamal-Hanjani M, Wilson GA, McGranahan N, Birkbak NJ, Watkins TBK, Veeriah S, Shafi S, Johnson DH, Mitter R, Rosenthal R et al (2017) Tracking the evolution of non-small-cell lung cancer. N Engl J Med 376:2109–2121

    Article  CAS  PubMed  Google Scholar 

  78. Zimmer A, Amar-Farkash S, Danon T, Alon U (2017) Dynamic proteomics reveals bimodal protein dynamics of cancer cells in response to HSP90 inhibitor. BMC Syst Biol 11:33

    Article  PubMed  PubMed Central  Google Scholar 

  79. Sharma SV, Lee DY, Li B, Quinlan MP, Takahashi F, Maheswaran S, McDermott U, Azizian N, Zou L, Fischbach MA et al (2010) A chromatin-mediated reversible drug tolerant state in cancer cell subpopulations. Cell 141:69–80

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  80. Wu P-H, Phillip JM, Khatau SB, Chen W-C, Stirman J, Rosseel S, Tschudi K, Van Patten J, Wong M, Gupta S et al (2015) Evolution of cellular morpho-phenotypes in cancer metastasis. Sci Rep 5:18437

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  81. Fluegen G, Avivar-Valderas A, Wang Y, Padgen MR, Williams JK, Nobre AR, Calvo V, Cheung JF, Bravo-Cordero JJ, Entenberg D et al (2017) Phenotypic heterogeneity of disseminated tumour cells is preset by primary tumour hypoxic microenvironments. Nat Cell Biol 19:120–132

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  82. Hensley CT, Faubert B, Yuan Q, Lev-Cohain N, Jin E, Kim J, Jiang L, Ko B, Skelton R, Loudat L et al (2016) Metabolic heterogeneity in human lung tumors. Cell 164:681–694

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  83. McLean K, Gong Y, Choi Y, Deng N, Yang K, Bai S, Cabrera L, Keller E, McCauley L, Cho KR et al (2011) Human ovarian carcinoma-associated mesenchymal stem cells regulate cancer stem cells and tumorigenesis via altered BMP production. J Clin Invest 121:3206–3219

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  84. Coffman LG, Choi Y-J, McLean K, Allen BL, di Magliano MP, Buckanovich RJ (2016) Human carcinoma-associated mesenchymal stem cells promote ovarian cancer chemotherapy resistance via a BMP4/HH signaling loop. Oncotarget 7:6916–6932

  85. Chen W-J, Ho C-C, Chang Y-L, Chen H-Y, Lin C-A, Ling T-Y, Yu S-L, Yuan S-S, Louisa Chen Y-J, Lin C-Y et al (2014) Cancer-associated fibroblasts regulate the plasticity of lung cancer stemness via paracrine signalling. Nat Commun 5:3472

  86. Vermeulen L, De Sousa E, Melo F, van der Heijden M, Cameron K, de Jong JH, Borovski T, Tuynman JB, Todaro M, Merz C, Rodermond H et al (2010) Wnt activity defines colon cancer stem cells and is regulated by the microenvironment. Nat Cell Biol 12:468–476

    Article  CAS  PubMed  Google Scholar 

  87. Straussman R, Morikawa T, Shee K, Barzily-Rokni M, Qian ZR, Du J, Davis A, Mongare MM, Gould J, Frederick DT et al (2012) Tumour micro-environment elicits innate resistance to RAF inhibitors through HGF secretion. Nature 487:500–504

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  88. Sansone P, Storci G, Tavolari S, Guarnieri T, Giovannini C, Taffurelli M, Ceccarelli C, Santini D, Paterini P, Marcu KB et al (2007) IL-6 triggers malignant features in mammospheres from human ductal breast carcinoma and normal mammary gland. J Clin Invest 117:3988–4002

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  89. Liu S, Ginestier C, Ou SJ, Clouthier SG, Patel SH, Monville F, Korkaya H, Heath A, Dutcher J, Kleer CG et al (2011) Breast cancer stem cells are regulated by mesenchymal stem cells through cytokine networks. Cancer Res 71:614–624

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  90. Thomas DA, Massagué J (2005) TGF-β directly targets cytotoxic T cell functions during tumor evasion of immune surveillance. Cancer Cell 8:369–380

  91. Vinay DS, Ryan EP, Pawelec G, Talib WH, Stagg J, Elkord E, Lichtor T, Decker WK, Whelan RL, Kumara HMCS et al (2015) Immune evasion in cancer: mechanistic basis and therapeutic strategies. Semin Cancer Biol 35:S185–S198

    Article  PubMed  Google Scholar 

  92. de Charette M, Marabelle A, Houot R (2016) Turning tumour cells into antigen presenting cells: the next step to improve cancer immunotherapy? Eur J Cancer 68:134–147

    Article  PubMed  Google Scholar 

  93. Haworth KB, Leddon JL, Chen C-Y, Horwitz EM, Mackall CL, Cripe TP (2015) Going back to class I: MHC and immunotherapies for childhood cancer. Pediatr Blood Cancer 62:571–576

    Article  CAS  PubMed  Google Scholar 

  94. Song G, Darr DB, Santos CM, Ross M, Valdivia A, Jordan JL, Midkiff BR, Cohen S, Feinberg NN, Miller CR et al (2014) Effects of tumor microenvironment heterogeneity on nanoparticle disposition and efficacy in breast cancer tumor models. Clin Cancer Res: Off J Am Assoc Cancer Res 20:6083–6095

    Article  CAS  Google Scholar 

  95. Mumenthaler SM, Foo J, Choi NC, Heise N, Leder K, Agus DB, Pao W, Michor F, Mallick P (2015) The impact of microenvironmental heterogeneity on the evolution of drug resistance in cancer cells. Cancer Informat 14:19–31

    CAS  Google Scholar 

  96. Mroz EA, Tward AM, Hammon RJ, Ren Y, Rocco JW (2015) Intra-tumor genetic heterogeneity and mortality in head and neck cancer: analysis of data from the cancer genome atlas. PLoS Med 12:e1001786

    Article  PubMed  PubMed Central  Google Scholar 

  97. McGranahan N, Furness AJS, Rosenthal R, Ramskov S, Lyngaa R, Saini SK, Jamal-Hanjani M, Wilson GA, Birkbak NJ, Hiley CT et al (2016) Clonal neoantigens elicit T cell immunoreactivity and sensitivity to immune checkpoint blockade. Science. https://doi.org/10.1126/science.aaf1490

  98. Dong ZY, Zhai HR, Hou QY, Su J, Liu SY, Yan HH, Li YS, Chen ZY, Zhong WZ, Wu YL (2017) Mixed responses to systemic therapy revealed potential genetic heterogeneity and poor survival in patients with non-small cell lung cancer. Oncologist 22:61–69

    Article  CAS  PubMed  Google Scholar 

  99. Lee Y, Kim HY, Lee S-H, Lim KY, Lee GK, Yun T, Han J-Y, Kim HT, Lee JS (2014) Clinical significance of heterogeneity in response to retreatment with epidermal growth factor receptor tyrosine kinase inhibitors in patients with lung cancer acquiring secondary resistance to the drug. Clin Lung Cancer 15:145–151

    Article  CAS  PubMed  Google Scholar 

  100. Connolly JLSS, Wang HH, Longtine JA, Dvorak A, Dvorak HF (2003) Role of the surgical pathologist in the diagnosis and management of the cancer patient. In: Kufe DWPR, Weichselbaum RR et al (eds) . Holland-Frei Cancer Medicine BC Decker, Hamilton (ON)

    Google Scholar 

  101. Wan JCM, Massie C, Garcia-Corbacho J, Mouliere F, Brenton JD, Caldas C, Pacey S, Baird R, Rosenfeld N (2017) Liquid biopsies come of age: towards implementation of circulating tumour DNA. Nat Rev Cancer 17:223–238

    Article  CAS  PubMed  Google Scholar 

  102. Lillie EO, Patay B, Diamant J, Issell B, Topol EJ, Schork NJ (2011) The n-of-1 clinical trial: the ultimate strategy for individualizing medicine? Personalized Med 8:161–173

    Article  Google Scholar 

  103. Catenacci DVT (2015) Next-generation clinical trials: novel strategies to address the challenge of tumor molecular heterogeneity. Mol Oncol 9:967–996

    Article  CAS  PubMed  Google Scholar 

  104. Joung J-G, Bae JS, Kim SC, Jung H, Park W-Y, Song S-Y (2016) Genomic characterization and comparison of multi-regional and pooled tumor biopsy specimens. PLoS One 11:e0152574

    Article  PubMed  PubMed Central  Google Scholar 

  105. Lennon NJ, Adalsteinsson VA, Gabriel SB (2016) Technological considerations for genome-guided diagnosis and management of cancer. Genome Med 8:112

    Article  PubMed  PubMed Central  Google Scholar 

  106. Lohr Jens G, Stojanov P, Carter Scott L, Cruz-Gordillo P, Lawrence Michael S, Auclair D, Sougnez C, Knoechel B, Gould J, Saksena G et al (2014) Widespread genetic heterogeneity in multiple myeloma: implications for targeted therapy. Cancer Cell 25:91–101

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  107. McGranahan N, Favero F, de Bruin EC, Birkbak NJ, Szallasi Z, Swanton C (2015) Clonal status of actionable driver events and the timing of mutational processes in cancer evolution. Sci Transl Med 7:283ra254–283ra254

    Article  Google Scholar 

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Acknowledgements

The authors wish to thank Dr. Samuel W. Brady for manuscript editing.

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This work was supported by funding from the National Institutes of Health (U54CA209978).

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Correspondence to Andrea H. Bild.

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McQuerry, J.A., Chang, J.T., Bowtell, D.D.L. et al. Mechanisms and clinical implications of tumor heterogeneity and convergence on recurrent phenotypes. J Mol Med 95, 1167–1178 (2017). https://doi.org/10.1007/s00109-017-1587-4

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  • DOI: https://doi.org/10.1007/s00109-017-1587-4

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