دورية أكاديمية
Blueprint for cancer research: Critical gaps and opportunities.
| العنوان: | Blueprint for cancer research: Critical gaps and opportunities. |
|---|---|
| المؤلفون: | Elmore LW; Office of the Chief Medical and Scientific Officer, American Cancer Society, Atlanta, Georgia., Greer SF; Office of the Chief Medical and Scientific Officer, American Cancer Society, Atlanta, Georgia., Daniels EC; Office of the Chief Medical and Scientific Officer, American Cancer Society, Atlanta, Georgia., Saxe CC; Office of the Chief Medical and Scientific Officer, American Cancer Society, Atlanta, Georgia., Melner MH; Office of the Chief Medical and Scientific Officer, American Cancer Society, Atlanta, Georgia., Krawiec GM; Office of the Chief Medical and Scientific Officer, American Cancer Society, Atlanta, Georgia., Cance WG; Office of the Chief Medical and Scientific Officer, American Cancer Society, Atlanta, Georgia., Phelps WC; Office of the Chief Medical and Scientific Officer, American Cancer Society, Atlanta, Georgia. |
| المصدر: | CA: a cancer journal for clinicians [CA Cancer J Clin] 2021 Mar; Vol. 71 (2), pp. 107-139. Date of Electronic Publication: 2020 Dec 16. |
| نوع المنشور: | Journal Article; Research Support, Non-U.S. Gov't |
| اللغة: | English |
| بيانات الدورية: | Publisher: Wiley Country of Publication: United States NLM ID: 0370647 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1542-4863 (Electronic) Linking ISSN: 00079235 NLM ISO Abbreviation: CA Cancer J Clin Subsets: MEDLINE |
| أسماء مطبوعة: | Publication: Hoboken, NJ : Wiley Original Publication: New York, American Cancer Society. |
| مواضيع طبية MeSH: | Professional Practice Gaps*, Evidence-Based Medicine/*organization & administration , Mass Screening/*organization & administration , Medical Oncology/*organization & administration , Neoplasms/*therapy, Biomarkers, Tumor/analysis ; Biomarkers, Tumor/genetics ; Cost of Illness ; Early Detection of Cancer/methods ; Early Detection of Cancer/trends ; Evidence-Based Medicine/methods ; Evidence-Based Medicine/trends ; Humans ; Mass Screening/methods ; Mass Screening/trends ; Medical Oncology/methods ; Medical Oncology/trends ; Neoplasms/diagnosis ; Neoplasms/genetics ; Neoplasms/mortality ; Precision Medicine/methods ; Precision Medicine/trends ; United States/epidemiology |
| مستخلص: | We are experiencing a revolution in cancer. Advances in screening, targeted and immune therapies, big data, computational methodologies, and significant new knowledge of cancer biology are transforming the ways in which we prevent, detect, diagnose, treat, and survive cancer. These advances are enabling durable progress in the goal to achieve personalized cancer care. Despite these gains, more work is needed to develop better tools and strategies to limit cancer as a major health concern. One persistent gap is the inconsistent coordination among researchers and caregivers to implement evidence-based programs that rely on a fuller understanding of the molecular, cellular, and systems biology mechanisms underpinning different types of cancer. Here, the authors integrate conversations with over 90 leading cancer experts to highlight current challenges, encourage a robust and diverse national research portfolio, and capture timely opportunities to advance evidence-based approaches for all patients with cancer and for all communities. (© 2020 American Cancer Society.) |
| References: | Lowy DR, Collins FS. Aiming high-changing the trajectory for cancer. N Engl J Med. 2016;374:1901-1904. doi:10.1056/nejmp1600894. Siegel RL, Miller KD, Jemal A. Cancer statistics, 2020. CA Cancer J Clin. 2020;70:7-30. doi:10.3322/caac.21590. Siegel RL, Miller KD, Fuchs H, Jemal A. Cancer statistics, 2021. CA Cancer J Clin. In press. Ma J, Jemal A, Fedewa SA, et al. The American Cancer Society 2035 challenge goal on cancer mortality reduction. CA Cancer J Clin. 2019;69:351-362. doi:10.3322/caac.21564. Islami F, Goding Sauer A, Miller KD, et al. Proportion and number of cancer cases and deaths attributable to potentially modifiable risk factors in the United States. CA Cancer J Clin. 2018;68:31-54. doi:10.3322/caac.21440. Jaffee EM, Dang CV, Agus DB, et al. Future cancer research priorities in the USA: a Lancet Oncology Commission. Lancet Oncol. 2017;18:e653-e706. doi:10.1016/S1470-2045(17)30698-8. Wender RC, Brawley OW, Fedewa SA, Gansler T, Smith RA. A blueprint for cancer screening and early detection: advancing screening's contribution to cancer control. CA Cancer J Clin. 2018;68:50-79. doi:10.3322/caac.21550. Yabroff KR, Gansler T, Wender RC, Cullen KJ, Brawley OW. Minimizing the burden of cancer in the United States: goals for a high-performing health care system. CA Cancer J Clin. 2019;69:166-183. doi:10.3322/caac.21556. Alfano CM, Leach CR, Smith TG, et al. Equitably improving outcomes for cancer survivors and supporting caregivers: a blueprint for care delivery, research, education, and policy. CA Cancer J Clin. 2018;68:35-49. doi:10.3322/caac.21548. Gapstur SM, Drope JM, Jacobs EJ, et al. A blueprint for the primary prevention of cancer: targeting established, modifiable risk factors. CA Cancer J Clin. 2018;68:446-470. doi:10.3322/caac.21496. Siegel RL, Jemal A, Wender RC, Gansler T, Ma J, Brawley OW. An assessment of progress in cancer control. CA Cancer J Clin. 2018;68:329-339. doi:10.3322/caac.21460. Alcaraz K, Wiedt TL, Daniels EC, Yabroff KR, Guerra CE, Wender RC. Understanding and addressing social determinants to advance cancer health equity in the United States: a blueprint for practice, research, and policy. J Clin Cancer. 2020;70:31-46. doi:10.3322/caac.21586. Tsodikov A, Gulati R, Heijnsdijk EAM, et al. Reconciling the effects of screening on prostate cancer mortality in the ERSPC and PLCO trials. Ann Intern Med. 2017;167:449-455. doi:10.7326/M16-2586. Siegel RL, Miller KD, Jemal A. Cancer statistics, 2019. CA Cancer J Clin. 2019;69:7-34. doi:10.3322/caac.21551. Negoita S, Feuer EJ, Mariotto A, et al. Annual Report to the Nation on the Status of Cancer, part II: recent changes in prostate cancer trends and disease characteristics. Cancer. 2018;124:2801-2814. doi:10.1002/cncr.31549. Smith RA, Andrews KS, Brooks D, et al. Cancer screening in the United States, 2018: a review of current American Cancer Society guidelines and current issues in cancer screening. CA Cancer J Clin. 2018;68:297-316. doi:10.3322/caac.21446. Sauer AG, Siegel RL, Jemal A, Fedewa SA. Updated review of prevalence of major risk factors and use of screening tests for cancer in the United States. Cancer Epidemiol Biomarkers Prev. 2017;26:1192-1208. doi:10.1158/1055-9965.EPI-17-0219. Watson M, Benard V, King J, Crawford A, Saraiya M. National assessment of HPV and Pap tests: changes in cervical cancer screening, National Health Interview Survey. Prev Med. 2017;100:243-247. doi:10.1016/j.ypmed.2017.05.004. de Moor JS, Cohen RA, Shapiro JA, et al. Colorectal cancer screening in the United States: trends from 2008 to 2015 and variation by health insurance coverage. Prev Med. 2018;112:199-206. doi:10.1016/j.ypmed.2018.05.001. Biomarkers Definitions Working Group. Biomarkers and surrogate endpoints: preferred definitions and conceptual framework. Clin Pharmacol Ther. 2001;69:89-95. doi:10.1067/mcp.2001.113989. Napel S, Mu W, Jardim-Perassi BV, Aerts HJWL, Gillies RJ. Quantitative imaging of cancer in the postgenomic era: radio(geno)mics, deep learning, and habitats. Cancer. 2018;124:4633-4649. doi:10.1002/cncr.31630. Houssami N, Lee CI, Buist DSM, Tao D. Artificial intelligence for breast cancer screening: opportunity or hype? Breast. 2017;36:31-33. doi:10.1016/j.breast.2017.09.003. Davatzikos C, Rathore S, Bakas S, et al. Cancer imaging phenomics toolkit: quantitative imaging analytics for precision diagnostics and predictive modeling of clinical outcome. J Med Imaging (Bellingham). 2018;5:011018. doi:10.1117/1.JMI.5.1.011018. Bi WL, Hosny A, Schabath MB, et al. Artificial intelligence in cancer imaging: clinical challenges and applications. CA Cancer J Clin. 2019;69:127-157. doi:10.3322/caac.21552. Mayer AT, Gambhir SS. The immunoimaging toolbox. J Nucl Med. 2018;59:1174-1182. doi:10.2967/jnumed.116.185967. de Vries EGE, de Ruijter LK, Lub-de Hooge MN, Dierckx RA, Elias SG, Oosting SF. Integrating molecular nuclear imaging in clinical research to improve anticancer therapy. Nat Rev Clin Oncol. 2019;16:241-255. doi:10.1038/s41571-018-0123-y. Meyer MG, Hayenga JW, Neumann T, et al. The Cell-CT 3-dimensional cell imaging technology platform enables the detection of lung cancer using the noninvasive LuCED sputum test. Cancer Cytopathol. 2015;123:512-523. doi:10.1002/cncy.21576. Pantanowitz L, Preffer F, Wilbur DC. Advanced imaging technology applications in cytology. Diagn Cytopathol. 2019;47:5-14. doi:10.1002/dc.23898. Srivastava A, Creek DJ. Discovery and validation of clinical biomarkers of cancer: a review combining metabolomics and proteomics. Proteomics. 2019;19:e17000448. doi:10.1002/pmic.201700448. Imperiale TF, Ransohoff DF, Itzkowitz SH, et al. Multitarget stool DNA testing for colorectal-cancer screening. N Engl J Med. 2014;370:1287-1297. doi:10.1056/nejmoa1311194. Muthu M, Nordstrom A. Current status and future prospects of clinically exploiting cancer-specific metabolism-why is tumor metabolism not more extensively translated into clinical targets and biomarkers? Int J Mol Sci. 2019;20:1385. doi:10.3390/ijms20061385. Bansal A, Singh M, Rai B. Human papillomavirus-associated cancers: a growing global problem. Int J Appl Basic Med Res. 2016;6:84-89. doi:10.4103/2229-516x.179027. US Preventive Services Task Force; Curry SJ, Krist AH, Owens DK, et al. Screening for cervical cancer: US Preventive Services Task Force recommendation statement. JAMA. 2018;320:674-686. doi:10.1001/jama.2018.10897. Ilie M, Hofman P. Pros: can tissue biopsy be replaced by liquid biopsy? Transl Lung Cancer Res. 2016;5:420-423. doi:10.21037/tlcr.2016.08.06. Cohen JD, Li L, Wang Y, et al. Detection and localization of surgically resectable cancers with a multi-analyte blood test. Science. 2018;359:926-930. doi:10.1126/science.aar3247. Bardelli A, Pantel K. Liquid biopsies, what we do not know (yet). Cancer Cell. 2017;31:172-179. doi:10.1016/j.ccell.2017.01.002. Lennon AM, Buchanan AH, Kinde I, et al. Feasibility of blood testing combined with PET-CT to screen for cancer and guide intervention. Science. 2020;369:eabb9601. doi:10.1126/science.abb9601. Wang Y, Li L, Douville C, et al. Evaluation of liquid from the Papanicolaou test and other liquid biopsies for the detection of endometrial and ovarian cancers. Obstet Gynecol Surv. 2018;73:463-464. doi:10.1097/01.ogx.0000542325.60681.a3. Eich ML, Rodriguez Pena MDC, Springer SU, et al. Incidence and distribution of UroSEEK gene panel in a multi-institutional cohort of bladder urothelial carcinoma. Mod Pathol. 2019;32:1544-1550. doi:10.1038/s41379-019-0276-y. Liu MC, Oxnard GR, Klein EA, et al. Sensitive and specific multi-cancer detection and localization using methylation signatures in cell-free DNA. Ann Oncol. 2020;31:745-759. doi:10.1016/j.annonc.2020.02.011. Kalishwaralal K, Kwon WY, Park KS. Exosomes for non-invasive cancer monitoring. Biotechnol J. 2019;14:e1800430. doi:10.1002/biot.201800430. Cohen JD, Javed AA, Thoburn C, et al. Combined circulating tumor DNA and protein biomarker-based liquid biopsy for the earlier detection of pancreatic cancers. Proc Natl Acad Sci U S A. 2017;114:10202-10207. doi:10.1073/pnas.1704961114. Siravegna G, Marsoni S, Siena S, Bardelli A. Integrating liquid biopsies into the management of cancer. Nat Rev Clin Oncol. 2017;14:531-548. doi:10.1038/nrclinonc.2017.14. Makarova JA, Shkurnikov MU, Wicklein D, et al. Intracellular and extracellular microRNA: an update on localization and biological role. Prog Histochem Cytochem. 2016;51:33-49. doi:10.1016/j.proghi.2016.06.001. Talasaz AA, Mortimer S, Sebisanovic D, et al. Use of the GUARDANT360 noninvasive tumor sequencing assay on 300 patients across colorectal, melanoma, lung, breast, and prostate cancers and its clinical utility [abstract]. J Clin Oncol. 2014;32(15 suppl):e22041. doi:10.1200/jco.2014.32.15_suppl.e22041. The Journal of Precision Medicine. Guardant Health Guardant360® CDx First FDA-Approved Liquid Biopsy for Comprehensive Tumor Mutation Profiling Across All Solid Cancers. Accessed December 3, 2020. thejournalofprecisionmedicine.com/guardant-health-guardant360-cdx-first-fda-approved-liquid-biopsy-for-comprehensive-tumor-mutation-profiling-across-all-solid-cancers/. Campbell JD, Mazzilli SA, Reid ME, et al. The case for a Pre-Cancer Genome Atlas (PCGA). Cancer Prev Res. 2016;9:119-124. doi:10.1158/1940-6207.CAPR-16-0024. Esserman LJ, Thompson IM, Reid B, et al. Addressing overdiagnosis and overtreatment in cancer: a prescription for change. Lancet Oncol. 2014;15:e234-e242. doi:10.1016/S1470-2045(13)70598-9. Sandhu GS, Andriole GL. Overdiagnosis of prostate cancer. J Natl Cancer Inst Monogr. 2012;2011:146-151. doi:10.1093/jncimonographs/lgs031. Aizer AA, Gu X, Chen MH, et al. Cost implications and complications of overtreatment of low-risk prostate cancer in the United States. J Natl Compr Cancer Netw. 2015;13:61-81. doi:10.6004/jnccn.2015.0009. Sebesta EM, Anderson CB. The surgical management of prostate cancer. Semin Oncol. 2017;44:347-357. doi:10.1053/j.seminoncol.2018.01.003. Shee K, Muller KE, Marotti J, Miller TW, Wells WA, Tsongalis GJ. Ductal carcinoma in situ biomarkers in a precision medicine era: current and future molecular-based testing. Am J Pathol. 2019;189:956-965. doi:10.1016/j.ajpath.2018.08.020. Rahib L, Smith BD, Aizenberg R, Rosenzweig AB, Fleshman JM, Matrisian LM. Projecting cancer incidence and deaths to 2030: the unexpected burden of thyroid, liver, and pancreas cancers in the United States. Cancer Res. 2014;74:2913-2921. doi:10.1158/0008-5472.CAN-14-0155. Noone AM, Howlader N, Krapcho M, et al, eds. SEER Cancer Statistics Review (CSR) 1975-2015. National Cancer Institute; 2018. Accessed October 9, 2018. seer.cancer.gov/csr/1975_2015. Torre LA, Trabert B, DeSantis CD, et al. Ovarian cancer statistics, 2018. CA Cancer J Clin. 2018;68:284-296. doi:10.3322/caac.21456. Gall TMH, Belete S, Khanderia E, Frampton AE, Jiao LR. Circulating tumor cells and cell-free DNA in pancreatic ductal adenocarcinoma. Am J Pathol. 2019;189:71-81. doi:10.1016/j.ajpath.2018.03.020. Kim J, Bamlet WR, Oberg AL, et al. Detection of early pancreatic ductal adenocarcinoma with thrombospondin-2 and CA19-9 blood markers. Sci Transl Med. 2017;9:eaah5582. doi:10.1126/scitranslmed.aah5583. Bartsch DK, Gercke N, Strauch K, et al. The combination of miRNA-196b, LCN2, and TIMP1 is a potential set of circulating biomarkers for screening individuals at risk for familial pancreatic cancer. J Clin Med. 2018;7:295. doi:10.3390/jcm7100295. Melo SA, Luecke LB, Kahlert C, et al. Glypican-1 identifies cancer exosomes and detects early pancreatic cancer. Nature. 2016;523:177-182. doi:10.1038/nature14581. Elias KM, Guo J, Bast RC Jr. Early detection of ovarian cancer. Hematol Oncol Clin North Am. 2018;32:903-914. doi:10.1016/j.hoc.2018.07.003. Giannopoulou L, Zavridou M, Kasimir-Bauer S, Lianidou ES. Liquid biopsy in ovarian cancer: the potential of circulating miRNAs and exosomes. Transl Res. 2019;205:77-91. doi:10.1016/j.trsl.2018.10.003. Carollo E, Paris B, Samuel P, et al. Detecting ovarian cancer using extracellular vesicles: progress and possibilities. Biochem Soc Trans. 2019;47:295-304. doi:10.1042/BST20180286. Ileana Dumbrava EE, Meric-Bernstam F, Yap TA. Challenges with biomarkers in cancer drug discovery and development. Expert Opin Drug Discov. 2018;13:685-690. doi:10.1080/17460441.2018.1479740. Jacob M, Lopata AL, Dasouki M, Abdel Rahman AM. Metabolomics toward personalized medicine. Mass Spectrom Rev. 2019;38:221-238. doi:10.1002/mas.21548. Nelson HD, Fu R, Cantor A, Pappas M, Daeges M, Humphrey L. Effectiveness of breast cancer screening: systematic review and meta-analysis to update the 2009 U.S. Preventive Services Task Force recommendation. Ann Intern Med. 2016;164:244-255. doi:10.7326/M15-0969. Nofech-Mozes S, Hanna W, Rakovitch E. Molecular evaluation of breast ductal carcinoma in situ with Oncotype DX DCIS. Am J Pathol. 2019;189:975-980. doi:10.1016/j.ajpath.2018.12.003. Khoury MJ, Bowen MS, Clyne M, et al. From public health genomics to precision public health: a 20-year journey. Genet Med. 2018;20:574-582. doi:10.1038/gim.2017.211. Manolio TA, Chisholm RL, Ozenberger B, et al. Implementing genomic medicine in the clinic: the future is here. Genet Med. 2013;15:258-267. doi:10.1038/gim.2012.157. Baskar R, Lee KA, Yeo R, Yeoh KW. Cancer and radiation therapy: current advances and future directions. Int J Med Sci. 2012;9:193-199. doi:10.7150/ijms.3635. Palumbo MO, Kavan P, Miller WH, et al. Systemic cancer therapy: achievements and challenges that lie ahead. Front Pharmacol. 2013;4:57. doi:10.3389/fphar.2013.00057. Schuck A, Konemann S, Heinen K, et al. Microscopic residual disease is a risk factor in the primary treatment of breast cancer. Strahlenther Onkol. 2002;178:307-313. doi:10.1007/s00066-002-0950-7. Formenti SC, Demaria S. Systemic effects of local radiotherapy. Lancet Oncol. 2009;10:718-726. doi:10.1016/S1470-2045(09)70082-8. Garraway LA, Verweij J, Ballman KV. Precision oncology: an overview. J Clin Oncol. 2013;31:1803-1804. doi:10.1200/JCO.2013.49.4799. Mayer-Schonberger V, Ingelsson E. Big data and medicine: a big deal? J Intern Med. 2018;283:418-429. doi:10.1111/joim.12721. Weigel RJ, McDougall IR. The role of radioactive iodine in the treatment of well-differentiated thyroid cancer. Surg Oncol Clin N Am. 2006;15:62-638. doi:10.1016/j.soc.2006.05.007. Druker BJ, Talpaz M, Resta DJ, et al. Efficacy and safety of a specific inhibitor of the BCR-ABL tyrosine kinase in chronic myeloid leukemia. N Engl J Med. 2001;344:1031-3017. doi:10.1056/nejm200104053441401. Lim SH, Levy R. Translational medicine in action: anti-CD20 therapy in lymphoma. J Immunol. 2014;193:1519-1524. doi:10.4049/jimmunol.1490027. Finn RS, Slamon DJ. Monoclonal antibody therapy for breast cancer: Herceptin. Cancer Chemother Biol Response Modif. 2003;21:223-233. doi:10.1016/s0921-4410(03)21010-3. Knight ZA, Lin H, Shokat KM. Targeting the cancer kinome through polypharmacology. Nat Rev Cancer. 2010;10:130-137. doi:10.1038/nrc2787. Roskoski R Jr. Properties of FDA-approved small molecule protein kinase inhibitors. Pharmacol Res. 2019;144:19-50. doi:10.1016/j.phrs.2019.03.006. Graves LM, Duncan JS, Whittle MC, Johnson GL. The dynamic nature of the kinome. Biochem J. 2013;450:1-8. doi:10.1042/BJ20121456. Bhullar KS, Lagaron NO, McGowan EM, et al. Kinase-targeted cancer therapies: progress, challenges and future directions. Mol Cancer. 2018;17:48. doi:10.1186/s12943-018-0804-2. Le DT, Uram JN, Wang H, et al. PD-1 blockade in tumors with mismatch-repair deficiency. N Engl J Med. 2015;372:2509-2520. doi:10.1056/NEJMoa1500596. Kiyotani K, Chan HT, Nakamura Y. Immunopharmacogenomics towards personalized cancer immunotherapy targeting neoantigens. Cancer Sci. 2018;109:542-549. doi:10.1111/cas.13498. Vargas FA, Furness AJS, Litchfield K, et al. Fc effector function contributes to the activity of human anti-CTLA-4 antibodies. Cancer Cell. 2018;33:649-663.e4. doi:10.1016/j.ccell.2018.02.010. Hamanishi J, Mandai M, Ikeda T, et al. Safety and antitumor activity of anti-PD-1 antibody, nivolumab, in patients with platinum-resistant ovarian cancer. J Clin Oncol. 2015;33:4015-4022. doi:10.1200/JCO.2015.62.3397. Iwa Y, Hamanishi J, Chamoto K, Honjo T. Cancer immunotherapies targeting the PD-1 signaling pathway. J Biomed Sci. 2017;24:26. doi:10.1186/s12929-017-0329-9. Nghiem P, Bhatia S, Lipson EJ, et al. Durable tumor regression and overall survival in patients with advanced Merkel cell carcinoma receiving pembrolizumab as first-line therapy. J Clin Oncol. 2019;37:693-702. doi:10.1200/JCO.18.01896. Topalian SL, Hodi FS, Brahmer JR, et al. Safety, activity, and immune correlates of anti-PD-1 antibody in cancer. N Engl J Med. 2012;366:2443-2454. doi:10.1056/NEJMoa1200690. Wolchok JD, Kluger H, Callahan MK, et al. Nivolumab plus ipilimumab in advanced melanoma. N Engl J Med. 2013;369:122-133. doi:10.1056/NEJMoa1302369. Rothschilds AM, Wittrup KD. What, why, where, and when: bringing timing to immuno-oncology. Trends Immunol. 2019;40:12-21. doi:10.1016/j.it.2018.11.003. Long KB, Young RM, Boesteanu AC, et al. CAR T cell therapy of non-hematopoietic malignancies: detours on the road to clinical success. Front Immunol. 2018;9:2740. doi:10.3389/fimmu.2018.02740. Maude SL, Frey N, Shaw PA, et al. Chimeric antigen receptor T cells for sustained remissions in leukemia. N Engl J Med. 2014;371:1507-1517. doi:10.1056/NEJMoa1407222. Maude SL, Laetsch TW, Buechner J, et al. Tisagenlecleucel in children and young adults with B-cell lymphoblastic leukemia. N Engl J Med. 2018;378:439-448. doi:10.1056/NEJMoa1709866. Schwaederle M, Daniels GA, Piccioni DE, et al. On the road to precision cancer medicine: analysis of genomic biomarker actionability in 439 patients. Mol Cancer Ther. 2015;14:1488-1494. doi:10.1158/1535-7163.MCT-14-1061. Porter DL, Levine BL, Kalos M, Bagg A, June CH. Chimeric antigen receptor-modified T cells in chronic lymphoid leukemia. N Engl J Med. 2011;365:725-733. doi:10.1056/NEJMoa1103849. Porter DL, Hwang WT, Frey NV, et al. Chimeric antigen receptor T cells persist and induce sustained remissions in relapsed refractory chronic lymphocytic leukemia. Sci Transl Med. 2015;7:303ra139. doi:10.1126/scitranslmed.aac5415. Neelapu SS, Locke FL, Bartlett NL, et al. Axicabtagene ciloleucel CAR T-cell therapy in refractory large B-cell lymphoma. N Engl J Med. 2017;377:2531-2544. doi:10.1056/NEJMoa1707447. Schuster SJ, Svoboda J, Chong EA, et al. Chimeric antigen receptor T cells in refractory B-cell lymphomas. N Engl J Med. 2017;377:2545-2554. doi:10.1056/NEJMoa1708566. Sun M, Shi H, Liu C, Liu J, Liu X, Sun Y. Construction and evaluation of a novel humanized HER2-specific chimeric receptor. Breast Cancer Res. 2014;16:R61. doi:10.1186/bcr3674. Thomas S, Straathof K, Himoudi N, Anderson J, Pule M. An optimized GD2-targeting retroviral cassette for more potent and safer cellular therapy of neuroblastoma and other cancers. PLoS One. 2016;11:e0152196. doi:10.1371/journal.pone.0152196. Liu X, Zhang N, Shi H. Driving better and safer HER2-specific CARs for cancer therapy. Oncotarget. 2017;8:62730-62741. doi:10.18632/oncotarget.17528. Romee R, Rosario M, Berrien-Elliott MM, et al. Cytokine-induced memory-like natural killer cells exhibit enhanced responses against myeloid leukemia. Sci Transl Med. 2016;8:357ra123. doi:10.1126/scitranslmed.aaf2341. Liu E, Marin D, Banerjee P, et al. Use of CAR-transduced natural killer cells in CD19-positive lymphoid tumors. N Engl J Med. 2020;382:545-553. doi:10.1056/NEJMoa1910607. Zhang Y, Wallace DL, de Lara CM, et al. In vivo kinetics of human natural killer cells: the effects of ageing and acute and chronic viral infection. Immunology. 2007;121:258-265. doi:10.1111/j.1365-2567.2007.02573.x. Lupo KB, Matosevic S. Natural killer cells as allogeneic effectors in adoptive cancer immunotherapy. Cancers (Basel). 2019;11:769. doi:10.3390/cancers11060769. Gauthier J, Turtle CJ. Insights into cytokine release syndrome and neurotoxicity after CD19-specific CAR-T cell therapy. Curr Res Transl Med. 2018;66:50-52. doi:10.1016/j.retram.2018.03.003. Klingemann H. Are natural killer cells superior CAR drivers? Oncoimmunology. 2014;3:e28147. doi:10.4161/onci.28147. Carlsten M, Childs RW. Genetic manipulation of NK cells for cancer immunotherapy: techniques and clinical implications. Front Immunol. 2015;6:266. doi:10.3389/fimmu.2015.00266. Coulie PG, Van den Eynde BJ, van der Bruggen P, Boon T. Tumour antigens recognized by T lymphocytes: at the core of cancer immunotherapy. Nat Rev Cancer. 2014;14:135-146. doi:10.1038/nrc3670. Air SK, Hull S, Coleman D, Giboa E, Lyerly HK, Morse MA. Induction of carcinoembryonic antigen (CEA)-specific cytotoxic T-lymphocyte responses in vitro using autologous dendritic cells loaded with CEA peptide or CEA RNA in patients with metastatic malignancies expressing CEA. Int J Cancer. 1999;124:121-124. doi:10.1002/(SICI)1097-0215(19990702)82:1<121::AID-IJC20>3.0.CO;2-X. Kimura T, Mckolanis JR, Dzubinski LA, et al. MUC1 vaccine for individuals with advanced adenoma of the colon: a cancer immunoprevention feasibility study. Cancer Prev Res (Phila). 2013;6:18-27. doi:10.1158/1940-6207.CAPR-12-0275. Tsuruma T, Hata F, Torigoe T, et al. Phase I clinical study of anti-apoptosis protein, survivin-derived peptide vaccine therapy for patients with advanced or recurrent colorectal cancer. J Transl Med. 2004;2:19. doi:10.1186/1479-5876-2-19. Wagner S, Mullins CS, Linnebacher M. Colorectal cancer vaccines: tumor-associated antigens vs neoantigens. World J Gastroenterol. 2018;24:5418-5432. doi:10.3748/wjg.v24.i48.5418. Pol J, Bloy N, Buque A, et al. Trial watch: peptide-based anticancer vaccines. Oncoimmunology. 2015;4:e974411. doi:10.4161/2162402X.2014.974411. Brown SD, Warren RL, Gibb EA, et al. Neo-antigens predicted by tumor genome meta-analysis correlate with increased patient survival. Genome Res. 2014;24:743-750. doi:10.1101/gr.165985.113. Shahabi V, Berman D, Chasalow SD, et al. Gene expression profiling of whole blood in ipilimumab-treated patients for identification of potential biomarkers of immune-related gastrointestinal adverse events. J Transl Med. 2013;11:75. doi:10.1186/1479-5876-11-75. Haratani K, Hayashi H, Chiba Y, et al. Association of immune-related adverse events with nivolumab efficacy in non-small cell lung cancer. JAMA Oncol. 2018;4:374-378. doi:10.1001/jamaoncol.2017.2925. Kfoury M, Voisin AL, Najean M, et al. Association between immune-related adverse events and efficacy in patients treated with anti-PD-(L)1 [abstract]. Ann Oncol. 2018;29(suppl 8):VII405. doi:10.1093/annonc/mdy288.014. Arbour KC, Mezquita L, Long N, et al. Deleterious effect of baseline steroids on efficacy of PD-(L)1 blockade in patients with NSCLC [abstract]. J Clin Oncol. 2018;36(15 suppl):9003. doi:10.1200/jco.2018.36.15_suppl.9003. Schuster SJ, Bishop MR, Tam C, et al. Updated analysis of the Juliet trial: a global, pivotal, phase 2 study of tisagenlecleucel in adult patients with relapsed or refractory diffuse large B-cell lymphoma [abstract]. J Oncol Pharm Pract. 2019;25(3 suppl):1-24. doi:10.1177/1078155218823168. Schuster SJ, Bishop MR, Tam C, et al. Sustained disease control for adult patients with relapsed or refractory diffuse large B-cell lymphoma: an updated analysis of Juliet, a global pivotal phase 2 trial of tisagenlecleucel. Blood. 2018;132(suppl 1):1684. doi:10.1182/blood-2018-99-115252. Neelapu SS, Ghobadi A, Jacobson CA, et al. 2-Year Follow-up and high-risk subset analysis of Zuma-1, the pivotal study of axicabtagene ciloleucel (Axi-Cel) in patients with refractory large B cell Lymphoma. Biol Blood Marrow Transplant. 2019;25(3 suppl). doi:10.1016/j.bbmt.2018.12.148. Nastoupil LJ, Jain MD, Spiegel JY, et al. Axicabtagene ciloleucel (Axi-Cel) CD19 chimeric antigen receptor (CAR) T-cell therapy for relapsed/refractory large B-cell lymphoma: real-world experience. Blood. 2018;132(suppl 1):91. doi:10.1182/blood-2018-99-114152. Grupp SA, Maude SL, Rives S, et al. Updated analysis of the efficacy and safety of tisagenlecleucel in pediatric and young adult patients with relapsed/refractory (r/r) acute lymphoblastic leukemia [abstract]. Blood. 2018;132(suppl 1):895. doi:10.1182/blood-2018-99-112599. Faramand R, Kotani H, Morrissey D, et al. Prediction of CAR T-related toxicities in R/R DLBCL patients treated with axicabtagene ciloleucel using point of care cytokine measurements. Biol Blood Marrow Transplant. 2019;25(3 suppl):S408-S409. doi:10.1016/j.bbmt.2018.12.827. Ying Z, Huang XF, Xiang X, et al. A safe and potent anti-CD19 CAR T cell therapy. Nat Med. 2019;25:947-953. doi:10.1038/s41591-019-0421-7. Du H, Hirabayashi K, Ahn S, et al. Antitumor responses in the absence of toxicity in solid tumors by targeting B7-H3 via chimeric antigen receptor T cells. Cancer Cell. 2019;35:221-237.e8. doi:10.1016/j.ccell.2019.01.002. Gargett T, Brown MP. The inducible caspase-9 suicide gene system as a “safety switch” to limit on-target, off-tumor toxicities of chimeric antigen receptor T-cells. Front Pharmacol. 2014;5:235. doi:10.3389/fphar.2014.00235. Commentary on and reprint of Freireich EJ, Karon M, Frei E III, Quadruple combination therapy (VAMP) for acute lymphocytic leukemia of childhood, in Proceedings of the American Association for Cancer Research (1964) 5:20. In: Lichtman MA, Spivak JL, Boxer LA, Shattil SJ, Henderson ES, eds. Hematology. Landmark Papers of the Twentieth Century. Academic Press; 2000;655-657. doi:10.1016/B978-012448510-5/50152-7. Devita VT Jr, Serpick AA, Carbone PP. Combination chemotherapy in the treatment of advanced Hodgkin's disease. Ann Intern Med. 1970;73:881-895. doi:10.7326/0003-4819-73-6-881. Ahmed A, Vundamati D, Farooqi M, Guest E. Precision medicine in pediatric cancer: current applications and future prospects. High Throughput. 2018;7:39. doi:10.3390/ht7040039. Dang CV, Reddy EP, Shokat KM, Soucek L. Drugging the “undruggable” cancer targets. Nat Rev Cancer. 2017;17:502-508. doi:10.1038/nrc.2017.36. Wong AW, Urisman A, Burlingame AL, Shokat KM. Chemically reprogramming the phospho-transfer reaction to crosslink protein kinases to their substrates. Protein Sci. 2019;28:654-662. doi:10.1002/pro.3570. Lambert M, Jambon S, Depauw S, David-Cordonnier MH. Targeting transcription factors for cancer treatment. Molecules. 2018;23:1479. doi:10.3390/molecules23061479. DuBois SG, Corson LB, Stegmaier K, Janeway KA. Ushering in the next generation of precision trials for pediatric cancer. Science. 2019;363:1175-1181. doi:10.1126/science.aaw4153. Kerres N, Steurer S, Schlager S, et al. Chemically induced degradation of the oncogenic transcription factor BCL6. Cell Rep. 2017;20:2860-2875. doi:10.1016/j.celrep.2017.08.081. Morabito F, Voso MT, Hohaus S, et al. Panobinostat for the treatment of acute myelogenous leukemia. Expert Opin Investig Drugs. 2016;25:1117-1131. doi:10.1080/13543784.2016.1216971. Hemming ML, Lawlor MA, Andersen JL, et al. Enhancer domains in gastrointestinal stromal tumor regulate KIT expression and are targetable by BET bromodomain inhibition. Cancer Res. 2019;79:994-1009. doi:10.1158/0008-5472.CAN-18-1888. Lavanya V, Adil M, Ahmed N, Rishi AK, Jamal S. Small molecule inhibitors as emerging cancer therapeutics. Integr Cancer Sci Ther. 2014;1:39-46. doi:10.15761/ICST.1000109. Roberts AW, Huang DCS. Targeting BCL2 with BH3 mimetics: basic science and clinical application of venetoclax in chronic lymphocytic leukemia and related B cell malignancies. Clin Pharmacol Ther. 2017;101:89-98. doi:10.1002/cpt.553. Erlanson DA, Fesik SW, Hubbard RE, Jahnke W, Jhoti H. Twenty years on: the impact of fragments on drug discovery. Nat Rev Drug Discov. 2016;15:605-619. doi:10.1038/nrd.2016.109. Pettersson M, Crews CM. PROteolysis TArgeting Chimeras (PROTACs)-past, present and future. Drug Discov Today Technol. 2019;31:15-27. doi:10.1016/j.ddtec.2019.01.002. Dyson NJ. RB1: a prototype tumor suppressor and an enigma. Genes Dev. 2016;30:1492-1502. doi:10.1101/gad.282145.116. Han G, Spitzer MH, Bendall SC, Fantl WJ, Nolan GP. Metal-isotope-tagged monoclonal antibodies for high-dimensional mass cytometry. Nat Protoc. 2018;13:2121-2148. doi:10.1038/s41596-018-0016-7. Lee SJC, Murphy CC, Geiger AM, et al. Conceptual model for accrual to cancer clinical trials. J Clin Oncol. 2019;37:1993-1996. doi:10.1200/jco.19.00101. Hwang TJ, Carpenter D, Lauffenburger JC, Wang B, Franklin JM, Kesselheim AS. Failure of investigational drugs in late-stage clinical development and publication of trial results. JAMA Intern Med. 2016;176:1826-1833. doi:10.1001/jamainternmed.2016.6008. Wei H, Jiang H, Song B. Role of medical imaging for immune checkpoint blockade therapy: from response assessment to prognosis prediction. Cancer Med. 2019;8:5399-5413. doi:10.1002/cam4.2464. Mirsoian A, Bouchlaka MN, Sckisel GD, et al. Adiposity induces lethal cytokine storm after systemic administration of stimulatory immunotherapy regimens in aged mice. J Exp Med. 2014;211:2373-2383. doi:10.1084/jem.20140116. Zitvogel L, Ayyoub M, Routy B, Kroemer G. Microbiome and anticancer immunosurveillance. Cell. 2016;165:276-287. doi:10.1016/j.cell.2016.03.001. Anderson R, Rapoport BL. Immune dysregulation in cancer patients undergoing immune checkpoint inhibitor treatment and potential predictive strategies for future clinical practice. Front Oncol. 2018;8:80. doi:10.3389/fonc.2018.00080. Prosperi M, Min JS, Bian J, Modave F. Big data hurdles in precision medicine and precision public health. BMC Med Inform Decis Mak. 2018;18:139. doi:10.1186/s12911-018-0719-2. Michel P, Hamidou Z, Baumstarck K, et al. Clustering based on unsupervised binary trees to define subgroups of cancer patients according to symptom severity in cancer. Qual Life Res. 2018;27:555-565. doi:10.1007/s11136-017-1760-9. Mooney K, Berry DL, Whisenant M, Sjoberg D. Improving cancer care through the patient experience: how to use patient-reported outcomes in clinical practice. Am Soc Clin Oncol Educ Book. 2017;37:695-704. doi:10.1200/EDBK_175418. de Lorenzo F, Apostolidis K. The European Cancer Patient Coalition and its central role in connecting stakeholders to advance patient-centric solutions in the mission on cancer. Mol Oncol. 2019;13:653-666. doi:10.1002/1878-0261.12448. White House Office. Precision Medicine Initiative: Data Security Policy Principles and Framework. White House Office; 2016. Collins FS, Varmus H. A new initiative in precision medicine. N Engl J Med. 2015;372:793-795. doi:10.1056/NEJMpo1500523. Sicklick JK, Kato S, Okamura R, et al. Molecular profiling of cancer patients enables personalized combination therapy: the I-PREDICT study. Nat Med. 2019;25:744-750. doi:10.1038/s41591-019-0407-5. Housman G, Byler S, Heerboth S, et al. Drug resistance in cancer: an overview. Cancers (Basel). 2014;6:1769-1792. doi:10.3390/cancers6031769. Alfarouk KO, Stock CM, Taylor S, et al. Resistance to cancer chemotherapy: failure in drug response from ADME to P-gp. Cancer Cell Int. 2015;15:71. doi:10.1186/s12935-015-0221-1. Lovly CM, Iyengar P, Gainor JF. Managing resistance to EFGR- and ALK-targeted therapies. Am Soc Clin Oncol Educ Book. 2017;37:607-618. doi:10.1200/EDBK_176251. Turner NC, Reis-Filho JS. Genetic heterogeneity and cancer drug resistance. Lancet Oncol. 2012;13:e178-e185. doi:10.1016/S1470-2045(11)70335-7. Gros P, Neriah Y Ben, Croop JM, Housman DE. Isolation and expression of a complementary DNA that confers multidrug resistance. Nature. 1986;323:728-731. doi:10.1038/323728a0. Choi Y, Yu AM. ABC transporters in multidrug resistance and pharmacokinetics, and strategies for drug development. Curr Pharm Des. 2014;20:793-807. doi:10.2174/138161282005140214165212. Cree IA, Charlton P. Molecular chess? Hallmarks of anti-cancer drug resistance. BMC Cancer. 2017;17:10. doi:10.1186/s12885-016-2999-1. Gottesman MM, Fojo T, Bates SE. Multidrug resistance in cancer: role of ATP-dependent transporters. Nat Rev Cancer. 2002;2:48-58. doi:10.1038/nrc706. Gorre ME, Mohammed M, Ellwood K, et al. Clinical resistance to STI-571 cancer therapy caused by BCR-ABL gene mutation or amplification. Science. 2001;293:876-880. doi:10.1126/science.1062538. Van Allen EM, Wagle N, Sucker A, et al. The genetic landscape of clinical resistance to RAF inhibition in metastatic melanoma. Cancer Discov. 2014;4:94-109. doi:10.1158/2159-8290.cd-13-0617. Arora VK, Schenkein E, Murali R, et al. Glucocorticoid receptor confers resistance to antiandrogens by bypassing androgen receptor blockade. Cell. 2013;155:1309-1322. doi:10.1016/j.cell.2013.11.012. Azzariti A, Porcelli L, Simone GM, et al. Tyrosine kinase inhibitors and multidrug resistance proteins: interactions and biological consequences. Cancer Chemother Pharmacol. 2010;65:335-346. doi:10.1007/s00280-009-1039-0. Adamska A, Falasca M. ATP-binding cassette transporters in progression and clinical outcome of pancreatic cancer: what is the way forward? World J Gastroenterol. 2018;24:3222-3238. doi:10.3748/wjg.v24.i29.3222. Cripe LD, Uno H, Paietta EM, et al. Zosuquidar, a novel modulator of P-glycoprotein, does not improve the outcome of older patients with newly diagnosed acute myeloid leukemia: a randomized, placebo-controlled trial of the Eastern Cooperative Oncology Group 3999. Blood. 2010;116:4077-4085. doi:10.1182/blood-2010-04-277269. Visakorpi T, Hyytinen E, Koivisto P, et al. In vivo amplification of the androgen receptor gene and progression of human prostate cancer. Nat Genet. 1995;9:401-406. doi:10.1038/ng0495-401. Chen CD, Welsbie DS, Tran C, et al. Molecular determinants of resistance to antiandrogen therapy. Nat Med. 2004;10:33-39. doi:10.1038/nm972. Miller SM, Goulet DR, Johnson GL. Targeting the breast cancer kinome. J Cell Physiol. 2017;232:53-60. doi:10.1002/jcp.25427. Miao W, Li L, Liu X, et al. A targeted quantitative proteomic method revealed a substantial reprogramming of kinome during melanoma metastasis. Sci Rep. 2020;10:2485. doi:10.1038/s41598-020-59572-5. McNeill RS, Canoutas DA, Stuhlmiller TJ, et al. Combination therapy with potent PI3K and MAPK inhibitors overcomes adaptive kinome resistance to single agents in preclinical models of glioblastoma. Neuro Oncol. 2017;19:1469-1480. doi:10.1093/neuonc/nox044. Johannessen CM, Johnson LA, Piccioni F, et al. A melanocyte lineage program confers resistance to MAP kinase pathway inhibition. Nature. 2013;504:138-142. doi:10.1038/nature12688. Mohammad RM, Muqbil I, Lowe L, et al. Broad targeting of resistance to apoptosis in cancer. Semin Cancer Biol. 2015;35(suppl):S78-S103. doi:10.1016/j.semcancer.2015.03.001. Roberson RS, Kussick SJ, Vallieres E, Chen SYJ, Wu DY. Escape from therapy-induced accelerated cellular senescence in p53-null lung cancer cells and in human lung cancers. Cancer Res. 2005;65:2795-2803. doi:10.1158/0008-5472.CAN-04-1270. Childs BG, Baker DJ, Kirkland JL, Campisi J, Deursen JM. Senescence and apoptosis: dueling or complementary cell fates? EMBO Rep. 2014;15:1139-1153. doi:10.15252/embr.201439245. Bhola NE, Balko JM, Dugger TC, et al. TGF-β inhibition enhances chemotherapy action against triple-negative breast cancer. J Clin Invest. 2013;123:1348-1358. doi:10.1172/JCI65416. Das CK, Mandal M, Kogel D. Pro-survival autophagy and cancer cell resistance to therapy. Cancer Metastasis Rev. 2018;37:749-766. doi:10.1007/s10555-018-9727-z. Yan C, Li TS. Dual role of mitophagy in cancer drug resistance. Anticancer Res. 2018;38:617-621. doi:10.21873/anticanres.12266. Doherty MR, Smigiel JM, Junk DJ, Jackson MW. Cancer stem cell plasticity drives therapeutic resistance. Cancers (Basel). 2016;8:8. doi:10.3390/cancers8010008. Gupta PB, Pastushenko I, Skibinski A, Blanpain C, Kuperwasser C. Phenotypic plasticity: driver of cancer initiation, progression, and therapy resistance. Cell Stem Cell. 2019;24:65-78. doi:10.1016/j.stem.2018.11.011. Corra F, Agnoletto C, Minotti L, Baldassari F, Volinia S. The network of non-coding RNAs in cancer drug resistance. Front Oncol. 2018;8:327. doi:10.3389/fonc.2018.00327. Hu WZ, Tan CL, He YJ, Zhang GQ, Xu Y, Tang JH. Functional miRNAs in breast cancer drug resistance. Onco Targets Ther. 2018;11:1529-1541. doi:10.2147/OTT.S152462. Qian Y. Inhibitors of glucose transport and glycolysis as novel anticancer therapeutics. World J Transl Med. 2014;3:37-57. doi:10.5528/wjtm.v3.i2.37. Wang X, Li Y, Qian Y, et al. Extracellular ATP, as an energy and phosphorylating molecule, induces different types of drug resistances in cancer cells through ATP internalization and intracellular ATP level increase. Oncotarget. 2017;8:87860-87877. doi:10.18632/oncotarget.21231. Kim IS, Zhang XHF. One microenvironment does not fit all: heterogeneity beyond cancer cells. Cancer Metastasis Rev. 2016;35:601-629. doi:10.1007/s10555-016-9643-z. Alizadeh AA, Aranda V, Bardelli A, et al. Toward understanding and exploiting tumor heterogeneity. Nat Med. 2015;21:846-853. doi:10.1038/nm.3915. McGranahan N, Swanton C. Clonal heterogeneity and tumor evolution: past, present, and the future. Cell. 2017;168:613-628. doi:10.1016/j.cell.2017.01.018. Roychowdhury S, Chinnaiyan AM. Translating cancer genomes and transcriptomes for precision oncology. CA Cancer J Clin. 2016;66:75-88. doi:10.3322/caac.21329. Wang Y, Navin NE. Advances and applications of single-cell sequencing technologies. Mol Cell. 2015;58:598-609. doi:10.1016/j.molcel.2015.05.005. Casasent AK, Schalck A, Gao R, et al. Multiclonal invasion in breast tumors identified by topographic single cell sequencing. Cell. 2018;172:205-217.e12. doi:10.1016/j.cell.2017.12.007. Polyak K. Tumor heterogeneity confounds and illuminates: a case for Darwinian tumor evolution. Nat Med. 2014;20:344-346. doi:10.1038/nm.3518. Maley CC, Aktipis A, Graham TA, et al. Classifying the evolutionary and ecological features of neoplasms. Nat Rev Cancer. 2017;17:605-619. doi:10.1038/nrc.2017.69. Wang D, Niu X, Wang Z, et al. Multiregion sequencing reveals the genetic heterogeneity and evolutionary history of osteosarcoma and matched pulmonary metastases. Cancer Res. 2019;79:7-20. doi:10.1158/0008-5472.CAN-18-1086. Bakhoum SF, Landau DA. Chromosomal instability as a driver of tumor heterogeneity and evolution. Cold Spring Harb Perspect Med. 2017;7:a029611. doi:10.1101/cshperspect.a029611. Sansregret L, Swanton C. The role of aneuploidy in cancer evolution. Cold Spring Harb Perspect Med. 2017;7:a028373. doi:10.1101/cshperspect.a028373. Brown R, Curry E, Magnani L, Wilhelm-Benartzi CS, Borley J. Poised epigenetic states and acquired drug resistance in cancer. Nat Rev Cancer. 2014;14:747-753. doi:10.1038/nrc3819. Miyahira AK, Den RB, Carlo MI, et al. Tumor cell heterogeneity and resistance; report from the 2018 Coffey-Holden Prostate Cancer Academy Meeting. Prostate. 2019;79:244-258. doi:10.1002/pros.23729. Bussard KM, Mutkus L, Stumpf K, Gomez-Manzano C, Marini FC. Tumor-associated stromal cells as key contributors to the tumor microenvironment. Breast Cancer Res. 2016;18:84. doi:10.1186/s13058-016-0740-2. Son B, Lee S, Youn H, Kim E, Kim W, Youn B. The role of tumor microenvironment in therapeutic resistance. Oncotarget. 2017;8:3933-3945. doi:10.18632/oncotarget.13907. Spitzer MH, Nolan GP. Mass cytometry: single cells, many features. Cell. 2016;165:780-791. doi:10.1016/j.cell.2016.04.019. Janes KA. Single-cell states versus single-cell atlases-two classes of heterogeneity that differ in meaning and method. Curr Opin Biotechnol. 2016;39:120-125. doi:10.1016/J.COPBIO.2016.03.015. Kim C, Gao R, Sei E, et al. Chemoresistance evolution in triple-negative breast cancer delineated by single-cell sequencing. Cell. 2018;173:879-893.e13. doi:10.1016/j.cell.2018.03.041. Harrison PT, Huang PH. Exploiting vulnerabilities in cancer signalling networks to combat targeted therapy resistance. Essays Biochem. 2018;62:583-593. doi:10.1042/ebc20180016. Gidoin C, Peischl S. Range expansion theories could shed light on the spatial structure of intra-tumour heterogeneity. Bull Math Biol. 2019;81:4761-4777. doi:10.1007/s11538-018-00540-6. Brown CH, Curran G, Palinkas LA, et al. An overview of research and evaluation designs for dissemination and implementation. Annu Rev Public Health. 2017;38:1-22. doi:10.1146/annurev-publhealth-031816-044215. Rous P. A sarcoma of the fowl transmissible by an agent separable from the tumor cells. J Exp Med. 1911;13:397-411. doi:10.1084/jem.13.4.397. Hartwell LH, Culotti J, Reid B. Genetic control of the cell-division cycle in yeast. I. Detection of mutants. Proc Natl Acad Sci U S A. 1970;66:352-359. doi:10.1073/pnas.66.2.352. Hartwell LH, Culotti J, Pringle JR, Reid BJ. Genetic control of the cell division cycle in yeast. Science. 1974;183:46-51. doi:10.1126/science.183.4120.46. Miles WO, Dyson NJ, Walker JA. Modeling tumor invasion and metastasis in Drosophila. Dis Model Mech. 2011;4:753-761. doi:10.1242/dmm.006908. Levinson S, Cagan RL. Drosophila cancer models identify functional differences between Ret fusions. Cell Rep. 2016;16:3052-3061. doi:10.1016/j.celrep.2016.08.019. Strange K. Drug discovery in fish, flies, and worms. ILAR J. 2016;57:133-143. doi:10.1093/ilar/ilw034. Yang SA, Portilla JM, Mihailovic S, Huang YC, Deng WM. Oncogenic notch triggers neoplastic tumorigenesis in a transition-zone-like tissue microenvironment. Dev Cell. 2019;49:461-472.e5. doi:10.1016/j.devcel.2019.03.015. Sulston JE, Horvitz HR. Post-embryonic cell lineages of the nematode, Caenorhabditis elegans. Dev Biol. 1977;56:110-156. doi:10.1016/0012-1606(77)90158-0. Akay A, Jordan D, Navarro IC, et al. Identification of functional long non-coding RNAs in C. elegans. BMC Biol. 2019;17:14. doi:10.1186/s12915-019-0635-7. Ceol CJ, Houvras Y, Jane-Valbuena J, et al. The histone methyltransferase SETDB1 is recurrently amplified in melanoma and accelerates its onset. Nature. 2011;471:513-517. doi:10.1038/nature09806. Stuelten CH, Parent CA, Montell DJ. Cell motility in cancer invasion and metastasis: insights from simple model organisms. Nat Rev Cancer. 2018;18:296-312. doi:10.1038/nrc.2018.15. Zhao S, Huang J, Ye J. A fresh look at zebrafish from the perspective of cancer research. J Exp Clin Cancer Res. 2015;34:80. doi:10.1186/s13046-015-0196-8. Kersten K, Visser KE, Miltenburg MH, Jonkers J. Genetically engineered mouse models in oncology research and cancer medicine. EMBO Mol Med. 2017;9:137-153. doi:10.15252/emmm.201606857. Bailey KL, Carlson MA. Porcine models of pancreatic cancer. Front Oncol. 2019;9:144. doi:10.3389/fonc.2019.00144. White KA, Swier VJ, Cain JT, et al. A porcine model of neurofibromatosis type 1 that mimics the human disease. JCI Insight. 2018;3:e120402. doi:10.1172/jci.insight.120402. Watson AL, Carlson DF, Largaespada DA, Hackett PB, Fahrenkrug SC. Engineered swine models of cancer. Front Genet. 2016;7:78. doi:10.3389/fgene.2016.00078. Kirienko NV, Mani K, Fay DS. Cancer models in Caenorhabditis elegans. Dev Dyn. 2010;239:1413-1448. doi:10.1002/dvdy.22247. Cagan RL, Zon LI, White RM. Modeling cancer with flies and fish. Dev Cell. 2019;49:317-324. doi:10.1016/j.devcel.2019.04.013. Talmadge JE, Singh RK, Fidler IJ, Raz A. Murine models to evaluate novel and conventional therapeutic strategies for cancer. Am J Pathol. 2007;170:793-804. doi:10.2353/ajpath.2007.060929. Sharpless NE, DePinho RA. The mighty mouse: genetically engineered mouse models in cancer drug development. Nat Rev Drug Discov. 2006;5:741-754. doi:10.1038/nrd2110. Ireson CR, Alavijeh MS, Palmer AM, Fowler ER, Jones HJ. The role of mouse tumour models in the discovery and development of anticancer drugs. Br J Cancer. 2019;121:101-108. doi:10.1038/s41416-019-0495-5. Huang CH, Lee KC, Doudna JA. Applications of CRISPR-Cas enzymes in cancer therapeutics and detection. Trends Cancer. 2018;4:499-512. doi:10.1016/j.trecan.2018.05.006. Paoloni MC, Khanna C. Comparative oncology today. Vet Clin North Am Small Anim Pract. 2007;37:1023-1032. doi:10.1016/j.cvsm.2007.08.003. Jackson SJ, Thomas GJ. Human tissue models in cancer research: looking beyond the mouse. Dis Model Mech. 2017;10:939-942. doi:10.1242/dmm.031260. Xu H, Lyu X, Yi M, Zhao W, Song Y, Wu K. Organoid technology and applications in cancer research. J Hematol Oncol. 2018;11:116. doi:10.1186/s13045-018-0662-9. D’Agosto S, Andreani S, Scarpa A, Corbo V. Preclinical modelling of PDA: is organoid the new black? Int J Mol Sci. 2019;20:2766. doi:10.3390/ijms20112766. Izumchenko E, Meir J, Bedi A, Wysocki PT, Hoque MO, Sidransky D. Patient-derived xenografts as tools in pharmaceutical development. Clin Pharmacol Ther. 2016;99:612-621. doi:10.1002/cpt.354. Tuveson D, Clevers H. Cancer modeling meets human organoid technology. Science. 2019;364:952-955. doi:10.1126/science.aaw6985. Fong ELS, Harrington DA, Farach-Carson MC, Yu H. Heralding a new paradigm in 3D tumor modeling. Biomaterials. 2016;108:197-213. doi:10.1016/j.biomaterials.2016.08.052. Sleeboom JJF, Amirabadi HE, Nair P, Sahlgren CM, Den Toonder JMJ. Metastasis in context: modeling the tumor microenvironment with cancer-on-a-chip approaches. Dis Model Mech. 2018;11:dmm033100. doi:10.1242/dmm.033100. Nguyen DHT, Lee E, Alimperti S, et al. A biomimetic pancreatic cancer on-chip reveals endothelial ablation via ALK7 signaling. Sci Adv. 2019;5:eaav6789. doi:10.1126/sciadv.aav6789. Bolck HA, Pauli C, Gobel E, et al. Cancer sample biobanking at the next level: combining tissue with living cell repositories to promote precision medicine. Front Cell Dev Biol. 2019;7:246. doi:10.3389/fcell.2019.00246. Materi W, Wishart DS. Computational systems biology in drug discovery and development: methods and applications. Drug Discov Today. 2007;12(7-8):295-303. doi:10.1016/j.drudis.2007.02.013. Cruz JA, Wishart DS. Applications of machine learning in cancer prediction and prognosis. Cancer Inform. 2007;2:59-77. Sumathipala Y, Shafiq M, Bongen E, Brinton C, Paik D. Machine learning to predict lung nodule biopsy method using CT image features: a pilot study. Comput Med Imaging Graph. 2019;71:1-8. doi:10.1016/j.compmedimag.2018.10.006. Capper D, Jones DTW, Sill M, et al. DNA methylation-based classification of central nervous system tumours. Nature. 2018;555:469-474. doi:10.1038/nature26000. Kourou K, Exarchos TP, Exarchos KP, Karamouzis MV, Fotiadis DI. Machine learning applications in cancer prognosis and prediction. Comput Struct Biotechnol J. 2014;13:8-17. doi:10.1016/j.csbj.2014.11.005. Gajewski TF, Schreiber H, Fu YX. Innate and adaptive immune cells in the tumor microenvironment. Nat Immunol. 2013;14:1014-1022. doi:10.1038/ni.2703. Tao L, Huang G, Song H, Chen Y, Chen L. Cancer associated fibroblasts: an essential role in the tumor microenvironment. Oncol Lett. 2017;14:2611-2620. doi:10.3892/ol.2017.6497. Kai FB, Drain AP, Weaver VM. The extracellular matrix modulates the metastatic journey. Dev Cell. 2019;49:332-346. doi:10.1016/j.devcel.2019.03.026. Doerstling SS, O’Flanagan CH, Hursting SD. Obesity and cancer metabolism: a perspective on interacting tumor-intrinsic and extrinsic factors. Front Oncol. 2017;7:216. doi:10.3389/fonc.2017.00216. Goodwin PJ, Meyerhardt JA, Hursting SD. Host factors and cancer outcome. J Clin Oncol. 2010;28:4019-4021. doi:10.1200/JCO.2010.31.5143. Thomas DW, Burns J, Audette J, Carroll A, Dow-Hygelund C, Hay M. Clinical development success rates 2006-2015. In: BIO Industry Analysis, Amplion, Inc, Biomedtracker. Biotechnology Innovation Organization (BIO); 2016:1-16. Lazo JS. The hubris and humility of cancer pharmacology in the post immuno-oncology era. Pharmacol Res Perspect. 2019;7:e00527. doi:10.1002/prp2.527. National Cancer Institute at the National Institutes of Health, US Department of Health and Human Services. The Cancer Genome Atlas Program. Accessed November 4, 2020. cancer.gov/about-nci/organization/ccg/research/structural-genomics/tcgadoi:10.1016/j.coph.2011.06.011. Patterson SL, Maresso KC, Hawk E. Cancer chemoprevention: successes and failures. Clin Chem. 2013;59:94-101. doi:10.1373/clinchem.2012.185389. Lisio MA, Fu L, Goyeneche A, Gao ZH, Telleria C. High-grade serous ovarian cancer: basic sciences, clinical and therapeutic standpoints. Int J Mol Sci. 2019;20:952. doi:10.3390/ijms20040952. Yeh AC, Ramaswamy S. Mechanisms of cancer cell dormancy-another hallmark of cancer? Cancer Res. 2015;75:5014-5022. doi:10.1158/0008-5472.CAN-15-1370. Yang L, Yang S, Li X, et al. Tumor organoids: from inception to future in cancer research. Cancer Lett. 2019;454:120-133. doi:10.1016/j.canlet.2019.04.005. Sontheimer-Phelps A, Hassell BA, Ingber DE. Modelling cancer in microfluidic human organs-on-chips. Nat Rev Cancer. 2019;19:65-81. doi:10.1038/s41568-018-0104-6. Vander Heiden MG, Cantley LC, Thompson CB. Understanding the Warburg effect: the metabolic requirements of cell proliferation. Science. 2009;324:1029-1033. doi:10.1126/science.1160809. Garber K. Targeting mTOR: something old, something new. J Natl Cancer Inst. 2009;101:288-290. doi:10.1093/jnci/djp034. Moreno A, Akcakanat A, Munsell MF, Soni A, Yao JC, Meric-Bernstam F. Antitumor activity of rapamycin and octreotide as single agents or in combination in neuroendocrine tumors. Endocr Relat Cancer. 2008;15:257-266. doi:10.1677/ERC-07-0202. Thompson LA, Kim M, Wenger SD, O’Bryant CL. Everolimus: a new treatment option for advanced pancreatic neuroendocrine tumors. Ann Pharmacother. 2012;46:1212-1219. doi:10.1345/aph.1R087. Hopkins BD, Goncalves MD, Cantley LC. Obesity and cancer mechanisms: cancer metabolism. J Clin Oncol. 2016;34:4277-4283. doi:10.1200/JCO.2016.67.9712. Demark-Wahnefried W, Schmitz KH, Alfano CM, et al. Weight management and physical activity throughout the cancer care continuum. CA Cancer J Clin. 2018;68:64-89. doi:10.3322/caac.21441. Ligibel JA, Alfano CM, Hershman D, et al. Recommendations for obesity clinical trials in cancer survivors: American Society of Clinical Oncology statement. J Clin Oncol. 2015;33:3961-3967. doi:10.1200/JCO.2015.63.1440. Hopkins JJ, Sawyer MB. A review of body composition and pharmacokinetics in oncology. Expert Rev Clin Pharmacol. 2017;10:947-956. doi:10.1080/17512433.2017.1347503. Emmons KM, Colditz GA. Realizing the potential of cancer prevention-the role of implementation science. N Engl J Med. 2017;376:986-990. doi:10.1056/NEJMsb1609101. Colditz GA, Wolin KY, Gehlert S. Applying what we know to accelerate cancer prevention. Sci Transl Med. 2012;4:127rv4. doi:10.1126/scitranslmed.3003218. Arnold M, Pandeya N, Byrnes G, et al. Global burden of cancer attributable to high body-mass index in 2012: a population-based study. Lancet Oncol. 2015;16:36-46. doi:10.1016/S1470-2045(14)71123-4. Williams EP, Mesidor M, Winters K, Dubbert PM, Wyatt SB. Overweight and obesity: prevalence, consequences, and causes of a growing public health problem. Curr Obes Rep. 2015;4:363-370. doi:10.1007/s13679-015-0169-4. Stigler FL, Lustig RH, Ma JI. Mechanisms, pathophysiology, and management of obesity. N Engl J Med. 2017;376:1491. doi:10.1056/NEJMc1701944. Sherling DH, Perumareddi P, Hennekens CH. Metabolic syndrome: clinical and policy implications of the new silent killer. J Cardiovasc Pharmacol Ther. 2017;22:365-367. doi:10.1177/1074248416686187. Avgerinos KI, Spyrou N, Mantzoros CS, Dalamaga M. Obesity and cancer risk: emerging biological mechanisms and perspectives. Metabolism. 2019;92:121-135. doi:10.1016/j.metabol.2018.11.001. Himbert C, Delphan M, Scherer D, Bowers LW, Hursting S, Ulrich CM. Signals from the adipose microenvironment and the obesity-cancer link-a systematic review. Cancer Prev Res (Phila). 2017;10:494-506. doi:10.1158/1940-6207.CAPR-16-0322. Helmink BA, Khan MAW, Hermann A, Gopalakrishnan V, Wargo JA. The microbiome, cancer, and cancer therapy. Nat Med. 2019;25:377-388. doi:10.1038/s41591-019-0377-7. Wroblewski LE, Peek RM, Wilson KT. Helicobacter pylori and gastric cancer: factors that modulate disease risk. Clin Microbiol Rev. 2010;23:713-739. doi:10.1128/CMR.00011-10. Levrero M, Zucman-Rossi J. Mechanisms of HBV-induced hepatocellular carcinoma. J Hepatol. 2016;64(1 suppl):S84-S101. doi:10.1016/j.jhep.2016.02.021. Yongvanit P, Pinlaor S, Loilome W. Risk biomarkers for assessment and chemoprevention of liver fluke-associated cholangiocarcinoma. J Hepatobiliary Pancreat Sci. 2014;21:309-315. doi:10.1002/jhbp.63. Sun J, Kato I. Gut microbiota, inflammation and colorectal cancer. Genes Dis. 2016;3:130-143. doi:10.1016/j.gendis.2016.03.004. Rooks MG, Garrett WS. Gut microbiota, metabolites and host immunity. Nat Rev Immunol. 2016;16:341-352. doi:10.1038/nri.2016.42. Gagniere J, Raisch J, Veziant J, et al. Gut microbiota imbalance and colorectal cancer. World J Gastroenterol. 2016;22:501-518. doi:10.3748/wjg.v22.i2.501. Bhatt AP, Redinbo MR, Bultman SJ. The role of the microbiome in cancer development and therapy. CA Cancer J Clin. 2017;67:326-344. doi:10.3322/caac.21398. Lehouritis P, Cummins J, Stanton M, et al. Local bacteria affect the efficacy of chemotherapeutic drugs. Sci Rep. 2015;5:14554. doi:10.1038/srep14554. Routy B, Le Chatelier E, Derosa L, et al. Gut microbiome influences efficacy of PD-1-based immunotherapy against epithelial tumors. Science. 2018;359:91-97. doi:10.1126/science.aan3706. Gopalakrishnan V, Spencer CN, Nezi L, et al. Gut microbiome modulates response to anti-PD-1 immunotherapy in melanoma patients. Science. 2018;359:97-103. doi:10.1126/science.aan4236. Matson V, Fessler J, Bao R, et al. The commensal microbiome is associated with anti-PD-1 efficacy in metastatic melanoma patients. Science. 2018;359:104-108. doi:10.1126/science.aao3290. Kroemer G, Lopez-Otin C, Madeo F, de Cabo R. Carbotoxicity-noxious effects of carbohydrates. Cell. 2018;175:605-614. doi:10.1016/j.cell.2018.07.044. Gu Y, Wang X, Li J, et al. Analyses of gut microbiota and plasma bile acids enable stratification of patients for antidiabetic treatment. Nat Commun. 2017;8:1785. doi:10.1038/s41467-017-01682-2. Spencer CN, Gopalakrishnan V, McQuade J, et al. Abstract 2838: The gut microbiome (GM) and immunotherapy response are influenced by host lifestyle factors. Cancer Res. 2019;79(suppl):2838. doi:10.1158/1538-7445.AM2019-2838. Welch DR, Hurst DR. Defining the hallmarks of metastasis. Cancer Res. 2019;79:3011-3027. doi:10.1158/0008-5472.CAN-19-0458. Giuliano M, Schettini F, Rognoni C, et al. Endocrine treatment versus chemotherapy in postmenopausal women with hormone receptor-positive, HER2-negative, metastatic breast cancer: a systematic review and network meta-analysis. Lancet Oncol. 2019;20:1360-1369. doi:10.1016/S1470-2045(19)30420-6. Vonderheide RH. CD40 agonist antibodies in cancer immunotherapy. Annu Rev Med. 2020;71:47-58. doi:10.1146/annurev-med-062518-045435. Niranjan A, Dade Lunsford L, Ahluwalia MS. Targeted therapies for brain metastases. Prog Neurol Surg. 2019;34:125-137. doi:10.1159/000493057. Venur VA, Cohen JV, Brastianos PK. Targeting molecular pathways in intracranial metastatic disease. Front Oncol. 2019;9:99. doi:10.3389/fonc.2019.00099. Lorente D, Fizazi K, Sweeney C, de Bono JS. Optimal treatment sequence for metastatic castration-resistant prostate cancer. Eur Urol Focus. 2016;2:488-498. doi:10.1016/j.euf.2016.10.008. Atkins MB, Larkin J. Immunotherapy combined or sequenced with targeted therapy in the treatment of solid tumors: current perspectives. J Natl Cancer Inst. 2016;108:djv414. doi:10.1093/jnci/djv414. Hunter KW, Amin R, Deasy S, Ha NH, Wakefield L. Genetic insights into the morass of metastatic heterogeneity. Nat Rev Cancer. 2018;18:211-223. doi:10.1038/nrc.2017.126. Ahronian LG, Corcoran RB. Strategies for monitoring and combating resistance to combination kinase inhibitors for cancer therapy. Genome Med. 2017;9:37. doi:10.1186/s13073-017-0431-3. Sharma S, Kelly TK, Jones PA. Epigenetics in cancer. Carcinogenesis. 2010;31:27-36. doi:10.1093/carcin/bgp220. McBride MJ, Kadoch C. Disruption of mammalian SWI/SNF and polycomb complexes in human sarcomas: mechanisms and therapeutic opportunities. J Pathol. 2018;244:638-649. doi:10.1002/path.5042. Rao RC, Dou Y. Hijacked in cancer: the KMT2 (MLL) family of methyltransferases. Nat Rev Cancer. 2015;15:334-346. doi:10.1038/nrc3929. Kandoth C, McLellan MD, Vandin F, et al. Mutational landscape and significance across 12 major cancer types. Nature. 2013;502:333-339. doi:10.1038/nature12634. Flavahan WA, Gaskell E, Bernstein BE. Epigenetic plasticity and the hallmarks of cancer. Science. 2017;357:eaal2380. doi:10.1126/science.aal2380. Raj K, Mufti GJ. Azacytidine (Vidaza®) in the treatment of myelodysplastic syndromes. Ther Clin Risk Manag. 2006;2:377-388. doi:10.2147/tcrm.2006.2.4.377. Santos FPS, Kantarjian H, Garcia-Manero G, Issa JP, Ravandi F. Decitabine in the treatment of myelodysplastic syndromes. Expert Rev Anticancer Ther. 2010;10:9-22. doi:10.1586/ERA.09.164. Kantarjian HM, Roboz GJ, Kropf PL, et al. Guadecitabine (SGI-110) in treatment-naive patients with acute myeloid leukaemia: phase 2 results from a multicentre, randomised, phase 1/2 trial. Lancet Oncol. 2017;18:1317-1326. doi:10.1016/S1470-2045(17)30576-4. Gayther SA, Batley SJ, Linger L, et al. Mutations truncating the EP300 acetylase in human cancers. Nat Genet. 2000;24:300-303. doi:10.1038/73536. Tao YF, Li P, Du XJ, et al. Differential mRNA expression levels of human histone-modifying enzymes in normal karyotype B cell pediatric acute lymphoblastic leukemia. Int J Mol Sci. 2013;14:3376-3394. doi:10.3390/ijms14023376. Eckschlager T, Plch J, Stiborova M, Hrabeta J. Histone deacetylase inhibitors as anticancer drugs. Int J Mol Sci. 2017;187:1414. doi:10.3390/ijms18071414. Suraweera A, O’Byrne KJ, Richard DJ. Combination therapy with histone deacetylase inhibitors (HDACi) for the treatment of cancer: achieving the full therapeutic potential of HDACi. Front Oncol. 2018;8:92. doi:10.3389/fonc.2018.00092. Cho JH, Oezkan F, Koenig M, Otterson GA, Herman JG, He K. Epigenetic therapeutics and their impact in immunotherapy of lung cancer. Curr Pharmacol Rep. 2017;3:360-373. doi:10.1007/s40495-017-0110-5. Berdasco M, Esteller M. Clinical epigenetics: seizing opportunities for translation. Nat Rev Genet. 2019. doi:10.1038/s41576-018-0074-2. Widschwendter M, Jones A, Evans I, et al. Epigenome-based cancer risk prediction: rationale, opportunities and challenges. Nat Rev Clin Oncol. 2018;15:292-309. doi:10.1038/nrclinonc.2018.30. Moufarrij S, Dandapani M, Arthofer E, et al. Epigenetic therapy for ovarian cancer: promise and progress. Clin Epigenetics. 2019;11:7. doi:10.1186/s13148-018-0602-0. Brown AF, Ma GX, Miranda J, et al. Structural interventions to reduce and eliminate health disparities. Am J Public Health. 2019;109(suppl 1):S72-S78. doi:10.2105/AJPH.2018.304844. Braveman PA, Kumanyika S, Fielding J, et al. Health disparities and health equity: the issue is justice. Am J Public Health. 2011;101(suppl 1):S149-S155. doi:10.2105/AJPH.2010.300062. Hall KL, Oh A, Perez LG, et al. The ecology of multilevel intervention research. Transl Behav Med. 2018;8:968-978. doi:10.1093/tbm/iby102. Ramsey SD, Willke RJ, Glick H, et al. Cost-effectiveness analysis alongside clinical trials II-an ISPOR Good Research Practices Task Force report. Value Health. 2015;18:161-172. doi:10.1016/j.jval.2015.02.001. Ginexi EM, Vollinger RE. National Cancer Institute's leadership role in promoting state and community tobacco control research. Tob Control. 2016;25(suppl 2):i4-i5. doi:10.1136/tobaccocontrol-2016-053153. American Cancer Society. Cancer Treatment and Survivorship Facts and Figures 2016-2017. American Cancer Society; 2016. Miller KD, Siegel RL, Lin CC, et al. Cancer treatment and survivorship statistics, 2016. CA Cancer J Clin. 2016;66:271-289. doi:10.3322/caac.21349. Institute of Medicine and National Research Council. From Cancer Patient to Cancer Survivor: Lost in Transition. The National Academies Press; 2006. Jacobsen PB, DeRosa AP, Henderson TO, et al. Systematic review of the impact of cancer survivorship care plans on health outcomes and health care delivery. J Clin Oncol. 2018;36:2088-2100. doi:10.1200/JCO.2018.77.7482. National Academies of Sciences, Engineering, and Medicine; Policy and Global Affairs; Board on Higher Education and Workforce; Committee on the Next Generation Initiative; Benison L, Daniels R, eds. The Next Generation of Biomedical and Behavioral Sciences Researchers: Breaking Through. National Academies Press; 2018. Alberts B, Kirschner MW, Tilghman S, Varmus H. Rescuing US biomedical research from its systemic flaws. Proc Natl Acad Sci U S A. 2014;111:5773-5777. doi:10.1073/pnas.1404402111. National Research Council (US) to Study the National Needs for Biomedical, Behavioral, and Clinical Research Personnel. Research Training in the Biomedical, Behavioral, and Clinical Research Sciences. National Academies Press; 2011. National Science Foundation. NSF's 10 Big Ideas. Accessed November 18, 2020. nsf.gov/news/special_reports/big_ideas/. |
| فهرسة مساهمة: | Keywords: cancer modeling; cancer screening; cancer treatment; precision medicine |
| المشرفين على المادة: | 0 (Biomarkers, Tumor) |
| تواريخ الأحداث: | Date Created: 20201216 Date Completed: 20210930 Latest Revision: 20210930 |
| رمز التحديث: | 20240829 |
| DOI: | 10.3322/caac.21652 |
| PMID: | 33326126 |
| قاعدة البيانات: | MEDLINE |
| تدمد: | 1542-4863 |
|---|---|
| DOI: | 10.3322/caac.21652 |