關鍵字: 消化系統癌(Digestive system cancers, DSC)、轉移、肝癌、胰臟癌、高轉移、高侵襲
消化系統癌症（DSC）是全球常見的惡性癌症類型。消化系統包括食道、胃、肝臟、胰臟，和大小腸。大多數DSC的病患初期通常因為沒有症狀或其他疾病掩蓋而造成延遲診斷，往往確診時已是晚期甚至出現轉移到其他器官的情況。而晚期的癌症診斷非常困難，治療後容易發生復發，導致在治療上出現棘手的問題。癌症死亡中，有高達90%的原因是因為癌症轉移。其中肝細胞癌（HCC）患者因為不易早期確診，通常確診時已為晚期並且可能出現轉移，造成傳統化療的效果不佳。儘管肝癌治療方式不斷突破，預後仍然很差，因此目前肝癌仍然是難以治療的癌症之一。另外，胰腺癌患者治療效果很差，亦是因為前期不易診斷，診斷後都已是晚期，腫瘤已造成局部浸潤和轉移，這也是造成胰腺癌為死亡率最高的癌症之一的主要原因。然而，肝癌和胰腺癌的轉移機制仍不清楚。因此在本論文中，我們使用人類肝癌Huh-7細胞和胰腺癌AsPC-1細胞透過transwell實驗的方式，建立高遷徙/侵襲的細胞模式。將癌細胞接種在不含基質的transwell chamber上，培養24小時後，收集移至chamber底部的細胞，將這些細胞繼續培養，反覆篩選三次後得到高遷徙細胞Huh-7/M3和AsPC-1/M3 細胞。接著我們進一步利用高遷徙細胞接種到含有基質的transwell上，培養72小時後，收集通過chamber底部的細胞，將這些細胞繼續培養，反覆二次後建立高侵襲細胞Huh-7/M3-I2和AsPC-1/M3-I2細胞。我們也利用了transwell遷移及侵襲實驗證實我們所建立之細胞株具有高遷移及高侵襲能力。我們也進一步比較了親代、高遷移及高侵襲細胞株型態、生長、遷移/侵襲及細胞週期之間差異。在未來，我們可以利用所建立的高轉移及高侵襲的肝癌以及胰臟癌細胞模型，篩選新的診斷標誌並作為發展有效的治療方法的參考依據。

Digestive system cancers (DSC) are the most common malignancy worldwide. The digestive system contained several organs, such as esophagus, stomach, intestine, colorectum, pancreas, gallbladder and liver. In clinical, the outcome of DSC remains unfavorable and the survival rate is poor, mainly because of late diagnosis, recurrence and tumor metastasis. Among 90% of cancer-associated deaths are due to cancer metastasis, which means the original tumor cells from initial or primary tumor to the distant sites. Metastasis is also the major wherefore for poor prognosis of liver cancer and pancreatic cancer. The metastatic process of liver cancer and pancreatic cancer including several steps, cancer cells via a peripheral blood vessel or lymphatic vessel move to liver, lung, peritoneum, brain and other parts of tissues and organs, then the tumor cells conduct division and growth. Nevertheless, the mechanisms of metastasis in liver cancer and pancreatic cancer are still not fully revealed. Therefore, understanding the mechanism of metastasis is important. In this study, we use human liver cancer (Huh-7) and pancreatic cancer (AsPC1) cell lines to establish high migration/invasion cell models by transwell assays. First, parental liver cancer and pancreatic cancer cells were seeded onto the noncoated membrane. After 24 hr. incubation, cells migrated to the bottom-well were collected. These cells were regrown and repeatedly passed through the migratory selection three times and resulted in the cells with high migratory ability, Huh-7/M3 and AsPC1/M3. Next, Huh-7/M3 and AsPC1/M3 cells were further seeded onto matrigel-coated membrane in the chamber. After 72 hr, the cells invade to the bottom of the chamber and cells were collected as invasive populations which grown in the culture medium. These steps were repeated for two times, the obtain cells have high invasive ability, we call the Huh-7/ M3-I2 and AsPC1/M3-I2 cells. Utilizing these valuable cell models, we can screen novel diagnostic biomarkers and develop effective therapeutic agents for liver cancer and pancreatic cancer patients.

Keywords: Digestive system cancers (DSC), liver cancer, pancreatic cancer, cancer metastasis, migration, invasion.  

目錄 (TABLE OF CONTENTS)
目錄 (TABLE OF CONTENTS) I
中文摘要 III
英文摘要(Abstract) IV
1. 前言(Introduction) 1
1.1 Digestive system cancer (DSC) 1
1.2 Metastasis and Cancers 3
1.3 Liver cancer 5
1.4 Pancreatic cancer 7
1.5 Hypothesis and Specific Aim 10
2. 材料與方法 (Materials and methods) 11
2.1 Cell lines 11
2.2 Cell proliferation assay 11
2.3 Colony formation 11
2.4 Migration assay 12
2.5 Invasion assay 12
2.6 Wound healing assay 13
2.7 Cell cycle analysis 13
2.8 Statistical analysis 13
3. 結果 (Results) 14
3.1 Establishment of HCC cell lines with difference migratory ability. 14
3.1-1 Cell growth and colony formation analyses of parental and migratory HCC cell lines. 14
3.1-2 Cell cycle analysis of parental and migratory HCC migration cell lines. 15
3.1-3 Migration ability of parental and migratory HCC migration cell lines. 15
3.2 Establishment of PDAC cell lines with difference migratory ability. 16
3.2-1 Cell growth and colony formation analyses of parental and migratory PDAC cell lines. 16
3.2-2 Cell cycle analysis of parental and migratory PDAC cell lines. 17
3.2-3 Migration ability of parental and migratory PDAC cell lines. 17
3.3 Establishment of HCC cell lines with difference invasionary ability. 18
3.3-1 Cell growth and colony formation analysis of parental and invasionary HCC invasion cell lines. 18
3.3-3 Cell cycle analysis of parental and invasionary HCC cell lines. 19
3.3-2 Invasion ability of parental and invasionary HCC cell lines. 19
3.4 Establishment of PDAC cell lines with difference invasionary ability. 20
3.4-1 Cell growth and colony formation analysis of parental and invasionary PDAC invasion cell lines. 21
3.4-2 Cell cycle analysis of parental and invasionary PDAC invasion cell lines. 21
3.4-3 Invasion ability of parental and invasionary PDAC cell lines. 21
4. 討論 (Discussion) 23
5. 參考文獻 (Reference) 26
6. 圖片 (Figures) 37

5. 參考文獻(Reference)
1. Keum, N., et al., Association of Physical Activity by Type and Intensity With Digestive System Cancer Risk. JAMA Oncol, 2016. 2(9): p. 1146-53.
2. Dong, J., et al., Potentially functional COX-2-1195G>A polymorphism increases the risk of digestive system cancers: a meta-analysis. J Gastroenterol Hepatol, 2010. 25(6): p. 1042-50.
3. Gastric Cancer Treatment (PDQ(R)): Patient Version, in PDQ Cancer Information Summaries. 2002: Bethesda (MD).
4. Pan, R., et al., Cancer incidence and mortality: A cohort study in China, 2008-2013. Int J Cancer, 2017. 141(7): p. 1315-1323.
5. Torre, L.A., et al., Global cancer statistics, 2012. CA Cancer J Clin, 2015. 65(2): p. 87-108.
6. Zhou, D.D., et al., Long non-coding RNA PVT1: Emerging biomarker in digestive system cancer. Cell Prolif, 2017. 50(6).
7. Siegel, R.L., K.D. Miller, and A. Jemal, Cancer statistics, 2016. CA Cancer J Clin, 2016. 66(1): p. 7-30.
8. Sakar, B., et al., Timing of death from tumor recurrence after curative gastrectomy for gastric cancer. Am J Clin Oncol, 2004. 27(2): p. 205-9.
9. Fatemi, S.R., et al., Recurrence and Five -Year Survival in Colorectal Cancer Patients After Surgery. Iran J Cancer Prev, 2015. 8(4): p. e3439.
10. Gbolahan, O.B., et al., Overall survival of patients with recurrent pancreatic cancer treated with systemic therapy: a retrospective study. BMC Cancer, 2019. 19(1): p. 468.
11. Wang, L.Y. and S.S. Zheng, Advances in predicting the prognosis of hepatocellular carcinoma recipients after liver transplantation. J Zhejiang Univ Sci B, 2018. 19(7): p. 497-504.
12. Riihimaki, M., et al., Metastatic spread in patients with gastric cancer. Oncotarget, 2016. 7(32): p. 52307-52316.
13. Qiu, M.Z., et al., Frequency and clinicopathological features of metastasis to liver, lung, bone, and brain from gastric cancer: A SEER-based study. Cancer Med, 2018. 7(8): p. 3662-3672.
14. Seyfried, T.N. and L.C. Huysentruyt, On the origin of cancer metastasis. Crit Rev Oncog, 2013. 18(1-2): p. 43-73.
15. Guan, X., Cancer metastases: challenges and opportunities. Acta Pharm Sin B, 2015. 5(5): p. 402-18.
16. Dillekas, H., M.S. Rogers, and O. Straume, Are 90% of deaths from cancer caused by metastases? Cancer Med, 2019. 8(12): p. 5574-5576.
17. Lin, L., et al., Incidence and death in 29 cancer groups in 2017 and trend analysis from 1990 to 2017 from the Global Burden of Disease Study. J Hematol Oncol, 2019. 12(1): p. 96.
18. Valastyan, S. and R.A. Weinberg, Tumor metastasis: molecular insights and evolving paradigms. Cell, 2011. 147(2): p. 275-92.
19. Chiang, S.P., R.M. Cabrera, and J.E. Segall, Tumor cell intravasation. Am J Physiol Cell Physiol, 2016. 311(1): p. C1-C14.
20. Jiang, W.G., In-vitro models of cancer invasion and metastasis: recent developments. Eur J Surg Oncol, 1994. 20(4): p. 493-9.
21. Jiang, W.G., M.C. Puntis, and M.B. Hallett, Molecular and cellular basis of cancer invasion and metastasis: implications for treatment. Br J Surg, 1994. 81(11): p. 1576-90.
22. Budczies, J., et al., The landscape of metastatic progression patterns across major human cancers. Oncotarget, 2015. 6(1): p. 570-83.
23. Peixoto, R.D., et al., Prognostic factors and sites of metastasis in unresectable locally advanced pancreatic cancer. Cancer Med, 2015. 4(8): p. 1171-7.
24. Law, H.C., et al., The Proteomic Landscape of Pancreatic Ductal Adenocarcinoma Liver Metastases Identifies Molecular Subtypes and Associations with Clinical Response. Clin Cancer Res, 2019.
25. Drewes, R., et al., Treatment of hepatic pancreatic ductal adenocarcinoma metastases with high-dose-rate image-guided interstitial brachytherapy: a single center experience. J Contemp Brachytherapy, 2019. 11(4): p. 329-336.
26. Doussot, A., et al., Pancreatic ductal adenocarcinoma and paraaortic lymph nodes metastases: The accuracy of intraoperative frozen section. Pancreatology, 2019. 19(5): p. 710-715.
27. Palumbo, M.O., et al., Systemic cancer therapy: achievements and challenges that lie ahead. Front Pharmacol, 2013. 4: p. 57.
28. Park, G.T. and K.C. Choi, Advanced new strategies for metastatic cancer treatment by therapeutic stem cells and oncolytic virotherapy. Oncotarget, 2016. 7(36): p. 58684-58695.
29. Ferrari, L., et al., Systemic Therapy in Locally Advanced or Metastatic Adrenal Cancers: A Critical Appraisal and Clinical Trial Update. Eur Urol Focus, 2016. 1(3): p. 298-300.
30. Aiello, N.M. and Y. Kang, Context-dependent EMT programs in cancer metastasis. J Exp Med, 2019. 216(5): p. 1016-1026.
31. Kim, D.H., et al., Epithelial Mesenchymal Transition in Embryonic Development, Tissue Repair and Cancer: A Comprehensive Overview. J Clin Med, 2017. 7(1).
32. Campbell, K. and J. Casanova, A common framework for EMT and collective cell migration. Development, 2016. 143(23): p. 4291-4300.
33. Lu, W. and Y. Kang, Epithelial-Mesenchymal Plasticity in Cancer Progression and Metastasis. Dev Cell, 2019. 49(3): p. 361-374.
34. Williams, E.D., et al., Controversies around epithelial-mesenchymal plasticity in cancer metastasis. Nat Rev Cancer, 2019. 19(12): p. 716-732.
35. Pradella, D., et al., EMT and stemness: flexible processes tuned by alternative splicing in development and cancer progression. Mol Cancer, 2017. 16(1): p. 8.
36. Lamouille, S., J. Xu, and R. Derynck, Molecular mechanisms of epithelial-mesenchymal transition. Nat Rev Mol Cell Biol, 2014. 15(3): p. 178-96.
37. Stemmler, M.P., et al., Non-redundant functions of EMT transcription factors. Nat Cell Biol, 2019. 21(1): p. 102-112.
38. Xu, R., et al., Roles of the Phosphorylation of Transcriptional Factors in Epithelial-Mesenchymal Transition. J Oncol, 2019. 2019: p. 5810465.
39. Bray, F., et al., Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin, 2018. 68(6): p. 394-424.
40. Choo, S.P., et al., Comparison of hepatocellular carcinoma in Eastern versus Western populations. Cancer, 2016. 122(22): p. 3430-3446.
41. Rawla, P., et al., Update in global trends and aetiology of hepatocellular carcinoma. Contemp Oncol (Pozn), 2018. 22(3): p. 141-150.
42. Siegel, R.L., K.D. Miller, and A. Jemal, Cancer statistics, 2019. CA Cancer J Clin, 2019. 69(1): p. 7-34.
43. Cai, Z. and Q. Liu, Understanding the Global Cancer Statistics 2018: implications for cancer control. Sci China Life Sci, 2019.
44. Kuo, C.N., et al., Cancers in Taiwan: Practical insight from epidemiology, treatments, biomarkers, and cost. J Formos Med Assoc, 2019.
45. Hsu, Y.Y., et al., Health Disparities of Employees in Taiwan with Major Cancer Diagnosis from 2004 to 2015: A Nation- and Population-Based Analysis. Int J Environ Res Public Health, 2019. 16(11).
46. Yang, J.D., et al., A global view of hepatocellular carcinoma: trends, risk, prevention and management. Nat Rev Gastroenterol Hepatol, 2019. 16(10): p. 589-604.
47. Balogh, J., et al., Hepatocellular carcinoma: a review. J Hepatocell Carcinoma, 2016. 3: p. 41-53.
48. Ringelhan, M., J.A. McKeating, and U. Protzer, Viral hepatitis and liver cancer. Philos Trans R Soc Lond B Biol Sci, 2017. 372(1732).
49. Chiang, C.H., et al., Chronic Viral Hepatitis Signifies the Association of Premixed Insulin Analogues with Liver Cancer Risks: A Nationwide Population-Based Study. Int J Environ Res Public Health, 2019. 16(12).
50. Mak, L.Y., et al., Global Epidemiology, Prevention, and Management of Hepatocellular Carcinoma. Am Soc Clin Oncol Educ Book, 2018. 38: p. 262-279.
51. Ozakyol, A., Global Epidemiology of Hepatocellular Carcinoma (HCC Epidemiology). J Gastrointest Cancer, 2017. 48(3): p. 238-240.
52. Sagnelli, E., et al., Epidemiological and etiological variations in hepatocellular carcinoma. Infection, 2019.
53. Chen, C.P., Role of Radiotherapy in the Treatment of Hepatocellular Carcinoma. J Clin Transl Hepatol, 2019. 7(2): p. 183-190.
54. Meng, X., et al., The Role of Radiation Oncology in Immuno-Oncology. Oncologist, 2019. 24(Suppl 1): p. S42-S52.
55. Llovet, J.M., et al., Hepatocellular carcinoma. Nat Rev Dis Primers, 2016. 2: p. 16018.
56. European Association for the Study of the Liver. Electronic address, e.e.e. and L. European Association for the Study of the, EASL Clinical Practice Guidelines: Management of hepatocellular carcinoma. J Hepatol, 2018. 69(1): p. 182-236.
57. European Association for the Study of the Liver. Electronic address, e.e.e., Corrigendum to "EASL Clinical Practice Guidelines: Management of hepatocellular carcinoma" [J Hepatol 69 (2018) 182-236]. J Hepatol, 2019. 70(4): p. 817.
58. Zhu, X.D. and H.C. Sun, Emerging agents and regimens for hepatocellular carcinoma. J Hematol Oncol, 2019. 12(1): p. 110.
59. Llovet, J.M., et al., Sorafenib in advanced hepatocellular carcinoma. N Engl J Med, 2008. 359(4): p. 378-90.
60. Wilhelm, S.M., et al., Preclinical overview of sorafenib, a multikinase inhibitor that targets both Raf and VEGF and PDGF receptor tyrosine kinase signaling. Mol Cancer Ther, 2008. 7(10): p. 3129-40.
61. Augustine, C.K., et al., Sorafenib, a multikinase inhibitor, enhances the response of melanoma to regional chemotherapy. Mol Cancer Ther, 2010. 9(7): p. 2090-101.
62. Chow, A.K., et al., The Enhanced metastatic potential of hepatocellular carcinoma (HCC) cells with sorafenib resistance. PLoS One, 2013. 8(11): p. e78675.
63. Zhu, Y.J., et al., New knowledge of the mechanisms of sorafenib resistance in liver cancer. Acta Pharmacol Sin, 2017. 38(5): p. 614-622.
64. Rawla, P., T. Sunkara, and V. Gaduputi, Epidemiology of Pancreatic Cancer: Global Trends, Etiology and Risk Factors. World J Oncol, 2019. 10(1): p. 10-27.
65. Rahib, L., et al., Projecting cancer incidence and deaths to 2030: the unexpected burden of thyroid, liver, and pancreas cancers in the United States. Cancer Res, 2014. 74(11): p. 2913-21.
66. Orth, M., et al., Pancreatic ductal adenocarcinoma: biological hallmarks, current status, and future perspectives of combined modality treatment approaches. Radiat Oncol, 2019. 14(1): p. 141.
67. Haeberle, L. and I. Esposito, Pathology of pancreatic cancer. Transl Gastroenterol Hepatol, 2019. 4: p. 50.
68. Makohon-Moore, A.P., et al., Precancerous neoplastic cells can move through the pancreatic ductal system. Nature, 2018. 561(7722): p. 201-205.
69. Pelosi, E., G. Castelli, and U. Testa, Pancreatic Cancer: Molecular Characterization, Clonal Evolution and Cancer Stem Cells. Biomedicines, 2017. 5(4).
70. Cicenas, J., et al., KRAS, TP53, CDKN2A, SMAD4, BRCA1, and BRCA2 Mutations in Pancreatic Cancer. Cancers (Basel), 2017. 9(5).
71. Kaur, S., et al., Early diagnosis of pancreatic cancer: challenges and new developments. Biomark Med, 2012. 6(5): p. 597-612.
72. Liu, X., et al., Predictors of distant metastasis on exploration in patients with potentially resectable pancreatic cancer. BMC Gastroenterol, 2018. 18(1): p. 168.
73. Swaroop Vege, S., Continuing Medical Education Questions: April 2017: A Multidisciplinary Approach to Pancreas Cancer in 2016: A Review. Am J Gastroenterol, 2017. 112(4): p. 555.
74. Fogel, E.L., et al., A Multidisciplinary Approach to Pancreas Cancer in 2016: A Review. Am J Gastroenterol, 2017. 112(4): p. 537-554.
75. Gao, G., et al., Potential use of aptamers for diagnosis and treatment of pancreatic cancer. J Drug Target, 2019. 27(8): p. 853-865.
76. Rofi, E., et al., The emerging role of liquid biopsy in diagnosis, prognosis and treatment monitoring of pancreatic cancer. Pharmacogenomics, 2019. 20(1): p. 49-68.
77. Ng, I.W., et al., Chemoradiotherapy versus chemotherapy for locally advanced unresectable pancreatic cancer: A systematic review and meta-analysis. Asia Pac J Clin Oncol, 2018. 14(6): p. 392-401.
78. Lambert, A., et al., An update on treatment options for pancreatic adenocarcinoma. Ther Adv Med Oncol, 2019. 11: p. 1758835919875568.
79. Ciliberto, D., et al., Role of gemcitabine-based combination therapy in the management of advanced pancreatic cancer: a meta-analysis of randomised trials. Eur J Cancer, 2013. 49(3): p. 593-603.
80. Saung, M.T. and L. Zheng, Current Standards of Chemotherapy for Pancreatic Cancer. Clin Ther, 2017. 39(11): p. 2125-2134.
81. Drewes, A.M., et al., Pain in pancreatic ductal adenocarcinoma: A multidisciplinary, International guideline for optimized management. Pancreatology, 2018. 18(4): p. 446-457.
82. Chen, J.L., et al., Gastrointestinal cancer metastasis. Gastroenterol Res Pract, 2012. 2012: p. 415498.
83. Franko, J., et al., Prognosis of patients with peritoneal metastatic colorectal cancer given systemic therapy: an analysis of individual patient data from prospective randomised trials from the Analysis and Research in Cancers of the Digestive System (ARCAD) database. Lancet Oncol, 2016. 17(12): p. 1709-1719.
84. Yamamoto, K.N., A. Nakamura, and H. Haeno, The evolution of tumor metastasis during clonal expansion with alterations in metastasis driver genes. Sci Rep, 2015. 5: p. 15886.
85. Nakabayashi, H., et al., Growth of human hepatoma cells lines with differentiated functions in chemically defined medium. Cancer Res, 1982. 42(9): p. 3858-63.
86. Tan, M.H. and T.M. Chu, Characterization of the tumorigenic and metastatic properties of a human pancreatic tumor cell line (AsPC-1) implanted orthotopically into nude mice. Tumour Biol, 1985. 6(1): p. 89-98.
87. Liu, C.Y., K.F. Chen, and P.J. Chen, Treatment of Liver Cancer. Cold Spring Harb Perspect Med, 2015. 5(9): p. a021535.
88. Messaoudi, R., et al., Ontology-Based Approach for Liver Cancer Diagnosis and Treatment. J Digit Imaging, 2019. 32(1): p. 116-130.
89. Fidler, I.J. and M.L. Kripke, The challenge of targeting metastasis. Cancer Metastasis Rev, 2015. 34(4): p. 635-41.
90. Bhullar, D.S., et al., Biomarker concordance between primary colorectal cancer and its metastases. EBioMedicine, 2019. 40: p. 363-374.
91. Wang, G., et al., Genetics and biology of prostate cancer. Genes Dev, 2018. 32(17-18): p. 1105-1140.
92. Manca, A., et al., Mutational concordance between primary and metastatic melanoma: a next-generation sequencing approach. J Transl Med, 2019. 17(1): p. 289.
93. Rodenhiser, D.I., et al., Gene signatures of breast cancer progression and metastasis. Breast Cancer Res, 2011. 13(1): p. 201.
94. Yang, M.Q., et al., High-throughput next-generation sequencing technologies foster new cutting-edge computing techniques in bioinformatics. BMC Genomics, 2009. 10 Suppl 1: p. I1.
95. Holubowicz, R., et al., [Biomineralization--precision of shape, structure and properties controlled by proteins]. Postepy Biochem, 2015. 61(4): p. 364-80.
96. Mittal, V. and D.J. Nolan, Genomics and proteomics approaches in understanding tumor angiogenesis. Expert Rev Mol Diagn, 2007. 7(2): p. 133-47.
97. Pierce, J.D., et al., Understanding proteomics. Nurs Health Sci, 2007. 9(1): p. 54-60.
98. Chevalier, F., Highlights on the capacities of "Gel-based" proteomics. Proteome Sci, 2010. 8: p. 23.
99. Kwon, O.K., et al., Comparative Secretome Profiling and Mutant Protein Identification in Metastatic Prostate Cancer Cells by Quantitative Mass Spectrometry-based Proteomics. Cancer Genomics Proteomics, 2018. 15(4): p. 279-290.
100. DeBerardinis, R.J. and N.S. Chandel, Fundamentals of cancer metabolism. Sci Adv, 2016. 2(5): p. e1600200.
101. Pavlova, N.N. and C.B. Thompson, The Emerging Hallmarks of Cancer Metabolism. Cell Metab, 2016. 23(1): p. 27-47.
102. Liberti, M.V. and J.W. Locasale, The Warburg Effect: How Does it Benefit Cancer Cells? Trends Biochem Sci, 2016. 41(3): p. 211-218.
103. van Beek, J., The dynamic side of the Warburg effect: glycolytic intermediate storage as buffer for fluctuating glucose and O 2 supply in tumor cells. F1000Res, 2018. 7: p. 1177.
104. Asgari, Y., et al., Alterations in cancer cell metabolism: the Warburg effect and metabolic adaptation. Genomics, 2015. 105(5-6): p. 275-81.
105. Muir, A., L.V. Danai, and M.G. Vander Heiden, Microenvironmental regulation of cancer cell metabolism: implications for experimental design and translational studies. Dis Model Mech, 2018. 11(8).
106. Liu, P., et al., Targeting the phosphoinositide 3-kinase pathway in cancer. Nat Rev Drug Discov, 2009. 8(8): p. 627-44.
107. Romero, R., et al., Keap1 loss promotes Kras-driven lung cancer and results in dependence on glutaminolysis. Nat Med, 2017. 23(11): p. 1362-1368.