Skip to main content

Advertisement

SpringerLink
Log in

Using functional genomics to overcome therapeutic resistance in hematological malignancies

  • Immunology in Colorado
  • Published:
Immunologic Research Aims and scope Submit manuscript

Abstract

Despite great advances in our understanding of the driving events involved in malignant transformation, only a small number of oncogenic drivers have been targeted and translated into tangible clinical benefit. Moreover, even when a targeted therapy can be shown to effectively inhibit an oncogenic driver, leading to cancer remission, disease persistence and/or relapse is typically inevitable. Reemergence of the cancer can result from either intrinsic or acquired resistance mechanisms that result in failure to eliminate all cancer cells. Intrinsic mechanisms of resistance include tumor heterogeneity and pathways that can compensate for the inhibition of the oncogenic driver. Acquired resistance mechanisms include mutation of the oncogenic driver to directly prevent drug-mediated inhibition and the activation of compensatory survival pathways. RNA interference (RNAi)-based screening provides a powerful approach for the interrogation of both intrinsic and acquired resistance mechanisms. The availability of short interfering (si)RNA libraries targeting all human and mouse genes has made it possible to perform large-scale unbiased screens to identify pathways that are specifically required in cancer cells of particular genotypes or following particular treatments, facilitating the design of potential new therapeutic strategies that may limit resistance mechanisms. In this review, we will discuss how RNAi screens can be used to uncover critical growth and survival pathways and aid in the identification of novel therapeutic targets for improved treatment of hematological malignancies.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2

Similar content being viewed by others

References

  1. Vardiman JW, et al. The 2008 revision of the World Health Organization (WHO) classification of myeloid neoplasms and acute leukemia: rationale and important changes. Blood. 2009;114(5):937–51.

    PubMed  CAS  Google Scholar 

  2. Weinberg OK, et al. Clinical characterization of acute myeloid leukemia with myelodysplasia-related changes as defined by the 2008 WHO classification system. Blood. 2009;113(9):1906–8.

    PubMed  CAS  Google Scholar 

  3. Campo E, et al. The 2008 WHO classification of lymphoid neoplasms and beyond: evolving concepts and practical applications. Blood. 2011;117(19):5019–32.

    PubMed  CAS  Google Scholar 

  4. Druker BJ, et al. Efficacy and safety of a specific inhibitor of the BCR-ABL tyrosine kinase in chronic myeloid leukemia. NEJM. 2001;344(14):1031–7.

    PubMed  CAS  Google Scholar 

  5. Druker BJ. Translation of the Philadelphia chromosome into therapy for CML. Blood. 2008;112(13):4808–17.

    PubMed  CAS  Google Scholar 

  6. Hughes TP, et al. Long-term prognostic significance of early molecular response to imatinib in newly diagnosed chronic myeloid leukemia: an analysis from the International Randomized Study of Interferon and STI571 (IRIS). Blood. 2010;116(19):3758–65.

    PubMed  CAS  Google Scholar 

  7. Huang ME, et al. Use of all-trans retinoic acid in the treatment of acute promyelocytic leukemia. Blood. 1988;72(2):567–72.

    PubMed  CAS  Google Scholar 

  8. Sanz MA, et al. Management of acute promyelocytic leukemia: recommendations from an expert panel on behalf of the European LeukemiaNet. Blood. 2009;113(9):1875–91.

    PubMed  CAS  Google Scholar 

  9. Alas S, Bonavida B. Rituximab inactivates signal transducer and activation of transcription 3 (STAT3) activity in B-non-Hodgkin’s lymphoma through inhibition of the interleukin 10 autocrine/paracrine loop and results in down-regulation of Bcl-2 and sensitization to cytotoxic drugs. Cancer Res. 2001;61(13):5137–44.

    PubMed  CAS  Google Scholar 

  10. Vega MI, et al. Rituximab (chimeric anti-CD20) sensitizes B-NHL cell lines to Fas-induced apoptosis. Oncogene. 2005;24(55):8114–27.

    PubMed  CAS  Google Scholar 

  11. Vega MI, et al. Rituximab-induced inhibition of YY1 and Bcl-xL expression in Ramos non-Hodgkin’s lymphoma cell line via inhibition of NF-kappa B activity: role of YY1 and Bcl-xL in Fas resistance and chemoresistance, respectively. J Immunol. 2005;175(4):2174–83.

    PubMed  CAS  Google Scholar 

  12. Armstrong GT, et al. Late mortality among 5-year survivors of childhood cancer: a summary from the Childhood Cancer Survivor Study. J Clin Oncol. 2009;27(14):2328–38.

    PubMed  CAS  Google Scholar 

  13. Reulen RC, et al. Long-term risks of subsequent primary neoplasms among survivors of childhood cancer. JAMA. 2011;305(22):2311–9.

    PubMed  CAS  Google Scholar 

  14. Corbin AS, et al. Human chronic myeloid leukemia stem cells are insensitive to imatinib despite inhibition of BCR-ABL activity. J Clin Invest. 2011;121(1):396–409.

    PubMed  CAS  Google Scholar 

  15. Hurtz C, et al. BCL6-mediated repression of p53 is critical for leukemia stem cell survival in chronic myeloid leukemia. J Exp Med. 2011;208(11):2163–74.

    PubMed  CAS  Google Scholar 

  16. Mahon F-X, et al. Discontinuation of imatinib in patients with chronic myeloid leukaemia who have maintained complete molecular remission for at least 2 years: the prospective, multicentre Stop Imatinib (STIM) trial. Lancet oncol. 2010;11(11):1029–35.

    PubMed  CAS  Google Scholar 

  17. Foà R, et al. Dasatinib as first-line treatment for adult patients with Philadelphia chromosome-positive acute lymphoblastic leukemia. Blood. 2011;118(25):6521–8.

    PubMed  Google Scholar 

  18. Schultz KR, et al. Improved early event-free survival with imatinib in Philadelphia chromosome-positive acute lymphoblastic leukemia: a children’s oncology group study. J Clin Oncol. 2009;27(31):5175–81.

    PubMed  CAS  Google Scholar 

  19. Mullighan CG, et al. BCR-ABL1 lymphoblastic leukaemia is characterized by the deletion of Ikaros. Nature. 2008;453(7191):110–4.

    PubMed  CAS  Google Scholar 

  20. Graham SM, et al. Primitive, quiescent, Philadelphia-positive stem cells from patients with chronic myeloid leukemia are insensitive to STI571 in vitro. Blood. 2002;99(1):319–25.

    PubMed  CAS  Google Scholar 

  21. Lemoli RM, et al. Molecular and functional analysis of the stem cell compartment of chronic myelogenous leukemia reveals the presence of a CD34- cell population with intrinsic resistance to imatinib. Blood. 2009;114(25):5191–200.

    PubMed  CAS  Google Scholar 

  22. Kumari A, et al. Low BCR-ABL expression levels in hematopoietic precursor cells enable persistence of chronic myeloid leukemia under imatinib. Blood. 2012;119(2):530–9.

    PubMed  CAS  Google Scholar 

  23. Agrawal SG, et al. Increased proteasomal degradation of Bax is a common feature of poor prognosis chronic lymphocytic leukemia. Blood. 2008;111(5):2790–6.

    PubMed  CAS  Google Scholar 

  24. Konopleva M, et al. Mechanisms of apoptosis sensitivity and resistance to the BH3 mimetic ABT-737 in acute myeloid leukemia. Cancer Cell. 2006;10(5):375–88.

    PubMed  CAS  Google Scholar 

  25. Paoluzzi L, et al. The BH3-only mimetic ABT-737 synergizes the antineoplastic activity of proteasome inhibitors in lymphoid malignancies. Blood. 2008;112(7):2906–16.

    PubMed  CAS  Google Scholar 

  26. Paoluzzi L, et al. Targeting Bcl-2 family members with the BH3 mimetic AT-101 markedly enhances the therapeutic effects of chemotherapeutic agents in in vitro and in vivo models of B-cell lymphoma. Blood. 2008;111(11):5350–8.

    PubMed  CAS  Google Scholar 

  27. Balakrishnan K, et al. AT-101 induces apoptosis in CLL B cells and overcomes stromal cell-mediated Mcl-1 induction and drug resistance. Blood. 2009;113(1):149–53.

    PubMed  CAS  Google Scholar 

  28. Bélanger SD, St-Pierre Y. Role of selectins in the triggering, growth, and dissemination of T-lymphoma cells: implication of L-selectin in the growth of thymic lymphoma. Blood. 2005;105(12):4800–6.

    PubMed  Google Scholar 

  29. Buchner M, et al. Spleen tyrosine kinase inhibition prevents chemokine- and integrin-mediated stromal protective effects in chronic lymphocytic leukemia. Blood. 2010;115(22):4497–506.

    PubMed  CAS  Google Scholar 

  30. De Toni-Costes F, et al. A New alpha5beta1 integrin-dependent survival pathway through GSK3beta activation in leukemic cells. PLoS ONE. 2010;5(3):e9807.

    PubMed  Google Scholar 

  31. Fenouille N, et al. Persistent activation of the Fyn/ERK kinase signaling axis mediates imatinib resistance in chronic myelogenous leukemia cells through upregulation of intracellular SPARC. Cancer Res. 2010;70(23):9659–70.

    PubMed  CAS  Google Scholar 

  32. Bellodi C, et al. Targeting autophagy potentiates tyrosine kinase inhibitor-induced cell death in Philadelphia chromosome-positive cells, including primary CML stem cells. J Clin Invest. 2009;119(5):1109–23.

    PubMed  CAS  Google Scholar 

  33. Amrein L, et al. p53 and autophagy contribute to dasatinib resistance in primary CLL lymphocytes. Leukemia Res. 2011;35(1):99–102.

    CAS  Google Scholar 

  34. Quintas-Cardama A, Cortes J. Molecular biology of bcr-abl1-positive chronic myeloid leukemia. Blood. 2009;113(8):1619–30.

    PubMed  CAS  Google Scholar 

  35. Sharma SV, et al. A chromatin-mediated reversible drug-tolerant state in cancer cell subpopulations. Cell. 2010;141(1):69–80.

    PubMed  CAS  Google Scholar 

  36. Braun T, et al. Molecular predictors of response to decitabine in advanced chronic myelomonocytic leukemia: a phase 2 trial. Blood. 2011;118(14):3824–31.

    PubMed  CAS  Google Scholar 

  37. Lubbert M, et al. Low-dose decitabine versus best supportive care in elderly patients with intermediate- or high-risk myelodysplastic syndrome (MDS) ineligible for intensive chemotherapy: final results of the randomized phase III study of the European Organisation for Research and Treatment of Cancer Leukemia Group and the German MDS Study Group. J Clin Oncol. 2011;29(15):1987–96.

    PubMed  Google Scholar 

  38. Stathis A, et al. Phase I study of decitabine in combination with vorinostat in patients with advanced solid tumors and non-Hodgkin’s lymphomas. Clin Cancer Res. 2011;17(6):1582–90.

    PubMed  CAS  Google Scholar 

  39. Cashen AF, et al. Multicenter, phase II study of decitabine for the first-line treatment of older patients with acute myeloid leukemia. J Clin Oncol. 2010;28(4):556–61.

    PubMed  CAS  Google Scholar 

  40. Issa JP, et al. Phase 1 study of low-dose prolonged exposure schedules of the hypomethylating agent 5-aza-2′-deoxycytidine (decitabine) in hematopoietic malignancies. Blood. 2004;103(5):1635–40.

    PubMed  CAS  Google Scholar 

  41. Beck WT, Mueller TJ, Tanzer LR. Altered surface membrane glycoproteins in Vinca alkaloid-resistant human leukemic lymphoblasts. Cancer Res. 1979;39(6 Pt 1):2070–6.

    PubMed  CAS  Google Scholar 

  42. Cole SP, et al. Overexpression of a transporter gene in a multidrug-resistant human lung cancer cell line. Science. 1992;258(5088):1650–4.

    PubMed  CAS  Google Scholar 

  43. le Coutre P, et al. Induction of resistance to the Abelson inhibitor STI571 in human leukemic cells through gene amplification. Blood. 2000;95(5):1758–66.

    PubMed  Google Scholar 

  44. Thomas J, et al. Active transport of imatinib into and out of cells: implications for drug resistance. Blood. 2004;104(12):3739–45.

    PubMed  CAS  Google Scholar 

  45. White DL, et al. Most CML patients who have a suboptimal response to imatinib have low OCT-1 activity: higher doses of imatinib may overcome the negative impact of low OCT-1 activity. Blood. 2007;110(12):4064–72.

    PubMed  CAS  Google Scholar 

  46. Aceves-Luquero CI, et al. ERK2, but not ERK1, mediates acquired and “de novo” resistance to imatinib mesylate: implication for CML therapy. PLoS ONE. 2009;4(7):e6124.

    PubMed  Google Scholar 

  47. Delva L, et al. Resistance to all-trans retinoic acid (ATRA) therapy in relapsing acute promyelocytic leukemia: study of in vitro ATRA sensitivity and cellular retinoic acid binding protein levels in leukemic cells. Blood. 1993;82(7):2175–81.

    PubMed  CAS  Google Scholar 

  48. Cornic M, et al. In vitro all-trans retinoic acid (ATRA) sensitivity and cellular retinoic acid binding protein (CRABP) levels in relapse leukemic cells after remission induction by ATRA in acute promyelocytic leukemia. Leukemia. 1994;8(6):914–7.

    PubMed  CAS  Google Scholar 

  49. Ozpolat B, Mehta K, Lopez-Berestein G. Regulation of a highly specific retinoic acid-4-hydroxylase (CYP26A1) enzyme and all-trans-retinoic acid metabolism in human intestinal, liver, endothelial, and acute promyelocytic leukemia cells. Leuk Lymph. 2005;46(10):1497–506.

    CAS  Google Scholar 

  50. Gorre ME, et al. Clinical resistance to STI-571 cancer therapy caused by BCR-ABL gene mutation or amplification. Science. 2001;293(5531):876–80.

    PubMed  CAS  Google Scholar 

  51. Shah NP, Sawyers CL. Mechanisms of resistance to STI571 in Philadelphia chromosome-associated leukemias. Oncogene. 2003;22(47):7389–95.

    PubMed  CAS  Google Scholar 

  52. Al-Ali HK, et al. High incidence of BCR-ABL kinase domain mutations and absence of mutations of the PDGFR and KIT activation loops in CML patients with secondary resistance to imatinib. Hematol J. 2004;5(1):55–60.

    PubMed  CAS  Google Scholar 

  53. Muller MC, et al. Dasatinib treatment of chronic-phase chronic myeloid leukemia: analysis of responses according to preexisting BCR-ABL mutations. Blood. 2009;114(24):4944–53.

    PubMed  Google Scholar 

  54. Sherbenou DW, et al. BCR-ABL SH3-SH2 domain mutations in chronic myeloid leukemia patients on imatinib. Blood. 2010;116(17):3278–85.

    PubMed  CAS  Google Scholar 

  55. Roche-Lestienne C, et al. A mutation conferring resistance to imatinib at the time of diagnosis of chronic myelogenous leukemia. NEJM. 2003;348(22):2265–6.

    PubMed  Google Scholar 

  56. Hofmann W-K, et al. Presence of the BCR-ABL mutation Glu255Lys prior to STI571 (imatinib) treatment in patients with Ph + acute lymphoblastic leukemia. Blood. 2003;102(2):659–61.

    PubMed  CAS  Google Scholar 

  57. Willis SG, et al. High-sensitivity detection of BCR-ABL kinase domain mutations in imatinib-naive patients: correlation with clonal cytogenetic evolution but not response to therapy. Blood. 2005;106(6):2128–37.

    PubMed  CAS  Google Scholar 

  58. Soverini S, et al. Philadelphia-positive patients who already harbor imatinib-resistant Bcr-Abl kinase domain mutations have a higher likelihood of developing additional mutations associated with resistance to second- or third-line tyrosine kinase inhibitors. Blood. 2009;114(10):2168–71.

    PubMed  CAS  Google Scholar 

  59. Soverini S, et al. Philadelphia-positive acute lymphoblastic leukemia patients already harbor BCR-ABL kinase domain mutations at low levels at the time of diagnosis. Haematologica. 2011;96(4):552–7.

    PubMed  CAS  Google Scholar 

  60. Bagrintseva K, et al. Mutations in the tyrosine kinase domain of FLT3 define a new molecular mechanism of acquired drug resistance to PTK inhibitors in FLT3-ITD-transformed hematopoietic cells. Blood. 2004;103(6):2266–75.

    PubMed  CAS  Google Scholar 

  61. Moore AS, et al. Selective FLT3 inhibition of FLT3-ITD(+) acute myeloid leukaemia resulting in secondary D835Y mutation: a model for emerging clinical resistance patterns. Leukemia 2012.

  62. Mullighan CG, et al. CREBBP mutations in relapsed acute lymphoblastic leukaemia. Nature. 2011;471(7337):235–9.

    PubMed  CAS  Google Scholar 

  63. Bunn PA Jr. Can acquired resistance to epidermal growth factor receptor tyrosine kinase inhibitors be overcome by different small-molecule tyrosine kinase inhibitors? J Clin Oncol. 2007;25(18):2504–5.

    PubMed  Google Scholar 

  64. Pao W, Chmielecki J. Rational, biologically based treatment of EGFR-mutant non-small-cell lung cancer. Nat Rev Cancer. 2010;10(11):760–74.

    PubMed  CAS  Google Scholar 

  65. Kobayashi S, et al. EGFR mutation and resistance of non-small-cell lung cancer to gefitinib. NEJM. 2005;352(8):786–92.

    PubMed  CAS  Google Scholar 

  66. Sequist LV, et al. Genotypic and histological evolution of lung cancers acquiring resistance to EGFR inhibitors. Sci Trans Med 2011;3(75):75ra26.

    Google Scholar 

  67. Herbst RS, Bunn PA Jr. Targeting the epidermal growth factor receptor in non-small cell lung cancer. Clin Cancer Res. 2003;9(16 Pt 1):5813–24.

    PubMed  CAS  Google Scholar 

  68. Engelman JA, et al. MET amplification leads to gefitinib resistance in lung cancer by activating ERBB3 signaling. Science. 2007;316(5827):1039–43.

    PubMed  CAS  Google Scholar 

  69. Bean J, et al. MET amplification occurs with or without T790 M mutations in EGFR mutant lung tumors with acquired resistance to gefitinib or erlotinib. PNAS USA. 2007;104(52):20932–7.

    PubMed  CAS  Google Scholar 

  70. Turke AB, et al. Preexistence and clonal selection of MET amplification in EGFR mutant NSCLC. Cancer Cell. 2010;17(1):77–88.

    PubMed  CAS  Google Scholar 

  71. Sosman JA, et al. Survival in BRAF V600-mutant advanced melanoma treated with vemurafenib. NEJM. 2012;366(8):707–14.

    PubMed  CAS  Google Scholar 

  72. Nazarian R, et al. Melanomas acquire resistance to B-RAF(V600E) inhibition by RTK or N-RAS upregulation. Nature. 2010;468(7326):973–7.

    PubMed  CAS  Google Scholar 

  73. Wagle N, et al. Dissecting therapeutic resistance to RAF inhibition in melanoma by tumor genomic profiling. J Clin Oncol. 2011;29(22):3085–96.

    PubMed  CAS  Google Scholar 

  74. Thomson S, et al. Epithelial to mesenchymal transition is a determinant of sensitivity of non-small-cell lung carcinoma cell lines and xenografts to epidermal growth factor receptor inhibition. Cancer Res. 2005;65(20):9455–62.

    PubMed  CAS  Google Scholar 

  75. Marusyk A, Polyak K. Tumor heterogeneity: causes and consequences. Biochim Biophys Acta. 2010;1805(1):105–17.

    PubMed  CAS  Google Scholar 

  76. Anderson K, et al. Genetic variegation of clonal architecture and propagating cells in leukaemia. Nature. 2011;469(7330):356–61.

    PubMed  CAS  Google Scholar 

  77. Gerlinger M, et al. Intratumor heterogeneity and branched evolution revealed by multiregion sequencing. NEJM. 2012;366(10):883–92.

    PubMed  CAS  Google Scholar 

  78. Snuderl M, et al. Mosaic amplification of multiple receptor tyrosine kinase genes in glioblastoma. Cancer Cell. 2011;20(6):810–7.

    PubMed  CAS  Google Scholar 

  79. Gerlinger M, Swanton C. How Darwinian models inform therapeutic failure initiated by clonal heterogeneity in cancer medicine. Brit J Cancer. 2010;103(8):1139–43.

    PubMed  CAS  Google Scholar 

  80. Katayama R, et al. Mechanisms of acquired crizotinib resistance in ALK-rearranged lung Cancers. Sci Trans Med 2012;4(120):120ra17.

    Google Scholar 

  81. Doebele RC, et al. Mechanisms of resistance to crizotinib in patients with ALK gene rearranged non-small cell lung cancer. Clin Cancer Res. 2012;18(5):1472–82.

    PubMed  CAS  Google Scholar 

  82. Deininger MW, Goldman JM, Melo JV. The molecular biology of chronic myeloid leukemia. Blood. 2000;96(10):3343–56.

    PubMed  CAS  Google Scholar 

  83. Notta F, et al. Evolution of human BCR-ABL1 lymphoblastic leukaemia-initiating cells. Nature. 2011;469(7330):362–7.

    PubMed  CAS  Google Scholar 

  84. Ding L, et al. Clonal evolution in relapsed acute myeloid leukaemia revealed by whole-genome sequencing. Nature. 2012;481(7382):506–10.

    PubMed  CAS  Google Scholar 

  85. Krol J, Loedige I, Filipowicz W. The widespread regulation of microRNA biogenesis, function and decay. Nat Revs Genet. 2010;11(9):597–610.

    CAS  Google Scholar 

  86. Czech MP, Aouadi M, Tesz GJ. RNAi-based therapeutic strategies for metabolic disease. Nat Revs Endocrinol. 2011;7(8):473–84.

    CAS  Google Scholar 

  87. Kittler R, Buchholz F. Functional genomic analysis of cell division by endoribonuclease-prepared siRNAs. Cell Cycle. 2005;4(4):564–7.

    PubMed  CAS  Google Scholar 

  88. Silva JM, et al. Second-generation shRNA libraries covering the mouse and human genomes. Nat Genet. 2005;37(11):1281–8.

    PubMed  CAS  Google Scholar 

  89. Root DE, et al. Genome-scale loss-of-function screening with a lentiviral RNAi library. Nat Methods. 2006;3(9):715–9.

    PubMed  CAS  Google Scholar 

  90. Moffat J, et al. A lentiviral RNAi library for human and mouse genes applied to an arrayed viral high-content screen. Cell. 2006;124(6):1283–98.

    PubMed  CAS  Google Scholar 

  91. Mullenders J, Bernards R. Loss-of-function genetic screens as a tool to improve the diagnosis and treatment of cancer. Oncogene. 2009;28(50):4409–20.

    PubMed  CAS  Google Scholar 

  92. Scholl C, et al. Synthetic lethal interaction between oncogenic KRAS dependency and STK33 suppression in human cancer cells. Cell. 2009;137(5):821–34.

    PubMed  CAS  Google Scholar 

  93. Barbie DA, et al. Systematic RNA interference reveals that oncogenic KRAS-driven cancers require TBK1. Nature. 2009;462(7269):108–12.

    PubMed  CAS  Google Scholar 

  94. Luo J, et al. A genome-wide RNAi screen identifies multiple synthetic lethal interactions with the Ras oncogene. Cell. 2009;137(5):835–48.

    PubMed  CAS  Google Scholar 

  95. Ngo VN, et al. A loss-of-function RNA interference screen for molecular targets in cancer. Nature. 2006;441(7089):106–10.

    PubMed  CAS  Google Scholar 

  96. Whitehurst AW, et al. Synthetic lethal screen identification of chemosensitizer loci in cancer cells. Nature. 2007;446(7137):815–9.

    PubMed  CAS  Google Scholar 

  97. Fotheringham S, et al. Genome-wide loss-of-function screen reveals an important role for the proteasome in HDAC inhibitor-induced apoptosis. Cancer Cell. 2009;15(1):57–66.

    PubMed  CAS  Google Scholar 

  98. Gregory MA, et al. Wnt/Ca2 +/NFAT signaling maintains survival of Ph + leukemia cells upon inhibition of Bcr-Abl. Cancer Cell. 2010;18(1):74–87.

    PubMed  CAS  Google Scholar 

  99. Burgess DJ, et al. Topoisomerase levels determine chemotherapy response in vitro and in vivo. PNAS USA. 2008;105(26):9053–8.

    PubMed  Google Scholar 

  100. Hahn CK, et al. Proteomic and genetic approaches identify Syk as an AML target. Cancer Cell. 2009;16(4):281–94.

    PubMed  CAS  Google Scholar 

  101. Pritchard JR, et al. Bcl-2 family genetic profiling reveals microenvironment-specific determinants of chemotherapeutic response. Cancer Res. 2011;71(17):5850–8.

    PubMed  CAS  Google Scholar 

  102. Porter CC, et al. Integrated genomic analyses identify WEE1 as a critical mediator of cell fate and a novel therapeutic target in acute myeloid leukemia. Leukemia 2012;26(6):1266–76.

    Google Scholar 

  103. Gilliland DG, Jordan CT, Felix CA, The molecular basis of leukemia. Hematology/the education program of the american society of hematology. American Society of Hematology. Educ Prog, 2004;80–97.

  104. Zuber J, et al. RNAi screen identifies Brd4 as a therapeutic target in acute myeloid leukaemia. Nature. 2011;478(7370):524–8.

    PubMed  CAS  Google Scholar 

  105. Figueroa ME, et al. Leukemic IDH1 and IDH2 mutations result in a hypermethylation phenotype, disrupt TET2 function, and impair hematopoietic differentiation. Cancer Cell. 2010;18(6):553–67.

    PubMed  CAS  Google Scholar 

  106. Fathi AT, Chabner BA. FLT3 inhibition as therapy in acute myeloid leukemia: a record of trials and tribulations. Oncologist. 2011;16(8):1162–74.

    PubMed  CAS  Google Scholar 

  107. Astsaturov I, et al. Synthetic lethal screen of an EGFR-centered network to improve targeted therapies. Sci signal 2010;3(140):ra67.

    Google Scholar 

  108. Bivona TG, et al. FAS and NF-kappaB signalling modulate dependence of lung cancers on mutant EGFR. Nature. 2011;471(7339):523–6.

    PubMed  CAS  Google Scholar 

  109. Casas-Selves M, et al. Tankyrase and the canonical Wnt pathway protect lung cancer cells from EGFR inhibition. Cancer Res. 72(16):4154–64.

  110. Kim J, Tan AC. BiNGS!SL-seq: a bioinformatics pipeline for the analysis and interpretation of deep sequencing genome-wide synthetic lethal screen. Methods Mol Biol. 2012;802:389–98.

    PubMed  Google Scholar 

  111. Sims D, et al. High-throughput RNA interference screening using pooled shRNA libraries and next generation sequencing. Genome Biol. 2011;12(10):R104.

    PubMed  CAS  Google Scholar 

  112. Marcotte R, et al. Essential gene profiles in breast, pancreatic, and ovarian cancer cells. Cancer Disc. 2012;2:172–89.

    CAS  Google Scholar 

  113. Luo B, et al. Highly parallel identification of essential genes in cancer cells. PNAS USA. 2008;105(51):20380–5.

    PubMed  CAS  Google Scholar 

  114. Konig R, et al. A probability-based approach for the analysis of large-scale RNAi screens. Nat Methods. 2007;4(10):847–9.

    PubMed  Google Scholar 

  115. Kanehisa M, et al. The KEGG databases at GenomeNet. Nucleic Acids Res. 2002;30(1):42–6.

    PubMed  CAS  Google Scholar 

  116. Luo T, et al. STK33 kinase inhibitor BRD-8899 has no effect on KRAS-dependent cancer cell viability. PNAS USA. 2012;109(8):2860–5.

    PubMed  CAS  Google Scholar 

  117. Babij C, et al. STK33 kinase activity is nonessential in KRAS-dependent cancer cells. Cancer Res. 2011;71(17):5818–26.

    PubMed  CAS  Google Scholar 

  118. Luo J, Solimini NL, Elledge SJ. Principles of cancer therapy: oncogene and non-oncogene addiction. Cell. 2009;136(5):823–37.

    PubMed  CAS  Google Scholar 

  119. Lam LT, et al. Compensatory IKKalpha activation of classical NF-kappaB signaling during IKKbeta inhibition identified by an RNA interference sensitization screen. PNAS USA. 2008;105(52):20798–803.

    PubMed  CAS  Google Scholar 

  120. Tyner JW, et al. RNAi screen for rapid therapeutic target identification in leukemia patients. PNAS USA. 2009;106(21):8695–700.

    PubMed  CAS  Google Scholar 

  121. Jiang H, et al. A mammalian functional-genetic approach to characterizing cancer therapeutics. Nat Chem Biol. 2011;7(2):92–100.

    PubMed  CAS  Google Scholar 

  122. Banerji V, et al. The intersection of genetic and chemical genomic screens identifies GSK-3α as a target in human acute myeloid leukemia. J Clin Invest. 2012;122(3):935–47.

    PubMed  CAS  Google Scholar 

  123. Zhu YX, et al. RNAi screen of the druggable genome identifies modulators of proteasome inhibitor sensitivity in myeloma including CDK5. Blood. 2011;117(14):3847–57.

    PubMed  CAS  Google Scholar 

  124. Tibes R, et al. RNAi screening of the kinome with cytarabine in leukemias. Blood 2012.

  125. Meacham CE, et al. In vivo RNAi screening identifies regulators of actin dynamics as key determinants of lymphoma progression. Nat Genet. 2009;41(10):1133–7.

    PubMed  CAS  Google Scholar 

  126. Bric A, et al. Functional identification of tumor-suppressor genes through an in vivo RNA interference screen in a mouse lymphoma model. Cancer Cell. 2009;16(4):324–35.

    PubMed  CAS  Google Scholar 

  127. Zender L, et al. An oncogenomics-based in vivo RNAi screen identifies tumor suppressors in liver cancer. Cell. 2008;135(5):852–64.

    PubMed  CAS  Google Scholar 

  128. Possemato R, et al. Functional genomics reveal that the serine synthesis pathway is essential in breast cancer. Nature. 2011;476(7360):346–50.

    PubMed  CAS  Google Scholar 

  129. Astier AL, et al. RNA interference screen in primary human T cells reveals FLT3 as a modulator of IL-10 levels. J Immunol. 2010;184(2):685–93.

    PubMed  CAS  Google Scholar 

  130. Karlas A, et al. Genome-wide RNAi screen identifies human host factors crucial for influenza virus replication. Nature. 2010;463(7282):818–22.

    PubMed  CAS  Google Scholar 

  131. Konig R, et al. Global analysis of host-pathogen interactions that regulate early-stage HIV-1 replication. Cell. 2008;135(1):49–60.

    PubMed  CAS  Google Scholar 

  132. Brass AL, et al. Identification of host proteins required for HIV infection through a functional genomic screen. Science. 2008;319(5865):921–6.

    PubMed  CAS  Google Scholar 

  133. Paul P, et al. A Genome-wide multidimensional RNAi screen reveals pathways controlling MHC class II antigen presentation. Cell. 2011;145(2):268–83.

    PubMed  CAS  Google Scholar 

  134. Solimini NL, Luo J, Elledge SJ. Non-oncogene addiction and the stress phenotype of cancer cells. Cell. 2007;130(6):986–8.

    PubMed  CAS  Google Scholar 

  135. Witt AE, et al. Functional proteomics approach to investigate the biological activities of cDNAs implicated in breast cancer. J Proteome Res. 2006;5(3):599–610.

    PubMed  CAS  Google Scholar 

  136. Hattori H, et al. RNAi screen identifies UBE2D3 as a mediator of all-trans retinoic acid-induced cell growth arrest in human acute promyelocytic NB4 cells. Blood. 2007;110(2):640–50.

    PubMed  CAS  Google Scholar 

  137. Friedberg JW, et al. Inhibition of Syk with fostamatinib disodium has significant clinical activity in non-Hodgkin lymphoma and chronic lymphocytic leukemia. Blood. 2010;115(13):2578–85.

    PubMed  CAS  Google Scholar 

Download references

Acknowledgments

These studies were supported by grants from the National Institutes of Health (R01-CA157850 to J.D, K01-CA133182 to M.A.G and F31-CA157166 to F.A.C) and the Leukemia Lymphoma Society. We would like to thank Matias Casas-Selves, Courtney Fleenor, Andriy Marusyk, Jennifer Salstrom, Aik-Choon Tan, and Christopher Porter for their comments and suggestions.

Conflicts of interest

The authors declare that they have no conflict of interest.

Author information

Authors and Affiliations

  1. Integrated Department of Immunology, National Jewish Health, Denver, CO, USA

    Francesca Alvarez-Calderon & James DeGregori

  2. Medical Scientist Training Program, University of Colorado School of Medicine, Aurora, CO, USA

    Francesca Alvarez-Calderon

  3. Department of Biochemistry and Molecular Genetics, University of Colorado School of Medicine, Aurora, CO, USA

    Mark A. Gregory & James DeGregori

  4. Department of Pediatrics, University of Colorado School of Medicine, Aurora, CO, USA

    James DeGregori

  5. Program in Molecular Biology, University of Colorado School of Medicine, Aurora, CO, USA

    James DeGregori

Authors
  1. Francesca Alvarez-Calderon
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Mark A. Gregory
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. James DeGregori
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to James DeGregori.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Alvarez-Calderon, F., Gregory, M.A. & DeGregori, J. Using functional genomics to overcome therapeutic resistance in hematological malignancies. Immunol Res 55, 100–115 (2013). https://doi.org/10.1007/s12026-012-8353-z

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12026-012-8353-z

Keywords

Search

Navigation