Education and Training:

B.S., Biology, Wright State University, Dayton, OH (1982)

M.D., The Ohio State University, Columbus, OH (1986)

Internship, Department of Medicine, Duke University (1986-87)

Residency, Department of Medicine, Duke University (1987-89)

Fellowship, Division of Oncology, University of Washington, Seattle, (1989-94)

CURRENT CLINICAL INTERESTS

General hematology, hemoglobinopathies, hematological malignancies


CURRENT RESEARCH INTERESTS

Hemopoietic stem cell biology, gene therapy, globin gene regulation, personalized approaches to cancer treatment

RESEARCH DESCRIPTION

Phase Transitions and the Pluripotent State

Mouse embryonic stem cells (ESC) are derived from the pre-implantation embryo. In 2007, two groups described a new type of mouse stem cell derived from the post-implantation embryo, called the epiblast stem cell (EpiSC) (Tesar et al., Nature 2007). Although EpiSC can form most tissues, they differ from ESC in their morphological appearance, culture requirements, and gene expression profile. Interestingly, human ESC are similar in their appearance and culture requirements to EpiSC.  

Our collaborator, Carol Ware, discovered that a low, narrow concentration of the histone deacetylase Inhibitor, sodium butyrate, can support the self renewal of ESC from humans, mice, and non-human primates (Ware et al., Cell Stem Cell 2009). Butyrate appears to induce a change in stem cell state. Gene expression profiling suggests that human ESC pulled backward to an earlier developmental stage, whereas mouse ESC are pushed forward.  

Papers

Ware CB, Chien S, and Blau CA. Slow, Controlled-Rate Freezing Improves Human Embryonic Stem Cell Survival. Biotechniques 38:879-883, 2005.

Ware CB, Nelson, AM, and Blau CA. A Comparison of NIH-Approved Human Embryonic Stem Cell Lines. Stem Cells 24:2677-84, 2006.

Wang L, Schulz TC, Sherrer ES, Dauphin DS, Shin S, Nelson AM, Ware CB, Zhan M, Song C-Z, Chen X, Brimble SN, Amanda M, Galeano MJ, Uhl EW, Damour KA, Chesnut J, Rao MS, Blau CA and Robins AJ. Self-renewal of human embryonic stem cells requires insulin-like growth factor-1 receptor and ERBB2 receptor signaling. Blood 110:4111-9, 2007.

Ware CB, Wang L, Mecham BH, Nelson AM, Dauphin DS, Buckingham B, Bar M, Lim R, Askari B, Gartler SM, Shen L, Issa J-P, Tewari M, Lamba DA, Pavlidis P, Duan Z, and Blau CA. Histone Deacetylase Inhibition Elicits an Evolutionarily Conserved Self-Renewal Program in Embryonic Stem Cells. Cell Stem Cell 4:359-369, 2009.

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Erythropoietin and Cancer

Up to 40% of patients with cancer are anemic at the time of diagnosis, and a large body of evidence indicates that anemia is a key predictor of survival, independent of disease severity. The mechanism whereby anemia impairs outcome in patients with cancer is not well understood, but has been attributed in part to tumor hypoxia, which can select for tumor cells resistant to chemotherapy and radiation therapy. This rationale helped to lay the groundwork for using Epo for the treatment of anemia in patients with cancer. Recombinant Epo first received FDA approval for the treatment of cancer-related anemia in 1993, and subsequently grew to become the most commercially successful drug in all of oncology. However, the results of Phase III clinical trials now indicate that Epo can reduce survival rates and promote tumor progression in cancers of the head and neck, breast and in most common forms of lung cancer. Although some of these trials are not yet published, and several of the published trials have been criticized for design limitations, the FDA issued a "black box" warning for Epo in March 2007. How Epo stimulates tumor progression is uncertain, but may reflect off-target effects (figure, below). EpoR transcripts have been detected in multiple primary cancers including tumors of the breast, head and neck, and non-small cell lung. Some reports have documented Epo-induced proliferation, invasion, migration, and protection from chemo- and radio-therapy in various cancer cell lines. Moreover, blocking endogenous Epo can inhibit breast cancer growth and tumor vascularization in a rat model, and ovarian and uterine cancers in mice. Finally, EpoR expression and function in endothelial cells is well-documented, and Epo might stimulate tumor progression by promoting tumor angiogenesis.  

Is Erythropoietin Induced Tumor Progression An Off-Target Effect?

From Nature Medicine, 2003  

One of the phase III trials suggesting that Epo might promote cancer progression, was ENHANCE, a trial of 351 patients with head and neck cancer (Henke et al., Lancet 2003). ENHANCE demonstrated a shorter locoregional progression free survival (LPFS) in head and neck cancer patients randomized to Epo rather than placebo during radiotherapy. ENHANCE incorporated patients who underwent complete, partial or no resection of tumor prior to radiotherapy. Adverse effects of Epo were confined to patients with residual tumor at the time of radiotherapy. We developed an assay to measure mRNA levels of genes implicated (EpoR, Jak2, Csf2rb, Hsp70) or not implicated (Krt5, Cd44) in Epo signaling in formalin-fixed paraffin-embedded (FFPE) tumors, and tested 136 tumors from ENHANCE. We compared LPFS between patients with tumors expressing above- versus below-median levels of the aforementioned mRNAs using the log rank statistic. Sufficient RNA for EpoR measurements was available in 101 tumors and EpoR varied over a 30-fold range. There was no association between tumor EpoR level and LPFS across all 101 patients. However in patients with unresected tumors (n=28), above-median EpoR mRNA levels were associated with significantly poorer LPFS if randomized to Epo rather than placebo (p=0.02, n=14). A similar association was observed in patients with above-median levels of Jak2 mRNA (p=0.02, n=18) or below-median levels of Hsp70 (p=0.01, n=20). LPFS was not significantly different when comparing Epo-treated patients with above-median mRNA levels to Epo-treated patients with below-median levels. EpoR mRNA levels can be reliably measured in FFPE tumors. These associations merit evaluation in larger numbers of tumors from other Phase III trials.

Papers

Blau CA. Erythropoietin in Cancer: Presumption of Innocence? Stem Cells 2007; 25:2094-7.

Bennett CL, Silver SM, Djulbegovic B, Samaras AT, Blau CA, Gleason KJ, Barnato SE, Elverman KM, Courtney DM, McKoy JM, Edwards BJ, Tigue CC, Raisch DW, Yarnold PR, Dorr DA, Kunzel TM, Tallman MS, Trifilio SM, West DP, Lai SY, Henke M. Venous Thromboembolism and Mortality Associated with Recombinant Erythropoietin and Darbepoietin Administration for the Treatment of Cancer-Associated Anemia. JAMA 2008;299: 914-924.

Miller CP, Lowe KA, Valliant-Saunders K, Kaiser JF, Mattern D, Urban N, Henke M, Blau CA. Evaluating Erythropoietin-Associated Tumor Progression Using Archival Tissues from a Phase III Clinical Trial. Stem Cells 27:2353-61, 2009.

Miller CP, Valliant-Saunders K, Blau CA. Limitations of a murine transgenic breast cancer model for studies of erythropoietin-induced tumor progression. Translational Oncology 2010 Jun 1;3(3):176-80.

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Pharmacologically Regulated Cell Therapy

We are developing a new generation of cell therapies that involves placing cells under the "remote control" of small molecule drugs. Over the past decade we have completed much of the ground-work establishing the feasibility of this approach. We believe that the approaches we are developing today will be commonplace 100 years from now (see the last chapter of "Thomas' Hematopoietic Cell Transplantation," written by Ernie Beutler), but we are most interested in pursuing approaches with (hopefully) nearer-term clinical applications.

Off target effects constrain the clinical applicability of growth factors. The safety and efficacy of a drug are determined by two forms of specificity: specificity of the drug for its target (usually a protein), and specificity of the drug target in the pathogenesis of the disease being treated. Side effects arise when either type of specificity falls short of physiologically dictated thresholds, phenomena collectively referred to as "off-target" effects. Although off-target effects plague all drug development, their impact on the clinical use of hematopoietic growth factors provide a case-in-point, and a little explored rationale for genetic manipulation.

The major hematopoietic growth factors in clinical use today, erythropoietin (Epo), granulocyte colony stimulating factor (G-CSF) and granulocyte-macrophage colony stimulating factor (GM-CSF) were all approved by the US Food and Drug Administration (FDA) more than 15 years ago. Since then no growth factors with novel biological activity have gained widespread use, a situation almost entirely attributable to off-target effects. For example, none of the many potential clinical uses for recombinant stem cell factor (SCF) were realized because its receptor (c-kit) is expressed not only in primitive hematopoietic progenitors, but also in mast cells, causing significant allergic reactions in 10 - 20% of patients. Fibroblast growth factors (FGFs) further illustrate the problem. 23 different FGFs bind 7 different receptor isoforms that are variably expressed in all tissues. Most FGFs activate more than one type of FGF receptor, leading to one type of off target effect. Furthermore, even when an FGF specific for a given receptor is used, the receptor is invariably expressed in multiple cell types, producing a second type of off target effect. Thus clinical trials of FGFs have yielded disappointing results. Over the past decade we have been developing a system that has the potential to circumvent off-target effects.

Pharmacologically-regulated cell therapy. An important obstacle to cell therapy is the loss of control over cells that have been transplanted. We used previously described technology to develop a way to regulate the proliferation of engineered cells using a growth factor receptor modified to substitute its normal ligand-binding site with the binding site for a drug called a chemical inducer of dimerization (CID). The CID brings together two copies of the artificial receptor, triggering its activation and leading to cell proliferation, thereby mimicking the effect of a growth factor.

Regulated Cell Therapy  

Figure 1. Left panel A proliferation switch consisting of a receptor and a dimerization domain is activated upon addition of a CID, thereby mimicking the effect of growth factors. Right panel: In vivo selection of genetically modified cells using CIDs. The vector may encode a therapeutic gene in addition to the CID selectable gene. Following infusion of transduced cells, the CID specifically induces genetically modified cells to proliferate.

First generation CIDs capitalized on the interaction between a drug, FK506, and its naturally occurring intracellular target, FKBP12, and dimerization was induced by covalently linking two copies of FK506 to generate a new ligand called FK1012. To dramatically reduce undesired interactions between FK1012 and endogenous FKBP12, second generation CIDs were developed using a "bump and hole" approach. These new CIDs (such as AP1903 and AP20187) contain chemical modifications ("bumps") that preclude binding to endogenous FKBP12, but which can be accommodated by a modification of FKBP12 to introduce a pocket ("hole") via a single amino acid substitution (F36V). AP1903 was well tolerated in a Phase I study in normal human volunteers. This approach has a number of advantages, many of which are described in greater detail below. One advantage is its generalizability. A single drug can be used to regulate hundreds of different signaling molecules, to elicit a variety of cellular responses. In previous studies we have used signaling domains taken from the erythropoietin receptor, GCSF receptor, gp130, flt-3, c-kit, Mpl, fibroblast growth factor receptor-1 (FGFR-1), and the 4 Janus kinase family members to induce CID-dependent proliferation. A second advantage is its versatility, allowing for regulated proliferation both in vitro and in vivo. A third advantage is its anticipated lack of immunogenicity, because CID responsive proteins can be entirely human in origin, in contrast to virtually all other regulated systems that rely on the expression of foreign proteins, and are therefore susceptible to immune responses. A fourth advantage is its wide applicability, with examples of CID-regulated proliferation ranging from myoblasts, hepatocytes and pancreatic islet cells, to primary hematopoietic cells, suggesting that CID-regulated approaches might provide an operating system for cell therapy. Hematopoietic applications enjoy a fifth advantage, pleiotropy, because different growth factor signaling domains can elicit different hematopoietic responses, allowing CIDs to regulate hematopoiesis in ways unachievable with conventional growth factors. A sixth advantage of this approach is its specificity. In contrast to conventional growth factors which can bind off-target receptors, or receptors expressed by off-target cell types, CIDs can deliver specific signals to specific cell types. It is this feature that is most relevant for the work described below. We are applying CID regulation to a recently recognized problem related to off-target effects of Epo in patients with cancer related anemia (LINK).

A platform for cell therapy. Preclinical studies have shown that CIDs can be used to regulate the proliferation of pancreatic islet cells for the treatment of diabetes, muscle cells for the treatment of heart failure, and hepatocytes for the treatment of liver disease. A derivative of this approach can be used to bring apoptotic proteins under pharmacological control, allowing for the CID induced killing of genetically modified cells. Thus CID regulation of various signaling molecules can provide a general operating system for cell therapy (Miller & Blau, Gene Therapy 2008).

CID-Regulated Cell Therapy for the Treatment of Cancer

CID-Regulated Red Cell Production.  We have used CIDs, in combination with a derivative of the thrombopoietin receptor (F36VMpl), to direct the Epo-independent production of red blood cells in mice in dogs followed for longer than six years (reference 16 and data not shown) and in human CD34+ cells ex vivo and following transplantation into immune deficient mice. Representative results from one of our mouse studies are shown in Figure 2 (below). While our vector expresses F36VMpl in all hematopoietic lineages, the predominant effect of CID administration is to enhance red blood cell production.  

Figure 2: CID regulated erythropoiesis. Left panel: Effect of AP20187 administration on mean percentages of GFP+ red cells (RBCs), in 5 mice transplanted with congenic marrow cells transduced with an MSCV-based vector encoding both F36VMpl and a GFP marker and treated with 4 separate courses of AP20187 beginning 4 months post transplant (left) or monitored for 8 months, then treated with AP20187 (right). Arrows indicate 3 day courses of AP20187 (10 mg/kg/day). Error bars denote standard deviations. Right panel: Spun hematocrits from 8 mice one week following a 7 day course of AP20187. GFP: Mice transplanted with marrow cells transduced with a control vector, with hematocrits ranging from 40-46%; F36VMpl: Mice transplanted with the F36VMpl vector had hematocrits ranging from 56-62% (p=0.003).

CID-induced erythrocytosis can down-regulate endogenous Epo.  One of the theoretical benefits of using CIDs in patients with cancer is the decline in endogenous Epo that is expected to accompany a CID-triggered increase in red cells. We have demonstrated that this prediction holds true in an anemic mouse model. Pyruvate kinase (pk)-deficient mice have a marked hemolytic anemia and dramatically reduced red cell survival. We established a chimeric mouse model in which 90% of marrow cells were of pk-deficient host origin, whereas the remaining 10% of cells originated from normal donor marrow cells that had been transduced with a vector encoding F36VMpl immediately prior to transplantation. CID administration specifically directed the expansion of the normal donor erythrocytes, promoting an increase in circulating red cells, (Figure 3A, below), and a decline in circulating Epo levels (Figure 3B, below).  

Figure 3. Epo levels decline following CID administration. Three of six pk deficient mice containing ~10% ^MSCVGFP^iresF36VMpl transduced normal donor marrow cells were assigned to treatment with AP20187 10 µg/kg, 3 days a week for 2 weeks, then every day for 2 weeks, while the remaining 3 mice provided non-CID treated controls. (A) Erythrocyte numbers and the percentage of GFP-positive erythrocytes increased in CID treated mice (+) relative to untreated mice (-). (B) Epo levels were measured in the 6 mice, 3 CBA/N mice, and 3 CBA-Pk-1^slc/Pk-1^slc mice (PK-/PK-). Treated mice had Epo levels between those of CBA/N mice and those of CBA-Pk-1^slc/Pk-1^slc mice. *Data from 1 of the untreated mice with an Epo level of 570 mU/mL was not included in the bar chart.

CID-dependent red cell production is Epo-independent. To test the premise that CID- stimulated erythropoiesis is not dependent on the presence of Epo, F36VMpl-transduced human CD34+ cord blood (CB) cells were evaluateded for their ability to generate red cells in response to CID treatment, in the presence or absence of the Epo antagonist, soluble recombinant human EpoR (srhEpoR). Results are shown in Figure 4 (below)..

 Figure 4: CID-dependent red cell production is not affected by Epo blockade. Cord blood CD34+ cells were transduced with a lentivirus vector encoding F36VMpl, then cultured in the presence (+) or absence (-) of Epo (5 U/ml), AP20187 (100 nM), and the competitive Epo antagonist, soluble recombinant human EpoR (at the concentration indicated). Cells counts (left panel) and flow cytometry (right panel were performed on day 12. Results show that AP20187 dependent red cell production is not impaired by Epo ablation.

Cells cultured in the absence of Epo did not proliferate (Figure 4, above) and retained expression of the myeloid marker CD33 (Right Panel, above). Epo (5 U/mL) induced proliferation (66.2-fold in 12 days) and CD33 expression was lost as the cells differentiated into glycophorin A+ erythroid cells. Addition of a competitive inhibitor of Epo binding (soluble human EpoR extracellular domain [shEpoR]) at a concentration of 2.7 μ/mL completely blocked Epo-dependent proliferation and, similar to cells cultured without Epo, CD33 expression persisted. Addition of CID (100nM AP20187) (without Epo) promoted cell expansion (89.8-fold in 12 days) and differentiation as glycophorin A+ erythroid cells, findings that were unchanged in the presence of shEpoR. These data suggest that F36VMpl does not require Epo signaling to support the proliferation and differentiation of human erythroid progenitor cells.

Advantages of CID regulated red cell production in patients with cancer.  Developing methods for converting red cell production from dependency on Epo to dependency on CIDs would provide at least 3 advantages in patients with cancer by i) circumventing the need for exogenous Epo; ii) reducing endogenous levels of Epo via feedback inhibition of renal Epo secretion (Figure 5, below); and iii) opening the potential for combining with Epo antagonists to achieve total ablation of Epo signaling, analogous to androgen blockade for prostate cancer or estrogen blockade for breast cancer, possibly providing a new way to treat a wide range of malignancies. Consistent with the strategy, studies in mice indicate that Epo blockade may provide a new way of treating cancer. A schematic depiction of the goal for our proposed approach is shown in Figure 5, below.

Erythropoietin Blockade for the Treatment of Cancer    

Figure 5. Epo blockade for the treatment of cancer. Cancer may be sustained not only by exogenous Epo, but also by endogenous levels of Epo that accompany anemia. F36VMpl gene transfer followed by AP1903 administration provides a mechanism for the Epo independent regulation of red cell production, avoiding exogenous Epo administration, and reducing endogensous Epo levels. This approach can also be combined with Epo/EpoR antagonists, allowing for the complete ablation of Epo signaling (not shown).

 

Figure 6. Potential applications of pharmacologically regulated cell therapy.

Papers

Blau CA, Peterson KR, Drachman JG and Spencer DM. A proliferation switch for genetically modified cells. PNAS USA 94:3076-3081, 1997.

Jin L, Asano H and Blau CA. Stimulating cell proliferation through the pharmacologic activation of c-kit. Blood 91:890-897, 1998.

Jin L, Siritanaraktul N, Emery DW, Richard RE, Kaushansky K, Papayannopoulou Th and Blau CA. Targeted expansion of genetically modified bone marrow cells. PNAS USA 95:8093-8097, 1998.

Jin L, Neff T and Blau CA. Marrow sensitization to 5 fluorouracil using the ligands for flt-3 and c-kit. Exp Hematol. 27:520-525, 1999.

Richard RE, Wood B, Zeng H, Papayannopoulou Th and Blau CA. Expansion of genetically modified primary human hemopoietic cells using chemical inducers of dimerization. Blood 95:430-6, 2000.

Jin L, Zeng H, Otto KG, Richard RE, Emery DW and Blau CA. In vivo selection using a cell growth switch. Nature Genet 26:64-66, 2000.

Otto KG, Jin L, Spencer DM and Blau CA. Cell Proliferation Induced by Forced Engagement of c-Kit and Flt-3. Blood 97:3662-3664, 2001.

Zeng H, Masuko M, Jin L, Neff T, Otto KG and Blau CA. Receptor specificity in the self-renewal and differentiation of primary multipotential hemopoietic cells. Blood 98:328-334, 2001.

Otto KG, Broudy VC, Lin N, Parganas E, Drachman JG, Luthi JN, Ihle JN and Blau CA. Membrane localization is not required for mpl function in normal hematopoietic cells. Blood  98:2077-2083, 2001.

Whitney ML, Otto K, Blau CA, Reinecke H and Murry CE. Control of myoblast proliferation with a synthetic ligand. J Biol Chem  276:41191-41196, 2001.

Ieremia J and Blau CA. Limitations of a mouse model of sickle cell anemia. Blood Cells Molec Dis 28:146-151, 2002.

Li Z-Y, Otto KG, Richard RE, Ni S, Kirillova, I, Fausto, N, Blau CA and Lieber, A. Dimerizer-induced proliferation of genetically modified hepatocytes. Molecular Therapy 5:420-6, 2002.

Zhao S, Zoller K, Masuko M, Rojnuckarin P, Yang X, Parganas E, Kaushansky K, Ihle JN, Papayannopoulou Th, Willerford DM, Clackson T and Blau CA. JAK2, complemented by a second signal from c-kit or flt-3, triggers extensive self-renewal of primary multipotential hemopoietic cells. EMBO J  21:2159-2167, 2002.

Neff T, Horn PA, Valli VE, Gown AM, Wardwell S, Wood BL, von Kalle C, Schmidt M, Peterson LJ, Morris JC, Richard RE, Clackson T, Kiem HP, Blau CA. Pharmacologically regulated in vivo selection in a large animal. Blood 100: 2026-2031, 2002.

Richard RE and Blau CA. Selective expansion of genetically modified cord blood cells. Stem Cells 21: 71-78, 2003.

Berger C, Blau CA, Huang M-L, Iuliucci JD, Dalgarno DC, Gaschet J, Heimfeld S, Clackson T, Riddell SR. Pharmacologically regulated Fas-mediated death of adoptively transferred T cells in a nonhuman primate model. Blood 103:1261-9, 2004.

Richard RE, Weinreich M, Chang K-H, Ieremia J, Stevenson MM, Blau CA. Modulating erythrocyte mixed chimerism in a mouse model of pyruvate kinase deficiency. Blood 103:4432-4439, 2004.

Zhao S, Weinreich M, Blau CA. In vivo selection using a JAK2-based cell growth switch. Molecular Therapy 10:456-458, 2004.

Richard RE, DeClaro A, Yan J, Chien S, Kiem HP, Clackson T, Andrews R, and Blau CA. Heterogeneity among large animal models of in vivo selection. Molecular Therapy 10:730-740, 2004.

Emery DW, Tubb J, Nishino Y, Nishino T, Otto KG, Stamatoyannopoulos G, and Blau CA. Selection with a regulated cell growth switch increases the likelihood of expression for a linked γ-globin gene in vitro and in vivo. Blood Cells Mol & Dis 34:235-47. 2005.

Gandi M, Ihara K, Cummings C, Pendergrass T, Blau CA and Drachman JD. Congenital Megakaryocytic Thrombocytopenia in Three Siblings: Molecular Analysis of Atypical Clinical Presentation. Exp Hematol 33:1215-21, 2005.

Blau CA, Yan J, Neades R, Navas PA, Peterson KR. g-globin gene expression in CID-dependent multi-potential cells established from b-YAC transgenic mice. J Biol Chem 280:36642-7, 2005.

Richard RE, Siritanaratkul N, Jonlin E, Skarpidi E, Heimfeld S, Blau CA. Collection of blood stem cells from patients with sickle cell anemia. Blood Cells Mol Dis 35:384-8, 2005.

Nagasawa Y, Wood B, Wang L, Lintmaer I, Guo W, Papayannopoulou Th, Harkey M, Nourigat C, Blau CA. Anatomical Compartments Modulate the Response of Human Hematopoietic Cells to a Mitogenic Signal In Vitro and In Vivo. Stem Cells 24:908-17, 2006.

Weinreich MA, Lintmaer I, Wang L, Liggitt D, Harkey M, Blau CA. Growth Factor Receptors as Regulators of Hematopoiesis. Blood 108:3713-21, 2006.

Miller CA, Blau CA. Using Gene Transfer to Circumvent Off-Target Effects. (2008) Gene Therapy 15:759-64, 2008

Architecture Analysis

One of the fundamental questions of the post-genome era is: How does genotype (an organism's genetic structure) translate into phenotype (an observable characteristic)? Our genetic information is contained in 23 pairs of chromosomes. The 46 chromosomes are arranged not in straight lines, but in a tangle, like a plate of cooked spaghetti. The result is that a gene's nearest neighbors in three-dimensional space may be on completely different chromosomes. In collaboration with the laboratories of Dr. Bill Noble, Dr. Stan Fields, and Dr. Jay Shendure (all faculty members in the Department of Genome Sciences), Zhijun Duan in our lab developed a method for capturing interactions within and between chromosomes genome-wide. Mirela Andronescu (Noble Lab) used this information to construct a three-dimensional model of the genome of budding yeast (Duan et al., Nature)

A Three-Dimensional Model of the Yeast Genome

Paper

Duan Z, Andronescu M, Schutz K, McIlwain S, Kim YJ, Lee C, Shendure J, Fields S, Blau CA*, Noble WS*. A three dimensional model of the yeast genome. Nature 2010 May 20;465(7296):363-7. Epub 2010 May 2. (* denotes co-corresponding authors)

A Smarter War on Cancer  

Cancers are far more variable on a molecular level than they appear under the microscope. Still, we continue to treat most cancers based on their appearance – an approach nearly as crude as giving a blood transfusion to everyone who complains of fatigue. Today, however, emerging genomic and computational technologies are transforming cancer research. That research, in turn, promises to transform cancer treatment as well.

An "N of 1" approach

The Blau Lab is establishing the infrastructure to treat a small number of highly motivated cancer patients as individual experiments: in scientific parlance, an "N of 1." Vast amounts of data will be analyzed from each patient's tumor to predict which proteins should be targeted in order to destroy the cancer. Each patient would then receive a drug regimen tailored to his or her tumor. In this kind of single-subject approach, there is no control group against which to compare the response of the experimental subject. Instead, each patient would serve as his or her own control, using a technique called serial molecular monitoring. In this technique, the patient would receive a drug designed to block a particular target protein. A biopsy would then be performed to confirm whether the drug had worked and the target had indeed been blocked. In this way, researchers would track the tumor's molecular response to treatment through repeated biopsies (a requirement that may eventually be replaced by sampling blood). One of the most important advantages of serial molecular monitoring is that it would reveal strategies that tumors adopt to evade therapy, possibly uncovering new targets of opportunity.

This patient-centered approach represents a dramatic departure from traditional oncology. Because these novel patient-specific combinations of drugs could have unforeseen side effects, the methodological, regulatory, and ethical framework for cancer research would need to be reconsidered from the ground up. Therapies that appear to be effective would be validated in small trials involving other patients with similar molecular profiles. Unsuccessful therapies could be analyzed to refine our understanding of tumor biology and drug mechanisms. The N of 1 approach may not hit immediate home runs. However, the extensive body of knowledge generated from each patient should, upon aggregation with data from other patients, enable us to tell from a blood sample which patients will respond to particular drugs. In time, we hope to be able to stop tumors by anticipating the escape routes they are likely to take.

Although this approach will be very expensive for early adopters, technology costs are falling at exponential rates (think of Moore's Law for integrated circuits). Eventually, the approach should lead to dramatic reductions in health-care costs. For one thing, the approach allows us to administer these expensive drugs only to patients for whom they are most likely to work. For another, the costs of the approach will go down and – and scalability increase – once expected advances in technology allow us to use simple blood draws rather than repeated tumor biopsies.

Although many significant challenges remain, the primary roadblock to implementing the single-subject approach is financial. Will insurance companies or federal agencies pay to test this new paradigm for cancer treatment? Will patients with difficult-to-treat cancers (and the means to fund their own treatment) be willing to take on this grand experiment – for their own benefit, potentially, and for the benefit of other patients? We believe that it's time to find out.