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Untitled Document
CANCER GENOMICS & PROTEOMICS
Volume 4, Number
3, May-June 2007
| CONTENTS |
PAGE |
| Editorial |
107 |
| Genomic and Proteomic Approach to Individualized Therapy |
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| *An Exploration into Study Design for Biomarker Identification: Issues and Recommendations. J.A. HALL, R. BROWN, J. PAUL (Glasgow, UK) |
111 |
| *Contribution of DNA and Tissue Microarray Technology to the Identification and Validation of Biomarkers. D.J. BRENNAN, C. KELLY, E. REXHEPAJ, P.A. DERVAN, M.J. DUFFY, W.M. GALLAGHER (Dublin, Ireland) |
121 |
*Application of Array-based Genomic and Epigenomic Technologies to Unraveling the Heterogeneous Nature of Breast Tumors: On the Road to Individualized Treatment. M. ABRAMOVITZ, B. LEYLAND-JONES (Montreal,
QC, Canada; Atlanta, GA, USA) |
135 |
| *Individualization of Therapy Using Mammaprint®™: from Development to the MINDACT Trial. S. MOOK, L.J. VAN’T VEER, E.J.T. RUTGERS, M.J. PICCART-GEBHART, F. CARDOSO (Amsterdam, The Netherlands; Brussels, Belgium) |
147 |
*Development of Reverse Phase Protein Microarrays for Clinical Applications and Patient-tailored Therapy. R. SPEER, J. WULFKUHLE, V. ESPINA,
R. AURAJO, K.H. EDMISTON, L.A. LIOTTA, E.F. PETRICOIN III
(Tübingen, Germany; Manassas; Falls Church, VA, USA) |
157 |
| *Cancer Stem Cells and Individualized Therapy. S. CHUMSRI, P. PHATAK, M.J. EDELMAN, N. KHAKPOUR,A.W. HAMBURGER, A.M. BURGER (Baltimore, MD, USA) |
165 |
*Tailoring-targeted Therapy to Individual Patients: Lessons to be Learnt from the Development of Mitomycin C. M. VOLPATO, R.M. PHILLIPS
(Bradford, UK) |
175 |
Gene Signature-based Prediction of Tumor Response to Cyclophosphamide.
A. KORRAT, T. GREINER, M. MAURER, T. METZ, H.-H. FIEBIG
(Freiburg, Germany) |
187 |
Gene Signatures Developed from Patient Tumor Explants Grown in Nude Mice to Predict Tumor Response to 11 Cytotoxic Drugs.H.-H. FIEBIG, J. SCHÜLER, N. BAUSCH, M. HOFMANN, T. METZ, A. KORRAT
(Freiburg, Germany) |
197 |
| New Molecular Targets |
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*Molecular Targets in Metastasis: Lessons from Genomic Approaches.
B. FINGLETON (Nashville, TN, USA) |
211 |
| Molecular Analysis of Xenograft Models of Human Cancer Cachexia – Possibilities for Therapeutic Intervention. A.J. BAUMGARTEN, H.-H. FIEBIG, A.M. BURGER (Freiburg, Germany; Baltimore, MD, USA) |
223 |
| Post-transcriptional Control of the MCT-1-associated Protein DENR/DRP by RNA-binding Protein AUF1. K. MAZAN-MAMCZARZ, R.B. GARTENHAUS (Baltimore, MD, USA) |
233 |
| Drug Transporters as Targets for Cancer Chemotherapy. T. NAKANISHI (Baltimore, MD, USA) |
241 |
*Reviews
CANCER GENOMICS & PROTEOMICS 4: 111-120 (2007)
An Exploration into Study Design for Biomarker Identification: Issues and Recommendations
JACQUELINE A. HALL, ROBERT BROWN and JIM PAUL
Centre for Oncology and Applied Pharmacology, Cancer Research UK Beatson laboratories, University of Glasgow, Garscube estate, Glasgow, G61 1BD, U.K.
Abstract: Genomic profiling produces large amounts of data and a challenge remains in identifying relevant biological processes associated with clinical outcome. Many candidate biomarkers have been identified but few have been successfully validated and make an impact clinically. This review focuses on some of the study design issues encountered in data mining for biomarker identification with illustrations of how study design may influence the final results. This includes issues of clinical endpoint use and selection, power, statistical, biological and clinical significance. We give particular attention to study design for the application of supervised clustering methods for identification of gene networks associated with clinical outcome and provide recommendations for future work to increase the success of identification of clinically relevant biomarkers.
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CANCER GENOMICS & PROTEOMICS 4: 121-134 (2007)
Contribution of DNA and Tissue Microarray Technology to the Identification and Validation of Biomarkers and Personalised Medicine in Breast Cancer
DONAL J. BRENNAN1, CATHERINE KELLY1, ELTON REXHEPAJ1,
PETER A. DERVAN2, MICHAEL J. DUFFY2,3 and WILLIAM M. GALLAGHER1*
1UCD School of Biomolecular and Biomedical Science,
2UCD School of Medicine and Medical Science, UCD Conway Institute,
University College Dublin, Belfield, Dublin 4;
3Department of Pathology and Laboratory Medicine,
St. Vincent's University Hospital, Elm Park, Dublin 4, Ireland.
Abstract: Completion of the human genome project has revolutionised translational medicine. High-throughput technology now permits investigators to systematically interrogate the genome, transcriptome, proteome and metabolome. It is expected that these advances will eventually be translated into new more sensitive diagnostic tests and less toxic therapeutics. A major shift is expected in clinical oncology over the next few decades as we start to move away from currently practiced, population-based approaches to personalised medicine. In this emerging approach, the molecular and pathophysiological characteristics of an individual patient and tumour will be measured and tailored therapeutic regimens will be administered based on these profiles. One of the key steps in this process will be the identification and validation of biomarkers. Whilst great advances have been made in the discovery of putative biomarkers, disappointingly few have been translated into clinically applicable assays. It is widely believed that this is due to a lack of well-designed, thorough validation studies. Here, we review the role of DNA microarrays and tissue microarrays in the validation of biomarkers in breast cancer, with emphasis on their potential application to determine mode of personalised therapy in the future.
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CANCER GENOMICS & PROTEOMICS 4: 135-146 (2007)
Application of Array-based Genomic and Epigenomic Technologies to Unraveling the Heterogeneous Nature of Breast Tumors: On the Road to Individualized Treatment
MARK ABRAMOVITZ1 and BRIAN LEYLAND-JONES2
1VM Institute of Research, Montreal, Quebec, Canada;
2Winship Cancer Institute, Emory University, Atlanta, GA, U.S.A.
Abstract: The recent application of genomic microarray technology to the molecular profiling of breast tumors has clearly demonstrated their heterogeneous nature. Targeted treatment strategies are having a clear impact on patient survival. It has also become apparent that accumulated mutations, genomic instability, epigenetic phenomena, genetic variability and environmental factors all contribute to the uniqueness of a patient's tumor. Novel genomic and epigenetic-based technologies have been or are being developed in order to greatly enhance the analysis of tumor samples including those samples previously thought unusable due to the fixation process, such as archival formalin-fixed paraffin-embedded (FFPE) samples. Patients and their tumors can now be studied with regard to genetic variation, genomic instability, gene expression, gene mutations, and methylation patterns. These areas of research are being made more accessible through genome-wide screening technologies and will, in the near future, rapidly expand our understanding of what contributes to the unique properties of each tumor and lead to the identification of genes that could be potential therapeutic targets for specific tumor subtypes. Application of these technologies to our understanding of breast cancer will undoubtedly have an impact on the individualization of treatment for breast cancer patients in the not to distant future.
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CANCER GENOMICS & PROTEOMICS 4: 147-156 (2007)
Individualization of Therapy Using Mammaprint®™: from Development to the MINDACT Trial
STELLA MOOK1, LAURA J. VAN'T VEER1, EMIEL J.T. RUTGERS1,
MARTINE J. PICCART-GEBHART2 and FATIMA CARDOSO2
1Netherlands Cancer Institute, Amsterdam, The Netherlands;
2Jules Bordet Institute, Brussels, Belgium
Abstract: To date, most treatment decisions for adjuvant chemotherapy in breast cancer are based on conventional clinicopathological criteria. Since breast cancer tumors with similar clinicopathological characteristics can have strikingly different outcomes, the current selection for adjuvant chemotherapy is far from accurate. Using high-throughput microarray analysis, a 70-gene signature was identified which can accurately select early stage breast cancer patients who are highly likely to develop distant metastases, and therefore, may benefit the most from adjuvant chemotherapy. This review describes the development of the 70-gene profile (Mammaprint®™), its retrospective validation and feasibility studies, and its prospective validation in the large adjuvant MINDACT (Microarray In Node-negative Disease may Avoid ChemoTherapy) clinical trial.
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CANCER GENOMICS & PROTEOMICS 4: 157-164 (2007)
Development of Reverse Phase Protein Microarrays for Clinical Applications and Patient-tailored Therapy
RUNA SPEER1, JULIA WULFKUHLE2, VIRGINIA ESPINA2, ROBYN AURAJO2,
KIRSTEN H. EDMISTON3, LANCE A. LIOTTA2 and EMANUEL F. PETRICOIN III2*
1University of Tubingen, Faculty of Medicine, Department of Obstetrics and Gynecology, Calwer Str. 7, 72076 Tubingen, Germany;2Center for Applied Proteomics and Molecular Medicine, George Mason University, Manassas, VA; 3Department of Surgery, Inova Fairfax Hospital Cancer Center, 3300, Gallows Road, Falls Church, VA, U.S.A.
Abstract: While genomics provide important information about the somatic genetic changes, and RNA transcript profiling can reveal important expression changes that correlate with outcome and response to therapy, it is the proteins that do the work in the cell. At a functional level, derangements within the proteome, driven by post-translational and epigenetic modifications, such as phosphorylation, is the cause of a vast majority of human diseases. Cancer, for instance, is a manifestation of deranged cellular protein molecular networks and cell signaling pathways that are based on genetic changes at the DNA level. Importantly, the protein pathways contain the drug targets in signaling networks that govern overall cellular survival, proliferation, invasion and cell death. Consequently, the promise of proteomics resides in the ability to extend analysis beyond correlation to causality. A critical gap in the information knowledge base of molecular profiling is an understanding of the ongoing activity of protein signaling in human tissue: what is activated and "in use" within the human body at any given point in time. To address this gap, we have invented a new technology, called reverse phase protein microarrays, that can generate a functional read-out of cell signaling networks or pathways for an individual patient obtained directly from a biopsy specimen. This "wiring diagram" can serve as the basis for both, selection of a therapy and patient stratification.
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CANCER GENOMICS & PROTEOMICS 4: 165-174 (2007)
Cancer Stem Cells and Individualized Therapy
SARANYA CHUMSRI1, PORNIMA PHATAK2, MARTIN J. EDELMAN1,
NAZANIN KHAKPOUR3, ANNE W. HAMBURGER4
and ANGELIKA M. BURGER2
Departments of 1Medicine, 2Pharmacology and Experimental Therapeutics,
3Surgery and 4Pathology, University of Maryland Marlene and
Stewart Greenebaum Cancer Center, Baltimore, MD, U.S.A.
Abstract: The concept of individualized cancer chemotherapy emerged three decades ago from the observation that a small fraction of cells in primary tumors can form colonies in soft agar similar to stem cells of the hematopoietic system. In a series of retrospective and prospective clinical studies, clonogenic tumor growth and effects of anticancer agents on the putative cancer stem cells were assessed as predictive factors. The results of these trials showed that clonogenic growth is associated with poor outcome and drug resistance. Recent breakthroughs enabling isolation and the molecular classification of cancer stem cells have renewed interest in cancer stem cells as a therapeutic target. Here, we provide a current overview of cancer stem cell biology and highlight possibilities for targeted intervention with existing and novel experimental anticancer agents.
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CANCER GENOMICS & PROTEOMICS 4: 175-186 (2007)
Tailoring Targeted Therapy to Individual Patients: Lessons to be Learnt from the Development of Mitomycin C
MILÈNE VOLPATO and ROGER M. PHILLIPS
Institute of Cancer Therapeutics, University of Bradford, Bradford BD7 1DP, U.K.
Abstract: The modern era of targeted therapeutics offers the potential to tailor therapy to individual patients whose tumours express a specific target. Previous attempts to forecast tumour response to conventional chemotherapeutics based on similar principles have however been disappointing. Mitomycin C (MMC), for example, is a bioreductive drug that requires metabolic activation by cellular reductases for activity. The enzyme NAD(P)H:Quinone oxidoreductase-1 (NQO1) can reduce MMC to DNA damaging species but attempts to establish the relationship between tumour response to MMC and NQO1 expression have generated conflicting reports of good and poor correlations. Several other reductases are known to activate MMC. This, in conjunction with the fact that various physiological and biochemical factors influence therapeutic response, suggests that the mechanism of action of MMC is too complex to allow tumour response to be predicted on the basis of a single enzyme. Alternative approaches using more complex biological and pharmacological systems that reflect the spectrum of reductases present within the tumour have been developed and it remains to be seen whether or not the predictive value of these approaches is enhanced. With regards to targeted therapeutics, the experience with MMC suggests that prediction of tumour response based on analysis of a single target may be too simplistic. Multiple mechanisms of action and the influence of tumour microenvironment on cell biology and drug delivery are likely to influence the final outcome of therapy. The challenge for the future progression of this field is to develop assays that reflect the overall biological and pharmacological processes involved in drug activation whilst retaining the simplicity and robustness required for routine chemosensitivity testing in a clinical setting.
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CANCER GENOMICS & PROTEOMICS 4: 187-196 (2007)
Gene Signature-based Prediction of Tumor Response to Cyclophosphamide
ANDRÉ KORRAT, THOMAS GREINER, MARTINA MAURER,
THOMAS METZ and HEINZ-HERBERT FIEBIG
Oncotest GmbH, Institute for Experimental Oncology, Am Flughafen 12-14,
D-79108 Freiburg, Germany
Abstract: Cyclophosphamide (CY) is a clinically used cytotoxic agent that is effective in a wide range of tumor types including breast and small cell lung cancers. However, by far not all patients benefit from CY therapy. We used patient tumor explants grown in nude mice as an experimental model system to identify a gene signature that, based on a tumor's gene expression profile, predicts its CY response. Forty-nine human tumor xenografts of different histologies were defined as the training set. Correlation of the gene expression profiles of untreated tumors to the sensitivity of the same tumors to CY led to the identification of 129 transcripts as predictive biomarkers for CY response. Interestingly, the products of 12 of these genes were known to interact at least indirectly with CY. A leave-one-out cross-validation approach led to a correct prediction of the CY response of the training set tumors in 15 out of 18 cases (83%) as compared to a response rate of 18 out of 49 (32%), following random testing. For an independent set of 25 previously untested tumors with known gene expression profiles (validation set) CY sensitivity was predicted correctly for 6 out of 8 tumors (75%), and CY resistance for 15 out of 17 tumors (88%). In comparison, random testing of the same tumors resulted in a response rate of 8 out of 25 (32%). For the same 25 tumors, the median minimum T/C value for predicted responders was 1% as compared to 49% for predicted non-responders. Finally, for tumor types considered as CY sensitive such as small cell lung and breast cancers as well as melanoma, the combined real and predicted response rates for 37 tested and 26 untested tumors was 49%. In contrast, for tumor types considered as CY resistant, including colon and renal cancer, the combined real and predicted response rate for 37 tested and 75 untested tumors was only 13%. Taken together, we identified a gene signature that can predict tumor response to CY and warrants clinical validation.
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CANCER GENOMICS & PROTEOMICS 4: 197-210 (2007)
Gene Signatures Developed from Patient Tumor Explants Grown in Nude Mice to Predict Tumor Response to 11 Cytotoxic Drugs
HEINZ-HERBERT FIEBIG, JULIA SCHULER, NIKO BAUSCH,
MICHAEL HOFMANN, THOMAS METZ and ANDRE KORRAT
Oncotest GmbH, Institute for Experimental Oncology, Am Flughafen 12-14,
D-79108 Freiburg, Germany
Abstract: Patient tumor explants established subcutaneously in serial passage in nude mice were characterized for their sensitivity towards 11 standard cytotoxic anti-cancer agents. The latter include the alkylating agents cyclophosphamide, ifosfamide, mitomycin C, cisplatin and CCNU, the antimetabolites 5-FU and methotrexate; the topoisomerase II inhibitors adriamycin and etoposide as, well as the tubulin binders paclitaxel and vindesine. The mean number of tumors treated with any of the various drugs was 54 (range 31-78). The tumor xenografts' gene expression profiles were determined using the Affymetrix HG-U133 plus 2.0 mRNA expression array representing ~38.500 human genes. The hypothesis was that the correlation of drug response to gene expression would identify gene signatures that can predict the drug response of individual tumors to these agents. Predictive gene signatures were found and subsequently verified using the leave-one-out cross-validation (LOOCV) technique. Tumors were considered as responsive if the drugs effected a tumor volume inhibition to less than 11-41% of the volume of vehicle control tumors (T/C%). The median cut-off over all drugs was a T/C of 25%. Using these criteria, on average one third of the test tumors were sensitive (responders) and two thirds were resistant (non-responders). The bio-informatic analysis yielded predictive gene signatures consisting of 42-129 genes (mean for the 11 drugs: 87 genes). On average, the response rate for predicted responders (83%) was 2.45 fold higher than that for all test tumors (random testing, 34%). This increase of response rates, following signature-guided testing, was consistent for all 11 agents. Conversely, 94% of the predicted non-responders (range: 84-100%) proved to be non-responders in nude mouse studies while the proportion of non-responders among all test tumors was approximately 66%. The majority of genes (59%) making up the predictive gene signatures had an unknown function. Known genes were implicated in cell proliferation, apoptosis, DNA repair, cell cycle, metabolism and transcription. The predictive gene signatures presented here for 11 cytotoxic agents have the potential, if employed in the clinic, to substantially increase tumor response rates compared to empirical drug treatment. However they need to be further validated, both preclinically and clinically.
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CANCER GENOMICS & PROTEOMICS 4: 211-222 (2007)
Molecular Targets in Metastasis: Lessons from Genomic Approaches
BARBARA FINGLETON
Department of Cancer Biology, 771 PRB, Vanderbilt University Medical Center,
Nashville, TN 37232-6840, U.S.A.
Abstract: Microarray studies have yielded valuable information that can be used to determine a cancer patient's prognosis and allow for optimum treatment choices. Tumor profiling has also changed our perception of metastatic propensity. Genomic analyses clearly showed that a metastasis signature is encoded within the genome so that when a cancer develops, the likelihood of metastasis is high, whereas other cancers which do not have this genotype metastasize as a result of random mutations. It is certain however, that cells other than tumor cells contribute to the development of metastasis through their production of various pro-metastatic proteins. Here, we review the published metastasis profiling studies and the role of the host in metastasis. Collagen type I, CXCR4, CSF-1, OPN and RhoC are metastasis-associated genes for which evidence exists for a causal contribution to elements of the metastatic process. These genes are discussed in detail and represent excellent drug targets for anti-metastasis therapies.
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CANCER GENOMICS & PROTEOMICS 4: 223-232 (2007)
Molecular Analysis of Xenograft Models of Human Cancer Cachexia - Possibilities for Therapeutic Intervention
AXEL J. BAUMGARTEN1, HEINZ-HERBERT FIEBIG1 and ANGELIKA M. BURGER2
1Institute for Experimental Oncology, Oncotest GmbH, Am Flughafen 12-14, D-79108 Freiburg, Germany; 2Department of Pharmacology and Experimental Therapeutics,
Marlene and Stewart Greenebaum Cancer Center,
University of Maryland School of Medicine, 655 W. Baltimore Street,
Baltimore, MD, U.S.A.
Abstract: Approximately 50% of all cancer patients develop cachexia, a paraneoplastic syndrome that is characterized by wasting of adipose tissue and skeletal muscle mass. Cytokines, including TNF-á, interleukins-1, -6, and interferon-A are known mediators of the cachectic process. The latter however represent only one of many imbalanced systems in cancer cachexia. The aim of this study was to further delineate the pathogenesis of cachexia by molecular profiling. Human renal cancer xenografts that do and do not induce cachexia in mice were used as disease models. Cachexia-associated gene expression was studied on Human Genome U95 Affymetrix arrays and revealed several new genes such as TNF-á ligand superfamily protein, interferon-A treatment inducible protein, and DKFZ5641I1922. The expression of the IL-8 gene was also elevated in cachexia inducing xenografts (CIX). At the protein level, TNF-á was found expressed only in CIX, whereas IL-1 and IL-6 were not cachexia specific. Levels of parathyroid hormone-related protein were elevated in CIX and accompanied by hypercalcemia. COX-2 and prostaglandin E2 were also found to be over expressed. By using the COX-2 inhibitors rofecoxib and nimesulide, we were able to delay tumor-mediated wasting in vivo. Overall, our results suggest that cachexia is a multigenetic disease that will require complex combinations of drugs for an effective therapeutic intervention.
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CANCER GENOMICS & PROTEOMICS 4: 233-240 (2007)
Post-transcriptional Control of the MCT-1-associated Protein DENR/DRP by RNA-binding Protein AUF1
KRYSTYNA MAZAN-MAMCZARZ and RONALD B. GARTENHAUS
University of Maryland, Marlene and Stewart Greenebaum Cancer Center 9-011 BRB,
655 West Baltimore Street, Baltimore, Maryland 21201, U.S.A.
Abstract: Background: There is often a poor correlation observed between protein and RNA in eukaryotic systems, supporting the emerging paradigm that many of the abnormalities in a cancer cell's proteome may be achieved by differential recruitment of mRNAs to polysomes referred to as the translational profile. The MCT-1 oncogene product has recently been shown to interact with the cap complex and to modulate the translational profile of cell lines when MCT-1 was highly expressed. The MCT-1 protein modifies mRNA translational profiles through its interaction with DENR/DRP, a protein containing an SUI1 domain involved in recognition of the translation initiation codon. It has been shown previously that the protein levels of DENR/DRP go up in parallel with increasing cell density, however the mechanism(s) underlying this increase is poorly understood at present. The 3'-untranslated region (3'UTR) of DENR/DRP was found to have a high number of uracyl (U)- and adenine (A)-rich sequences (AREs). Many RNA-binding proteins (RBPs) have been shown to recognize and bind to mRNAs that contains AREs generally present in the 3'UTR of mRNAs. RBPs binding to AREs such as AUF1, BRF1, KSRP, and TTP are known to regulate mRNA turnover, while TIAR and TIA-1 influence mRNA translation. Materials and Methods: We assessed the association of several ARE binding proteins with DENR/DRP mRNA by reverse transcription of the RNA obtained after immunoprecipitation of cell lysates from HEK 293 cells growing at varying levels of cell density. HEK 293 cells were transfected with an AUF1 silencing vector (shRNA), and protein levels of DENR/DRP were analyzed by Western blotting. Results: We demonstrated that both HuR and AUF1 bind to discrete regions of DENR/DRP mRNA and that AUF1 silencing increases DENR/DRP protein levels. Conclusion: Our data established a cell density-dependent interaction of AUF1 protein with DENR/DRP mRNA that modulates DENR/DRP protein levels.
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CANCER GENOMICS & PROTEOMICS 4: 241-254 (2007)
Drug Transporters as Targets for Cancer Chemotherapy
TAKEO NAKANISHI
The Program in Experimental Therapeutics, Marlene and Stewart Greenebaum Cancer Center, School of Medicine, University of Maryland at Baltimore, Room 9-20 Bressler Research Building, 655 West Baltimore Street, Baltimore, MD 21201, U.S.A..
Abstract: Transporter proteins play an important role in taking up nutrients into and effluxing xenobiotics out of cells to sustain cell survival. Transporters that affect drug absorption, distribution and excretion are the so-called drug transporters. In the last decade, a number of studies revealed interactions between drug transporters and clinically important anticancer agents. Utilizing the knowledge of transporter functions offers us the possibility of delivering a drug to the target tissues, avoiding distribution to other tissues and improving oral bioavailability. Many transporters have been reported to be differentially up-regulated in cancer cells compared to normal tissues, suggesting that the differential expression of transporters in cancer cells may provide good targets for enhancing drug delivery as well as diagnostic markers for cancer therapy. This review will focus on the role of drug transporters in the adaptation and growth of tumors and in their potential usefulness as therapeutic targets in cancer.
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