Molecular-guided therapy predictions reveal drug resistance phenotypes and treatment alternatives in malignant peripheral nerve sheath tumors
© Peacock et al.; licensee BioMed Central Ltd. 2013
Received: 31 May 2013
Accepted: 12 September 2013
Published: 17 September 2013
Malignant peripheral nerve sheath tumors (MPNST) are rare highly aggressive sarcomas that affect 8-13% of people with neurofibromatosis type 1. The prognosis for patients with MPNST is very poor. Despite TOP2A overexpression in these tumors, doxorubicin resistance is common, and the mechanisms of chemotherapy resistance in MPNST are poorly understood. Molecular-guided therapy prediction is an emerging strategy for treatment refractory sarcomas that involves identification of therapy response and resistance mechanisms in individual tumors. Here, we report the results from a personalized, molecular-guided therapy analysis of MPNST samples.
Established molecular-guided therapy prediction software algorithms were used to analyze published microarray data from human MPNST samples and cell lines, with benign neurofibroma tissue controls. MPNST and benign neurofibroma-derived cell lines were used for confirmatory in vitro experimentation using quantitative real-time PCR and growth inhibition assays. Microarray data was analyzed using Affymetrix expression console MAS 5.0 method. Significance was calculated with Welch’s t-test with non-corrected p-value < 0.05 and validated using permutation testing across samples. Paired Student’s t-tests were used to compare relative EC50 values from independent growth inhibition experiments.
Molecular guided therapy predictions highlight substantial variability amongst human MPNST samples in expression of drug target and drug resistance pathways, as well as some similarities amongst samples, including common up-regulation of DNA repair mechanisms. In a subset of MPNSTs, high expression of ABCC1 is observed, serving as a predicted contra-indication for doxorubicin and related therapeutics in these patients. These microarray-based results are confirmed with quantitative, real-time PCR and immunofluorescence. The functional effect of drug efflux in MPNST-derived cells is confirmed using in vitro growth inhibition assays. Alternative therapeutics supported by the molecular-guided therapy predictions are reported and tested in MPNST-derived cells.
These results confirm the substantial molecular heterogeneity of MPNSTs and validate molecular-guided therapy predictions in vitro. The observed molecular heterogeneity in MPNSTs influences therapy prediction. Also, mechanisms involving drug transport and DNA damage repair are primary mediators of MPNST chemotherapy resistance. Together, these findings support the utility of individualized therapy in MPNST as in other sarcomas, and provide initial proof-of concept that individualized therapy prediction can be accomplished.
Malignant peripheral nerve sheath tumors (MPNSTs) are aggressive sarcomas associated with substantial morbidity and mortality . MPNSTs are rare in the general population, affecting about 1 in 100,000 people each year , whereas individuals with neurofibromatosis type 1 (NF1) carry an 8-13% lifetime risk of developing an MPNST . Despite aggressive, multi-modal treatment, overall survival is poor for both primary and metastatic MPNST [1, 3].
Chemotherapy resistance is a hallmark of both primary and recurrent MPNSTs [4, 5] owing to a variety of factors, most notably up-regulation of drug efflux transporters [4, 6–8]. Alternative mechanisms of chemotherapy resistance in MPNSTs and other sarcomas have been described, including Twist 1 overexpression , Bcl-xl overexpression , and autophagy induction . Escalation of DNA repair processes is also observed in other chemotherapy-resistant sarcomas [12–14]. The doxorubicin target, topoisomerase II (TOP2A), is significantly overexpressed in MPNSTs  compared to neurofibromas . Doxorubicin binds to the topoisomerase II complex following DNA strand breaks, interrupting cellular replication . However, overexpression of TOP2A is associated with diminished survival in MPNST, confirming that overexpression of the doxorubicin target is insufficient to overcome established mechanisms of doxorubicin resistance . Doxorubicin-based chemotherapy regimens are typically used to treat MPNST, but the therapeutic benefit is modest and closely parallels that of other soft-tissue sarcoma regimens [18, 19], and dose limiting toxicity is common .
The refractory nature of MPNSTs is attributable to a high degree of molecular heterogeneity, both in terms of mechanisms underlying disease progression  and rapidly evolving therapy resistance. Studies confirm deletion or loss of function in tumor suppressor genes, including NF1, HMMR/RHAMM, TP53, and duplications or gain of function mutations in several oncogenes, including MET, HGF, EGFR, ITGB4, and PDGFRA . Other deregulated pathways in MPNSTs include a variety of well-characterized drug targets such as mTOR, HGF/Met, TOP2A, Ras, and steroid hormones [15, 16, 22–27].
Molecular-guided therapy prediction or personalized medicine (PMED) strategies are currently under evaluation for use in recurrent and refractory pediatric brain tumors (NCT01802567), neuroblastoma (NCT01355679) and sarcomas (NCT01772771). This approach is also a promising treatment alternative for therapy-resistant cancers like MPNST [28–30]. PMED workflows follow a knowledge and rules-based statistical algorithm that converts genomic profiling data into an ordinal ranking of therapies. Drug predictions are therefore agnostic to disease context and adaptable to a variety of clinical scenarios. Essential to the PMED drug prediction algorithm is the reconciliation of predicted therapies selected from a comprehensive drug list against known mechanisms of chemotherapy resistance and drug resistance biomarkers. This knowledge-based rules approach relies on databases, such as DrugBank, that feature annotated references to over one thousand drugs and target molecules. PMED platforms also feature topological analysis tools which identify drug targets and potential mechanisms of resistance based on gene network perturbation. This approach is complementary to a single gene interrogation and allows for a broader systems-based analysis of disease-specific molecular pathogenesis (GeneGo-Thomson Reuters) [31–35]. While the clinical efficacy of PMED approaches is still under investigation, the PMED bioinformatics approach is a robust tool for discovery-level research into the molecular pathogenesis of MPNSTs.
Here, we present data supporting the PMED strategy as a useful method for determining mechanisms of chemotherapy resistance and identifying potential alternative therapeutics in individual MPNSTs. The use of benign precursor neurofibromas as a biologically relevant control in the PMED analysis is novel and provides insight into the genomic alterations underlying conversion from neurofibroma to MPNST. We also demonstrate that novel predicted therapies have in vitro efficacy against highly drug resistant MPNST-derived cells .
Microarray data on MPNST samples, neurofibromas, and MPNST-derived cell lines were accessed via NCBI Gene Expression Omnibus (GEO) repository  as indicated in text. Additional benign neurofibroma samples were acquired through an established tissue collection initiative in collaboration with Spectrum Health. All specimens were obtained according to an IRB approved protocol within Spectrum Health. Affymetrix U133 2.0 plus chip arrays were performed at Clinical Research Laboratories (CRL, Lenexa, KS). Purified RNA was used for the preparation of amplified cDNA (NuGen Ovation Pico WTA System). Amplified cDNA was then fragmentated and labelled (NuGen Encore Biotin Module) and hybridized to GeneChip Human Genome U133 Plus 2.0 Array (GeneChip® Hybridization, Wash and Stain Kit, Affymetrix). The arrays were scanned by using GeneChip Scanner 3000 7G and the intensity files were analyzed by Expression Console Software. Array data was normalized using Affymetrix expression console MAS 5.0 method and further filtered to remove probes with absent calls and expression intensities less than 100 in over 40% of samples. Differentially expressed genes were identified using Welch’s t-test with non-corrected p-value < 0.05 and validated using permutation testing across samples. Most significant probe sets of top 100 and top 200 probes were submitted to GeneGo for extensive network and pathway enrichment analysis. Heat maps were generated using XenoBase® version 3.5 from Affymetrix array data using MAS 5.0 normalization. Clustering was performed in both sample and probe dimensions using average linkages with a Pearson correlation distance metric.
Molecular-guided personalized medicine (PMED) analysis
Quantitative real-time PCR
Microarray data was confirmed using real-time polymerase chain reaction (qRT-PCR). Total RNA was extracted from cultured MPNST cell lines and benign neurofibroma-derived cell lines during logarithmic cell growth using TRIzol reagent (Invitrogen). Neurofibroma cell lines were derived from benign neurofibromas using established protocols . Synthesis of cDNA was performed using 500 ng of RNA according to manufacturer’s instructions (High Capacity cDNA Reverse Transcription Kit, Invitrogen). Primers used for qRT-PCR were as follows ABCC1-Forward (F), GAGGAAGGGAGTTCAGTCTT; ABCC1-Reverse (R), ACAAGACGAGCTGAATGAGT; ABCC3-F, CACACGGATCTGACAGACAATGA; ABCC3-R, ACAGGGCACTCAGCTGTCTCA; ABCC4-F, TGTGCTTTTTAAGGCTTCACTCAAT; ABCC4-R, TTGTCCTTCGTATAGCAAGTTTTTTG; ABCC5-F, GAGAACCAGCACTTCTGGGA; ABCC5-R, TGAGCTGAGAATGCATGGAG; ABCC6-F, AAAGTACACACAGCATGGCAGTTC; ABCC6-R64, GCTCCCGGCTAGACCCTTAA; ABCG5-R232, GTTCACATACACCTCCCCCA; ABCG5-F101, TCCTTGTACGTGGAGAGCG; GAPDHF, TGGTATCGTGGAAGGACTCATGAC; GAPDHR, TGCCAGTGAGCTTCCCGTTCAGC. Reactions were performed in duplicate at 10 μl volume using Sybr Select master mix (Applied Biosystems) according to manufacturer’s instructions. Melt curve analyses are performed following all reactions to ensure detection of a single product based upon single and consistent melting temperatures for each primer set using StepOne Software v2.3 (Applied Biosystems) standard parameters. Data is normalized using GAPDH expression and represented as fold change relative to a control sample (2^ΔΔCT) as indicated in the respective results.
Cells grown on 8-well chamber slides (Nunc) were fixed in 4% paraformaldehyde, blocked in PBS with 10% goat serum, and incubated in primary antibodies against ABCC1 (Abcam ab24102) and S100 (Dako Z0311) at 1:50 and 1:400 dilution, respectively, overnight at 4°C. Cells were washed in PBS, and secondary incubations were conducted for 45 minutes at room temperature with respective Alexa Fluor-488 Donkey anti-Mouse IgG and Alexa Fluor-568 Donkey anti-Rabbit IgG secondary antibodies at 1:400 dilution. Slides were mounted in Vectashield with DAPI (Vector Labs) for nuclear counterstaining. All images were obtained using identical acquisition settings with 60× objective on an A1 confocal Ti microscope (Nikon).
Growth inhibition experiments
MPNST-derived cell lines NF96.2, NF02.2, and NF94.3 (ATCC) and benign neurofibroma cell lines were maintained in 5% CO2 at 37C, in modified DMEM with 10% fetal bovine serum and 1% penicillin/streptomycin. Growth inhibition experiments were carried out in DMEM supplemented with 10% FBS in 96-well plate format. Cells were seeded at 2×103 cells per well and allowed to attach for 24 hours prior to drug treatment for 96 hours. Doxorubicin (LC Laboratories) dosages included 5 μg/ml, 2.5 μg/ml, 1.25 μg/ml, 625 ng/ml, 312 ng/ml, 156 ng/ml, 78 ng/ml, 40 ng/ml, 20 ng/ml, and 10 ng/ml. Vorinostat, rapamycin, and etoposide (LC Laboratories), as well as thalidomide (Sigma), were used at doses ranging from 2 mM to 100 nM. Freshly prepared verapamil (Sigma) was added at 100 μM where indicated. Trichloroacetic acid fixation and sulforhodamine B (SRB) staining was performed as described  as a surrogate cell count measurement. EC50 was defined as the drug concentration causing a 50% reduction in net signal versus untreated controls as interpolated from line of best fit. An EC50 was calculated for each individual experiment (n = 5) and Student’s t-test was used to compare EC50 from doxorubicin only treatments to verapamil (100 μM) plus doxorubicin.
Molecular-guided therapy predictions
Top 3 drugs indicated by personalized medicine analysis for MPNST and neurofibroma samples
MPNST-derived cell lines
MMP2, MMP14, TIMP2
ABL1, FYN, KIT
KDR, FLT1, PDGFRB
KDR, FLT1, PDGFRB
KDR, FLT1, PDGFRB
Benign neurofibroma samples
As expected, TOP2A overexpression is observed in nearly all MPNST and MPNST-derived samples, favoring doxorubicin and other TOP2A inhibitors based on drug target expression (Figure 1B). Variable expression of other drug-targetable pathways is also observed, including mTOR (rapamycin). In several samples, high ABCC1 expression is apparent (Figure 1B) and is highlighted by the molecular-guided therapy analysis as a hypothetical doxorubicin resistance mechanism. TYMS overexpression, also observed, has been shown by others to correlate with doxorubicin resistance phenotypes as well [43, 44]. Re-analysis of the published  microarray dataset confirms that ABCC1 is the most highly expressed ABC transporter significantly elevated in MPNSTs relative to benign plexiform neurofibromas (Additional file 5). Other members of the ABCC family are also elevated in the MPNSTs as a group, including ABCC3, ABCC4, and ABCC6.
Function and expression of ABC transporters in vitro
Microarray analysis of drug transport gene expression
Our results demonstrate that molecular-guided therapy predictions can be used to identify systematic patterns of drug resistance in MPNSTs based on analysis of human MPNST samples when compared to benign neurofibroma precursors. Significant molecular heterogeneity amongst MPNSTs is observed, and the functional consequences of this are examined in vitro. ABCC transporters are highly overexpressed in some samples, and transporter activity appears to play a modest but significant role in decreasing doxorubicin effectiveness in this subset of cultured MPNST-derived cells. Although transporter inhibitors have not yet shown clinical utility [46, 47], new agents targeting this important resistance mechanism are currently under investigation .
Considering only the list of current FDA approved drugs, however, we have also identified alternative therapeutics that may be effective in these drug-resistant patients using our molecular-guided therapy analysis. This analysis synthesizes biomarker, network, and drug target based predictions for each individual tumor sample by comparing the tumor to benign controls. The top three drugs predicted for each cell line and tumor studied are listed in Table 1. The top four alternative therapeutics for the doxorubicin-insensitive NF02.2 cell line were vorinostat, etoposide/teniposide, sirolimus, and lenalidomide. However, many previous studies have demonstrated cross-resistance to doxorubicin and etoposide or teniposide, so these are likely not meaningful alternatives in doxorubicin-refractory tumors [49–51]. Vorinostat, an HDAC inhibitor, is suggested for use in NF02.2 cells based on drug response signature, network target activity (including elevation of HDAC1, 2, 3, and 6), and drug target expression (elevated HDAC2) evidence. Sirolimus (rapamycin) is suggested due to elevated drug target (mTOR) expression and pathway signaling. Elevated mTOR activity has been observed previously in MPNSTs and neurofibromas and is currently the subject of multiple clinical trials (NCT00634270, NCT01661283, NCT00652990) [52, 53]. Lenalidomide, a derivative of thalidomide, was suggested for use based on elevated PTGS2 and TNF expression (see Additional file 2) [54–56].
Additionally, we examined the efficacy of these predicted therapeutics in NF02.2 cells in vitro. Our results demonstrate efficacy at low μM concentrations for rapamycin (Sirolimus) [1.63 μM ± 0.26] and vorinostat [2.57 μM ± 0.88]. EC50 values for etoposide [16.2 μM ± 5.92] and thalidomide [34.72 μM ± 25.13] are relatively higher (n = 4; one representative experiment is shown in Figure 4H), but deserve further examination in combination with cytotoxic agents.
Notably, drug transport expression is highly variable between MPNSTs and does not fully account for the observed therapy resistance. Our additional analysis highlighted DNA damage repair gene expression as a possible chemotherapy resistance mechanism. DNA damage repair pathways are significantly elevated in MPNSTs as a group. This implies an elevated resistance to DNA damaging cytotoxic chemotherapy agents, including doxorubicin, and consideration should be made to routinely include elevation in DNA damage repair pathway gene expression in future molecular-guided therapy prediction analyses.
Here, we provide evidence that the impact of patient heterogeneity and drug transporter expression must be considered in the selection of alternative treatment strategies for treatment refractory MPNST patients. We also confirm that PMED-predicted therapies have potential activity against MPNSTs. Future studies should focus on validating individualized drug predictions in vivo, improving identification of effective drug combinations, and expanding strategies to leverage PMED tools in discovery-level research.
Availability of supporting data
Microarray data for this study are deposited with the GEO repository: GSE50208.
Malignant peripheral nerve sheath tumor
Neurofibromatosis type 1
Quantitative real-time polymerase chain reaction
Phosphate buffered saline
American type culture collection
Drug concentration causing a 50% reduction in net signal (cell content) versus untreated controls.
We thank Marcy Ross for assistance with tissue banking logistics and Dr. Dominic Pelle for critical review of the manuscript. We also thank the Jay and Betty Van Andel Foundation and Neurofibromatosis Michigan for financial support of this work.
- Evans DGR, Baser ME, McGaughran J, Sharif S, Howard E, Moran A: Malignant peripheral nerve sheath tumours in neurofibromatosis 1. J Med Genet. 2002, 39: 311-314. 10.1136/jmg.39.5.311.PubMed CentralView ArticlePubMedGoogle Scholar
- Ducatman BS SB, Piepgras DG, Reiman HM, Ilstrup DM: Malignant peripheral nerve sheath tumors. a clinicopathologic study of 120 cases. Cancer. 1986, 57: 2006-2021. 10.1002/1097-0142(19860515)57:10<2006::AID-CNCR2820571022>3.0.CO;2-6.View ArticlePubMedGoogle Scholar
- Ingham S, Huson SM, Moran A, Wylie J, Leahy M, Evans DGR: Malignant peripheral nerve sheath tumours in NF1: improved survival in women and in recent years. Eur J Cancer. 2011, 47: 2723-2728. 10.1016/j.ejca.2011.05.031.View ArticlePubMedGoogle Scholar
- Slomiany MG, Dai L, Bomar PA, Knackstedt TJ, Kranc DA, Tolliver L, Maria BL, Toole BP: Abrogating drug resistance in malignant peripheral nerve sheath tumors by disrupting hyaluronan-CD44 interactions with small hyaluronan oligosaccharides. Cancer Res. 2009, 69: 4992-4998. 10.1158/0008-5472.CAN-09-0143.PubMed CentralView ArticlePubMedGoogle Scholar
- Ho-Jin P, Su-Jin L, Young Bae S, Hyun-Seok J, JaeHo H, Young-Bae K, Hyunee Y, Jeong S-Y: NF1 deficiency causes Bcl-xL upregulation in Schwann cells derived from neurofibromatosis type 1-associated malignant peripheral nerve sheath tumors. Int J Oncol. 2012, 42: 657-666.Google Scholar
- Suto RAY, Lee YH, Ueyama Y, Yamazaki H, Kijima H, Hiraoka N, Fukuda H, Tamaoki N, Nakamura M: A case of malignant schwannoma with overexpression of multidrug resistance gene (MDR1) after chemotherapy. Anticancer Res. 1997, 17: 2273-2277.PubMedGoogle Scholar
- Komdeur R, Plaat BEC, van der Graaf WTA, Hoekstra HJ, Hollema H, van den Berg E, Zwart N, Scheper RJ, Molenaar WM: Expression of multidrug resistance proteins, P-gp, MRP1 and LRP, in soft tissue sarcomas analysed according to their histological type and grade. Eur J Cancer. 2003, 39: 909-916. 10.1016/S0959-8049(03)00029-7.View ArticlePubMedGoogle Scholar
- Oda Y, Saito T, Tateishi N, Ohishi Y, Tamiya S, Yamamoto H, Yokoyama R, Uchiumi T, Iwamoto Y, Kuwano M, Tsuneyoshi M: ATP-binding cassette superfamily transporter gene expression in human soft tissue sarcomas. Int J Cancer. 2005, 114: 854-862. 10.1002/ijc.20589.View ArticlePubMedGoogle Scholar
- Miller SJ, Rangwala F, Williams J, Ackerman P, Kong S, Jegga AG, Kaiser S, Aronow BJ, Frahm S, Kluwe L: Large-scale molecular comparison of human schwann cells to malignant peripheral nerve sheath tumor cell lines and tissues. Cancer Res. 2006, 66: 2584-2591. 10.1158/0008-5472.CAN-05-3330.View ArticlePubMedGoogle Scholar
- Su-Jin Lee H-JP, Young-Hwa K, Bo-Young K, Hyun-Seok J, Kim HJ, Jae-Ho H, Hyunee Y, Seon-Yong J: Inhibition of Bcl-xL by ABT-737 enhances chemotherapy sensitivity in neurofibromatosis type 1-associated malignant peripheral nerve sheath tumor cells. Int J Mol Med. 2012, 30: 443-450.PubMedGoogle Scholar
- Lopez G, Torres K, Liu J, Hernandez B, Young E, Belousov R, Bolshakov S, Lazar AJ, Slopis JM, McCutcheon IE: autophagic survival in resistance to histone deacetylase inhibitors: novel strategies to treat malignant peripheral nerve sheath tumors. Cancer Res. 2011, 71: 185-196. 10.1158/0008-5472.CAN-10-2799.PubMed CentralView ArticlePubMedGoogle Scholar
- Lonning PE, Knappskog S: Mapping genetic alterations causing chemoresistance in cancer: identifying the roads by tracking the drivers. Oncogene. 2013, Advance online publication 11 March 2013; doi: 10.1038/onc.2013.48Google Scholar
- Tsioli PGPE, Giaginis C, Theocharis SE: DNA repair systems in Rhabdomyosarcoma. Histol Histopathol. 2013, 8: 971-984.Google Scholar
- Maria Papaefthymiou CG, Stamatios T: DNA repair alterations in common pediatric malignancies. Med Sci Monit. 2008, 14: 8-15.Google Scholar
- Skotheim RI, Kallioniemi A, Bjerkhagen B, Mertens F, Brekke HR, Monni O, Mousses S, Mandahl N, Sœter G, Nesland JM: Topoisomerase-IIα is upregulated in malignant peripheral nerve sheath tumors and associated with clinical outcome. J Clin Oncol. 2003, 21: 4586-4591. 10.1200/JCO.2003.07.067.View ArticlePubMedGoogle Scholar
- Levy P, Vidaud D, Leroy K, Laurendeau I, Wechsler J, Bolasco G, Parfait B, Wolkenstein P, Vidaud M, Bieche I: Molecular profiling of malignant peripheral nerve sheath tumors associated with neurofibromatosis type 1, based on large-scale real-time RT-PCR. Mol Cancer. 2004, 3: 20-10.1186/1476-4598-3-20.PubMed CentralView ArticlePubMedGoogle Scholar
- Fornari FA, Randolph JK, Yalowich JC, Ritke MK, Gewirtz DA: Interference by doxorubicin with DNA unwinding in MCF-7 breast tumor cells. Mol Pharmacol. 1994, 45: 649-656.PubMedGoogle Scholar
- Tierney JF, Stewart LA, Parmar MKB: Adjuvant chemotherapy for localised resectable soft-tissue sarcoma of adults: meta-analysis of individual data. Lancet. 1997, 350: 1647-1654.View ArticleGoogle Scholar
- Kroep JR, Ouali M, Gelderblom H, Le Cesne A, Dekker TJA, Van Glabbeke M, Hogendoorn PCW, Hohenberger P: First-line chemotherapy for malignant peripheral nerve sheath tumor (MPNST) versus other histological soft tissue sarcoma subtypes and as a prognostic factor for MPNST: an EORTC soft tissue and bone sarcoma group study. Ann Oncol. 2011, 22: 207-214. 10.1093/annonc/mdq338.PubMed CentralView ArticlePubMedGoogle Scholar
- D'Adamo DR: Appraising the current role of chemotherapy for the treatment of sarcoma. Semin Oncol. 2011, 38 (Supplement 3): S19-S29.View ArticlePubMedGoogle Scholar
- Upadhyaya M, Spurlock G, Majounie E, Griffiths S, Forrester N, Baser M, Huson SM, Gareth Evans D, Ferner R: The heterogeneous nature of germline mutations in NF1 patients with malignant peripheral serve sheath tumours (MPNSTs). Hum Mutat. 2006, 27: 716-View ArticlePubMedGoogle Scholar
- Mantripragada KK, Spurlock G, Kluwe L, Chuzhanova N, Ferner RE, Frayling IM, Dumanski JP, Guha A, Mautner V, Upadhyaya M: High-resolution DNA copy number profiling of malignant peripheral nerve sheath tumors using targeted microarray-based comparative genomic hybridization. Clin Cancer Res. 2008, 14: 1015-1024. 10.1158/1078-0432.CCR-07-1305.View ArticlePubMedGoogle Scholar
- Fishbein L, Zhang X, Fisher LB, Li H, Campbell-Thompson M, Yachnis A, Rubenstein A, Muir D, Wallace MR: In vitro studies of steroid hormones in neurofibromatosis 1 tumors and schwann cells. Mol Carcinog. 2007, 46: 512-523. 10.1002/mc.20236.View ArticlePubMedGoogle Scholar
- Kobayashi C, Oda Y, Takahira T, Izumi T, Kawaguchi K, Yamamoto H, Tamiya S, Yamada T, Iwamoto Y, Tsuneyoshi M: Aberrant expression of CHFR in malignant peripheral nerve sheath tumors. Mod Pathol. 2006, 19: 524-532. 10.1038/modpathol.3800548.View ArticlePubMedGoogle Scholar
- Mo W, Chen J, Patel A, Zhang L, Chau V, Li Y, Cho W, Lim K, Xu J, Lazar Alexander J: CXCR4/CXCL12 mediate autocrine cell- cycle progression in NF1-associated malignant peripheral nerve sheath tumors. Cell. 2013, 152: 1077-1090. 10.1016/j.cell.2013.01.053.PubMed CentralView ArticlePubMedGoogle Scholar
- Torres KE, Zhu Q-S, Bill K, Lopez G, Ghadimi MP, Xie X, Young ED, Liu J, Nguyen T, Bolshakov S: Activated MET is a molecular prognosticator and potential therapeutic target for malignant peripheral nerve sheath tumors. Clin Cancer Res. 2011, 17: 3943-3955. 10.1158/1078-0432.CCR-11-0193.PubMed CentralView ArticlePubMedGoogle Scholar
- Watanabe T, Oda Y, Tamiya S, Masuda K, Tsuneyoshi M: Malignant peripheral nerve sheath tumour arising within neurofibroma. an immunohistochemical analysis in the comparison between benign and malignant components. J Clin Pathol. 2001, 54: 631-636. 10.1136/jcp.54.8.631.PubMed CentralView ArticlePubMedGoogle Scholar
- Ottini L, Esposito DL, Richetta A, Carlesimo M, Palmirotta R, Verì MC, Battista P, Frati L, Caramia FG, Calvieri S: Alterations of microsatellites in Neurofibromas of von Recklinghausen's disease. Cancer Res. 1995, 55: 5677-5680.PubMedGoogle Scholar
- Feitsma H, Kuiper RV, Korving J, Nijman IJ, Cuppen E: Zebrafish with mutations in mismatch repair genes develop neurofibromas and other tumors. Cancer Res. 2008, 68: 5059-5066. 10.1158/0008-5472.CAN-08-0019.View ArticlePubMedGoogle Scholar
- Kobayashi C, Oda Y, Takahira T, Izumi T, Kawaguchi K, Yamamoto H, Tamiya S, Yamada T, Oda S, Tanaka K: Chromosomal aberrations and microsatellite instability of malignant peripheral nerve sheath tumors: a study of 10 tumors from nine patients. Cancer Genet Cytogenet. 2006, 165: 98-105. 10.1016/j.cancergencyto.2005.07.006.View ArticlePubMedGoogle Scholar
- Croes D, Couche F, Wodak S, van Helden J: Inferring meaningful pathways in weighted metabolic networks. J Mol Biol. 2006, 356: 222-236. 10.1016/j.jmb.2005.09.079.View ArticlePubMedGoogle Scholar
- Knox C, Law V, Jewison T, Liu P, Ly S, Frolkis A, Pon A, Banco K, Mak C, Neveu V: DrugBank 3.0: a comprehensive resource for ‘Omics’ research on drugs. Nucleic Acids Res. 2011, 39: D1035-D1041. 10.1093/nar/gkq1126.PubMed CentralView ArticlePubMedGoogle Scholar
- Nikolsky Y, Ekins S, Nikolskaya T, Bugrim A: A novel method for generation of signature networks as biomarkers from complex high throughput data. Toxicol Lett. 2005, 158: 20-29. 10.1016/j.toxlet.2005.02.004.View ArticlePubMedGoogle Scholar
- Dezso Z, Nikolsky Y, Nikolskaya T, Miller J, Cherba D, Webb C, Bugrim A: Identifying disease-specific genes based on their topological significance in protein networks. BMC Syst Biol. 2009, 3: 36-10.1186/1752-0509-3-36.PubMed CentralView ArticlePubMedGoogle Scholar
- Saulnier Sholler WF GL, Bergendahl G, Currier E, Lenox SR, Bond J, Slavik M, Roberts W, Mitchell D, Eslin D, Kraveka J, Kaplan J, Parikh N, Malempati S, Hanna G, Eugster E, Cherba D, Miller J, Webb C: A pilot trial testing the feasibility of using molecular-guided therapy in patients with recurrent neuroblastoma. J Cancer Ther. 2012, 3: 602-612. 10.4236/jct.2012.35077.View ArticleGoogle Scholar
- Miller SJ, Jessen WJ, Mehta T, Hardiman A, Sites E, Kaiser S, Jegga AG, Li H, Upadhyaya M, Giovannini M: Integrative genomic analyses of neurofibromatosis tumours identify SOX9 as a biomarker and survival gene. EMBO Mol Med. 2009, 1: 236-248. 10.1002/emmm.200900027.PubMed CentralView ArticlePubMedGoogle Scholar
- Overington JP, Al-Lazikani B, Hopkins AL: How many drug targets are there?. Nat Rev Drug Discov. 2006, 5: 993-996. 10.1038/nrd2199.View ArticlePubMedGoogle Scholar
- Furge KA, Chen J, Koeman J, Swiatek P, Dykema K, Lucin K, Kahnoski R, Yang XJ, Teh BT: Detection of DNA copy number changes and oncogenic signaling abnormalities from gene expression data reveals MYC activation in high-grade papillary renal cell carcinoma. Cancer Res. 2007, 67: 3171-3176. 10.1158/0008-5472.CAN-06-4571.View ArticlePubMedGoogle Scholar
- Lamb J, Crawford ED, Peck D, Modell JW, Blat IC, Wrobel MJ, Lerner J, Brunet JP, Subramanian A, Ross KN: The connectivity map: using gene-expression signatures to connect small molecules, genes, and disease. Sci. 2006, 313: 1929-1935. 10.1126/science.1132939.View ArticleGoogle Scholar
- Von Hoff DD, Stephenson JJ, Rosen P, Loesch DM, Borad MJ, Anthony S, Jameson G, Brown S, Cantafio N, Richards DA: Pilot study using molecular profiling of patients' tumors to find potential targets and select treatments for their refractory cancers. J Clin Oncol. 2010, 28: 4877-4883. 10.1200/JCO.2009.26.5983.View ArticlePubMedGoogle Scholar
- Muir D, Neubauer D, Lim IT, Yachnis AT, Wallace MR: Tumorigenic properties of neurofibromin-deficient neurofibroma Schwann cells. Am J Pathol. 2001, 158: 501-513. 10.1016/S0002-9440(10)63992-2.PubMed CentralView ArticlePubMedGoogle Scholar
- Skehan P, Storeng R, Scudiero D, Monks A, McMahon J, Vistica D, Warren JT, Bokesch H, Kenney S, Boyd MR: New colorimetric cytotoxicity assay for anticancer-drug screening. J Natl Cancer Inst. 1990, 82: 1107-1112. 10.1093/jnci/82.13.1107.View ArticlePubMedGoogle Scholar
- Volm M, Mattern J: Elevated expression of thymidylate synthase in doxorubicin resistant human non small cell lung carcinomas. Anticancer Res. 1992, 12: 2293-2296.PubMedGoogle Scholar
- Chekhun VF, Kulik GI, Yurchenko OV, Tryndyak VP, Todor IN, Luniv LS, Tregubova NA, Pryzimirska TV, Montgomery B, Rusetskaya NV, Pogribny IP: Role of DNA hypomethylation in the development of the resistance to doxorubicin in human MCF-7 breast adenocarcinoma cells. Cancer Lett. 2006, 231: 87-93. 10.1016/j.canlet.2005.01.038.View ArticlePubMedGoogle Scholar
- Fieber LA, González DM, Wallace MR, Muir D: Delayed rectifier K currents in NF1 Schwann cells: pharmacological block inhibits proliferation. Neurobiol Dis. 2003, 13: 136-146. 10.1016/S0969-9961(03)00031-7.View ArticlePubMedGoogle Scholar
- Choi Y, Yu A: ABC transporters in multidrug resistance and pharmacokinetics, and strategies for drug development. Curr Pharm Des. in press
- Binkhathlan Z, Lavasanifar A: P-glycoprotein inhibition as a therapeutic approach for overcoming multidrug resistance in cancer: current status and future perspectives. Curr Cancer Drug Targets. 2013, 13: 326-346. 10.2174/15680096113139990076.View ArticlePubMedGoogle Scholar
- Falasca M, Linton KJ: Investigational ABC transporter inhibitors. Expert Opin Investig Drugs. 2012, 21: 657-666. 10.1517/13543784.2012.679339.View ArticlePubMedGoogle Scholar
- Cole SPC, Sparks KE, Fraser K, Loe DW, Grant CE, Wilson GM, Deeley RG: Pharmacological characterization of multidrug resistant MRP-transfected human tumor cells. Cancer Res. 1994, 54: 5902-5910.PubMedGoogle Scholar
- Slovak ML, Hoeltge GA, Dalton WS, Trent JM: Pharmacological and biological evidence for differing mechanisms of doxorubicin resistance in two human tumor cell lines. Cancer Res. 1988, 48: 2793-2797.PubMedGoogle Scholar
- Long BH, Wang L, Lorico A, Wang RCC, Brattain MG, Casazza AM: Mechanisms of resistance to etoposide and teniposide in acquired resistant human colon and lung carcinoma cell lines. Cancer Res. 1991, 51: 5275-5283.PubMedGoogle Scholar
- Brems H, Beert E, de Ravel T, Legius E: Mechanisms in the pathogenesis of malignant tumours in neurofibromatosis type 1. Lancet Oncol. 2009, 10: 508-515. 10.1016/S1470-2045(09)70033-6.View ArticlePubMedGoogle Scholar
- Johannessen CM, Reczek EE, James MF, Brems H, Legius E, Cichowski K: The NF1 tumor suppressor critically regulates TSC2 and mTOR. Proc Natl Acad Sci U S A. 2005, 102: 8573-8578. 10.1073/pnas.0503224102.PubMed CentralView ArticlePubMedGoogle Scholar
- Zeldis JB, Schafer PH, Bennett BL, Mercurio F, Stirling DI: Potential new therapeutics for Waldenstrom's macroglobulinemia. Semin Oncol. 2003, 30: 275-281. 10.1053/sonc.2003.50078.View ArticlePubMedGoogle Scholar
- Melchert M, List A: The thalidomide saga. Int J Biochem Cell Biol. 2007, 39: 1489-1499. 10.1016/j.biocel.2007.01.022.View ArticlePubMedGoogle Scholar
- Payvandi F, Wu L, Haley M, Schafer PH, Zhang L-H, Chen RS, Muller GW, Stirling DI: Immunomodulatory drugs inhibit expression of cyclooxygenase-2 from TNF-α, IL-1β, and LPS-stimulated human PBMC in a partially IL-10-dependent manner. Cell Immunol. 2004, 230: 81-88. 10.1016/j.cellimm.2004.09.003.View ArticlePubMedGoogle Scholar
This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.