Ajia Town

Bio: Ajia Town is an academic researcher from Oregon Health & Science University. The author has contributed to research in topics: Imatinib mesylate & PDGFRA. The author has an hindex of 14, co-authored 17 publications receiving 6292 citations. Previous affiliations of Ajia Town include Veterans Health Administration & United States Department of Veterans Affairs.

PDGFRA Activating Mutations in Gastrointestinal Stromal Tumors

Abstract: Most gastrointestinal stromal tumors (GISTs) have activating mutations in the KIT receptor tyrosine kinase, and most patients with GISTs respond well to Gleevec, which inhibits KIT kinase activity. Here we show that approximately 35% (14 of 40) of GISTs lacking KIT mutations have intragenic activation mutations in the related receptor tyrosine kinase, platelet-derived growth factor receptor alpha (PDGFRA). Tumors expressing KIT or PDGFRA oncoproteins were indistinguishable with respect to activation of downstream signaling intermediates and cytogenetic changes associated with tumor progression. Thus, KIT and PDGFRA mutations appear to be alternative and mutually exclusive oncogenic mechanisms in GISTs.

PDGFRA Mutations in Gastrointestinal Stromal Tumors: Frequency, Spectrum and In Vitro Sensitivity to Imatinib

Abstract: Purpose Gastrointestinal stromal tumors (GISTs) commonly harbor oncogenic mutations of the KIT tyrosine kinase, which is a target for the kinase inhibitor imatinib. A subset of GISTs, however, contains mutations in the homologous kinase platelet derived growth factor receptor alpha (PDGFRA), and the most common of these mutations is resistant to imatinib in vitro. Little is known of the other types of PDGFRA mutations that occur in GISTs. Materials and Methods We determined the KIT and PDGFRA mutation status of 1,105 unique GISTs using a combination of denaturing high-performance liquid chromatography and direct sequencing. Results There were 80 tumors (7.2%) with a PDGFRA mutation: 66 in exon 18, 11 in exon 12, and three in exon 14. Transient expression of representative PDGFRA isoforms in CHO cells revealed imatinib sensitivity of exon 12 mutations (SPDHE566-571R and insertion ER561-562) and an exon 14 substitution (N659K). However, most isoforms with a substitution involving codon D842 in exon 18 (D842...

Primary and Secondary Kinase Genotypes Correlate With the Biological and Clinical Activity of Sunitinib in Imatinib-Resistant Gastrointestinal Stromal Tumor

Abstract: Purpose Most gastrointestinal stromal tumors (GISTs) harbor mutant KIT or platelet-derived growth factor receptor α (PDGFRA) kinases, which are imatinib targets. Sunitinib, which targets KIT, PDGFRs, and several other kinases, has demonstrated efficacy in patients with GIST after they experience imatinib failure. We evaluated the impact of primary and secondary kinase genotype on sunitinib activity. Patients and Methods Tumor responses were assessed radiologically in a phase I/II trial of sunitinib in 97 patients with metastatic, imatinib-resistant/intolerant GIST. KIT/PDGFRA mutational status was determined for 78 patients by using tumor specimens obtained before and after prior imatinib therapy. Kinase mutants were biochemically profiled for sunitinib and imatinib sensitivity. Results Clinical benefit (partial response or stable disease for ≥ 6 months) with sunitinib was observed for the three most common primary GIST genotypes: KIT exon 9 (58%), KIT exon 11 (34%), and wild-type KIT/PDGFRA (56%). Progre...

KIT Gene Mutations and Copy Number in Melanoma Subtypes

Abstract: Purpose: We recently identified a KIT exon 11 mutation in an anorectal melanoma of a patient who had an excellent response to treatment with imatinib. To determine the frequency of KIT mutations across melanoma subtypes, we surveyed a large series of tumors. Experimental Design: One hundred eighty-nine melanomas were screened for mutations in KIT exons 11, 13, and 17. KIT copy number was assessed by quantitative PCR. A subset of cases was evaluated for BRAF and NRAS mutations. Immunohistochemistry was done to assess KIT (CD117) expression. Results: KIT mutations were detected in 23% (3 of 13) of acral melanomas, 15.6% (7 of 45) of mucosal melanomas, 7.7% (1 of 13) of conjunctival melanomas, 1.7% (1 of 58) of cutaneous melanomas, and 0% (0 of 60) of choroidal melanomas. Almost all the KIT mutations were of the type predicted to be imatinib sensitive. There was no overlap with NRAS mutations (11.1% of acral and 24.3% of mucosal tumors) or with BRAF mutations (absent in mucosal tumors). Increased KIT copy number was detected in 27.3% (3 of 11) of acral and 26.3% (10 of 38) of mucosal melanomas, but was less common among cutaneous (6.7%; 3 of 45), conjunctival (7.1%; 1 of 14), and choroidal melanomas (0 of 28). CD117 expression, present in 39% of 105 tumors representing all melanoma types, did not correlate with either KIT mutation status or KIT copy number. Conclusions: Our findings confirm that KIT mutations are most common in acral and mucosal melanomas but do not necessarily correlate with KIT copy number or CD117 expression. Screening for KIT mutations may open up new treatment options for melanoma patients.

Sunitinib versus interferon alfa in metastatic renal-cell carcinoma.

Abstract: Background Since sunitinib malate has shown activity in two uncontrolled studies in patients with metastatic renal-cell carcinoma, a comparison of the drug with interferon alfa in a phase 3 trial is warranted. Methods We enrolled 750 patients with previously untreated, metastatic renal-cell carcinoma in a multicenter, randomized, phase 3 trial to receive either repeated 6-week cycles of sunitinib (at a dose of 50 mg given orally once daily for 4 weeks, followed by 2 weeks without treatment) or interferon alfa (at a dose of 9 MU given subcutaneously three times weekly). The primary end point was progression-free survival. Secondary end points included the objective response rate, overall survival, patient-reported outcomes, and safety. Results The median progression-free survival was significantly longer in the sunitinib group (11 months) than in the interferon alfa group (5 months), corresponding to a hazard ratio of 0.42 (95% confidence interval, 0.32 to 0.54; P<0.001). Sunitinib was also associated with a higher objective response rate than was interferon alfa (31% vs. 6%, P<0.001). The proportion of patients with grade 3 or 4 treatment-related fatigue was significantly higher in the group treated with interferon alfa, whereas diarrhea was more frequent in the sunitinib group (P<0.05). Patients in the sunitinib group reported a significantly better quality of life than did patients in the interferon alfa group (P<0.001). Conclusions Progression-free survival was longer and response rates were higher in patients with metastatic renal-cell cancer who received sunitinib than in those receiving interferon alfa (ClinicalTrials.gov numbers, NCT00098657 and NCT00083889).

Theoretical Basis, Experimental Design, and Computerized Simulation of Synergism and Antagonism in Drug Combination Studies

Abstract: The median-effect equation derived from the mass-action law principle at equilibrium-steady state via mathematical induction and deduction for different reaction sequences and mechanisms and different types of inhibition has been shown to be the unified theory for the Michaelis-Menten equation, Hill equation, Henderson-Hasselbalch equation, and Scatchard equation. It is shown that dose and effect are interchangeable via defined parameters. This general equation for the single drug effect has been extended to the multiple drug effect equation for n drugs. These equations provide the theoretical basis for the combination index (CI)-isobologram equation that allows quantitative determination of drug interactions, where CI 1 indicate synergism, additive effect, and antagonism, respectively. Based on these algorithms, computer software has been developed to allow automated simulation of synergism and antagonism at all dose or effect levels. It displays the dose-effect curve, median-effect plot, combination index plot, isobologram, dose-reduction index plot, and polygonogram for in vitro or in vivo studies. This theoretical development, experimental design, and computerized data analysis have facilitated dose-effect analysis for single drug evaluation or carcinogen and radiation risk assessment, as well as for drug or other entity combinations in a vast field of disciplines of biomedical sciences. In this review, selected examples of applications are given, and step-by-step examples of experimental designs and real data analysis are also illustrated. The merging of the mass-action law principle with mathematical induction-deduction has been proven to be a unique and effective scientific method for general theory development. The median-effect principle and its mass-action law based computer software are gaining increased applications in biomedical sciences, from how to effectively evaluate a single compound or entity to how to beneficially use multiple drugs or modalities in combination therapies.

A census of human cancer genes

Abstract: A central aim of cancer research has been to identify the mutated genes that are causally implicated in oncogenesis ('cancer genes'). After two decades of searching, how many have been identified and how do they compare to the complete gene set that has been revealed by the human genome sequence? We have conducted a 'census' of cancer genes that indicates that mutations in more than 1% of genes contribute to human cancer. The census illustrates striking features in the types of sequence alteration, cancer classes in which oncogenic mutations have been identified and protein domains that are encoded by cancer genes.

The somatic genomic landscape of glioblastoma

Abstract: We describe the landscape of somatic genomic alterations based on multidimensional and comprehensive characterization of more than 500 glioblastoma tumors (GBMs). We identify several novel mutated genes as well as complex rearrangements of signature receptors, including EGFR and PDGFRA. TERT promoter mutations are shown to correlate with elevated mRNA expression, supporting a role in telomerase reactivation. Correlative analyses confirm that the survival advantage of the proneural subtype is conferred by the G-CIMP phenotype, and MGMT DNA methylation may be a predictive biomarker for treatment response only in classical subtype GBM. Integrative analysis of genomic and proteomic profiles challenges the notion of therapeutic inhibition of a pathway as an alternative to inhibition of the target itself. These data will facilitate the discovery of therapeutic and diagnostic target candidates, the validation of research and clinical observations and the generation of unanticipated hypotheses that can advance our molecular understanding of this lethal cancer.