Imatinib in myeloid/lymphoid neoplasms with eosinophilia and rearrangement of PDGFRB in chronic or blast phase.

We evaluated clinical characteristics and outcome on imatinib of 22 patients with myeloid/lymphoid neoplasms with eosinophilia and rearrangement of PDGFRB. Median age was 49 years (range 20-80), 91% were male. Fifteen different PDGFRB fusion genes were identified. Eosinophilia was absent in 4/19 (21%) cases and only 11/19 (58%) cases had eosinophils ≥1.5×109/L. On imatinib, 17/17 (100%) patients in chronic phase achieved complete hematologic remission after median 2 months (range 0-13)​. Complete cytogenetic remission and/or complete molecular remission by RT-PCR were achieved in 12/13 (92%) and 12/14 patients (86%) after median 10 (range 3-34) and 19 months (range 7-110), respectively. In patients with blast phase (myeloid, n = 2; lymphoid, n = 3), treatment included combinations of imatinib (n = 5), intensive chemotherapy (n = 3), and/or allogeneic stem cell transplantation (n = 3). All 3 transplanted patients (complex karyotype, n = 2) experienced early relapse. Initially, patients were treated with imatinib 400 mg/day (n = 15) or 100 mg/day (n = 7), the dose was reduced from 400 mg/day to 100 mg/day during follow-up in 9 patients. After a median treatment of 71 months (range 1-135), the 5-year survival rate was 83%; 4/22 (18%) patients died (chronic phase; n = 2; blast phase, n = 2) due to progression (n = 3) or comorbidity while in remission (n = 1). Of note, 3/4 patients had a complex karyotype. In summary, the most important characteristics of myeloid/lymphoid neoplasms with rearrangement of PDGFRB include (a) male predominance, (b) frequent lack of hypereosinophilia,

Fusion of PDGFRB to MPRIP, CPSF6, and GOLGB1 in three patients with eosinophilia-associated myeloproliferative neoplasms.

In eosinophilia-associated myeloproliferative neoplasms (MPN-eo), constitutive activation of protein tyrosine kinases (TK) as consequence of translocations, inversions, or insertions and creation of TK fusion genes is recurrently observed. The most commonly involved TK and their potential TK inhibitors include PDGFRA at 4q12 or PDGFRB at 5q33 (imatinib), FGFR1 at 8p11 (ponatinib), and JAK2 at 9p24 (ruxolitinib). We here report the identification of three new PDGFRB fusion genes in three male MPN-eo patients: MPRIP-PDGFRB in a case with t(5;17)(q33;p11), CPSF6-PDGFRB in a case with t(5;12)(q33;q15), and GOLGB1-PDGFRB in a case with t(3;5)(q13;q33). The fusion proteins identified by 5'-rapid amplification of cDNA ends polymerase chain reaction (PCR) or DNA-based long distance inverse PCR are predicted to contain the TK domain of PDGFRB. The partner genes contain domains like coiled-coil structures, which are likely to cause dimerization and activation of the TK. In all patients, imatinib induced rapid and durable complete remissions.

Plasma proteomic profiling of pediatric osteosarcoma.

The development of a sensitive, specific, and non-invasive approach for cancer detection will facilitate early detection and, hence, improve the outcome of individuals with known cancer predispositions. Proteomic profiling of blood emerges to be a logical choice of such non-invasive or minimal invasive detection. However, plasma biomarker discovery of pediatric cancers lags behind that of adult cancers, suggesting more efforts are needed in this area. In this study, we used surface-enhanced laser desorption/ionization-time of flight mass spectrometry to profile plasma proteome in osteosarcoma patients. Osteosarcoma is a bone cancer that affects many children and young adults. We have shown that the plasma proteome contains a unique cancer signature that can distinguish patients with osteosarcoma from those with a benign bone disease. To improve cancer biomarker discovery in plasma, we have also shown that depletion of two highly abundant plasma proteins increases the detection sensitivity of lower-abundance proteins. The combination of depletion and proteomic profiling may increase the chance of identifying tumor-derived proteins within the plasma of pediatric cancer patients.

An integrated proteomic approach to identifying circulating biomarkers in high-risk neuroblastoma and their potential in relapse monitoring.

PURPOSE: Despite intensive treatment regimens, overall survival for high-risk neuroblastoma (HRNB) is still poor. This is in part due to an inability to cure the disease once a patient has reached clinical relapse. Identifying plasma biomarkers of active disease may provide a way of relapse monitoring in HRNB. EXPERIMENTAL DESIGN: In this study, we developed an integrated proteomic approach to identify plasma biomarkers for HRNB. RESULTS: We identified seven candidate biomarkers (SAA, APOA1, IL-6, EGF, MDC, sCD40L and Eotaxin) for HRNB. These biomarkers were then used to create a multivariate classifier of HRNB, which showed a specificity of 90% (95% confidence interval (CI), 73%, 98%), and a sensitivity of 81% (95%CI, 54%, 96%) for classifying HRNB in a training set. When evaluated on independent test samples, the classifier exhibited 86% accuracy (95% CI, 42%, 100%) of identifying diagnostic samples, and 86% accuracy (95% CI, 70%, 100%) of detecting post-diagnosis longitudinal samples that having active disease. CONCLUSION AND CLINICAL RELEVANCE: Further validation of these biomarkers may improve patients' outcomes by developing a simple blood test for the detection of relapse prior to the development of clinically evident disease. Understanding the role of these biomarkers in immune surveillance of neuroblastoma may also provide a new direction of therapeutic strategies.

Plasma proteome predicts chemotherapy response in osteosarcoma patients.

Osteosarcoma is the most common malignant bone tumor that affects hundreds of children and young adults every year. The major prognostic factor in patients with localized osteosarcoma is the development of resistance towards pre-operative chemotherapy. However, modifications of post-operative chemotherapy based on the histological response have not significantly improved the outcome of patients. Thus, it would be of tremendous clinical value if the poor responders could be identified at the time of diagnosis, so that ineffective therapy can be prevented and intensified or alternative therapy could be provided to improve their outcome. We hypothesized that plasma proteomic profiles could be used to distinguish good from poor responders prior to the start of treatment. In order to test this hypothesis, we analyzed the proteomic profiles in two sets of plasma samples (n=54) from osteosarcoma patients collected before (n=27) and after (n=27) pre-operative chemotherapy. Using a linear support vector machine algorithm and external leave-one-out cross validation, we developed two classifiers that classified good and poor responders with an equal accuracy of 85% (p<0.01 after 5000 permutations) in both sets of plasma samples. In order to understand the biological basis of the classifiers, we further identified and validated two plasma proteins, serum amyloid protein A and transthyretin, in the classifiers. Our results suggest that plasma proteomic profiles can predict chemotherapy response before treatment as accurately as after treatment. Our study could lead to the development of a simple blood test that can predict chemotherapy response in osteosarcoma patients. Since the two identified proteins are involved in innate immunity, our findings are corroborated by the notion that boosting the innate immunity in conjunction with chemotherapy, achieves a better anti-tumor activity, thus improving the overall survival of osteosarcoma patients.

Identification of a plasma proteomic signature to distinguish pediatric osteosarcoma from benign osteochondroma.

Osteosarcoma (OS) is the most common malignant bone tumor in children. To identify a plasma proteomic signature that can detect OS, we used SELDI MS to perform proteomic profiling on plasma specimens from 29 OS and 20 age-matched osteochondroma (OC) patients. Nineteen statistically significant ion peaks that were differentially expressed in OS when compared with OC patients were identified (p < 0.001 and false discovery rate < 10%). Using the proteomic profiles, we constructed a multivariate 3-nearest neighbors classifier to distinguish OS from OC patients with a sensitivity of 97% and a specificity of 80% based on external leave-one-out crossvalidation. Permutation test showed that the classification result was statistically significant (p < 0.00005). One of the proteins (m/z 11 704) in the proteomic signature was identified as serum amyloid protein A (SAA) by PMF. The higher plasma level of SAA in OS patients was further validated by Western blotting when compared to that of osteochrondroma patients and normal subjects as reference. The classifier based on this plasma proteomic signature may be useful to differentiate malignant bone cancer from benign bone tumors and for early detection of OS in high-risk individuals.

Optimising the use of TRIzol-extracted proteins in surface enhanced laser desorption/ ionization (SELDI) analysis.

BACKGROUND: Research with clinical specimens is always hampered by the limited availability of relevant samples, necessitating the use of a single sample for multiple assays. TRIzol is a common reagent for RNA extraction, but DNA and protein fractions can also be used for other studies. However, little is known about using TRIzol-extracted proteins in proteomic research, partly because proteins extracted from TRIzol are very resistant to solubilization. RESULTS: To facilitate the use of TRIzol-extracted proteins, we first compared the ability of four different common solubilizing reagents to solubilize the TRIzol-extracted proteins from an osteosarcoma cell line, U2-OS. Then we analyzed the solubilized proteins by Surface Enhanced Laser Desorption/Ionization technique (SELDI). The results showed that solubilization of TRIzol-extracted proteins with 9.5 M Urea and 2% CHAPS ([3-[(3-cholamidopropyl)-dimethylammonio]propanesulfonate]) (UREA-CHAPS) was significantly better than the standard 1% SDS in terms of solubilization efficiency and the number of detectable ion peaks. Using three different types of SELDI arrays (CM10, H50, and IMAC-Cu), we demonstrated that peak detection with proteins solubilized by UREA-CHAPS was reproducible (r > 0.9). Further SELDI analysis indicated that the number of ion peaks detected in TRIzol-extracted proteins was comparable to a direct extraction method, suggesting many proteins still remain in the TRIzol protein fraction. CONCLUSION: Our results suggest that UREA-CHAPS performed very well in solubilizing TRIzol-extracted proteins for SELDI applications. Protein fractions left over after TRIzol RNA extraction could be a valuable but neglected source for proteomic or biochemical analysis when additional samples are not available.

Differential protein expression profiles of gastric epithelial cells following Helicobacter pylori infection using ProteinChips.

Helicobacter pylori infects approximately half of the world's population and the bacterium is associated with gastric cancer and peptic and duodenal ulcers. In this study, Surface Enhanced Laser Desorption /Ionization time-of-flight mass spectrometry (SELDI-TOF-MS) was used to identify the biomarkers from H. pylori infected gastric epithelial cells (GEC) to understand key mechanisms associated with pathogenesis. Using different chip surfaces, differential protein expression profile of GEC was obtained and several upregulated or downregulated biomarkers were detected on GEC, following H. pylori infection. Four different H. pylori infected GECs were compared based on their expression of MHC class II, a receptor reported to trigger apoptosis. One biomarker was identified in H. pylori infected GEC as Annexin A2 (Annexin II) from the flow through of the anion-exchange resin. The increased expression of Annexin II in GEC following H. pylori infection was further confirmed by Western Blot analyses and indicates its involvement in H. pylori pathogenesis.