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  • 1
    In: Journal of Clinical Oncology, American Society of Clinical Oncology (ASCO), Vol. 41, No. 16_suppl ( 2023-06-01), p. 12129-12129
    Abstract: 12129 Background: Palliative care benefits have been widely studied in solid tumors with early palliative care demonstrating prolonged survival in several malignancies including lung and esophageal cancer. There are limited data and guidelines for use of palliative care in hematopoietic stem cell transplants (HSCT). Methods: We used the National cancer database (NCDB) to identify HSCT recipients between 2004 to 2017 and retrospectively examined the outcomes based on receipt of palliative care. Chi-square and Wilcoxon tests were used to compare categorical and continuous variables respectively. Kaplan Meier analysis and a Cox multivariable proportional hazards model were used for survival analysis using R software. The NCDB is available as de-identified data. Hence, this study was exempt from a full IRB review. Results: We identified 17,464 eligible patients with hematologic malignancies who underwent HSCT during 2004-2017. The table below shows differences in baseline characteristics in patients who received palliative care vs no palliative care and shows an improved median survival in those receiving vs those not receiving (43.5 vs 31.6 months) (p = 0.0003). Patients with median household income in the lowest quartile as per 2016 survey data were taken as low-income group. A multivariable cox regression analysis that adjusted for age, sex, Charlson-Deyo Comorbidity Index, insurance status, income and Hispanic ethnicity found that integration of palliative care was associated with improved survival outcomes (HR 0.85, CI 0.77- 0.93, p = 0.0002). Conclusions: To our knowledge, this is the largest study demonstrating improved outcomes in HSCT recipients when palliative care was incorporated despite there beingmore economically challenged patients in the group that received palliative care. Although these data are retrospective and correlational, it underscores how palliative care should be incorporated as part of national society guidelines for HSCT recipients. [Table: see text]
    Type of Medium: Online Resource
    ISSN: 0732-183X , 1527-7755
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    Language: English
    Publisher: American Society of Clinical Oncology (ASCO)
    Publication Date: 2023
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  • 2
    In: Blood, American Society of Hematology, Vol. 137, No. 8 ( 2021-02-25), p. 1050-1060
    Abstract: Bortezomib (BTZ) was recently evaluated in a randomized phase 3 clinical trial by the Children’s Oncology Group (COG) that compared standard chemotherapy (cytarabine, daunorubicin, and etoposide [ADE]) vs standard therapy with BTZ (ADEB) for de novo pediatric acute myeloid leukemia (AML). Although the study concluded that BTZ did not improve outcome overall, we examined patient subgroups benefiting from BTZ-containing chemotherapy using proteomic analyses. The proteasome inhibitor BTZ disrupts protein homeostasis and activates cytoprotective heat shock responses. Total heat shock factor 1 (HSF1) and phosphorylated HSF1 (HSF1-pSer326) were measured in leukemic cells from 483 pediatric patients using reverse phase protein arrays. HSF1-pSer326 phosphorylation was significantly lower in pediatric AML compared with CD34+ nonmalignant cells. We identified a strong correlation between HSF1-pSer326 expression and BTZ sensitivity. BTZ significantly improved outcome of patients with low-HSF1-pSer326 with a 5-year event-free survival of 44% (ADE) vs 67% for low-HSF1-pSer326 treated with ADEB (P = .019). To determine the effect of HSF1 expression on BTZ potency in vitro, cell viability with HSF1 gene variants that mimicked phosphorylated (S326A) and nonphosphorylated (S326E) HSF1-pSer326 were examined. Those with increased HSF1 phosphorylation showed clear resistance to BTZ vs those with wild-type or reduced HSF1-phosphorylation. We hypothesize that HSF1-pSer326 expression could identify patients who benefit from BTZ-containing chemotherapy.
    Type of Medium: Online Resource
    ISSN: 0006-4971 , 1528-0020
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    Language: English
    Publisher: American Society of Hematology
    Publication Date: 2021
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  • 3
    In: Blood, American Society of Hematology, Vol. 138, No. Supplement 1 ( 2021-11-05), p. 1538-1538
    Abstract: The availability of targeted therapy and improved molecular characterization of Chronic Lymphocytic Leukemia (CLL) require a re-evaluation of treatment paradigms. As CLL heterogeneity is dependent on molecular and environmental factors, there is a need to create a new classification based on the integration of several factors. Here, we accomplish this goal by identifying CLL signatures using Reverse Phase Protein Array. Protein expression for 384 total and post translationally modified proteins was assessed in 871 CLL and Mature Small B Cell Leukemia (MSBL: HCL, HCLV, LGL-T, MCL, MZL, PLL, Richter's, T-Cell PLL) patients and was integrated with clinical data to identify strategies for improving diagnostics and therapy, making this the largest CLL proteomics study to date. Proteins were categorized into 40 protein functional groups (PFGs) based on literature and intra-dataset protein correlations and patients clustered based on PFG expression patterns into 6 recurrent protein expression signatures (PES) (Figure 1A). Individual protein expression (58/384 proteins), PFG expression (32/40) and overall PES were all highly prognostic of survival (OS) and time to first or second treatment (TTFT, TTST) (Figures 1B-C). The adhesion, apoptosis-occurring, apoptosis-regulating, heat shock, histone1 (marks), histone 2 (modifiers) and the STP-regulation PFGs were prognostic for all 3 outcome measures. Notably SG-A contained most of the MSBL and 15/16 cases of hairy cell leukemia, but the CLL cases within this SG fared very poorly. For OS, groups A and C had markedly inferior survival (P & lt;0.0001) (10.3 and 20.3 median years) relative to the other 4 groups, which were statistically similar to each other. First treatment occurred sooner for Groups A and C (5.8 and 5.23 median years). Additionally, the TTST was also inferior for Group A (median 3.5 years). There were significant differences in age, hemoglobin, platelets, % BM and PB lymphocytes and β2M between the SG, but not for race (p = 0.84) or gender (p = 0.72). , Historically adverse cytogenetic aberrations del 11q and del17p events (23% overall) were less common in SG A, B, D and E (15, 14, 16, 17%) and overrepresented in SG C (32%), while historically favorable 13q changes were seen across all groups as was Trisomy 12 (14% overall), although SGs A and E were enriched (25%, 22%) while SG-F was low (5%) for Trisomy 12. SG membership superseded other traditional prognostic factors (Rai Staging, IGHV Status) and were prognostic for modern (BTK inhibition) and older CLL therapies. SGs A and C responded poorly to chemotherapy regimens compared to the other groups, whereas all groups responded well to BTK inhibitors except for SG-A. SGs and PFGs membership provided novel drug targets (see our other abstracts on TP53BP1 and ASNS) and defined optimal candidates for Watch and Wait (WaW) vs. early intervention. A model based on the accumulation of irregularities in ANXA1, TFRC, and SMAD2.p245 expression, optimally predicted TTFT overall and in early stage CLL patients. Patients with & lt; 1 negative level of either of the 3 proteins, have a median TTFT of 14.59 years, whereas patients having 2-3 have a median of 5-6.27 years (P & lt;0.0001). CHEK1.pS345, GAB2, IGFBP2, S100A4, WEE1.pS642, and ZAP70 were universally overexpressed by all SGs, suggesting them as ideal targets for inhibition. Collectively proteomics demonstrates promise for improving classification, therapy strategy determination, and identifying novel therapeutic targets. Figure 1 Figure 1. Disclosures Ferrajoli: Janssen: Other: Advisory Board ; AstraZeneca: Other: Advisory Board, Research Funding; BeiGene: Other: Advisory Board, Research Funding. Thompson: Genentech: Other: Institution: Advisory/Consultancy, Honoraria, Research Grant/Funding; Amgen: Other: Institution: Honoraria, Research Grant/Funding; Adaptive Biotechnologies: Other: Institution: Advisory/Consultancy, Honoraria, Research Grant/Funding, Expert Testimony; Pharmacyclics: Other: Institution: Advisory/Consultancy, Honoraria, Research Grant/Funding; Janssen: Consultancy, Honoraria; Gilead: Other: Institution: Advisory/Consultancy, Honoraria; AbbVie: Other: Institution: Advisory/Consultancy, Honoraria, Research Grant/Funding. Burger: Pharmacyclics LLC: Consultancy, Other: Travel/Accommodations/Expenses, Research Funding, Speakers Bureau; Beigene: Research Funding, Speakers Bureau; TG Therapeutics: Other: Travel/Accommodations/Expenses, Research Funding, Speakers Bureau; Gilead: Consultancy, Other: Travel/Accommodations/Expenses, Research Funding, Speakers Bureau; Novartis: Other: Travel/Accommodations/Expenses, Speakers Bureau; AstraZeneca: Consultancy; Janssen: Consultancy, Other: Travel/Accommodations/Expenses, Speakers Bureau. Wierda: Xencor: Research Funding; Karyopharm: Research Funding; Gilead Sciences: Research Funding; Acerta Pharma Inc.: Research Funding; Pharmacyclics LLC, an AbbVie Company: Research Funding; AstraZeneca: Research Funding; Juno Therapeutics: Research Funding; KITE Pharma: Research Funding; Sunesis: Research Funding; Miragen: Research Funding; Oncternal Therapeutics, Inc.: Research Funding; Cyclacel: Research Funding; Loxo Oncology, Inc.: Research Funding; Janssen: Research Funding; Genentech: Research Funding; GSK/Novartis: Research Funding; Genzyme Corporation: Consultancy; AbbVie: Research Funding.
    Type of Medium: Online Resource
    ISSN: 0006-4971 , 1528-0020
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    Language: English
    Publisher: American Society of Hematology
    Publication Date: 2021
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  • 4
    In: Blood, American Society of Hematology, Vol. 128, No. 22 ( 2016-12-02), p. 1975-1975
    Abstract: Background: Myelodysplastic syndromes (MDS) are heterogeneous clonally derived bone marrow disorders characterized by ineffective hematopoiesis and propensity to transform to acute myeloid leukemia. With greater than 15,000 new cases identified yearly, patients (pts) with MDS have a wide range of clinical manifestations and outcomes. Challenges in treating MDS include disease heterogeneity and a small number of effective treatments, particularly beyond first-line approaches and supportive care. Although mutational analysis of MDS provides prognostic information, the plethora of genetic events in a single case complicates using this information for guiding clinical therapy. We hypothesized that these genetic events coalesce into a finite number of protein expression signatures and that these would guide individualized therapy. Methods: A custom Reverse Phase Protein Array (RPPA) with 378 samples (including replicates) from 123 newly diagnosed and 76 relapsed/refractory MDS pts as well as 20 normal CD34+ bone marrow samples was created and probed with 136 antibodies to determine relative protein expression. To assess impact of source cell type on protein expression, 112 of the 378 samples (representing some replicates from 95 pts) had paired CD34+ and CD34+CD38- samples. Since proteins interact with each other and function within networks, proteins were first divided into 25 Protein Functional Groups (ProFnGp) based on their known functionality in the literature. Progeny clustering was then performed for each ProFnGp to determine the optimal number of protein clusters. Principal component analysis (PCA) was used to map global differences and similarities between protein clusters and normal CD34+ samples. Hierarchical clustering (HC) was performed on a compilation of all protein clusters in one binary matrix to identify recurrent protein expression signatures (PrSIG)that comprised similar combinations of protein constellations (PrCON). Associations between signature membership, clinical and molecular features, and outcome were assessed. Proteins that were universally over or under expressed and specific for a given signature were identified. Results: Clustering of pts for each ProFnGp revealed distinct relative expression and activation states compared to normal CD34+ samples. For each ProFnGp, 2 to 6 distinct expression clusters were identified, providing 110 protein clusters for HC. Of the 25 ProFnGp, all had MDS specific patterns and 19 had at least one cluster similar to normal CD34+ cells. HC revealed strong co-correlation between multiple groups of protein clusters from various ProFnGp and suggested 11 PrCON. Pts that expressed similar recurrent combinations of PrCON formed 11 PrSIG (Figure 1). Within PrSIG, no bias was observed in sample status (fresh or cryopreserved), source (peripheral blood or bone marrow), gender, or relapse status. Analysis of paired samples revealed 84% of CD34+ samples were present in separate PrSIG from corresponding CD34+CD38- samples, suggesting cases where CD34+ samples were distinct from CD34+CD38- samples. This suggests cell type should be considered in future analyses. Structured cluster memberships were identified, suggesting ProFnGp targets. The distinct cluster identified in PrCON 4 x PrSIG 1 revealed associations with ProFnGp including apoptosis, SMAD, PKC, mTOR, MEK, and Hippo pathways. Within this cluster, upregulation was identified in proteins including PKCα, PI3Kp110α, and SMAD6 and downregulation in SMAC, PKCd, SMAD1, SMAD4, TSC2, and NF2, suggesting targets for directed combination therapy with agents such as selective PKCα and PI3K inhibitors or SMAC mimetics. Overall summation of expression for each protein across each signature revealed many proteins with either significantly higher or lower expression relative to CD34+ controls. Conclusions: Analysis of protein expression levels in a network-based approach revealed classification of MDS pts into finite protein expression signatures based on the existence of recurrent protein constellations. Recognition of universal differentially expressed proteins, together with signature specific proteins, suggests targets for personalized and directed combinatorial therapeutics. Figure 1 HC based on binary ProFnGp cluster membership. Each vertical pt column consists of 25 of 110 protein clusters. Blue squares indicate positive cluster membership. Figure 1. HC based on binary ProFnGp cluster membership. Each vertical pt column consists of 25 of 110 protein clusters. Blue squares indicate positive cluster membership. Disclosures No relevant conflicts of interest to declare.
    Type of Medium: Online Resource
    ISSN: 0006-4971 , 1528-0020
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    Language: English
    Publisher: American Society of Hematology
    Publication Date: 2016
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  • 5
    In: Molecular Cancer Research, American Association for Cancer Research (AACR), Vol. 16, No. 8 ( 2018-08-01), p. 1275-1286
    Abstract: Heterogeneity in the genetic landscape of pediatric acute myeloid leukemia (AML) makes personalized medicine challenging. As genetic events are mediated by the expression and function of proteins, recognition of recurrent protein patterns could enable classification of pediatric AML patients and could reveal crucial protein dependencies. This could help to rationally select combinations of therapeutic targets. To determine whether protein expression levels could be clustered into functionally relevant groups, custom reverse-phase protein arrays were performed on pediatric AML (n = 95) and CD34+ normal bone marrow (n = 10) clinical specimens using 194 validated antibodies. To analyze proteins in the context of other proteins, all proteins were assembled into 31 protein functional groups (PFG). For each PFG, an optimal number of protein clusters was defined that represented distinct transition states. Block clustering analysis revealed strong correlations between various protein clusters and identified the existence of 12 protein constellations stratifying patients into 8 protein signatures. Signatures were correlated with therapeutic outcome, as well as certain laboratory and demographic characteristics. Comparison of acute lymphoblastic leukemia specimens from the same array and AML pediatric patient specimens demonstrated disease-specific signatures, but also identified the existence of shared constellations, suggesting joint protein deregulation between the diseases. Implication: Recognition of altered proteins in particular signatures suggests rational combinations of targets that could facilitate stratified targeted therapy. Mol Cancer Res; 16(8); 1275–86. ©2018 AACR. See related article by Hoff et al., p. 1263
    Type of Medium: Online Resource
    ISSN: 1541-7786 , 1557-3125
    Language: English
    Publisher: American Association for Cancer Research (AACR)
    Publication Date: 2018
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  • 6
    In: PROTEOMICS, Wiley, Vol. 18, No. 8 ( 2018-04)
    Abstract: Posttranslational histone tail modifications are known to play a role in leukemogenesis and are therapeutic targets. A global analysis of the level and patterns of expression of multiple histone‐modifying proteins (HMP) in acute myeloid leukemia (AML) and the effect of different patterns of expression on outcome and prognosis has not been investigated in AML patients. Here we analyzed 20 HMP by reverse phase protein array (RPPA) in a cohort of 205 newly diagnosed AML patients. Protein levels were correlated with patient and disease characteristics, including survival and mutational state. We identified different protein clusters characterized by higher ( more on) or lower ( more off) expression of HMP, relative to normal CD34+ cells. On state of HMP was associated with poorer outcome compared to normal ‐like and a more off state. FLT3 mutated AML patients were significantly overrepresented in the more on state. DNA methylation related mutations showed no correlation with the different HMP states. In this study, we demonstrate for the first time that HMP form recurrent patterns of expression and that these significantly correlate with survival in newly diagnosed AML patients.
    Type of Medium: Online Resource
    ISSN: 1615-9853 , 1615-9861
    URL: Issue
    Language: English
    Publisher: Wiley
    Publication Date: 2018
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    SSG: 12
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  • 7
    In: Leukemia, Springer Science and Business Media LLC, Vol. 36, No. 3 ( 2022-03), p. 712-722
    Type of Medium: Online Resource
    ISSN: 0887-6924 , 1476-5551
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    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2022
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  • 8
    In: Haematologica, Ferrata Storti Foundation (Haematologica), Vol. 107, No. 10 ( 2022-01-13), p. 2329-2343
    Abstract: Pediatric acute myeloid leukemia (AML) remains a fatal disease for at least 30% of patients, stressing the need for improved therapies and better risk stratification. As proteins are the unifying feature of (epi)genetic and environmental alterations, and are often targeted by novel chemotherapeutic agents, we studied the proteomic landscape of pediatric AML. Protein expression and activation levels were measured in 500 bulk leukemic patients’ samples and 30 control CD34+ cell samples, using reverse phase protein arrays with 296 strictly validated antibodies. The multistep MetaGalaxy analysis methodology was applied and identified nine protein expression signatures (PrSIG), based on strong recurrent protein expression patterns. PrSIG were associated with cytogenetics and mutational state, and with favorable or unfavorable prognosis. Analysis based on treatment (i.e., ADE vs. ADE plus bortezomib) identified three PrSIG that did better with ADE plus bortezomib than with ADE alone. When PrSIG were studied in the context of cytogenetic risk groups, PrSIG were independently prognostic after multivariate analysis, suggesting a potential value for proteomics in combination with current classification systems. Proteins with universally increased (n=7) or decreased (n=17) expression were observed across PrSIG. Certain proteins significantly differentially expressed from normal could be identified, forming a hypothetical platform for personalized medicine.
    Type of Medium: Online Resource
    ISSN: 1592-8721 , 0390-6078
    Language: Unknown
    Publisher: Ferrata Storti Foundation (Haematologica)
    Publication Date: 2022
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  • 9
    In: Blood, American Society of Hematology, Vol. 132, No. Supplement 1 ( 2018-11-29), p. 2761-2761
    Abstract: Background: Dysregulation of histone modifying marks and their modulators leads to aberrant gene expression and could contribute to leukemogenesis via misregulation of gene transcription of tumor suppressor genes and oncogenes. Although understanding of the role of the epigenome in cancer has expanded greatly, until recently there has not been a comprehensive characterization of protein expression patterns for multiple histone modifications, histone modification-related proteins (HistModProt), or their association with clinical characteristics in AML. We recently demonstrated that adult AML HistModProt form recurrent patterns of expression that predict prognosis (van Dijk et al. 2018). We now seek to determine whether HistModProt expression can predict prognosis in pediatric AML. Methods: We simultaneously analyzed expression of 7 histone modification marks (H3 core protein, H3K4me2 (2 antibodies), H3K4me3, H3K9me2, H3K27me3, H3K36me3) and 17 HistModProt (ASH2L, BMI1, BRD4, NCL, CLPP, HDAC1, HDAC2, HDAC3, HDAC6, hnRNPK, JMJD6, KDM1A, NPM1 (2 antibodies), SIRT1, SIRT6, WTAP) in 505 de novo pediatric AML patients by the reverse phase protein array (RPPA) methodology. Expression was compared to 20 non-malignant CD34+ bone marrow derived samples. Patients were clustered by the progeny clustering algorithm coupled with k-means, which computationally calculated the optimal number of clusters. Patients were treated according the COG Phase 3 AAML1031 trial with a 1:1 randomization to cytarabine (ara-C), daunorubicin, etoposide (ADE) ± the proteasome inhibitor bortezomib. Results: Cluster analysis identified 4 groups of correlated Protein Groups (PrG) that defined 5 recurrent Patient Clusters (PC, figure 1). The first PrG consisting of HDAC's, SIRT's and BRD4 showed homogeneous normal range expression across all patients. PrG2 contains most varying expression of HistModProt and was therefore termed as modulators. PrG3, miscellaneous defined (misc) group, had universally low expression across all patients. PrG4 consists of the histone marks including total H3. Interestingly, all variation between the PC was due to modulation within PrG2 modulators and PrG4 histone marks. Patient protein patterns in PC1 were identified as closest to that of the normal bone marrow derived CD34+ cells by performing linear discriminant analysis and were therefore defined as most normal-like cluster. PC2 had very low expression of both PrG2 and PrG4, representing a more deactivated/off cluster. PC3 had somewhat low histone marks, with higher modulators relative to the CD34+ normal-like PC1. PC4 showed relative normal levels of histone marks but had the highest levels of modulators (i.e. NPM1, NCL and hnRNPK). PC5 had elevated levels of both modulators and histone marks and therefore PC4 and PC5 were considered to represent a more activated/on protein signature that was associated with a higher proliferative potential, as manifested by higher WBC, and percent peripheral blasts and absolute blood count (all p 〈 0.001). These findings correlate with clinical features of adult AML patients with upregulated HistModProt. However, in adults, different proteins (e.g. high BRD4 and KDM1) were more prominent in the upregulated HistModProt signature. HistModProt PC membership did not correlate with outcome overall (OS) or event free survival (EFS). However, pediatric patients with the on signature (PC4 and PC5) that received the ADE + bortezomib regimen had a trend towards longer EFS compared to those treated with ADE (P = 0.055), whereas PC2 patients did not benefit from the addition of bortezomib (p = 0.43). Conclusion: Similar to adult AML patients, recurrent patterns of HistModProt were observed in pediatric AML and associates with outcome. Relative low expression of histone marks and HistModProt correlated with favorable outcomes in both adults and pediatrics suggesting that these patients contain a more open chromatin state with potential for diagnostic and prognostic implications in AML at all age. Figure legend: RPPA-based heatmap of 505 de novo pediatric AML samples containing 7 histone marks and 17 HistModProt. The five cluster colors along the top bar delineate the five identified protein clusters (PC). Protein expression is normalized for each protein to range from the lowest (blue) to the highest (red) compared to non-malignant CD34+ cells. Identification of protein groups (PrG's) is shown. Disclosures No relevant conflicts of interest to declare.
    Type of Medium: Online Resource
    ISSN: 0006-4971 , 1528-0020
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    Language: English
    Publisher: American Society of Hematology
    Publication Date: 2018
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  • 10
    In: Blood, American Society of Hematology, Vol. 128, No. 22 ( 2016-12-02), p. 4089-4089
    Abstract: Background: Pediatric acute lymphoblastic leukemia (ALL) is the most common pediatric malignancy and remains a leading cause of mortality and morbidity. Heterogeneity in the genetic and epigenetic landscape renders almost every patient genetically unique, making individualized medicine hard to achieve. Since genetic events are revealed by the expression and activation status of proteins, we hypothesized that these genetic events would coalesce into a finite number of protein expression signatures and that these could guide individualized therapy. Methods:To determine relative protein expression patterns a custom Reverse Phase Protein Arrays (RPPA) with samples from 73 pediatric ALL patients and 10 normal CD34+ bone marrow samples were created and probed with 194 validated antibodies. As proteins interact with each other and act within networks, proteins were divided into 31 Protein Functional Groups (ProFnGrp) based on known associations from the literature. Progeny clustering was performed to determine the optimal number of protein clusters and principal component analysis was used to map global differences and similarities between protein clusters and normal CD34+ samples. Protein networks were constructed using literature associations and correlation within the data set. Associations between clinical features, outcomes and signatures were determined. Hierarchical clustering was performed on a compilation of all protein clusters into one binary matrix to identify recurrent protein expression signatures that comprised similar combinations of protein constellations. From this we constructed a list of proteins that were over or under expressed in each signature. Results: Each ProFnGrp had 3 to 5 distinct expression clusters; at least one protein cluster was similar to the normal CD34+ samples in 23 of the 31 ProFnGrp and all had leukemia specific patterns. Protein expression levels were mapped onto the networks and showed different expression and activation states. Hierarchical clustering showed strong co-correlation between multiple groups of protein clusters from various ProFnGrp and suggested 10 protein constellations. Patients that expressed similar recurrent combinations of constellations formed 7 protein signatures (Figure). Most constellations and signatures were T- or B-cell specific, however 2 constellations showed overlap between the two diseases. Reanalysis limited to T-cell ALL revealed 3 protein signatures. Signature membership was correlated with overall risk stratification as determined by clinical features (P=0.001) as well as cytogenetics (P=0.017, Favorable risk with sig. 5 and 7, Intermediate risk with sig. 1 and 4) and absolute blast count (P=0.001). For both B- and T-cell ALL there were signatures that were significantly enriched for, and depleted of, patients of Hispanic ethnicity, suggesting that pathophysiological differences likely exist between non-Hispanic and some Hispanic ALL cases. Given the high CR and low relapse rates that resulted in a high overall survival in our cohort, signatures did not show significant correlation with clinical outcome. However, 3 of the 4 relapsing cases were in signature 6. The net level of expression and activation for each protein across each signature identified numerous proteins with significantly higher or lower expression, relative to normal CD34+ cells suggesting specific targets for combined targeted therapy. Conclusion: Despite genetic heterogeneity ALL can be classified into a finite set of recurrent protein expression signatures. Signature membership correlated with risk stratification and cytogenetics. The identification of signatures associated with Hispanic ethnicity suggests that pathophysiology, rather than socioeconomic factors may underlie the inferior outcome of Hispanic patients. The net protein expression and activation status within each signature suggest targets for directed combinatorial inhibition or replacement to enable individualized therapy. Figure Hierarchical clustering based on binary ProFnGrp cluster membership. Each vertical patient column consists of 31 out of the 114 protein clusters. The suggested number of protein expression signatures is 7 together with 10 protein constellations. Blue squares indicate positive cluster membership. Figure. Hierarchical clustering based on binary ProFnGrp cluster membership. Each vertical patient column consists of 31 out of the 114 protein clusters. The suggested number of protein expression signatures is 7 together with 10 protein constellations. Blue squares indicate positive cluster membership. Disclosures No relevant conflicts of interest to declare.
    Type of Medium: Online Resource
    ISSN: 0006-4971 , 1528-0020
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    Language: English
    Publisher: American Society of Hematology
    Publication Date: 2016
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