Gotowa bibliografia na temat „Arkansas Foundation of Associated Colleges”

Relying on data from an in-depth study of 15 community colleges, this article explores online education through the lens of institutional theory. This theoretical perspective highlights the colleges’ environmental contexts and offers a critical examination of the ways that the institutional contexts have structured the colleges’ approaches to online education. At the core of this analysis is the contention that community colleges are interpreting and responding to a set of taken-for-granted ideas about online education. These ideas have taken on the status of myth and have played a powerful role in guiding and legitimating colleges’ online activity. This analysis provides a research-based foundation for understanding online activity at the community college level and for carefully addressing the challenges associated with its adoption.

Abstract Introduction: Molecular assessment using conventional karyotyping, interphase FISH and gene expression profiling (GEP) has revealed multiple subgroups of myeloma with distinct pathogenesis and clinical course. While these technologies have tremendously impacted risk assessment they have had little contribution to the identification of therapeutic targets. Next generation sequencing (NGS) technology can identify mutations in genes of key cancer pathways, which impact outcome and are targetable by new drugs. Targeted gene panels can analyze clinical samples in sufficient depth affording the opportunity to incorporate NGS into clinical decision making in a meaningful way. Using the FoundationOne Heme test (F1H), we aimed to determine the mutational spectra of cancer-associated genes in multiple myeloma (MM), their association with disease risk and their effect on clinical outcome. Methods: DNA and RNA were extracted from CD138-selected MM cells. Comprehensive genomic profiling (CGP) using F1H was performed by Foundation Medicine, Inc (Cambridge, MA). Sequencing to an average depth of 470x (range: 5-3781) was performed on a HiSeq2500 sequencer. Sequences were analyzed for base substitutions, insertions, deletions, copy number alterations, and rearrangements in frequently altered genes. Annotated germline variants (dbSNP135) were removed. Somatic alterations in COSMIC (v62) and inactivating variants in tumor suppressor genes were called as biologically significant. GEP of CD138-selected MM cells using Affymetrix U133 2.0 plus arrays was performed as described. Overall survival analysis was done using log-rank tests. Results: CGP was performed on a total of 630 patients (3.4% MGUS, 6.5% SMM, 24.9% newly diagnosed MM, 24.9% relapsed MM, 18.8% MM in remission). We found increasing mutation load in from MGUS to relapsed MM. Later stages of the disease had an increased frequency of mutations in genes coding for epigenetic modulators and proteins involved in DNA repair. Alterations of TP53 and RB1 among others weresignificantly more frequent in GEP-defined high-risk (HR) disease and after relapse. Patients of the GEP-defined MF molecular subgroup carried a significantly greater mutation load. While there was no difference in the frequency of altered RAS/MAPK pathway genes between newly diagnosed and relapsed patients, we found an increased average mutant allele frequency in relapsed patients, indicating clonal selection. Using paired GEP data we identified gene expression signatures for patients with RAS/MAPK activation and patients with loss-of-function mutations in the DNA repair pathway, suggesting a functional relevance of these mutations. Mutations in either of these pathways were associated with significantly worse overall survival (OS) (Figure 1). Presence of DNA repair gene mutations resulted in significantly worse OS within the GEP-defined low-risk subgroup. Among the 630 patients who underwent CGP, 396 had clinically relevant alterations, which were associated with either an FDA approved drug or a clinical trial. For example, 316 patients had alterations of the RAS/MAPK pathway. Recently we have shown clinical benefit of MEK directed therapy in this patient population. 39 patients had alterations in the mTOR pathway, suggesting benefit from mTOR inhibitors. 426 patients with MM had mutations in epigenetic modulators. For 37 of them therapy with demethylating agents was recommended. Many more epigenetic targeted drugs, such as EZH2 or Bromodomain inhibitors are currently in development. Conclusion: Using the F1H test we demonstrate a negative impact of somatic mutations of the MAPK and DNA repair pathways on outcome. In tandem, for 396 patients we identified genomic alterations, which suggest benefit from targeted treatment. Thus targeted therapy, guided by comprehensive genomic profiling, may be applied to the majority of MM patients, with the potential of significantly improving clinical outcomes. Comprehensive genomic profiling should therefore be considered in the routine work-up, especially for HR patients where outcomes remain poor. Figure 1. Inferior outcome of patients with mutations in the MAPK or DNA repair pathway. Panels A) and C) mutation of MAPK pathway; Panels B) and D) mutation of the DNA repair pathway. Overall survival is measured from time of disease diagnosis in panels A) and B) and is shown from sample date in panels C) and D) Figure 1. Inferior outcome of patients with mutations in the MAPK or DNA repair pathway. Panels A) and C) mutation of MAPK pathway; Panels B) and D) mutation of the DNA repair pathway. Overall survival is measured from time of disease diagnosis in panels A) and B) and is shown from sample date in panels C) and D) Disclosures Heuck: Millenium: Other: Advisory Board; Janssen: Other: Advisory Board; Celgene: Consultancy; University of Arkansas for Medical Sciences: Employment; Foundation Medicine: Honoraria. Chavan:University of Arkansas for Medical Sciences: Employment. Stein:University of Arkansas for Medical Sciences: Employment. Tytarenko:University of Arkansas for Medical Sciences: Employment. Weinhold:University of Arkansas for Medical Sciences: Employment; Janssen Cilag: Other: Advisory Board. Ali:Foundation Medicine, Inc.: Employment, Equity Ownership. Miller:Foundation Medicine, Inc.: Employment, Equity Ownership. Thanendrarajan:University of Arkansas for Medical Sciences: Employment. Schinke:University of Arkansas for Medical Sciences: Employment. Mohan:University of Arkansas for Medical Sciences: Employment. Sawyer:University of Arkansas for Medical Sciences: Employment. Peterson:University of Arkansas for Medical Sciences: Employment. Bauer:University of Arkansas for Medical Sciences: Employment. Ashby:University of Arkansas for Medical Sciences: Employment. Johann:University of Arkansas for Medical Sciences: Employment. van Rhee:University of Arkansa for Medical Sciences: Employment. Waheed:University of Arkansas for Medical Sciences: Employment. Davies:Millenium: Consultancy; Onyx: Consultancy; Janssen: Consultancy; Celgene: Consultancy; University of Arkansas for Medical Sciences: Employment. Barlogie:University of Arkansas for Medical Sciences: Employment. Morgan:CancerNet: Honoraria; Weismann Institute: Honoraria; MMRF: Honoraria; Takeda: Honoraria, Membership on an entity's Board of Directors or advisory committees; University of Arkansas for Medical Sciences: Employment; Bristol Myers Squibb: Honoraria, Membership on an entity's Board of Directors or advisory committees; Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees.

Abstract Introduction: Next generation sequencing of over 800 newly diagnosed multiple myeloma (NDMM) cases has established the mutational landscape and key cancer driver pathways. The mutational basis of relapse has not been systematically studied. Two previous studies (Keats et al.; Bolli et al.) identified 4 patterns of clonal evolution. Neither study included uniformly treated patients and looked at the impact of therapy on clonal structure at relapse. Understanding the mutational patterns underlying relapse and how they relate to specific therapies is crucial in order to improve MM outcomes, especially for high-risk (HR) MM. In this study we compare the clonal structure at presentation (PRES) and at relapse (REL), after exposure to Total Therapy (TT). Materials and Methods: We studied 33 pairs of tumor samples collected at PRES and REL. 9 patients were treated on TT2, 13 on TT3, 10 on TT4 and 1 on TT5-like regimen. Eleven patients had HR disease at PRES. DNA was extracted from CD138+ selected cells from random bone marrow aspirates. Germline controls were obtained from leukapheresis products. Whole exome sequencing libraries were prepared using the Agilent qXT kit and the Agilent SureSelect Clinical Research Exome kit with additional baits covering the Ig and MYC loci. All samples were sequenced on an Illumina HiSeq2500 to a median depth of 120x. Sequencing data were aligned to the Ensembl GRCh37/hg19 human reference using BWA. Somatic variants were called using MuTect. Translocations were identified using MANTA. Copy number variations were inferred using TITAN. Gene expression profiles (GEP), generated using the Affymetrix U133plus2 microarray, were available for all tumor samples. Nonnegative matrix factorization (NMF) was used to define mutation signatures. Results: The median time to progression was 30 months with a median follow up of 9.5 years. 22 cases achieved a complete remission (CR) or near CR. There were 11 cases of HR at PRES. Of the 22 cases with low risk (LR) MM, 7 relapsed with HR disease. There were on average 478 SNVs per sample at PRES and 422 at REL. All but 2 cases had evidence of new mutations at REL. There were no consistent patterns or number of mutation associated with REL or GEP-defined risk. Patients of the MF molecular subgroup had more mutations compared to other molecular subgroups (657 vs. 379) and were enriched for mutations with an APOBEC signature. We did not detect any mutation signature consistent with chemotherapy-induced alterations, providing evidence that TT itself does not cause additional mutations. Primary recurrent IgH translocations called by MANTA were confirmed by GEP data. A number of new translocations were identified , several only at REL. In particular we demonstrate a case with a newly acquired MYC translocation at relapse, indicating that it contributed to progression. We identified 5 patterns of clonal evolution (Figure 1): A) genetically distinct relapse in 3 patients, B) linear evolution in 8 patients, C) clonal selection in 9 patients, D) branching evolution in 11 patients, and E) stable clone(s) in 2 patients. Patterns A (distinct) and B (linear) were associated with low risk and longer survival, whereas patterns D (branching) and E (stable) were associated with high risk and shorter time to relapse and overall survival (Table 1). Conclusion: This is the first study to systematically analyze the pattern of clonal evolution using NGS in patients treated with combination chemotherapy and tandem ASCT. We identified 5 patterns of evolution, which correlate with survival. We identified 3 cases with a loss of the original clone and emergence of a new clone, suggesting high effectiveness of Total Therapy for those patients. The persistence of major clones despite multi agent chemotherapy in most other cases supports a concept of a tumor-initiating cell population that persist in a protective niche, for which new therapies are needed. Table 1. Pattern of Evolution GEP70 Pres.(high risk: ≥0.66) Proliferation Index Pres. GEP70 Rel.(high risk: ≥0.66) Proliferation Index Rel Mean OS Mean TTR A: distinct (n=3) -0.690 -3.34 -0.015 2.04 8.18 5.00 B: linear (n=8) -0.171 -0.34 0.618 9.22 5.70 4.05 C: selection (n=9) 0.366 3.20 0.569 6.97 3.95 2.64 D: branching (n=11) 0.710 5.17 1.173 11.15 3.84 2.21 E: stable (n=2) 1.532 7.42 1.124 2.54 0.96 0.35 Pres.: Presentation; Rel.: Relapse; OS: Overall Survival; TTR: Time to Relapse Figure 1. Patterns of Relapse Figure 1. Patterns of Relapse Disclosures Heuck: Foundation Medicine: Honoraria; Millenium: Other: Advisory Board; Janssen: Other: Advisory Board; Celgene: Consultancy; University of Arkansas for Medical Sciences: Employment. Weinhold:Janssen Cilag: Other: Advisory Board; University of Arkansas for Medical Sciences: Employment. Peterson:University of Arkansas for Medical Sciences: Employment. Bauer:University of Arkansas for Medical Sciences: Employment. Stein:University of Arkansas for Medical Sciences: Employment. Ashby:University of Arkansas for Medical Sciences: Employment. Chavan:University of Arkansas for Medical Sciences: Employment. Stephens:University of Arkansas for Medical Sciences: Employment. Johann:University of Arkansas for Medical Sciences: Employment. van Rhee:University of Arkansa for Medical Sciences: Employment. Waheed:University of Arkansas for Medical Sciences: Employment. Johnson:University of Arkansas for Medical Sciences: Employment. Zangari:University of Arkansas for Medical Sciences: Employment; Millennium: Research Funding; Onyx: Research Funding; Novartis: Research Funding. Matin:University of Arkansas for Medical Sciences: Employment. Petty:University of Arkansas for Medical Sciences: Employment. Yaccoby:University of Arkansas for Medical Sciences: Employment. Davies:University of Arkansas for Medical Sciences: Employment; Millenium: Consultancy; Janssen: Consultancy; Onyx: Consultancy; Celgene: Consultancy. Epstein:University of Arkansas for Medical Sciences: Employment. Barlogie:University of Arkansas for Medical Sciences: Employment. Morgan:Weismann Institute: Honoraria; MMRF: Honoraria; Bristol Myers Squibb: Honoraria, Membership on an entity's Board of Directors or advisory committees; Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees; University of Arkansas for Medical Sciences: Employment; CancerNet: Honoraria; Takeda: Honoraria, Membership on an entity's Board of Directors or advisory committees.

Abstract INTRODUCTION Profound osteolytic lesions are a hallmark of multiple myeloma (MM) bone disease. Bone destruction is associated with severely unbalanced bone remodeling, secondary to the secretion of osteoclast activating factors and significant osteoblast suppression. Lytic lesions of the pelvis are relatively common in MM patients and contribute to increase morbidity due to the high risk of fracture that frequently demands surgical intervention. Since we observed significant improvements in the pelvic CT of patients following total therapy 4 (TT4) we retrospectively analyzed the appearance on pelvic osteolytic lesions by CT during TT4 treatment for myeloma. METHODS The UAMS Myeloma data base was interrogated to identify patients enrolled on the TT4 trial. TT4 is a protocol designed for low risk MM patients as defined by a baseline plasma cell GEP score < than 0.66. The treatment protocol includes two induction chemotherapy cycles followed by tandem autologous bone marrow transplantation, two consolidation cycles and 3 years of maintenance. During treatment, patients were exposed to alkylating agents, IMIDS and proteasome inhibitor agents as well as bisphosphonates. Baseline pelvic osteolytic lesions with > 1 cm in minimal diameter identified by PET/CT or CT of the pelvis were compared to the most recent radiological study available for the same subject. All identified cases were reviewed by radiology faculty to confirm the baseline and follow-up reported findings. Radiological findings were correlated with disease status, molecular subgroup, PET scanning and MRI. RESULTS Sixty-three (63) patients, with a median age of 62 years, were identified for this analysis. Baseline patient characteristics are shown in Table 1. With a median follow up of 41 months, CT studies indicate that 44% (28/63) of patients with large baseline pelvic lytic lesions achieved re-accumulation of radio-dense mineralized tissue at the lytic site. Sixty-eight percent of such patients reached at least VGPR. The average size of the lytic lesions that re-mineralized was 4.0 cm (minimum 1.3 cm - maximum 10 cm). Baseline GEP-defined molecular subgroups and cytogenetic distribution was not different from the entire patient population of TT4. CONCLUSION This study clearly shows that mineral redeposition in large pelvic lytic lesions of MM patients on TT4 is achievable in a significant proportion of individuals. We observed that the amount of re-mineralization was prominent in pelvic lytic lesions with cortical bone destruction. Since flat bones, such as the pelvis, are formed via intramembranous ossification further investigation of the mechanism responsible for this effect is warranted at skeletal sites with different regenerative capacity. These data also suggest that, contrary to much dogma, MM bone lesions can regain matrix mineralization capacity. Table 1. Baseline Patient Characteristics n/N (%) Male 43/63 (69%) IgA Isotype 11/63 (17.5%) IgD Isotype 1/63 (1.6%) IgG Isotype 36/63 (57.1%) Nonsecretory 1/63 (1.6%) Light Chain Isotype 14/63 (22.2%) LDH > = 190 U/L 8/63 (12.7%) Abnormal Cytogenetics 44/63 (69.8%) GEP CD-1 subgroup 4/64 (6.3%) GEP CD-2 subgroup 17/64 (26.6%) GEP HY subgroup 24/64 (37.5%) GEP LB subgroup 8/64 (12.5%) GEP MF subgroup 1/64 (1.6%) GEP MS subgroup 2/64 (3.1%) GEP PR subgroup 5/64 (7.8%) Disclosures Mohan: University of Arkansas for Medical Sciences: Employment. Samant:University of Arkansas for Medical Sciences: Employment. Suva:University of Arkansas for Medical Sciences: Employment. Montgomery:University of Arkansas for Medical Sciences: Employment. Alapat:University of Arkansas for Medical Sciences: Employment. Morello:University of Arkansas for Medical Sciences: Employment. van Rhee:University of Arkansa for Medical Sciences: Employment. Waheed:University of Arkansas for Medical Sciences: Employment. Thanendrarajan:University of Arkansas for Medical Sciences: Employment. Schinke:University of Arkansas for Medical Sciences: Employment. Heuck:Millenium: Other: Advisory Board; Celgene: Consultancy; Foundation Medicine: Honoraria; Janssen: Other: Advisory Board; University of Arkansas for Medical Sciences: Employment. Jethava:University of Arkansas for Medical Sciences: Employment. Johann:University of Arkansas for Medical Sciences: Employment. Barlogie:University of Arkansas for Medical Sciences: Employment. Davies:University of Arkansas for Medical Sciences: Employment; Celgene: Consultancy; Janssen: Consultancy; Millenium: Consultancy; Onyx: Consultancy. Morgan:CancerNet: Honoraria; Bristol Myers Squibb: Honoraria, Membership on an entity's Board of Directors or advisory committees; University of Arkansas for Medical Sciences: Employment; MMRF: Honoraria; Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees; Weismann Institute: Honoraria; Takeda: Honoraria, Membership on an entity's Board of Directors or advisory committees. Zangari:Novartis: Research Funding; Millennium: Research Funding; Onyx: Research Funding; University of Arkansas for Medical Sciences: Employment.

Abstract Introduction: Recent next generation sequencing studies have defined the mutation spectrum in multiple myeloma (MM) and uncovered significant intra-clonal heterogeneity, showing that clinically relevant mutations are often only present in sub-clones. Longitudinal analyses demonstrated that tumor clones under therapeutic pressure behave in a "Darwinian" fashion, with shifting dominance of tumor clones over time. Recently, stratification of clonal substructures in distinct areas of the tumor bulk has been shown for multiple cancer types. So far, spatial genomic heterogeneity has not been systematically analyzed in MM. This stratification in space is becoming increasingly important as we begin to understand the contribution of Focal Lesions (FL) to tumor progression and emergence of drug resistance in MM. We have recently shown that high numbers of FL are associated with gene expression profiling (GEP) defined high risk (HR). A comparison of GEP data of 170 paired random bone marrow (RBM) and FL aspirates showed differences in risk signatures, supporting the concept of spatial clonal heterogeneity. In this study we have extended the analysis by performing whole exome sequencing (WES) and genotyping on paired RBM and FL in order to gain further insight into spatial clonal heterogeneity in MM and to find site-specific single nucleotide variant (SNV) spectra and copy number alterations (CNA), which contribute to disease progression and could form the basis of adaptation of the tumor to therapeutic pressure. Materials and Methods: We included 50 Total Therapy MM patients for whom paired CD138-enriched RBMA and FL samples were available. Leukapheresis products were used as controls. For WES we applied the Agilent qXT kit and a modified Agilent SureSelect Clinical Research Exome bait design additionally covering the immunoglobulin heavy chain locus and sequences located within 1Mb of the MYC locus. Paired-End sequencing to a minimum average coverage of 120x was performed on an Illumina HiSeq 2500. Sequencing data were aligned to the Ensembl GRCh37/hg19 human reference using BWA. Somatic variants were identified using MuTect. For detection of CNA we analyzed Illumina HumanOmni 2.5 bead chip data with GenomeStudio. Subclonal reconstruction was performed using PhyloWGS. Mutational signatures were investigated using SomaticSignatures. The GEP70 risk signature was calculated as described previously. Informed consent in accordance with the Declaration of Helsinki was obtained for all cases included in this study. Results: Analyzing RBM and FL WES data, we detected between 100 and 200 somatic SNVs in covered regions, with approximately 30% of them being non-synonymous, and less than 5% stop gained or splice site variants. A comparison of paired RBM and FL WES data showed different extents of spatial heterogeneity. Some pairs had very similar mutation profiles with up to 90% shared variants, whereas others demonstrated marked heterogeneity of point mutations. We did not detect differences in mutational signatures between RBM and FL using the 'SomaticSignatures' package. We found site-specific driver mutations with high variant allele frequencies, indicating replacement of other clones in these areas. For example we observed a clonal KRAS mutation exclusively in the RBM, whereas a NRAS variant was only identified in the paired FL. The same holds true for large-scale CNAs (>1 Mb). We identified a case in which the high risk CNAs gain(1q) and del(17p) were only detectable in the FL. Further examples for site-specific CNAs were a del(10q21) and a gain(4q13) detected in FLs only. As a prominent pattern, we observed outgrowth of sub-clonal RBM CNAs as clonal events in the FL. Based on mutation and CNA data we identified different forms of spatial evolution, including parallel, linear and branching patterns. Of note, a stratified analysis by GEP70-defined risk showed that a more pronounced spatial genomic heterogeneity of SNVs and CNAs was associated with HR disease. Conclusion: We show that spatial heterogeneity in clonal substructure exists in MM and that it is more pronounced in HR. The existence of site-specific HR CNAs and driver mutations highlights the importance of heterogeneity analyses for targeted treatment strategies, thereby facilitating optimal personalized MM medicine. Disclosures Weinhold: University of Arkansas for Medical Sciences: Employment; Janssen Cilag: Other: Advisory Board. Chavan:University of Arkansas for Medical Sciences: Employment. Heuck:Millenium: Other: Advisory Board; Janssen: Other: Advisory Board; Celgene: Consultancy; University of Arkansas for Medical Sciences: Employment; Foundation Medicine: Honoraria. Stephens:University of Arkansas for Medical Sciences: Employment. Tytarenko:University of Arkansas for Medical Sciences: Employment. Bauer:University of Arkansas for Medical Sciences: Employment. Peterson:University of Arkansas for Medical Sciences: Employment. Ashby:University of Arkansas for Medical Sciences: Employment. Stein:University of Arkansas for Medical Sciences: Employment. Johann:University of Arkansas for Medical Sciences: Employment. Johnson:University of Arkansas for Medical Sciences: Employment. Yaccoby:University of Arkansas for Medical Sciences: Employment. Epstein:University of Arkansas for Medical Sciences: Employment. van Rhee:University of Arkansa for Medical Sciences: Employment. Zangari:Novartis: Research Funding; Onyx: Research Funding; Millennium: Research Funding; University of Arkansas for Medical Sciences: Employment. Schinke:University of Arkansas for Medical Sciences: Employment. Thanendrarajan:University of Arkansas for Medical Sciences: Employment. Davies:Millenium: Consultancy; Onyx: Consultancy; Celgene: Consultancy; University of Arkansas for Medical Sciences: Employment; Janssen: Consultancy. Barlogie:University of Arkansas for Medical Sciences: Employment. Morgan:University of Arkansas for Medical Sciences: Employment; MMRF: Honoraria; CancerNet: Honoraria; Takeda: Honoraria, Membership on an entity's Board of Directors or advisory committees; Weismann Institute: Honoraria; Bristol Myers Squibb: Honoraria, Membership on an entity's Board of Directors or advisory committees; Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees.

Abstract Introduction: Focal lesions (FL) are detected by magnetic resonance imaging (MRI) and positron emission tomography (PET) and precede the development of osteolytic lesions in multiple myeloma (MM). FLs are absent in most patients with benign disease and their detection is associated with earlier disease progression suggesting that a distinct MM cell niche in the FLs is associated with conditions that promote the transition to MM. Studying the nature of this niche can significantly enhance our understanding of the biology and progression of MM. Methods: Random BM aspiration samples were taken from the posterior superior iliac crest whereas FL samples were sampled under CT guidance from newly diagnosed MM patients. Gene expression profiling (GEP) was performed on CD138-enriched plasma cells (PC, n=170) and non-enriched BM trephine biopsies (n=49) from paired RBM and FL samples from the same patients and from unrelated RBM cases with no detectable FL (n=79). 8-multicolor flow cytometry (MFC) analysis was performed on 25 paired PC samples and selected genes were validated using immunohistochemistry (IHC). Results: AComparison of GEP from paired RBM-PC and FL-PC showed discrepancies in GEP-based risk score and molecular subgroups and lower Polyclonal-PC score (reflecting the proportion of normal PC infiltration) in FL-PC samples (p=0.0001). There is 89% concordance for the GEP70 risk signature with 10 patients having low-risk PCs in RBM but high-risk PCs in the paired FL, and 8 patients showing high-risk PCs in RBM but low-risk PCs in the paired FL samples. In this setting progression-free and overall survival are mediated by the presence of a high-risk score in either sample. When molecular subgroups were identified there were more high risk-associated PR cases in FL samples (n=28) compared to only 16 PR cases in respective paired RBM-PC samples (p=0.005). Flow cytometry data from 25 paired MM cell samples showed consistently lower surface expression of CD138 in FL (p=0.0001). Cases with detectable CD81 had lower CD81 expression on FL-PC (p=0.03). Discrepancies were also observed in cell surface expression of CD38 and CD45. Pathway's analysis was based on of 523 differentially expressed genes between paired FL and RBM-PC samples (n=170; FDR<0.001) after adjusting for the level of normal PC infiltration. The top KEGG-based pathways enrichment analysis were associated with energy and drug metabolism, survival, cell-cell contact interaction and factors involved in activity of dexamethasone (e.g. NR3C1) and IMiDs (e.g. IZKF1), Figure 1A. Differential expression of ABCA1, the most upregulated gene in FL, was validated by IHC in biopsies. To test whether PCs from patients with FL have specific characteristics irrespective of their location, we compared RBM-PC GEP with RBM-PC GEP of unrelated patients with no detectable FLs. We detected increased expression of cell cycle genes in PC from patients with detectable FL. Reduced osteogenesis and interaction with mesenchymal and vascular lineages have been linked with MM cell phenotypes and dissemination in BM. Microenvironmental reactive stroma (e.g. POSTN, collagen genes) and angiogenic (e.g. EDNRA) gene signatures were significantly upregulated in non-enriched FL biopsies albeit expected high proportion of PC in this site, whereas osteoblastic markers such as BGLAP and IBSP were underexpressed in these samples in comparison to paired non-enriched RBM trephine biopsies, Figure 1B. Conclusions: PC in FL and RBM sites of the same patient are heterogeneous in their phenotype, molecular classification based on risk-score and subgroups, and pathways. GEP signatures of MM cells and the stroma in this niches stressing the biological and clinical relevance of FL as a hallmark in MM. Disclosures Yaccoby: University of Arkansas for Medical Sciences: Employment. Epstein:University of Arkansas for Medical Sciences: Employment. Johnson:University of Arkansas for Medical Sciences: Employment. Qu:Cancer Research and Biostatistics: Employment. van Rhee:University of Arkansa for Medical Sciences: Employment. Jethava:University of Arkansas for Medical Sciences: Employment. Stein:University of Arkansas for Medical Sciences: Employment. Mitchell:Cancer Research and Biostatistics: Employment. Heuck:Millenium: Other: Advisory Board; University of Arkansas for Medical Sciences: Employment; Celgene: Consultancy; Janssen: Other: Advisory Board; Foundation Medicine: Honoraria. Davies:Millenium: Consultancy; Janssen: Consultancy; Celgene: Consultancy; University of Arkansas for Medical Sciences: Employment; Onyx: Consultancy. Crowley:Cancer Research and Biostatistics: Employment. Weinhold:Janssen Cilag: Other: Advisory Board; University of Arkansas for Medical Sciences: Employment. Barlogie:University of Arkansas for Medical Sciences: Employment. Morgan:Takeda: Honoraria, Membership on an entity's Board of Directors or advisory committees; Bristol Myers Squibb: Honoraria, Membership on an entity's Board of Directors or advisory committees; CancerNet: Honoraria; Weismann Institute: Honoraria; MMRF: Honoraria; University of Arkansas for Medical Sciences: Employment; Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees.

Purpose The purpose of this paper is to reflect upon experiences of measuring the influences of the Recovery Academy within Greater Manchester Mental Health (GMMH) NHS Foundation Trust amongst a student population of health professionals. This paper aims to present considerations for future quantitative research surrounding the efficacy of Recovery Colleges such as the Recovery Academy. Design/methodology/approach This paper utilised baseline data collected from health professionals as part of a quantitative evaluation of the Recovery Academy. The paper discusses challenges experienced in measuring change amongst this student population within GMMH. Findings Health professionals reported positive attitudes towards recovery at baseline presenting challenges in measuring attitudinal change associated with the Recovery Academy. The experiences of conducting research amongst health professionals within GMMH offers insights into the selection and use of self-report measures in Recovery College research; the representativeness of health professional student populations; and models of course attendance within Recovery Colleges. Originality/value The existing literature specific to Recovery College influences upon health professionals remains predominantly qualitative and anecdotal. It is important to gather empirical evidence regarding Recovery Colleges to establish their ability to re-orientate health professionals around principles of recovery. This paper therefore offers considerations for future researchers aiming to gather empirical evidence which may facilitate quantitative evaluations of Recovery Colleges such as the Recovery Academy amongst staff populations.

Abstract Introduction In multiple myeloma (MM), deletion of chromosome 17 p13 (del17p) is a poor prognostic feature. The percentage of cells carrying an abnormality has been reported to be important with thresholds of 20% being taken generally but thresholds as high as 60% being suggested more recently. We have reported previously in the Total Therapy (TT)-2 trial (NCT00083551) for newly diagnosed (ND) MM that del17p is an adverse prognostic factor (Blood 112: 4235). The TT3 trial (NCT00081939) incorporated Brtezomib into tandem Melphalan-based autotransplants with DT-PACE for induction/consolidation and Thalidomide and Dexamethasone for maintenance to treat patients with newly diagnosed MM. In more recent iterations of these trials following the introduction of novel agents in induction and during maintenance the impact of carrying del17p has not been studied. In particular we have stratified patients into low- or high-risk molecular subgroups based on the GEP-70 (TT4 protocol [NCT00734877] or TT5 protocol [NCT00869232], respectively). We have used interphase FISH (iFISH) to detect the presence of del17p in baseline bone marrow samples. Method The iFISH slides were prepared with bone marrow aspirates after removing erythrocytes. A specific TP53 probe at chromosome 17 arm p13 combined with a control probe for the ERBB3 locus (HER2, 17q12), in different colors, were hybridized to bone marrow cells. Myeloma PCs were identified by restricted Kappa or Lambda immunoglobulin light-chain staining. We investigated role of 20% cutoffs per ≥100 tumor cells for significant deletion of the TP53 probe. Kaplan-Meier analysis was used to estimate the distributions of overall survival (OS) and progression-free survival (PFS) during the follow-ups. OS was calculated from registration until the date of decease. PFS was similarly calculated, but also incorporated progressive disease as an event. Results We examined 709 baseline samples from TT3, 4, and 5 trials with the two probes at chromosome 17. Overall, 66 of 709 patients (9.3%) had deletion of TP53 locus, including 44 of the 591 (7.5%) of low-risk patients and 20 of the 118 (17.0%) high-risk patients (Table). The range of TP53-deleted cells among newly diagnosed patients is 20-99% (median=75%) overall; 35-100% (median=62%) in TT3-low-risk; 30-97% (median=80%) in TT3-high-risk; 21-99% (median=76%) in TT4; and 20-97% (median=81%) in TT5. Deletion of TP53 was associated with significant shorter OS and PFS in HR patients treated on TT3. The 3 year estimated OS of patients for TT3-HR with del17p was 33% compared with 56% for TT3-LR with del17p, and PFS of patients for TT3-HR with del17p was 25% compared with 51% for TT3-LR with del17p (Figure). The comparison of TT4 to TT5 continued showing short OS in HR patients treated on TT5. The 3 year estimated OS of patients for HRMM with del17p was 17% compared with 75% for TT5 patients without deletion (p=0.0008). But, del17p was neutral in LR patients treated on TT4 (Figure). Conclusion Since the introduction of novel agents during various stages of the disease and a focus on HRMM and LRMM defined by GEP70 we show that while TP53 deletion is an adverse prognostic factor for patients with HRMM it is no longer prognostically relevant in LRMM. Table 1. Patients with iFISH results GEP-70 riskLow ≤0.66 High >0.66 Deletion TP53 in 20-59% PCs (n/N [%]) Deletion TP53 in ≥60% PCs (n/N, [%]) Total TT3 (N=329) Low=256 9/329, [2.7%] 9/329, [2.7%] 18/329, [5.5%] High=73 3/329, [0.9%] 9/329, [2.7%] 12/329, [3.7%] TT4 (N=313) Low=313 5/313, [1.6%] 21/313, [6.7%] 26/313, [8.3%] High=0 0 0 0 TT5 (N=67) Low=22 2/67, [3.0%] 0 2/67, [3.0%] High=45 0 8/67, [11.9%] 8/67, [11.9%] Sum (N=709) Low=591 (83.4%) 14/709, [2.0%] 30/709, [4.2%] High=118 (16.6%) 3/709, [0.4%] 17/709, [2.4%] 66/709 (9.3%) Figure 1. Figure 1. Disclosures Tian: University of Arkansas for Medical Sciecnes: Employment. Epstein:University of Arkansas for Medical Sciences: Employment. Qu:Cancer Research and Biostatistics: Employment. Heuck:Millenium: Other: Advisory Board; Janssen: Other: Advisory Board; Celgene: Consultancy; Foundation Medicine: Honoraria; University of Arkansas for Medical Sciences: Employment. van Rhee:University of Arkansa for Medical Sciences: Employment. Zangari:University of Arkansas for Medical Sciences: Employment; Millennium: Research Funding; Onyx: Research Funding; Novartis: Research Funding. Hoering:Cancer Research and Biostatistics: Employment. Sawyer:University of Arkansas for Medical Sciences: Employment. Barlogie:University of Arkansas for Medical Sciences: Employment. Morgan:Weismann Institute: Honoraria; CancerNet: Honoraria; Takeda: Honoraria, Membership on an entity's Board of Directors or advisory committees; MMRF: Honoraria; University of Arkansas for Medical Sciences: Employment; Bristol Myers Squibb: Honoraria, Membership on an entity's Board of Directors or advisory committees; Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees.

Abstract Introduction Over the last 15 years gene expression profiling (GEP) has been used to define myeloma molecular subgroups and to determine clinical prognosis. Two major molecular subgroup classifications have been used: the UAMS which determines 7 subgroups and the TC classification based on the presence of IgH translocations and expression of D group cyclins. For prognosis, although a number of different GEP signatures have been defined, the widely used GEP70 identifies 15% of patients with high risk (HR) disease who have a median PFS and OS of 1.75 and 2.83 years. An ideal classification system would identify clinically relevant subgroups with distinct etiology and biology using standardized techniques. We have examined a large group of patients characterized at multiple genetic levels to optimize the diagnostic approach of newly diagnosed patients going forward. Materials and methods Study subjects included 1349 cases enrolled in Total Therapy trials (median follow up 7.5 years). Gene expression profiling was used to determine GEP70 risk status, molecular subgroup by UAMS and TC classifications, and to devise a new and extended TC classification (TC10). Interphase FISH associated with IgH translocations and 1q+ and 17p- were used to build GEP proxies. Data from mutational analysis generated by the FoundationOne targeted sequence panel was also incorporated. Results were validated on the UK MRC MyelomaIX and Hovon65/GMMG-4 studies. Results An initial agnostic analysis of GEP data using sparse k-means clustering verified the existence of TC based groups. Six groups were identified that corresponded overwhelmingly with known TC subgroups; CCND1-t(11;14), D1-HRD, D2-HRD, MMSET, MAF/CCND2, and CCND3. Further comparisons between the molecular subgroup and TC classifier revealed that the UAMS 7 subgroups clustered strongly within one predominant TC group: CD-1 and CD-2 to t(11;14), HY to D1, LB and PR to D2, MF to t(14;16) or t(14;20), and MS to t(4;14). As the UAMS molecular subgroups are largely contained within the TC framework, we aimed to extend the TC by developing the TC10. To extend the known TC subgroups, unsupervised clustering was applied to the 3 largest subgroups [t(11;14), D1, and D2] to determine the strongest single divisor within each respective subgroup. The dominant feature within the t(11;14) cases was CD20 expression, while the D1 and D2 subgroups both split according to RRAS2. CD20 is associated with PAX5 and VPREB3 expression, and RRAS2 is associated with decreased PTP4A3 and increased TNFAIP3 and BIRC3 expression. RRAS2 activation within D1 subgroup and CD20 activation within t(11;14) cases corresponds to an increased time to response to induction therapy suggesting they constitute important biological subgroups. The TC10 combines the known etiologic subgroups of the TC with functionally relevant subdivisions to create 10 novel subgroups: t(11;14) CD20+/-, D1: RRAS2+/-, D2: RRAS2+/-, t(4;14), t(14;16), t(14;20), and t(6;14). Analysis of mutational data revealed that RRAS2 and CD20 activation within the D1, D2, and t(11;14) subgroups reduced the number of mutations in the MAPK pathway. Further mutational analysis revealed that median mutational load was highest in t(14;16) and lowest in D2: RRAS2+ subgroups. The GEP70 score identifies 15% of patients with HR disease and is specific for this purpose. In an analysis of risk assessment methods, we compared GEP detected adverse lesions [t(4;14), t(14;16), t(14;20), 17p- and 1q+] with the GEP70 and revealed that GEP70 HR identified samples have lower OS rates than cases with more than one adverse lesion (validated in external sets). GEP70 HR segregates non-uniformly across molecular subgroups as over 40% of all HR cases are found in the TC10 t(4;14), t(14;16), and t(14;20) subgroups. GEP70 HR cases also have a higher mutational load than low risk cases. Furthermore, GEP70 HR is uniquely associated with 1q+ and 17p- as cases with at least one of these adverse lesions are 4.9 times as likely to be GEP70 HR as cases with neither. Conclusion GEP profiling has a central role in simplifying and standardizing the molecular subgroup designation and risk stratifying of MM patients. The GEP70 risk score reliably identifies HR cases and outperforms FISH in risk assessment, even in validation data sets. The TC10 provides a classification system that improves upon previous methods by defining both etiological and functionally meaningful subgroups. Disclosures Stein: University of Arkansas for Medical Sciences: Employment. Davies:University of Arkansas for Medical Sciences: Employment; Celgene: Consultancy; Janssen: Consultancy; Millenium: Consultancy; Onyx: Consultancy. Heuck:University of Arkansas for Medical Sciences: Employment; Celgene: Consultancy; Janssen: Other: Advisory Board; Millenium: Other: Advisory Board; Foundation Medicine: Honoraria. Weinhold:University of Arkansas for Medical Sciences: Employment; Janssen Cilag: Other: Advisory Board. Chavan:University of Arkansas for Medical Sciences: Employment. Thanendrarajan:University of Arkansas for Medical Sciences: Employment. Epstein:University of Arkansas for Medical Sciences: Employment. Yaccoby:University of Arkansas for Medical Sciences: Employment. Zangari:University of Arkansas for Medical Sciences: Employment; Novartis: Research Funding; Onyx: Research Funding; Millennium: Research Funding. van Rhee:University of Arkansa for Medical Sciences: Employment. Kaiser:Janssen: Honoraria; Amgen: Consultancy, Honoraria; Celgene: Consultancy, Honoraria, Research Funding; BristolMyerSquibb: Consultancy; Chugai: Consultancy. Sonneveld:Janssen-Cilag, Celgene, Onyx, Karyopharm: Honoraria, Research Funding; novartis: Honoraria. Goldschmidt:Takeda: Consultancy, Membership on an entity's Board of Directors or advisory committees; Onyx: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Bristol-Myers Squibb: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Janssen-Cilag: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Celgene: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Millenium: Honoraria, Research Funding, Speakers Bureau; Amgen: Consultancy, Membership on an entity's Board of Directors or advisory committees; Chugai: Honoraria, Research Funding, Speakers Bureau; Novartis: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau. Barlogie:University of Arkansas for Medical Sciences: Employment. Morgan:Bristol Myers Squibb: Honoraria, Membership on an entity's Board of Directors or advisory committees; MMRF: Honoraria; CancerNet: Honoraria; Takeda: Honoraria, Membership on an entity's Board of Directors or advisory committees; University of Arkansas for Medical Sciences: Employment; Weismann Institute: Honoraria; Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees.

: Professional degree graduate students emphasize cultivating application-oriented high-level talents with a solid theoretical foundation and the ability to adapt to the industry, unlike academic degree graduate students. Providing support for national policy, Shanghai universities vigorously cultivate Master of International Business, integrating education with labor demand and cultivating MIB by integrating industry and education, thereby improving students' literacy levels and fostering the development of employment opportunities. It examines the current situation and problems associated with integrating industry and education by examining the master's degree programs in international business offered at Shanghai universities. It argues that the integration of industry and education in Shanghai universities exists in the status quo of dual tutoring, talent cultivation, schoolenterprise associations, and various ways industry and education are integrated.