ALBERT

Description: © The Author(s), 2018. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Frontiers in Microbiology 9 (2018): 189, doi:10.3389/fmicb.2018.00189.

Description: Only select prokaryotes can biosynthesize vitamin B12 (i.e., cobalamins), but these organic co-enzymes are required by all microbial life and can be vanishingly scarce across extensive ocean biomes. Although global ocean genome data suggest cyanobacteria to be a major euphotic source of cobalamins, recent studies have highlighted that 〉95% of cyanobacteria can only produce a cobalamin analog, pseudo-B12, due to the absence of the BluB protein that synthesizes the α ligand 5,6-dimethylbenzimidizole (DMB) required to biosynthesize cobalamins. Pseudo-B12 is substantially less bioavailable to eukaryotic algae, as only certain taxa can intracellularly remodel it to one of the cobalamins. Here we present phylogenetic, metagenomic, transcriptomic, proteomic, and chemical analyses providing multiple lines of evidence that the nitrogen-fixing cyanobacterium Trichodesmium transcribes and translates the biosynthetic, cobalamin-requiring BluB enzyme. Phylogenetic evidence suggests that the Trichodesmium DMB biosynthesis gene, bluB, is of ancient origin, which could have aided in its ecological differentiation from other nitrogen-fixing cyanobacteria. Additionally, orthologue analyses reveal two genes encoding iron-dependent B12 biosynthetic enzymes (cbiX and isiB), suggesting that iron availability may be linked not only to new nitrogen supplies from nitrogen fixation, but also to B12 inputs by Trichodesmium. These analyses suggest that Trichodesmium contains the genus-wide genomic potential for a previously unrecognized role as a source of cobalamins, which may prove to considerably impact marine biogeochemical cycles.

Description: This work was funded by NSF research grants OCE-1260233, OCE-1260490, OCE-1657757, and OCE-143566.

Description: Introduction - Multiple Myeloma (MM) is a hematologic malignancy characterized by clonal growth of differentiated plasma cells (PCs). Despite improvement in MM therapy, the disease remains mostly incurable and is characterized by recurrent relapses with development of resistant clones that eventually lead to patient death. The pathways that lead to resistant and aggressive MM are not fully understood highlighting the need to improve our understanding of MM biology to identify potential new pathways and therapeutical targets. PHD Finger Protein 19 (PHF19) is a regulator of Polycomb Repressive Complex 2 (PRC2), the sole methyltransferase complex capable of catalyzing H3K27me3 to induce and enforce gene repression. PRC2 employs enhancer of zeste homolog 1 and 2 (EZH1/EZH2) as enzymatic subunits to hypermethylate H3K27. While overexpression and gain of function mutations of EZH1/2 have been observed in many cancers the role of this particular pathway in MM remains poorly understood. In the present study, we report on PHF19 as a new candidate gene to play a potential crucial role in MM oncogenesis. Methods- Gene expression profiling (GEP; Affymetrix U133 Plus 2.0) was performed on 739 MM patients (from total therapy trials [TT] 3-5; low risk MM n=636, high risk MM n=103), 42 patients with monoclonal gammopathy of undetermined significance (MGUS), 73 smoldering MM patients, 42 patients with primary plasma cell leukemia and 34 healthy donors. Myeloma risk was determined by the GEP 70 signature as previously defined. To test the implications of functional PHF19 knock down (KD) we used TRIPZ inducible PHF19 shRNA vs. scrambled control (Dharmacon) in two MM cell lines (JJN3 and ARP1). Real time PCR as well as western blotting was used to confirm PHF19 KD as well as to elucidate the effect on H3K27me3 (Cell Signaling). Functional in vitro studies included proliferation (Promega), clonogenic assays (StemCell), cell cycle and apoptosis assays (both Invitrogen). In vivo studies were performed using SCID mice that were subjected to tail vain injection with PHF19 KD JJN3 cells (n=10) or scrambled shRNA control (n=10). Weekly ELISA (Bethyl) and in vivo imaging (Xenogen) were performed and survival was recorded. Results- GEP of the previously mentioned patient populations and healthy controls identified PHF19 (chr9q33.2) as a candidate gene that was consistently dysregulated in MM patients. Mean expression levels at different MM stages correlated with disease aggressiveness (ANOVA, p10.46) at diagnosis correlated significantly with adverse clinical parameters, including ISS III, anemia and elevated LDH, as well as worse overall survival (5 yr OS = 29% for patients with high PHF19 expression vs 77% for patients with low PHF19 expression [log275% reduction in both cell lines, p

Description: 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.

Description: Introduction: We have previously used global gene expression (GEP)-based clinical pharmacogenomics of dexamethasone, thalidomide, pomalidomide and bortezomib (Bor) to understand their mechanism of actions and how this impacts their clinical efficacy in multiple myeloma (MM) patients. High dose therapy with melphalan (Mel) followed by autologous stem cell transplantation is a major treatment regimen for MM and consequently assessing the pharmacogenomics of Mel is clinically relevant. Importantly not all patients benefit from Mel exposure and, therefore, it remains important to understand the molecular mechanism of its actions and how they underlie treatment resistance. Materials and methods: 252 newly diagnosed MM patients randomized to Total Therapy (TT)4 (GEP70 low-risk, N=210) and TT5 (GEP70 high-risk, n=42) clinical trials received single administration of Bor (1.0mg/m2) followed after 48 hrs latter by a single administration of Mel (10mg/m2). BM aspirates were obtained at baseline, 48 hrs post-Bor and 48 hrs Post-Mel. Purified CD138-selected MM cells underwent GEP analysis using the Affymetrix U133plus2 microarrays and the results generated were analyzed using Gene Set Enrichment Analysis (GSEA) and Ingenuity. The effect of Mel on expression of cell surface receptors in MM cell lines was validated by flow cytometry. Results: Expression of 176 probe sets was changed 48 hours after a single Bor administration at FDR 〈 0.01, and expression of 5117 additional probe sets was further changed after Mel. Expression of 6309 probe sets was changed when comparing post-Mel to baseline, of these 108 were also changed post-Bor and 4043 overlapped with changes observed between post-Mel and post-Bor. By utilizing GSEA and Ingenuity we identified the top pathways associated with Mel activity including activation of p53, nitrogen metabolism and metabolism of xenobiotics by p450, whereas Bor was associated with proteasome activation. Bor and Mel both downregulated pathways related to cell cycle and DNA replication and damage response. Top listed genes differentially expressed between baseline and post-Mel and/or post-Bor and post-Mel and reportedly linked to MM pathogenesis include underexpression of IRF4, ASPM, MYC and NEK2, and upregulation of TNFSF10 (TRAIL), MDM2, BAX and KLF9. Among the top upregulated genes by Mel were also set of 7 cell surface receptors (MERTK, CXCR4, OGFRL1, INSR, TGFBR2, S1PR1, IL1R2) and 5 cytokines (AREG, TNFSF8, BDNF, IGF1, TNFSF15). We initially focused our analysis on MERTK and CXCR4 which have been previously implicated in MM and whose expression was upregulated by 2.5 (FDR 〈 4.6x10-39) and 1.8 (FDR 〈 3.9x10-36) folds, respectively. Increased expression of MERTK and CXCR4 was associated with shorter progression-free survival (PFS) and over survival (OS) in our Total Therapy trials, including analysis restricted to GEP70 high-risk patients in TT3 and TT5. Moreover, GEP of paired MM cell samples obtained from focal lesion and random BM sites of the same patient (n=170) showed reduced CXCR4 expression in MM cells residing within focal lesions (FDR 〈 6.1x10-5), further implicating intra-patient heterogeneity of CXCR4 expression in distinct BM niches with response to Mel. To validate direct effect of Mel on these factors at the protein level, flow cytometry analysis for MERTK and CXCR4 was performed on MM cell lines (n=3) following treatment with Mel (5-10µM) or Bor (2.5-5nM) for 72 hrs. Mel but not Bor increased mean fluorescent intensity of MERTK and CXCR4 by 3.1±0.5 (p 〈 0.05) and 5.1±0.5 (p

Description: Introduction Extramedullary disease (EMD) is a primary disease manifestation of MM, which while not seen frequently at presentation increases in incidence at relapse where its incidence seems to be increasing following the introduction of novel agents. Patients with EMD have a shorter overall survival as well as an increased incidence of anemia, thrombocytopenia, elevated serum lactate dehydrogenase, cytogenetic abnormalities, and high-risk features as determined by gene expression profiling. There is also an increased incidence of the high risk MAF subtypes t (14:16 or 14; 20). Understanding the biology of EMD and identifying its present could give important information about how to improve the outcome of this group. In this work we have used GEP analysis of bone marrow derived plasma cells to predict the presence of EMD so that we can identify the genomic risk factors that define the features of a plasma cell clone, which can develop the capacity to metastasize outside the BM. Materials and Methods We focused on patients treated on TT protocols, at the UAMS, Myeloma Institute between 1989 - 2010, a total of 1154 patients, of which 46 developed EMD before the start of therapy (EMD-1), and 91 developed EMD after registration to UAMS for MM treatment EMD-2. Results We show that most EMD2 cases (57.14%) develop within 3 years after initiation of therapy at the UAMS with few cases developing after this time. Predicting the risk of EMD Combining patients with EMD1 and EMD2 diagnosis within 3 years gave a total of 98 EMD cases. We used 824 samples from 1017 myeloma patients who never developed EMD and had follow up at least 3 years as a comparator group. The data were divided into training (n=619 with 66 EMD cases and 553 controls) and test sets (n=303 with 32 EMD cases and 271 controls). Using the training set, we identified 5 significant gene probes (with a q value 〈 0.001) and made a score to predict cases and controls. The sensitivity and specificity turned out to be 74.24% and 77.40% in the training set, and 56.25% and 76.75% in the test set, respectively. Predicting the time to EMD2 We tested whether we could predict time to EMD2 based on using baseline GEP samples. In this analysis, all EMD2 cases and controls were included. We divided the data into training (n=743 with 61 EMD2 and 682 controls) and test sets (n=365 with 30 EMD2 and 335 controls). By fitting a uniform Cox regression model to each gene in the training set, we identified 68 gene probes that are associated with time to EMD2 (with a q-value

Description: Introduction Mesenchymal lineages including osteoblasts, adipocytes and pericytes derived from mesenchymal stem cells (MSCs) are key components of hematopoietic stem cell and myeloma (MM) niches in bone marrow (BM). The aim of the study was to define high risk signatures of mesenchymal cells in BM of MM patients at diagnosis and post-treatment, and their biological importance. Methods Uniquely we have generated and extracted RNA from random BM biopsy (BM-BX) and focal lesion (FL-BX) samples that contain all cellular populations and factors of the marrow, including malignant plasma cells. By comparison of global gene expression profiling (GEP) derived from cultured MSCs, purified MM cells, and buffy coat BM samples as a source of hematopoietic cells, we identified a set of 485 probe sets encoding 350 specific MSC genes. GEP were available from baseline BM-BX from healthy donors, patients with MGUS, SMM, and presenting cases of GEP70 low-risk (LR, n=467) and high-risk (HR, n=64) MM. Also available are paired BM-BX and FL-BX cases (n=77). To address the post-treatment role of signatures on outcome, BM-BX were taken during the first year of maintenance (n=161) and complete remission (n=132). Associations between expression of MSC genes and progression-free survival (PFS) was assessed in Total Therapy (TT) 3-5 patients of whom 2/3 were randomly selected for training set and 1/3 used for test set. Immunohistochemistry for EDNRA and IGFBP2 was performed in bone biopsy sections. Cell lysates and conditioned media from normal MSCs cultured alone or preconditioned with HR MM cells underwent GEP and proteomics analysis (n=4). Results Our analysis identified 61 and 178 MSC probe sets differentially expressed (FDR

Description: Introduction: Certain studies suggest that multiple myeloma (MM) induces expansion of bone marrow (BM) mesenchymal stem cells (MSCs), but others showed induction of MSC senescence. MM cells suppress MSC lineages such as osteoblasts, while their effects on adipocytes remain to be elucidated. Recent studies identified "regulated" adipocytes that are smaller in size than large adipocytes that are constitutively present (Scheller et al, Nature Commun 2015), and that function as an endocrine tissue and regulators of hematopoiesis (Cawthorn et al, Cell Metab 2014), suggesting that BM adipocytes are functionally heterogeneous. We established a MSC gene signature in whole bone biopsies and showed that it gradually changes in different disease stages and is associated with outcome (Schinke et al, CCR 2018). The aim of the study was to identify changes in expression of MSC genes in BM of patients with high risk MM and in focal lesions (FLs), and to elucidate whether these changes reflect altered proportion and function of MSCs and their lineages. Methods: MSC gene expression in whole bone biopsies from normal donors (n=68), and patients with MGUS/SMM (n=90) and MM (n=531) was analyzed using global gene expression profiles. Unexpanded single MSCs from normal donors (n=3; 175 single MSCs) and MM patients (n=3; 162 single MSCs) were sorted by FACSAria and expression of mesenchymal cell, proliferation and senescence markers were analyzed by qRT-PCR using Fluidigm Biomark HD. Functionally, single MSCs were tested for their ability to multiply using supportive serum and MSC-conditioned media. Cell senescence was analyzed by SA-βGal staining. IGFBP2 and adiponectin protein were detected using immunohistochemistry (IHC). Numbers of IGFBP2+ cells were analyzed in biopsies from patients with MGUS/SMM, low risk (LR) and high risk (HR) MM (10 biopsies/group). Cultured MSCs were differentiated to adipocytes by treatment with dexamethasone, insulin and indomethacin for 3-4 weeks. The effects of recombinant IGF1 and IGFBP2 on MM cell growth were performed on BM-dependent MM lines (n=3) cultured in serum-free conditions for 48 hrs. Results: We compared MSC gene expression levels in random interstitial BM biopsies of patients with LR and HR MM, and in paired biopsy samples from random BM and FLs; 41 of the 345 MSC genes were differentially expressed in both comparisons. Most overexpressed genes were related to angiogenesis and ECM, including several collagen genes (e.g., COL4A1, POSTN, and HSPG2). Several underexpressed genes were associated with adipocytes, including IGFBP2 and aldo/keto reductases. To unravel whether these differences in gene expression reflect changes in the proportion of MSCs we tested expression of genes associated with MSCs, osteoblastogenesis, adipogenesis, proliferation and senescence in unexpanded single MSCs. MM single MSCs had significant reduction in expression of KI67 and increased expression of the senescence marker, CDKN2A/p16, whereas expression of other tested genes were modestly differentially expressed between the two groups. Functionally, unexpanded MM MSCs had increased SA-βGal expression, and only 65±8% of single MSCs divided at least once compared to 90±4% of their normal donor counterparts (p

Description: Introduction: Poor prognosis and drug resistance in multiple myeloma (MM) is associated with increased mutational load. APOBEC3B is a major contributor to mutagenesis, especially in myeloma patients with t(14;16) MAF subgroup. It was shown recently that presence of the APOBEC signature at diagnosis is an independent prognostic factor for progression free survival (PFS) and overall survival (OS). We hypothesized that high levels of APOBEC3B gene expression at diagnosis may also have a prognostic impact in myeloma. To consider APOBEC3B as a potential target for therapy more studies are necessary to understand how APOBEC3B expression is regulated and how APOBEC3B generates mutations. Methods: Gene expression profiling (GEP, U133 Plus 2.0) of MM patients was performed. APOBEC3B gene expression levels were investigated in plasma cells of healthy donors (HD; n=34), MGUS (n=154), smoldering myeloma (SMM; n=219), MM low risk (LR; n=739), MM high risk (HR; n=129), relapsed MM (RMM; n=74), and primary plasma cell leukemia (pPCL; n=19) samples. The samples from relapse were taken on or after the progression/relapse date but within 30 days after progression/relapse from Total Therapy trials 3, 4, 5 & 6. GEP70 score was used to separate samples into LR and HR groups. We also investigated APOBEC3B expression in different MM molecular subgroups and used logrank statistics with covariate frequency distribution to determine an optimal cut off APOBEC3B expression value. Gene expression was compared in cases with low expression of APOBEC3B (log210), and an optimal cut-point in APOBEC3B expression was identified with respect to PFS. To explore the role of MAF and the non-canonical NF-ĸB pathway we performed functional studies using a cellular model of MAF downregulation. TRIPZ lentiviral shRNA MAF knockdown in the RPMI8226 cell lines was used to explore MAF-dependent genes. NF-ĸB proteins, p52 and RelB, were investigated in the nuclear fraction by immunoblot analysis. Results: Expression of APOBEC3B in HD control samples (log2=10.9) was surprisingly higher than in MGUS (log2=9.51), SMM (log2=9.09), and LR (log2=9.40) and was comparable to HR (log2=10.4) and RMM (log2=10.6) groups. Expression levels of APOBEC3B were gradually increased as disease progressed from SMM to pPCL. The high expression of APOBEC3B in HD places plasma cells at risk of APOBEC induced mutagenesis where the regulation of APOBEC3B function is compromised. The correlation between APOBEC3B expression and GEP70 score in MM was 0.37, and there was a significant difference in APOBEC3B expression between GEP70 high and low risk groups (p=0.0003). An optimal cut-point in APOBEC3B expression of log2=10.2 resulted in a significant difference in PFS (median 5.7 yr vs.7.4 yr; p=0.0086) and OS (median 9.1 yr vs. not reached; p

Description: 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

Description: Key Points Using the largest set of patients with newly diagnosed myeloma, we identified 63 mutated driver genes. We identified oncogenic dependencies, particularly relating to primary translocations, indicating a nonrandom accumulation of genetic hits.