Expression of Anti-Lipopolysaccharide Factor Isoform 3 in Chlamydomonas reinhardtii Showing High Antimicrobial Activity

Antimicrobial peptides are a class of proteins with antibacterial functions. In this study, the anti-lipopolysaccharide factor isoform 3 gene (ALFPm3), encoding an antimicrobial peptide from Penaeus monodon with a super activity was expressed in Chlamydomonas reinhardtii, which would develop a microalga strain that can be used for the antimicrobial peptide production. To construct the expression cluster, namely pH2A-Pm3, the codon optimized ALFPm3 gene was fused with the ble reporter by 2A peptide and inserted into pH124 vector. The glass-bead method was performed to transform pH2A-Pm3 into C. reinhardtii CC-849. In addition to 8 μg/mL zeocin resistance selection, the C. reinhardtii transformants were further confirmed by genomic PCR and RT-PCR. Western blot analysis showed that the C. reinhardtii-derived ALFPm3 (cALFPm3) was successfully expressed in C. reinhardtii transformants and accounted for 0.35% of the total soluble protein (TSP). Furthermore, the results of antibacterial assay revealed that the cALFPm3 could significantly inhibit the growth of a variety of bacteria, including both Gram-negative bacteria and Gram-positive bacteria at a concentration of 0.77 μM. Especially, the inhibition could last longer than 24 h, which performed better than ampicillin. Hence, this study successfully developed a transgenic C. reinhardtii strain, which can produce the active ALFPm3 driven from P. monodon, providing a potential strategy to use C. reinhardtii as the cell factory to produce antimicrobial peptides.

PD-L1 expression in liver metastasis: its clinical significance and discordance with primary tumor in colorectal cancer

Background The outcomes of immune checkpoint inhibitors in cancer patients with liver metastases are poor, which may be related to a different tumor microenvironment in liver metastases from primary tumors. This study was aimed to analyze PD-L1 expression and the immune microenvironment status in liver metastases and compare the differences of PD-L1 expression between primary tumors and liver metastases of colorectal cancer. Methods 74 cases of pathologically confirmed colorectal cancer with liver metastasis underwent resection from our hospital were included. Tissue microarrays were used for the interpretation of PD-L1 expression, cluster of differentiation 4 (CD4) and CD8 density by immunohistochemistry. We evaluated the disparity between primary tumor and liver metastasis in PD-L1 expression, CD4 and CD8 density and analyzed the factors associated with obvious PD-L1 disparity. Results The expression of PD-L1 was positively related to the density of CD4 and CD8 in liver metastases. The expression of PD-L1 in liver metastases was higher than in primary tumors in certain subgroups, including patients with concurrent liver metastases (n = 63, p = 0.05), patients receiving concurrent resection of primary and metastatic tumors (n = 56, p = 0.04). The two subgroups generally reflected those without inconsistent external influences, such as treatment and temporal factors, between primary tumors and liver metastases. In these subgroups, the intrinsic differences of microenvironment between primary tumors and liver metastases could be identified. Furthermore, tumor differentiation [moderate vs. poor: OR = 0.23, 95% CI: 0.03–0.99, p = 0.05)] were demonstrated to be associated with obvious discordance of PD-L1 expression between primary tumors and liver metastases. Conclusions The expression of PD-L1 in liver metastases was higher than in primary tumors in subgroups, reflecting intrinsic microenvironment differences between primary and metastatic tumors. Obvious discordance of PD-L1 expression between primary tumor and liver metastasis was significantly related to the tumor differentiation.

Molecular and Expression Characterization of Monosomy 7 and Del(7q)

The loss of chromosome 7 (monosomy 7, -7) or its long arm [del(7q)] is a common karyotypic abnormality found in MDS and are associated with a poor prognosis. However recent studies may suggest a difference in survival outcomes. These lesions occur both independently and in a complex karyotype (CK). The leukemogenic features of -7/del7q can be explained through loss of heterozygosity or haploinsufficiency (HI) of key deleted genes. In addition, the phenotype of del(7q) and -7 might be further modified by the clonal architecture determining the mode of molecular evolution. Based on the hypothesis that a deletion will exert its biologic consequences in genes with HI expression and by co-associated mutations, a comprehensive analysis of genes on chr.7 was performed. Within a cohort of 8,161 patients with myeloid neoplasms (MN), we identified 511 with -7 (6%) and 143 with del(7q) (2%). In 29% of cases, del(7q) was found as an isolated alteration, while 90% of CK had del(7q); -7 showed similar percentages of isolated cases but was less common in CK (20%, 55%; respectively) cases. Del(7q) was significantly (P<.01) associated with MDS, while -7 was significantly (P=.0038) associated with sAML. When we focused on antecedent diagnosis, patients with -7 were more likely to have a previous diagnosis of aplastic anemia or chemotherapy treatment (60%; 41%, P<.01, for both). The most common co-associated molecular lesions with -7/del(7q) were: TP53 (31%), DNMT3A (13%), TET2 (13%), RUNX1 (12%), ASXL1 (11%), del(5q) (25%) and CK (54%). Del(7q) vs. -7 differed in the frequency of TP53 (39 vs. 29%; P=.03), DNMT3A (19 vs. 11%; P=.03), and IDH1/2 (13 vs. 52%; P<.01). Isolated -7/del(7q) was associated with mutations of TET2 (24% vs. 9%, P<.001), SRSF2 (12% vs. 3%, P<.001), EZH2 (10% vs. 3%, P<.001), and SETBP1 (8% vs. 2%; P<.001). Complex -7/del(7q) correlated with TP53 (39% vs. 4%; P<.01) and PTPN11 (9% vs. 6%; P=.02). When we focused on mutations on genes located in the 7q common deleted regions (CDR1, 7q22 and CDR2, 7q35-q36), EZH2 was the most represented 7q mutant gene (6 mutants in del(7q) and 24 mutants in -7) totaling 5% of all -7/del(7q) cases. Other mutated genes on 7q were: CUX1 in 1% del(7q) and 1% -7, CUL1 in 1% of del(7q), and LUC7L2 which was only found mutated in -7. Comparing the -7/del(7q) clone (calculated using allelic imbalance bio-analytic pipeline) to co-associated mutations allow us to identify the rank of -7/del(7q) in the clonal hierarchy: -7/del(7q) was an ancestral event in 58% and a secondary hit in 42% of the patients. When -7/del(7q) was the dominant hit, patients had fewer associated mutations, while in cases with secondary -7/del7q somatic mutations of TP53 (60%), IDH1/2 (30%), and DNMT3A (20%) were the ancestral hits suggesting a different clonal architecture according to -7/del(7q) clone size. Expression data was available for 49 of -7/del(7q) and 643 diploid cases for chr.7. Of the 694 informative genes on chr.7: 147 were deleted in all patients according to CNV analysis. We restricted the analysis to 15 uniformly HI genes selected because the expression inversely correlated with the level of 7q ploidy (ACTR3B, FASTK, GSTK1, IMPDH1, LRRC4, MEST, MGAM, NUP205, PRRT4, SLC37A3, SSBP1, TMEM209, TNPO3, ZC3HC1, ZNF277). Expression for these genes was then analyzed following normalization by -7/del7q clonal size. Unsupervised clustering grouped 72% of -7/del(7q) in one expression cluster. Classical -7/del(7q) signature genes fulfilled these criteria and with uniform HI in all cases. However, when we also included CUL1, CUX1, EZH2, KMT2C, and LUC7L2 to this analysis, the precision of -7/del(7q) clustering was 75% and defined a subcluster (#6). We were also able to identify cases previously misclassified (n=9) which were dispersed into 3 other clusters (14%, 8%, 3%) while 4% (n=23) of diploid cases were also misclassified and re-assigned into cluster 6. When we restricted the analysis to -7 cases only, a signature of 6 unique genes (C7orf43, CDK14, POLM, STAG3L5P, TRIM4) were found. Interestingly only POLM was on 7p, while the rest were on 7q22.1. In sum, we describe an integrated genomic and transcriptomic analysis of -7/del(7q) and we present data showing a complex heterogeneity of genes with HI expression which suggest that the clinical picture of patients carrying -7/del(7q) might be the result of a combination of clonality and HI. Disclosures Patel: Alexion: Other: educational speaker. Sekeres:Pfizer: Consultancy; Takeda/Millenium: Consultancy; BMS: Consultancy. Maciejewski:Alexion, BMS: Speakers Bureau; Novartis, Roche: Consultancy, Honoraria.

Combinatorial analysis of Saccharomyces cerevisiae regulatory elements

Gene expression in Saccharomyces cerevisiae is regulated at multiple levels. Genomic and epigenomic mapping of transcription factors and chromatin components has led to the definition and delineation of various regulatory elements. Enhancers, promoters, 5’ untranslated regions (5’UTR) and transcription terminators/3’ untranslated regions (3’UTR) have all been defined. However, the specific contributions of each of these features as part of a regulatory unit and the functional communications between these regulatory elements remains under explored.We built a combinatorial library of 26 different enhancers, core promoters, 5’UTRs and transcription terminators/3’UTRs. This library was analyzed with respect to gene expression in order to better understand the interactions between different regulatory elements. In the process we developed new methods to estimate the contribution of individual regulatory parts from just a few simple measurements. Our data show that different pairs of regulatory parts follow specific interaction rules affecting overall activity either positively or negatively. We find that while enhancers are the initiators of gene activity, core promoters modulate the levels of enhancer mediated expression. Cluster analysis based on expression show that TATA-box containing core promoters appear to increase enhancer-driven transcription to a greater extent than TATA-less promoters. Principal component analysis highlight outliers and suggest differences in mechanisms of regulation. These results provide a system to characterize regulatory elements and use these elements in the design of synthetic regulatory circuits.

The co-expression networks of differentially expressed RBPs with TFs and LncRNAs related to clinical TNM stages of cancers

Background RNA-binding proteins (RBPs) play important roles in cellular homeostasis by regulating the expression of thousands of transcripts, which have been reported to be involved in human tumorigenesis. Despite previous reports of the dysregulation of RBPs in cancers, the degree of dysregulation of RBPs in cancers and the intrinsic relevance between dysregulated RBPs and clinical TNM information remains unknown. Furthermore, the co-expressed networks of dysregulated RBPs with transcriptional factors and lncRNAs also require further investigation. Results Here, we firstly analyzed the deviations of expression levels of 1,542 RBPs from 20 cancer types and found that (1) RBPs are dysregulated in almost all 20 cancer types, especially in BLCA, COAD, READ, STAD, LUAD, LUSC and GBM with proportion of deviation larger than 300% compared with non-RBPs in normal tissues. (2) Up- and down-regulated RBPs also show opposed patterns of differential expression in cancers and normal tissues. In addition, down-regulated RBPs show a greater degree of dysregulated expression than up-regulated RBPs do. Secondly, we analyzed the intrinsic relevance between dysregulated RBPs and clinical TNM information and found that (3) Clinical TNM information for two cancer types—CHOL and KICH—is shown to be closely related to patterns of differentially expressed RBPs (DE RBPs) by co-expression cluster analysis. Thirdly, we identified ten key RBPs (seven down-regulated and three up-regulated) in CHOL and seven key RBPs (five down-regulated and two up-regulated) in KICH by analyzing co-expression correlation networks. Fourthly, we constructed the co-expression networks of key RBPs between 1,570 TFs and 4,147 lncRNAs for CHOL and KICH, respectively. Conclusions These results may provide an insight into the understanding of the functions of RBPs in human carcinogenesis. Furthermore, key RBPs and the co-expressed networks offer useful information for potential prognostic biomarkers and therapeutic targets for patients with cancers at the N and M stages in two cancer types CHOL and KICH.

MicroRNA Profiling in Low-Grade Ocular MALT and Diffuse Large B-Cell Lymphoma: A Role for MYC and NFKB1 Mediated Dysregulation of MicroRNA Expression in Aggressive Disease

Abstract 1600 Introduction: Although rare, ocular adnexal lymphomas (i.e. lymphoma of the orbit, eyelids, conjunctiva, lacrimal gland and lacrimal sac), are among the most common malignant tumors involving the ocular adnexal regions. The main subtypes are low-grade mucosa associated lymphoid tissue (MALT) lymphoma and aggressive diffuse large B cell lymphoma (DLBCL). In rare cases low-grade MALT lymphoma are reported to transform to DLBCL. It is unclear, however, which genetic events distinguish low-grade disease from aggressive, potentially fatal, disease. Material and methods: A total of 18 MALT lymphomas and 25 DLBCLs involving ocular adnexal sites were included in the study. All sections were analyzed immunohistochemically by two independent pathologists (ER, SH) using the following panel of antibodies: bcl-2, bcl-6, CD3, CD5, CD10, CD20, CD23, CD79α, cyclin D1, MUM-1 and Ki-67. Confirmed cases of DLBCL were categorized as either germinal centre B-cell-like (GCB) or non-GCB types according to the algorithm by Hans et al. Using LNA-based arrays from Exiqon, we performed global miRNA expression profiling of RNA extracted from formalin-fixed paraffin-embedded (FFPE) tissue. The most differentially expressed microRNAs were confirmed by RT-qPCR analyses. Microarray processing was performed using the R environment. Results: Of the18 MALT patients (pts.) 15 pts. (83%) presented with Stage I lymphoma and 3 pts. (17%) had Stage IV. The 5-year overall survival for the entire population was 77%. In the DLBCL group 13 pts. (52%) presented with Stage I lymphoma, 3 pts. (12%) Stage II lymphoma, 1 pt. (4%) Stage III and 8 pts. (32%) presented with Stage IV lymphoma. Nine of the DLBCLs were classified as GCB and 16 as non-GCB type. The 5-year overall survival for the entire group was only 13%. Our miR arrays and confirmatory qPCR analysis revealed 43 miRNAs with significantly altered expression profiles (41 down- and 2 upregulated) in DLBCL compared to MALT lymphoma. Seven of the miRNAs down-regulated in DLBCL relative to MALT lymphoma showed enrichment for a direct transcriptional repression by the oncoprotein MYC. Supervised hieracical clustering analysis identified tree clusters: Cluster 1: MALT (high expression), cluster 2: DLBCL (intermediate expression), cluster 3 DLBCL (low expression). Thus, apparently the DLBCLs in cluster 2 seem to resemble MALT more than DLBCLs in cluster 3. We also report loss of miRNAs involved in the regulation of NFKB1 and DNA methyltransferases in DLBCL vs MALT. Conclusion: We conclude that fundamental differences in miRNA expression exist between ocular adnexal MALT lymphoma and DLBCL. Among the possible consequences of altered miRNA expression are increased NF-kB signaling and DNA hypermethylation. However, in line with the recent observations in gastric MALT/DLBCL transformation1, we suggest the differences may at least in part be caused by MYC transcriptional regulation of miRNAs in aggressive cases. The fraction of DLBCL that is reported to arise from MALT is exceedingly low. However, in the current study we find a group of DLBCLs (cluster 2), whose level of MYC regulated miRNA expression is intermediate between MALT (cluster 1) and DLBCL (cluster 3). Thus it could be speculated whether cluster 2 DLBCLs have developed secondary to a preceding MALT lesion, which, however was not detected by histology. Disclosures: No relevant conflicts of interest to declare.