Bacteroidetes, Gamma- and Alphaproteobacteria, and constituted by a compact, conserved and positively-correlated group of anaerobes and other competitive aerobic chemoheterotrophs. Null-model test based on βNTI and RCBray indicated that stochastic processes, including dispersal limitation and undominated fractions, were the main forces driving community assembly. On the other hand, environmental factors, mainly temperature, organic matter and chlorophyll, were significantly correlated with bacterial richness, diversity and community structure. Moreover, metabolic and physiological features of the prokaryotic taxa were mapped to evaluate the adaptive mechanisms and functional composition of the benthic bacterial community. Our study is helpful to understand the structural and functional aspects, as well as the ecological and biogeochemical role of the benthic bacterial community in the Ross Sea.The benthic bacterial community in Antarctic continental shelf ecosystems are not well-documented. We collected 13 surface sediments from the Ross Sea, a biological hotspot in high-latitude maritime Antarctica undergoing rapid climate change and possible microflora shift, and aimed to study the diversity, structure and assembly mechanism of benthic bacterial community using both culture-dependent and -independent approaches. High-throughput sequencing of 16S rRNA gene amplicons revealed 370 OTUs distributed in 21 phyla and 284 genera. The bacterial community was dominated by  Marine sediments represent the largest reservoir of organic carbon and consequently support abundant and diverse benthic bacterial communities    . The insin situ using a ship-borne Seabird/Seapoint measurement system .Marine surface sediments were collected using box corer at 13 stations from the Ross Sea in February 2015. Each sample was divided into aliquots with a sterile trowel, and stored in sterilized plastic containers at 4 and −80°C, respectively. Salinity, temperature, pH, depth, chlorophyll and chromophoric dissolved organic matter (CDOM) were measured Two gram of each sediment stored at 4°C was measured out with a stainless steel spoon and subsequently resuspended in 20 mL sterile seawater. The suspension were serially diluted and spread on Marine Agar 2216 , MC  and subsequently mix together. The V4–V5 region of 16S rRNA gene was amplified using inside primers (5′-TTCCCTACACGACGCTCTTCCGATCT-GTGCCAGCMGCCGCGGTAA-3′ and 5′-GAGTTCCTTGGCACCCGAGAATTCCA-CCGTCAATTCMTTTGAGTTT-3′). The PCR products were purified using AxyPrep™ DNA Gel Extraction kit , and subsequently amplified using outside primers to add sequencing primers, barcodes and adapters. After gel-purification, the copies of target fragments were quantified using FTC-3000 Real-Time PCR system . The DNA library (2 × 300 bp) was sequenced on an Illumina MiSeq platform  in TinyGene .http://mem.rcees.ac.cn) was used to plot the Venn diagram, taxonomically classify the representative sequences in SILVA database version 132, and infer species functions with FAPROTAX .The raw data containing complete barcode sequences were separated into fastq files to obtain valid reads. The paired-end sequences were merged and quality filtered using the Usearch commands of fastq_mergepairs and fastq_filter (version 10.0.240), respectively Edgar, . The UPAT-test and ANOSIM were used to test the differences for single and multiple parameters, respectively, between the inshore and offshore groups. The alpha diversity  were estimated using QIIME2 with rarified OTU table  based on R to determine the correlations between geographic distance, environmental variables, α- and β-diversity. Permutation test of multivariate homogeneity of group dispersions (variances) was performed using the function “betadisper” of R (version 3.5.1) package “vegan” (version 2.5.2).Bray) based on null model test of the Bray-Curtis taxonomic β-diversity, were calculated using the R package “picante” (version 1.7) and “vegan” (version 2.5-2).A null-model-based statistical framework was applied to determine the relative impact of stochastic and deterministic processes on community assembly , concentration of chlorophyll (p = 9e-4) and CDOM (p = 0.002) than the offshore samples . Whereas, salinity, pH and depth showed no significant difference between the two groups of samples. According to Spearman's rank correlation analysis (p < 1e-6), CDOM , and salinity . In addition, the concentration of chlorophyll was positively correlated with CDOM .Geographical and chemical information of the 13 sediment samples were presented in analysis , temperaAfter sequencing and quality check, 450,029 valid reads were retrieved from 13 sediment samples . After paired-reads assembly, quality filtering and chimera removal, 284,963 sequences , with an average length of ca. 415 bp, were finally obtained and subsequently clustered into 370 OTUs . The insp < 1e-4 based on Chao1 index; p < 7e-7 based on ACE index) and diversity  than the offshore samples. Specifically, the highest richness and diversity occurred at station R02, whereas the lowest were found at station R17.For all 13 samples, the Good's coverage values ranged from 99.81 to 99.93% , and theR = 0.51, p < 0.003). The results of permutational analysis of group dispersion (PERMDISP)   .Bacteroidetes  and Proteobacteria  dominated the overall bacterial community, followed by Firmicutes , Fusobacteria  and Planctomycetes  (Proteobacteria (188 OTUs) and Bacteroidetes (78 OTUs) were also the most diverse phyla. At the class level, Bacteroidia (45.92%), Gammaproteobacteria (34.15%), Alphaproteobacteria (11.25%), Fusobacteriia (2.04%), Clostridia (1.78%), and Deltaproteobacteria (1.11%) were the most abundant classes (>1%). Bacteroidetes, Gammaproteobacteria, Alphaproteobacteria, Firmicutes, Fusobacteria, and Actinobacteria were shared in all 13 sediments.The 370 OTUs were classified into 21 phyla, 42 classes, 107 orders, 174 families, and 284 genera. In total,  11.17%) . These 5Bacteroidetes was predominated by Flavobacteriales , Bacteroidales , and Cytophagales . Gammaproteobacteria was mainly comprised of Alteromonadales (16.78%), Oceanospirillales (6.14%), Pseudomonadales (4.33%) and Thiotrichales (1.84%). Most Alphaproteobacteria were classified to Sphingomonadales (5.36%), Rhodobacterales (1.78%), and Rhodospirillales (1.06%). Most sequences of Firmicutes belonged to Clostridiales . All Fusobacteria (2.04%) sequences belonged to the genus Fusobacterium.Marinobacter (13.92%), Bacteroides (10.37%), Salegentibacter (7.78%), Bizionia (7.70%), an uncultured Cryomorphaceae genus (7.45%), Maribacter (3.61%), Pseudomonas (2.60%), Fusobacterium (2.04%), Escherichia-Shigella (1.24%), and Halomonas (1.19%), with abundance >1%, were shared in all 13 samples. Other abundant genera included Gillisia (5.47%), Sphingorhabdus (4.07%), Idiomarina (2.57%), Cobetia (2.39%), Arenibacter (1.86%), Alcanivorax (1.74%), Psychrobacter (1.65%), Sulfitobacter (1.23%), and Altererythrobacter (1.13%).At the genus level, Alcanivoracaceae, Cytophagales, Cyclobacteriaceae, Caulobacterales, Magnetospiraceae, Hyphomonadaceae, Cellvibrionales, Pseudohongiellaceae, and Rhizobiales were significantly more abundant in inshore sediments than in offshore ones  . A more rigorous methodology (ANCOM) that accounts for compositional constraints indicated that the abundance of Microbacteriaceae and Psychrobacter differed significantly between inshore and offshore groups  . By conte groups .Bacteroides , Lachnospiraceae , Phascolarctobacterium (OTU37), Fusobacterium (OTU47), and Parabacteroides distasonis (OTU79), which are anaerobic taxa according to Bergey's Manual of Systematic Bacteriology , OTU97 (Maribacter), OTU164 (Rhodospirillaceae), OTU13 (Erythrobacteraceae), OTU294 , OTU80 (Marinobacter), OTU217 (Phycisphaeraceae), OTU78 (Gillisia), and OTU219 (Roseivirga) (Bizionia), OTU24 (Marinobacter), and OTU45  (Marinobacter), OTU228 (Bizionia), OTU87 (Psychrobacter pacificensis), OTU82 (Psychrobacter), OTU150 (Erythrobacteraceae), and OTU97 (Maribacter) were key nodes connecting the competitive taxa  . In offsnadales) . In all ive taxa . These Oive taxa , indicatAlteromonadales, Oceanospirillales, Sphingomonadales, Flavobacteriaceae, and Cyclobacteriaceae. These taxa have been reported as widespread and abundant degraders of dissolved organic carbon in seawater and marine sediments  and aerobic chemoheterotrophs  were predicted in offshore group than in inshore group. Moreover, bacteria associated with anaerobic fermentation accounted for 19.68% in inshore group and 14.41% in offshore group, respectively, but with no significant difference as evaluated by Welch's t-test. Some possible adaptive mechanisms of the bacterial community to environmental stresses were also revealed, such as nitrate/nitrite reduction, fumarate respiration, sulfur respiration, arsenate respiration, dark sulfur oxidation, manganese oxidation, utilization of xylan, cellulose, chitin, hydrocarbon, plastic, and C1 compounds.FAPROTAX was used to map prokaryotic taxa to metabolic and ecological functions . Most ofA null-model-based statistical and quantitative framework was used to disentangle the community assembly mechanism and quantify the relative importance of the stochastic and deterministic processes  including dispersal, diversification and drift. According to Bray values of the pairwise comparisons with |βNTI| <2 were >0.95 (α = 0.05 by a two-tailed test), indicating the given pairs shared significantly less similarity of community structure than the null expectation. Thus, dispersal limitation, which would lead to less similar communities, was quantified as the dominant fraction of the pairwise comparisons with |βNTI| <2 and RCBray >0.95.Secondly, the null-model-based taxonomic β-diversity metrics RCBray| <0.95 were inferentially controlled by “undominated” fraction, which was mostly consisted of diversification and/or drift and could not be further partitioned at this moment.At last, the pairwise comparisons with |βNTI| <2 and |RCThe assembly processes across all pairwise combinations were listed in Spearman's rank correlation analysis was performed to assess the relationships between environmental variables and α-diversity indices . BacteriAccording to Mantel test , temperaProteobacteria 73.61%, Bacteroidetes 17.81%, Actinobacteria 5.09% and Firmicutes 3.50%), 6 classes , 14 orders, 26 families and 40 established genera. At the genus level, the abundant taxa included Halomonas (22.22%), Marinobacter (20.20%), Pseudomonas (7.58%), Salegentibacter (6.06%), Salinibacterium (5.30%), Arenibacter (4.55%), Idiomarina (4.55%), Thalassospira (4.29%), Bacillus (3.79%), Gillisia (3.03%), Martelella (2.02%), Methylophaga (1.52%), Planomicrobium (1.26%), Pseudidiomarina (1.26%), Roseivirga (1.26%), and Loktanella (1.01%).Conventional spread-plate method was used to isolate culturable bacteria. In total, 629 bacterial isolates were obtained from 13 sediment samples . The taxActinobacteria, Alphaproteobacteria, Cytophagales, Bacillus, Pseudomonas, and Marinobacter, were not detected by culture-independent technique , R14-M19/OTU299 (Marinobacter), JB01-H16B/OTU24 (Marinobacter), JB01-H12/OTU45 , R14-H23/OTU304 (Pseudomonadaceae), JB01-H9/OTU34 (Rhodobacteraceae), and JB01-H10/OTU69  , R14-M6/OTU84 (Aurantimonadaceae), R18H24/OTU104 (Pseudomonas), R04-H28/OTU86 (Brevundimonas), and OTU113 (Zhouia). Most of the culture-dependent OTUs could be isolated on MA plates, whereas 7 out of 60 OTUs could only be isolated by MC and/or LC plates.With a sequence identity cutoff of 97%, the 629 isolates obtained from conventional spread-plate method were clustered into 60 OTUs, 47 of which were also discovered by culture-independent technique . Interesechnique . When shechnique , the bacibacter) . HoweverThe bacterial community in Antarctic marine benthic ecosystems were barely studied, compared with in terrestrial habitats, sea ice and seawater of Antarctica. Especially in higher latitude Antarctic continental shelf, only few sediments from coastal shallows and individual stations were studied for bacterial diversity and community composition (Carr et al., The bacterial richness and diversity in 13 sediments of the Ross Sea were lower than in the sediments beneath the Ross Ice Shelf (Carr et al., Bacteroidetes, Gamma and Alphaproteobacteria, which also dominated other various marine and terrestrial habitats in polar regions (Carr et al., Actinobacteria, Alpha-, Beta- and Gammaproteobacteria, Acidobacteria, and Planctomycetes (Malard and Pearce, Bacteroidetes, Gamma- and Alphaproteobacteria were reported to have adaptive mechanisms in such harsh environments (Hamdan et al., The most abundant and diverse taxa in sediments of the Ross Sea were Gammaproteobacteria and Cytophaga-Flavobacteria-Bacteroides group were reported to be associated with algal blooms and capable of degrading complex polysaccharides (Bowman et al., Alcanivorax, Marinobacter, Sphingomonas, and Rhodococcus, were able to utilize alkanes and/or polycyclic aromatic hydrocarbons produced by marine algae, natural hydrocarbon seeps and anthropogenic activities in marine ecosystems (Wang and Shao, Methylococcales was a key component of consuming methane and other C1 compounds to produce organics and energy (Ruff et al., Gammaproteobacteria (Dyksma et al., Psychroserpens, Psychroflexus, Psychrobacter, some members of Marinobacter, Halomonas, Gillisia, Pseudomonas, and Flavobacteriaceae were also reported to show adaptive characteristics to low temperature, such as production of exopolysaccharides, cold active enzymes and pigments, and changes in membrane lipid composition and fluidity (Fan et al., The bacterial community in the Ross Sea sediments has developed adaptive mechanisms to environmental stresses including oligotrophy, anoxia, and low temperature. The aerobic chemoheterotrophs displayed competitive relationships in network analysis , emphasiHow did this characteristic bacterial community form? Although the debate between niche and neutral theory is one of the central issues of community ecology in last a couple of decades, recent conclusions deemed that both deterministic and stochastic processes jointly drive the assembly of communities (Cira et al., On the other hand, the deterministic process also played non-negligible roles in shaping community structure. Correlation analysis and Mantel test suggested that bacterial richness, diversity and structure were significantly influenced by CDOM, temperature and chlorophyll. Since majority of the bacteria detected in this study were chemoheterotrophs, it was logical that CDOM positively correlated with bacterial richness and diversity. Temperature, organic matter and chlorophyll were frequently reported to account for variability of bacterial communities in polar marine sediments and other deep sea and benthic environments (Learman et al., In consistent with some other researches, this study found that bacterial communities in inshore sediments showed higher species richness and α-diversity than in offshore sediments (Semprucci et al., The present study found that temperature was positively correlated with chlorophyll and CDOM, and chlorophyll was positively correlated with CDOM. In the climate warming scenario, temperature elevation significantly increased the release of land-derived materials into the aquatic environments, the uptake of inorganic nutrients, the chlorophyll concentration, the primary production, and subsequently the concentration of organic matter in marine sediments (Cormier et al., Isolating and characterizing microorganisms could provide insights into their phylogenetic systematics, metabolic reactions and physiological properties, and help to understand the formation, persistence, adaptation mechanisms and ecological functions of microbial community. Moreover, Antarctic continental shelf is a fertile ground for bioprospecting, attracting increasing attention and research efforts recently (Van Trappen et al., Actinobacteria, Alphaproteobacteria, and Bacillales, which were reported to be underestimated during high-throughput sequencing (Guo and Zhang, Pseudomonas and Marinobacter were abundant taxa as revealed by both techniques, Pseudomonas sp. JB01-H21 and Marinobacter sp. R17-H24 were not detected by high-throughput sequencing based on 16S rRNA gene amplicons. Due to the huge number, small size and widely distribution of microbes in environment, it has been proved that the conventional sampling process and high-throughput sequencing of 16S rRNA gene amplicons would dramatically underestimated the bacterial diversity, especially for the rare community members (Zhou et al., Compared with culture-dependent techniques which had limitations because of the selectivity of isolation media and culture conditions, sequencing-based molecular techniques were considered to provide better resolution of microbial community composition, however, it still showed biases. Although the Good's coverage values and rarefaction curves indicated that overwhelming majority of bacteria were revealed from the sediments, there were still 13 OTUs only detected by culture-dependent technique . Most ofBacteroidetes, Gamma- and Alphaproteobacteria, which are abundant and widely distributed in worldwide seawaters and marine sediments. Previous studies focused on the effect of environmental factors on bacterial community of maritime Antarctica (Carr et al., In summary, the present study provided detailed insights into the diversity, structure and assembly mechanisms of the benthic bacterial community in the Ross Sea, using both culture-dependent and -independent approaches. The bacterial community was dominated by SRR8505880 to SRR8505892. The 16S rRNA gene sequences of 629 isolates were submitted to NCBI GenBank database under the accession numbers of MK476530 to MK477158.The raw data obtained by high-throughput sequencing of 16S rRNA gene amplicons in this study were deposited in NCBI Sequence Read Archive database under the accession numbers of H-HZ and QY designed the study and reviewed the manuscript prior to submission. X-BH collected the sediment samples and geochemical data. M-XZ and MC processed the samples for sequencing. A-ZL performed the metagenomics analysis, generated all tables and figures, and wrote the draft manuscript. A-ZL and YZ performed the statistical analysis.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


However, in the vast majority of human tumors the molecular basis of CIN remains unknown, partly because not all genes controlling chromosome transmission have yet been identified. To address this question, we developed an experimental high-throughput imaging (HTI) siRNA assay that allows the identification of novel CIN genes. Our method uses a human artificial chromosome (HAC) expressing the GFP transgene. When this assay was applied to screen an siRNA library of protein kinases, we identified PINK1, TRIO, IRAK1, PNCK, and TAOK1 as potential novel genes whose knockdown induces various mitotic abnormalities and results in chromosome loss. The HAC-based assay can be applied for screening different siRNA libraries  to identify additional genes involved in CIN. Identification of the complete spectrum of CIN genes will reveal new insights into mechanisms of chromosome segregation and may expedite the development of novel therapeutic strategies to target the CIN phenotype in cancer cells.One of the hallmarks of cancer is  Chromosome instability (CIN), involving the unequal distribution of chromosomes to daughter cells during mitosis, is observed in the majority of solid tumors . CIN maySaccharomyces cerevisiae have revealed 692 genes  terms associated with proper chromosomal transmission, and systematic CIN gene screens in the yeast 92 genes , 2012. R92 genes . Thus, t92 genes , 2012. B92 genes . CharactGenome-wide siRNA screens have been used to interrogate a variety of molecular mechanisms related to increased sensitivity to ionizing radiation or spontaneous gamma H2AX (phosphorylated histone H2AX at serine 139) . In a laS. cerevisiae  siRNA assay to identify unknown human CIN genes. This assay is based on a nonessential human artificial chromosome (HAC) expressing a short half-life green fluorescent protein (GFP). This HAC, like other HACs, follows the rules of mitosis and chromosome segregation just like the natural chromosomes during the cell cycle progression . It is wrevisiae . We usedtetO-HAC  containing two modified short half-life green fluorescent transgenes. More precisely, the plasmid encodes two fusions of GFP: GFP-fused with a 30–120 amino acid domain of CDT1, and GFP-fused with a 1–110 amino acid domain of geminin DNA replication inhibitor (GMNN). CDT1 and GMNN are the marker-proteins for different cell cycle stages  and lose the GFP signal within hours after HAC loss. We called this class of GFP-fusions “destabilized GFP” (dGFP). The p264-GFP-CDT1-GFP-GEMININ plasmid was inserted into the single loxP site of an alphoidtetO-HAC in hamster CHO cells by Cre-lox-mediated recombination producing HAC/dGFP, which was then transferred via microcell-mediated chromosome transfer (MMCT) to the human HT1080 fibrosarcoma cell line .In the current study, we hypothesized that siRNA-dependent knockdown of the genes that are essential for proper transmission of natural human chromosomes would induce HAC loss. To develop the assay, the plasmid p264-GFP-CDT1-GFP-GEMININ was constructed  no change in the percentage of GFP-expressing cells (no effect on HAC stability), or (2) an increase in the percentage of GFP-negative cells if siRNAs induce chromosome segregation errors C. Controalf-life . In thisCENPA encoding the centromere-specific histone H3 variant CENPA   , OIP5 entromeres , and SKA binding .CENPA, CENPN, CENPE, AURKB, OIP5, or SKA3 was measured by three independent techniques: flow cytometry (FACS), HTI, and FISH . Knockdown of OIP5 and SKA3 showed the strongest effect, with significant HAC/dGFP loss at 96 h after siRNA transfection. Following these experiments, siRNAs against SKA3 and OIP5 were used as positive controls; more specifically, SKA3 for siRNA screening (HTI) and OIP5 for FACS experiments.Mitotic stability of the HAC/dGFP in HT1080 human cells transfected with siRNAs against either and FISH A–D. The In large-scale screens for chromosome instability in yeast, 937 CIN genes were identified . Most ofSupplemental Table S1). This allowed us to use the verified siRNAs for cell treatment. The following gene orthologs were selected for the analysis: CNOT6, NAT10, PIGB, TANGO6, PIGU, PIGS, GPN2, PRC1, IPO11, CIAO2B, NPEPPS, RTN2, UAP1, MSI1, AP2B1, PPIP5K1, WDR76, C12orf10, PLCD3, MUC4, NF1, RAB1A, MEMO1, SMARCAD1, RPL13, XAB2, MYO5B, and PRKCE. They are orthologs of yeast proteins whose down-regulation in yeast leads to chromosomal instability . Among 28 siRNA knockdowns analyzed, only the knockdown of PRKCE induced a significant increase in HAC/dGFP loss. PRKCE is an ortholog of yeast PKC1, which is required for yeast cell growth and division . In this arrayed library, each well contained a pool of four independent siRNAs targeting the same gene. We optimized the transfection conditions of the library to maximize cell viability while still maintaining efficient siRNA knockdown  . In these experiments, SKA3 siRNA knockdown was used as a positive control. Z-score  . In further analysis we focused on siRNAs that did not show high cytotoxic effects (P < 0.05) when compared to the negative control. Among 714 genes analyzed, the strongest effect on HAC/dGFP stability was detected after siRNA-mediated knockdown of the ITPKB, IRAK1, MYLK, TNK2, STK38, BLK, MAPK7, FRK, TRIO, STK11, CRIM1, CSK, PDXK, PHKG1, KSR2, CAMK2G, PHKB, CSNK1G2, TAOK1, MYLK4, NYD-SP25, RBKS, TTBK1, PNCK, PINK1, BTK, HIPK2, BUB1, ATM, BUB1B, PRKCE, TAOK1, and NEK9 genes. Silencing efficiency of the proteins was monitored by western blot analysis .A siRNA library against 714 genes previously annotated as either kinases or phosphatases was used for analysis . Supplemental Table S8). After these experiments, a final list of the CIN candidates included the following genes: PINK1, STK38, TRIO, IRAK1, PNCK, TAOK1, BUB1, BUB1B, and PRKCE . It is worth noting that the human BUB1 and BUB1B genes are known to promote the spindle assembly checkpoint, which is important for proper chromosome transmission  cells. This assay revealed a significant difference in NPB formation between cells treated with scrambled siRNA (nontargeting) and the cells depleted for these genes  . Indeed, inhibition of PRKCE has previously been shown to result in chromosome bridging  . When the same experiments were performed in human fibrosarcoma HT1080 cells, the percentage of NPBs formation was elevated after knockdown of all nine of these proteins compared to the control . The percentage of MNi formation was also elevated after knockdown of these genes except for TRIO compared to the control .Micronucleus formation assays (MNi) have been extensively used to evaluate chromosome instability . In addise genes A,B,D. Thbridging . In our PINK1, TRIO, IRAK1, TAOK1, and PNCK gene products are required for accurate chromosome transmission. Identification of BUB1, BUB1B, STK38, and PRKCE genes, which were previously known to be involved in proper chromosome transmission  support the hypothesis that smission , in thesPINK1, STK38, IRAK1, PNCK, TAOK1, TRIO, PRKCE, BUB1, and BUB1B genes with an antibody against phosphorylated histone gamma H2AX. A statistically significant increase of gamma H2AX foci in interphase was observed after knockdown of the four genes, PINK1, TRIO, STK38, and BUB1 (PINK1 (20% of cells) compared to control levels of DNA damage in RPE cells (<3%). Thus, in RPE cells chromosome instability after knockdown of PINK1, TRIO, STK38, BUB1, and BUB1B genes is accompanied by induction of DSBs. On the contrary, the number of H2AX foci in HT1080 cells changed little after siRNA knockdown of the same genes, possibly because of the high endogenous level of DNA damage in these cells. The negative control in HT1080 cells showed ∼8% of spontaneous DNA damage, masking possible effects of siRNA treatment .To determine whether the observed chromosome instability was accompanied by an increased number of double-stranded breaks (DSBs), we stained RPE cells after knockdown of and BUB1 E,F. The To explore the mechanism(s) by which knockdown of the newly identified CIN genes results in chromosome loss, we performed an additional set of siRNA-mediated knockdown experiments. To rule out cancer cell line–specific phenotypes in HT1080, all experiments were also performed in nontransformed RPE cells. Changes affecting only HT1080 cells were considered specific for this cell line.PINK1, STK38, TRIO, PNCK, IRAK1, TAOK1, BUB1, or BUB1B. In RPE cells, no statistically significant increase in the mitotic index was observed , although we could observe an increased number of prophases following STK38 knockdown . In HT1080 cells, we observed a statistically significant increase of the mitotic index, but no statistically significant change in the distribution of mitotic phases following knockdown of PINK1 and IRAK1 . Knockdown of PINK1, STK38, TRIO, TAOK1, and PRKCE in RPE cells led to an increased number of mitotic abnormalities ; whereas in HT1080 cells, this phenotype was observed only after knockdown of STK38 and TAOK1 . The results of these experiments suggest that PINK1, STK38, TRIO, TAOK1, and PRKCE genes may be necessary for mitotic progression and for maintenance of the cell cycle. Earlier it was shown that the STK38 gene regulates essential processes, such as centrosome duplication (PRKCE is involved in mitotic spindle organization (We first measured the mitotic index in RPE and HT1080 cells after siRNA knockdown of lication  and celllication  and PRKCnization  that supSTK38 caused problems with mitotic spindle formation (absence of the connection to one spindle pole) in prophase. Knockdown of PINK1 led to severe problems with chromosome alignment in metaphase, anaphase, as well as lagging chromosomes in early telophase. Knockdown of TRIO, BUB1, and BUB1B resulted in formation of chromatin bridges in anaphase. All these phenotypes can lead to aneuploidy, chromosome damage, and micronucleus formation. In HT1080 cells, we also observed a wide range of mitotic abnormalities in siRNA knockdown cells (PINK1 indicated severe problems with spindle formation in metaphase (multiple polarity). Knockdown of TRIO correlated with chromosomal loss at anaphase possibly caused by kinetochore attachment problems. Knockdown of BUB1 and BUB1B showed lagging and bridging chromosomes at anaphase.We next characterized in more detail the mitotic defects at the different stages of mitosis observed after siRNA knockdown of CIN gene candidates in RPE and HT1080 cells. The cells were stained with antibodies against tubulin alpha to visualize the mitotic spindles  and agaiwn cells B. SimilaPINK1 and TRIO in RPE cells and tested their ability to rescue the knockdown phenotypes. In both cases, mitotic abnormalities caused by knockdown of these genes were rescued by expression of the corresponding cDNAs . In addition, to evaluate the observed phenotypes, we performed live imaging analyses of PINK1, TRIO, IRAK1, PNCK, TAOK1, and STK38 genes . The analyses confirmed the mitotic defects observed after siRNA knockdown of these genes . Live imaging analyses of PINK1, IRAK1, TRIO, and STK38 showed that formation of lagging chromosomes leads to micronuclei formation.In control siRNA rescue experiments, we attempted to exclude that off-target effects might account for the most unexpected mitotic abnormalities induced by siRNA-mediated knockdown of these genes. We therefore ectopically expressed siRNA-resistant cDNAs encoding Supplemental Methods) for the five kinases of greatest interest to us  and determined the resulting phenotypes. STK38 was included as a control because, as previously shown, this gene is involved in proper chromosome transmission . All these genes have previously been associated with human disorders. Earlier biochemical and genetic studies revealed that PINK1, which has been associated to Parkinson's disease, works together with PRKN  in the pathway involved in mitochondrial quality control   , 2012.PINK1, STK38, TRIO, TAOK1, and PRKCE causes problems during mitosis progression. More specifically, knockdown of PINK1 leads to severe defects in metaphase and anaphase chromosome alignment as well as lagging chromosomes in telophase . Knockdown of STK38 was associated with problems in mitotic spindle formation in prophase, whereas knockdown of TRIO, BUB1, and BUB1B was associated with formation of chromatin bridges in anaphase . All these phenotypes can lead to aneuploidy, chromosome damage, and micronucleation formation. We also showed that knockdown of PINK1, TRIO, STK38, BUB1, and BUB1B induces formation of DSBs that may also cause chromosome instability.Here, we went on to show that siRNA knockdown of PINK1, TRIO, IRAK1, BUB1, and BUB1B and an increased level of cytogenetic alterations .Our results are supported by bioinformatical data. The NCI-60 cell lines derived from nine tissues of origin types of cancer have been characterized for multiple parameters, including transcript expression , 2015. BSupplemental Fig. S13). The most frequent relationship was protein–protein interactions (54), followed by activation (27) and phosphorylation (21) . Knowledge about interacting proteins is crucial for understanding their biological functions, which can be performed by studying networks of these interactions. Also, this network may also help in planning the future experiments to shed light on the role of these kinases in the complex process of chromosome transmission.In addition, we constructed a gene interaction network map that represents potential functional relationships among the CIN kinases, PINK1, STK38, TRIO, IRAK1, PNCK, and TAOK, and the proteins involved in cell division and cell cycle regulation . The primers contain EcoRI restriction sites at the 5′ ends of the fragments, which are necessary for the further steps of construction. The amplified products were ligated with the EcoRI-digested pCX vector producing the pCX-GFP-CDT1 vector of 5813 bp in length and pCX-GFP-Geminin vector of 5861 bp in length. Each sensor and a green fluorescent protein are under the SV40 virus promoter . The second step of construction included restriction of the pCX-GFP-CDT1 and pCX-GFP-Geminin vectors with BamHI/SpeI and AvrII/SpeI, respectively, that produced two fragments of 465 and 3700 bp in length, respectively. The third step of construction included ligation of the BamHI/SpeI pCX-GFP-CDT1 fragment with the linearized p264 vector . The fourth step of construction included ligation of the AvrII/SpeI pCX-GFP-Geminin fragment with the AvrII-digested p264_GFP-CDT1 vector producing the p264_GFP-CDT1-GFP-GEMININ vector . The final p264-GFP-CDT1-GFP-GEMININ vector contains the open reading frames of GFP-CDT1 and GFP-GMNN, each under control of the CAG promoter that allows their expression in hamster CHO and human HT1080 cells. The final p264-GFP-CDT1-GFP-GEMININ vector contains a single loxP site and a 3′ part of the HPRT gene flanked by the cHS4 insulators that is essential for its loading into the alphoidtetO-HAC by Cre-lox-mediated recombination. Primers used for plasmids construction are provided in Supplemental Table S7.At the first step of construction, the 1043- and 1091-bp fragments of the cell cycle sensors, GFP-CDT1 and GFP-GMNN, containing the coding region of the GFP were PCR-amplified from GFP-CDT1 and GFP-GMNN synthetized gBlocks (Integrated DNA Technologies [IDT]) using the corresponding primers (4 vector  producintetO-HAC with a single loxP site by lipofection using X-tremeGENE 9 (Roche). HPRT-positive colonies were selected after 2–3 wk growth in HAT medium. For each experiment, from 10 to 15 clones were usually selected. The correct loading of the p264-GFP-CDT1-GFP-GEMININ vector in the HAC was confirmed by PCR using a specific pair of primers to detect reconstitution of the HPRT gene . The final construct was designated as HAC/dGFP .Two micrograms of the p264-GFP-CDT1-GFP-GEMININ vector and 0.2 µg of the Cre expressing pCpG-iCre vector DNA were cotransfected into HPRT-deficient hamster CHO cells containing the alphoidMMCT transfer of HAC/dGFP from hamster CHO cells to human HT1080 cells was performed as described previously .Supplemental Methods).The presence of the HAC in an autonomous form was confirmed by FISH analysis as previously described . Per one well of a six-well plate, 150,000 cells were seeded and transfected by 2 µg of each plasmid using a standard protocol provided by DNA Transfection Reagent X-tremeGENE 9 (Roche). To select the cells with stable GFP expression, we used MoFlo Astrios EQ cell sorter (Beckman Coulter). The cells were sorted and seeded on 96-well plate. The clones with the brightest GFP expression were taken for the time-lapse microscopy experiment.Human HT1080 cells were transfected with the pCX-CDT1-GFP and pCX-GEMININ-GFP vectors described above (2) on a separate µ-Slide 8 Well (ibidi) in DMEM (Thermo Fisher Scientific) supplemented with 10% (v/v) fetal bovine serum (Clontech Laboratories) at 37°C in 5% CO2 atmosphere. Time-lapse imaging was performed using the FV1200 confocal laser scanning microscopy system equipped with the objective lens . A 405 nm LD Laser with Integrated Transmitted Light Photomultiplier Detector and 488 nm Argon laser with High-Sensitivity Detector (GaAsP) were used. To avoid cross detection, the images were acquired sequentially at 488 nm (Argon) and 405 nm (LD). The transmitted light signal and GFP fluorescence were merged for each confocal image. The recording interval was 15 min.HT1080 cells containing HAC/dGFP and HT1080 cells transfected by either pCX-CDT1-GFP or pCX-GEMININ-GFP vectors were seeded (1000 cells per cm4 events (at minimum). Flow cytometry analysis was primarily performed using C-Flow Plus (BD Biosciences).The HT1080 containing HAC/dGFP cells were grown for 96 h after transfection, harvested by trypsin-treatment, and resuspended in PBS containing 3 µM DRAQ7. Flow cytometry was performed on an BD Accuri C6. All samples were vortexed immediately before flow cytometry examination. Fluorescence of GFP-positive cells was measured by the 488 nm laser and detected at 510 nm. The dead cells were counted by DRAQ7 fluorescence excited by the 640 nm laser and detected at 722 nm. Samples were acquired in at least three separate triplicates for 30 sec or 1 × 10Supplemental Table S1) purchased from Dharmacon. For siRNA treatment, 12.5 × 103/well cells were seeded in 24-well plates a day before the experiment. Cells were transfected with each siRNA (a working concentration 17 nM) using Lipofectamine RNAiMAX (Thermo Fisher Scientific) following the manufacturer's protocol. Cells were grown without blasticidine for 96 h after transfection. Silencing efficiency of each protein was monitored by western blot analysis . After 96 h, the cells were collected and analyzed by flow cytometry to detect the proportion of cells that reactivated GFP fluorescence or lost GFP signal. All the experiments were performed in triplicate.The genes of interest were knocked down using siRNAs , which were purchased from Dharmacon. For siRNA treatment, 12.5 × 103/well cells were seeded in 24-well plates a day before the experiment. Cells were transfected with each siRNA (a working concentration of 12 nM) using Lipofectamine RNAiMAX (Thermo Fisher Scientific). To complement siRNA effect, cotransfection of siRNA and cDNA resistant to siRNA was performed . Cells were grown for 96 h after transfection. After 96 h, the cells were fixed, immunostained, and analyzed by confocal microscopy. All the experiments were performed in triplicates.The rescue experiments were performed as described in the Lipofectamine RNAiMAX protocol (Thermo Fisher Scientific). The genes of interest were depleted using siRNAs . siRNA oligos of a negative, nontargeting control siRNA , a positive control siRNA pool , and two positive biological controls of siRNA pools  at the same concentration were included in eight replicates for each plate. Two microliters per well of siRNA of each oligo pool at the concentration of 1.25 µM were spotted at the bottom of 384-well CellCarrier Ultra imaging plate (PerkinElmer 6057300) using a PerkinElmer Janus Automated liquid handler. The 384-well plates were air dried under a sterile laminar flow for at least 30 min, sealed, and then stored at −80°C until transfection.Supplemental Fig. S14). Twenty-five microliters of 450 cells (18 cells/µL) in DMEM, 20% FBS were added to the siRNA oligo/RNAiMax mix, incubated for 30 min at RT and then incubated for 96 h at 37°C. The final concentration of siRNA oligos in the medium was 50 nM.On the day of transfection, the plates were equilibrated for at least 30 min at RT and then spun at 4000 rpm for 2 min. Twenty-five microliters of Opti-MEM (Thermo Fisher Scientific 51985034) containing 0.075 µL of premixed Lipofectamine RNAiMAX (Thermo Fisher Scientific 13778150) was dispensed in each well of the imaging plate using Thermo Fisher Scientific Multidrop Combi and incubated for 30 min at RT  directly to the media, incubated for 15 min at RT, washed three times with 50 µL of PBS, and then incubated with 50 µL of DAPI (0.1 µg/mL) in PBS at 4°C until imaging.Fixed and stained plates were imaged using a Yokogawa CV7000S spinning disk confocal microscope with Olympus 40× (NA 0.95) PlanApoChromat lens, an emission 405/488/561/640 dichroic mirror, and a 16-bit sCMOS camera (2550 × 2160 pixels) with pixel binning set to 2 × 2. For the DAPI channel, a 405-nm laser source and a 445/45-nm bandpass acquisition filter were used. For the GFP channel, a 488-nm laser source and a 525/50-nm bandpass acquisition filter were used. The DAPI and GFP channels were acquired sequentially at a single focal plane in nine fields of view per well. Images were saved as 16-bit TIFF files.TIFF files generated by the CV7000S microscope were imported and analyzed using PerkinElmer Columbus 2.7. The DAPI channel was used to segment a nuclear ROI mask, which was then used to measure the mean fluorescence intensity in the nucleus in the GFP channel. Nuclei touching the image borders and nuclei with a roundness value <0.7, often representing nuclear segmentation errors, were excluded from the subsequent analysis steps. The cells with values of GFP mean fluorescence intensity <100 AU, an empirically determined threshold that was kept constant for all plates in the screen, were classified as GFP−. The percentage of GFP− cells was used as a proxy for measuring HAC loss. Well-level data were exported as tab-separated text files.2) were seeded in a six-well tissue culture plate and cultivated in the presence of 10 µg/mL blasticidin for 210 h using Cell-IQ high-content in vivo imaging system equipped with 20× LUCPlanFLN Olympus Objective and Hamamatsu CCD camera. The growth curve was performed by time-lapse cell population analysis, recognizing each cell by its peculiar image using a phase-contrast microscopy using computer vision as well as fluorescent signal analysis to identify GFP-positive cells. The growth curve was generated automatically using Cell-IQ Analyzer software after the image library was performed, and each cell was marked with a specific dot marker plotted on the image mask for an operator's visual control .HT1080 cells containing HAC/dGFP cells .The rate of HAC loss was calculated as previously described  with somSupplemental Methods).Cytokinesis-block micronucleus assay was performed as described  with min


A proof-of-concept study was conducted to assess whether patients with advanced stage IV cancer for whom predominantly no standard therapy was available could benefit from comprehensive molecular profiling of their tumor tissue to provide targeted therapy. Tumor samples of 83 patients were collected under highly standardized conditions and analyzed using immunohistochemistry, next-generation sequencing and phosphoprotein profiling. Expression and phosphorylation of key oncogenic pathways were measured to identify targets at the (phospho-) proteomic level. At genomic level, 50 oncogenes and tumor suppressor genes were analyzed. Based on molecular profiling, targeted therapies were decided by the attending oncologist. Accordingly, 28 patients who met the defined criteria fell in two equal-sized groups. One group received targeted therapies while the other did not. Following six months of treatment, disease control was achieved by 49% of patients receiving targeted therapy  and 21% of patients receiving non-targeted therapy . Individual patients experienced dramatic responses to a therapy which otherwise would not have been applied. This approach clarifies the value of multi-omic molecular profiling for cancer diagnostics. Given estimates that over 800 cancer treatments are currently in clinical development , moleculThe aim of this proof-of-concept study was to evaluate whether patients with advanced stage IV cancer, independent of its origin, could benefit from comprehensive molecular profiling of their tumor tissue to enable targeted therapy. Potential drug targets resulting from molecular profiling were summarized in a scientific report for the attending physicians/oncologists who were responsible for therapy selection. The key oncogenes and major signaling pathways in oncogenesis and tumor progression relate to the mitogen-activated protein kinase (MAPK) and phosphoinositide 3-kinase (PI3K)/protein kinase B (Akt)/molecular target of rapamycin (mTOR) signaling pathways . In thisTumor samples from 83 patients  with different primary entities were collected and analyzed using three different methods whenever possible, which was feasible for 51/83 (61%) of patients. Immunohistochemistry, phosphoprotein profiling and NGS was applicable for 82/83 (99%), 52/83 (63%), 73/83 (88%) of patients, respectively. At least one “druggable” target was found for the majority of the 83 analyzed patients with at least one of the described methods, specifically 75/82 (91%) using immunohistochemistry, 18/52 (35%) using phosphoprotein profiling and 21/73 (29%) by applying NGS. To investigate whether the attending oncologist took the identified potential drug target(s) into account for therapy decision and to evaluate the treatment process, follow-up data were collected three months after molecular profiling. Follow-up data were available for 66/83 (80%) patients; however, 38/66 patients (58%) were excluded from the evaluation, due to the fact that the majority of these patients (32/38 [84%]) died prior to the first follow-up interval, two tumor samples were not collected under high-quality standardized conditions, two patients received therapy based on oncological experience and not due to the outcome of molecular profiling, and follow-up data had been collected at only one interval for two patients  was initially treated with targeted therapy based on molecular profiling while the other group (N=14) was treated with non-targeted therapy independent of molecular profiling. The targeted treatment group also contains patients who received chemotherapies. These therapy decisions were also based on the results of the molecular profiling approach, because Ki-67 and Topoisomerase were part of the test and these agents were topoisomerase inhibitors.Based on the oncologists' treatment decision, one group  patients, intracellular proteomic alterations in signaling pathways were found in 8/14 (57%) patients using phosphoprotein profiling and genomic alterations were identified in 5/14 (36%) patients by NGS. Figure Using NGS, the most commonly identified mutations were HRAS, TP53 and c-Kit which were detected in 47%, 36% and 26% of patients, respectively. Activating mutations indicating sensitivity to available targeted drugs or predictive mutations indicating the probability of response or resistance to drugs were found in the genes KRAS, PIK3CA, APC, EGFR, FLT3 and PTEN in a fraction of 16%, 11%, 7%, 3%, 1% and 1%, respectively . In the other group, 21% of patients treated with non-targeted therapy achieved disease control  while 64% showed PD. In both groups, two patients (14%) died within six months, irrespective of the initial treatment approach Figure .P=0.23)  survived ≥1 year from the point of time when the attending oncologist received their results, and 8/14 (57%) had an overall survival time of ≥1.5 years. While there was a trend towards improved overall survival with targeted therapy compared with non-targeted therapy, this did not reach statistical significance (4% surviv) Figure .in situ hybridization (FISH or CISH). In addition, the majority of patients with CUP (8/15 [53%]) did not meet the criteria for molecular profiling as they died prior to the first follow-up or had no follow-up data (2/15 [13%]) and one of the probes was external. Overall, four patients with CUP (4/15 [27%]) were included in the follow-up analysis: one patient received targeted therapy based on molecular profiling for 3 months before the attending oncologist initiated chemotherapy, and three were treated with non-targeted therapy. Two patients were alive ≥9 months following molecular profiling independent of the initial therapy decision.For CUP, few guidelines are available indicating that molecular profiling for this tumor type may be particularly advantageous . In totaThe following case reports are from the follow-up data of the attending physician/oncologist of patients receiving targeted therapy based on molecular profiling. Case numbers correspond to patient numbers in Table This patient was a 73-year-old male diagnosed with cholangiocarcinoma of the right hepatic lobe. Explorative laparotomy, a hemihepatectomy (right), a diaphragmatic resection, cholecystectomy and adrenalectomy were performed. The moderately differentiated cholangiocarcinoma with infiltration of the perihepatic soft tissue was treated with chemotherapy (gemcitabine/cisplatin) until CR, but liver metastases developed. Molecular profiling of the primary tumor and liver metastases was requested by the patient and three potential targets for targeted treatment were identified.Wildtype for KRAS and a strong EGFR expression were detected in >90% of the tumor cells, thus addition of the EGFR monoclonal antibody cetuximab or panitumumab to a platinum-based chemotherapy was recommended. A combination of gemcitabine/cisplatin and cetuximab resulted in PR during the first 3 months of follow-up, but cetuximab was discontinued due to skin toxicity. During the following three months the disease progressed and the quantity and size of metastases increased despite changing therapy to capecitabine.An identified KIT mutation led to the “off-label” use of imatinib, but despite promising data from the gastrointestinal stromal tumor (GIST), the patient did not achieve a positive clinical response. The patient then received the previously used chemotherapy consisting of gemcitabine and cisplatin with further changes to the chemotherapy including three cycles of FOLFIRI and a combination of gemcitabine and oxaliplatin. Finally, nivolumab was trialed, but showed no improvement. Additional identified alterations in the MET pathway as a moderately expressed c-MET receptor, an activation of the signaling protein Akt and an activating mutation of the PIK3CA gene were not considered for therapy decision by the attending oncologist.This patient is a 51-year-old female diagnosed in July 1997 with breast cancer. A tumor of the right breast was surgically resected in July 1997, followed by radiotherapy. The tumor was histologically classified as a hormone receptor-negative adenocarcinoma (Grade 2) with unknown HER-2 expression. In July 2001, tumor recurrence developed in the right breast and chest wall, which was hormone receptor-negative but strongly HER-2 positive (3+). Breast removal was necessary, followed by adjuvant chemotherapy with epirubicin/cyclophosphamide (EC) from July 2001 to December 2001, adjuvant radiotherapy of the right chest wall from January 2002 to March 2002, and trastuzumab monotherapy from May 2002 to April 2004. Lymph node and bone metastases were found in January 2005, both hormone receptor-negative and HER-2 strongly positive (3+), leading to a therapy of radiation, trastuzumab and vinorelbine. This combination therapy resulted in SD for approximately two years.In 2007, the cancer progressed with cutaneous metastasis with no change in hormone receptor or HER-2 expression. From 2007 to 2012, the patient received several single-agent chemotherapies, intermittently in combination with trastuzumab and bevacizumab. In 2013, the patient received trastuzumab emtansine (TDM-1) in the TH3RESA trial (NCT01419197) (TDM-1) ); epidermal growth factor receptor (EGFR [EGFR CONFIRM anti-EGFR (3C6)]); human epidermal growth factor receptor 2 (HER-2 [PATHWAY anti-HER-2/neu (4B5)]); insulin-like growth factor 1 receptor (IGF-1R [CONFIRM anti-IGF-1R (G11)]); Ki-67 (CONFIRM anti-Ki-67 (30-9)]); programmed death-ligand 1 (PD-L1 [SP263]); topoisomerase-II-α (TOP2A [CONFIRM anti-topoisomerase-II-α (JS5B4)]); tyrosine-protein kinase Met ]); and vascular endothelial growth factor receptor 2 (VEGFR-2 [VEGF Receptor 2 (55B11)]). All primary antibodies were rabbit monoclonal antibodies, except anti-EGFR which was a mouse monoclonal antibody, and were purchased from Ventana Medical Systems Inc. , except for EML4–ALK and VEGFR-2 . HER-2 chromogenic in situ hybridization (CISH) , EGFR-fluorescence in situ hybridization (FISH), c-MET FISH and EML4-ALK FISH , were used if required. Following staining, the slides underwent an ascending alcohol series and were covered with Pertex . An indirect biotin-free system was used for the detection of rabbit primary antibodies . For the mouse primary antibody EGFR (3C6) the iView DAB Detection kit, an indirect biotin streptavidin system was used. Evaluation and interpretation of results were performed by a pathologist.Tumor samples (3 μM sections of FFPE) were prepared and mounted on Superfrost™ Ultra PlusFor DNA sequencing, the Ion AmpliSeq™ Cancer Hotspot Panel v2  was applied covering “hotspot” regions of 50 oncogenes and tumor suppressor genes including: ABL1, AKT1, ALK, APC, ATM, BRAF, CDH1, CDKN2A, CSF1R, CTNNB1, EGFR, ERBB2, ERBB4, EZH2, FBXW7, FGFR1, FGFR2, FGFR3, FLT3, GNA11, GNAS, GNAQ, HNF1A, HRAS, IDH1, JAK2, JAK3, IDH2, KDR, KIT, KRAS, MET, MLH1, MPL, NOTCH1, NPM1, NRAS, PDGFRA, PIK3CA, PTEN, PTPN11, RB1, RET, SMAD4, SMARCB1, SMO, SRC, STK11, TP53, VHL. FF tissue was preferred to FFPE tissue. NGS analyses were conducted by an external provider .Phosphorylated protein of extracellular signal-regulated protein kinases 1/2 (ERK1/2), mitogen-activated protein kinase kinase (MEK1/2) of the MAPK pathway, and Akt of the PI3K/Akt/mTOR pathway were analyzed using NanoPro™ 1000 Technology . To detect total protein and phosphorylated isoforms, pan antibodies were applied against: ERK , MEK1/2 and Akt . Phosphoprotein profiling was conducted by Indivumed GmbH, Hamburg, Germany.survival was applied for the survival analysis. Kaplan-Meier survival curves were created from a model formula in which the response variable was based on the starting and ending times of the follow-up intervals, as well as the event of dying [The R package of dying , 33. To of dying . To testof dying .


In this review, we will first briefly describe the diverse molecular mechanisms associated with PTEN loss of function in cancer. We will then proceed to discuss the molecular mechanisms linking PTEN loss to PI3K activation and demonstrate how these mechanisms suggest possible therapeutic approaches for patients with PTEN-null tumors. PTEN also functions as a protein phosphatase in the cytoplasm, where it has been shown to inhibit cell migration and induce cell cycle arrest [PTEN tumor suppressor has been shown to drive the development of a variety of human cancers [The phosphoinositide 3-kinase (PI3K) signaling pathway regulates a wide range of vital cellular functions, including cell cycle progression, survival, motility, and metabolism . Becausee arrest ,10, or ie arrest ,12,13,14 cancers .PIK3CA, the gene encoding p110α, or through gain-of-function mutations/amplification in receptor tyrosine kinases (RTKs) and oncogenes such as KRAS. Preclinical studies have shed light on the reasons that PIK3CA, but not PIK3CB, the gene encoding p110β, is so frequently mutated in human tumors. In genetically-engineered mouse (GEM) models, the activation of p110α, either directly via activating mutations at so-called hotspots due to their high mutational frequency (E545K and H1047R), or indirectly via activating mutations or overexpression of RTKs, such as Her2, is sufficient to drive tumor formation. In the case of tumors driven by activated RTKs, the deletion of p110α is sufficient to block tumor initiation, while deleting p110β can actually increase tumor size [PIK3CA gene is a better mutational target in human tumors, though other mechanisms may be relevant. However, the quantitation of class IA PI3Ks using quantitative mass spectrometry revealed at least five times higher loading of p110α-heterodimers than p110β-heterodimers to activated platelet-derived growth factor receptors in mouse embryonic fibroblasts [Hyperactivation of the PI3K pathway is frequently found in many types of human cancer. Increased activity of the PI3K pathway is often associated with tumor progression and resistance to cancer therapies . Enzymatmor size . This aproblasts . The othroblasts ,20.PIK3CA, PTEN, and/or AKT1 mutations are present in over 40% of uterine, lung, breast, prostate, brain, and head and neck cancers [PIK3CA, PTEN, and AKT1, in 19,784 consecutive diverse solid tumors from 60 countries supported previous studies that aberrations in the PI3K pathway are frequently observed in a broad range of human tumors [An integrative analysis of cancer genomics using cBioPortal reported that  cancers ,22. A tan tumors . In addiPTEN is altered in a wide range of human cancers, including breast cancer, prostate cancer, endometrial cancer, and glioblastoma [PTEN was first discovered as a frequently mutated tumor suppressor gene on chromosome 10q23 [PTEN [PTEN are scattered along the entire gene. There are mutational hotspots , but mutations at these hotspots have not been shown to be specific for a certain type of cancer [PTEN function is frequently observed in the clinic. Hemizygous loss of PTEN leads to cancer progression in the prostate, thyroid, colon, lymphatic system, mammary gland, and endometrium [PTEN is observed more frequently in endometrial carcinoma and glioblastoma, it appears in less than 15% of prostate, breast, colon, and lung cancers. Even in the cancers with the highest biallelic mutation frequencies, monoallelic mutation and loss of protein expression are observed more commonly [PTEN are also associated with genetic disorders with an increased risk of cancer, collectively referred to as PTEN hamartoma syndromes (PHTS), which include Cowden syndrome, Bannayan–Zonana syndrome, Lhermitte–Duclos syndrome, Proteus syndrome, and Proteus-like syndrome [PTEN are nonsense or frame-shift mutations and occur in the C-terminal region, resulting in premature stop codons and truncations of the protein in approximately 70% of the total mutations studied [Pten-knockout develop tumors in various organs, supporting the role of PTEN as a potent tumor suppressor [As one of the most frequently mutated tumor suppressor genes in human cancer, blastoma ,25. PTENme 10q23 ,8. Mutatme 10q23 . A cance23 [PTEN . Somaticf cancer . R130 anf cancer . R233, Kometrium ,32. Studometrium ,35. Althcommonly ,37. Germsyndrome . The maj studied . Experimppressor ,39,40.In addition to the frequent occurrence of PTEN mutations in various cancer types, PTEN levels are also downregulated at both transcriptional and post-transcriptional levels.PTEN mRNA levels are regulated by several transcription factors. The p53 tumor suppressor upregulates PTEN expression in response to irradiation and other sources of DNA damage via direct binding to a cis-element in the PTEN promoter to trans-activate PTEN. The induction of p53 in cells elevates PTEN at both mRNA and protein levels in a variety of cell lines [Pten transcription by direct binding to a GCGGCGGCG site in the 5’ untranslated region [PTEN expression and survival in non-small-cell lung cancer patients [PTEN through the dual-function transcription factor CBF-1. In the absence of active Notch-1 signaling, CBF-1 binds to the PTEN promoter and represses PTEN expression. Overexpression of constitutively active Notch-1 converts CBF-1 into a transcriptional activator and induces PTEN expression in 293T cells and human prostate cancer cells [ll lines . Loss ofll lines . EGR1 upd region . It has patients . The EGRpatients ,48,49,50er cells ,52,53. Der cells ,55,56,57er cells ,59,60,61er cells ,63,64. Per cells ,66.Aberrant methylation of the PTEN promoter provides another mechanism for the loss of PTEN expression. Hypermethylation of CpG islands in the PTEN promoter is found in various types of cancers, including breast, lung, ovarian, cervical, colorectal, and thyroid cancer, as well as melanoma, gastric carcinoma, and metabolic syndrome ,76,77,78PTEN. For example, Mir-21 binds to the 3’-UTR of PTEN mRNA and inhibits PTEN expression [MiR-21 confers resistance to some chemotherapy drugs and radiation therapy in cancers [MiR-29 regulates PTEN in various ways. Previous research demonstrates that YAP1 downregulates PTEN by inducing MiR-29 to inhibit PTEN translation. In this case, PTEN knockdown mimics the YAP-induced increase in cell size and LY294002 treatment rescues the effect of YAP on cell size [MiR-29a may confer the acquisition of resistance to adriamycin in breast cancer cells by the downregulation of PTEN and activation of the PI3K pathway [MiR-29 on PTEN level is a cell type-dependent. Studies in hepatic stellate cells and liver fibrosis models suggest that MiR-29 upregulates PTEN expression by targeting DNA methyltransferases such as Dnmt1, Dnmt3b, and Set1a to prevent excess liver fibrosis [MiR-130 family downregulates PTEN to promote cell proliferation, invasion, migration, and EMT in cancer [A number of miRNAs have been shown to participate in the regulation of biological processes by targeting pression . MiR-21  cancers ,84,85,86 cancers . Similar cancers . MiR-29 ell size . MiR-29a pathway . The efffibrosis ,90. Finan cancer ,92,93.PTEN expression either by functioning as a decoy for PTEN-targeting miRNAs or by altering PTEN promoter methylation. PTENP1 is a processed pseudogene with high homology to PTEN. PTENP1 is targeted by PTEN-targeting miRNAs, and can function as a competing endogenous RNA (ceRNA) to protect PTEN from miRNA recognition [PTEN by PTENP1 inhibits cell proliferation, invasion, and migration in cancers [GAS5, FER1L4, XIST, MEG3, and NBAT, have also been reported to sequester miRNAs that specifically target PTEN, thereby stabilizing PTEN mRNA and modulating PTEN function [HOTAIR regulates PTEN expression via several different mechanisms [HOTAIR in laryngeal squamous cell carcinoma decreases PTEN methylation to reduce invasion and tumor growth [HOTAIR can also upregulate PTEN expression by targeting miR-19, miR-29b, and miR-17-5-p [Long non-coding RNAs can upregulate ognition . The sta cancers ,100,101.function ,115,116.chanisms ,119,120.r growth . HOTAIR R-17-5-p ,119,120.The activity, stability, and subcellular localization of PTEN can be regulated by several post-translational modifications . The secH. pylori inactivates PTEN by inducing PTEN phosphorylation at residues S380/T382/T383, resulting in the enhanced survival of gastric epithelial cells [The phosphorylation of PTEN has different functions on the activity, stability, and subcellular localization. CK2 phosphorylates several Ser (S)/Thr (T) residues in the C-terminal tail of PTEN to decrease the activity and increase the stability of PTEN ,122. Theal cells . The mutal cells ,128. Theal cells ,131. A ral cells . Y240 phal cells ,131.WWP1-depleted cells [The activity and stability of PTEN has been reported to be down-regulated by monoubiquitination and polyubiquitination. Two main monoubiquitination sites, K13 and K289, are important for PTEN nuclear localization and stability . Nedd4-1ed cells . WWP1 meed cells ,139. XIAed cells .The Cys124 residue of PTEN forms a disulfide bond with Cys71 in response to oxidation by both endogenous and exogenous hydrogen peroxide, leading to the reversible inactivation of the lipid phosphatase function of PTEN ,142. In PCAF mediates acetylation of PTEN at lysine 125 and 128 to inhibit its activity in the regulation of the PI3K/AKT pathway . The acePARK2 depletion contributes to AMPK-mediated activation of endothelial nitric oxide synthase (eNOS), promoting both S-nitrosylation and ubiquitination of PTEN [Nitric oxide regulates the activity of PTEN via S-nitrosylation during transient global ischemia in the rat hippocampus . The S-n of PTEN ,154. NOS of PTEN .TNKS1 and TNKS2 interact with and ribosylate PTEN, which promotes the recognition of PTEN by RNF146, leading to PTEN ubiquitination and degradation .The SUMO1 modification of PTEN at Lys266 in its C2 domain was shown to increase the localization of PTEN at the plasma membrane, resulting in the suppression of the PI3K-AKT pathway signaling and inhibition of anchorage-independent cell growth and tumor growth in vivo .The loss of PTEN in a tumor amounts to removing the brake on PI3K signaling . However3 production, raft nanodomains were involved in recruiting AKT to the plasma membrane [3 via PIP3-activated guanine-nucleotide exchange factors (GEFs) [To address this question, Cizmecioglu et al. first examined how p110β is activated under physiological conditions by GPCRs . Since tmembrane . Cizmecimembrane . A uniqumembrane  and Rac s (GEFs) ,163. In The data on the Rac/p110β feedback loop described above (see  for detaPTEN loss, and p110β activation. As previously mentioned, YAP activation decreases PTEN expression via miR-29 [PTEN loss is known to activate Rac, which in turn can activate YAP [Additionally, there may be an interesting feedback loop connecting YAP activation, a miR-29 . Activata miR-29 . Reciprovate YAP ,168. Thuvate YAP .Early clinical trials with so-called pan-PI3K inhibitors were unimpressive for most PTEN-null tumor indications ,171. ThiInevitably, single agent therapies are likely to have only short-lasting effects in solid tumors. Hence, preclinical research is now focused on finding combination therapies, largely building on p110β inhibitors. Unlike compounds that target p110α, which have shown high on-target toxicity due to effects on insulin signaling, a pure p110β inhibitor is expected to have relatively low on-target adverse effects. Indeed a mouse with whole-body knock-in of a kinase-dead allele of p110β is fairly healthy with only relatively minor insulin resistance . One exaRecently, exciting new roles of PTEN in immune regulation and inflammatory diseases have been discovered. PTEN has been found to play important roles in both T cells and in cloaking tumors from the immune system. A study in mice demonstrated that the T cell-specific loss of PTEN in mice causes defects in central and peripheral tolerance and increase susceptibility to T cell lymphoma and leukemia . More exCHD1 inhibits cell growth in PTEN-null prostate cancer cells while it has minimal effect in PTEN-intact cell lines [L had a synergistic effect with PI3K/AKT inhibitors in PTEN-mutant prostate cancer cells, such as LNCap and PC3, but not in PTEN-proficient DU145 cells [Synthetic lethality is said to occur for two genes when alteration in either gene alone does not affect cell viability but perturbation of both genes at the same time leads to cell death. The concept of synthetic lethality can be applied to cancer therapy by inhibiting one protein activity in cancer cell harboring a loss of function mutation of the second gene to induce cell death . Numeroull lines . RAD51 ill lines . ITGA5 k45 cells . The ATM45 cells . BRG1 wa45 cells . In PTEN45 cells . Finally45 cells .Recent research suggested that it is possible to reactivate PTEN expression/activity for cancer treatment ,139,191.Tumors lacking the PTEN expression comprise one of the largest tumor classes. Despite the fact that PTEN loss results in abnormally high PI3K pathway activation, therapeutic approaches to this tumor class have been disappointing. Historically, the development of anti-cancer therapeutics targeting tumor suppressors has been particularly challenging. In the case of PTEN, this challenge has been exacerbated by the multiple functions of the PTEN protein and its highly complex modes of regulation. However, with the advent of p110β-selective PI3K inhibitors and promising combinations of these inhibitors with both targeted and immunotherapies, it can be hoped for that a more favorable outlook for patients with PTEN-null tumors is on the horizon.


Lam1, Thy1, Gli1, Gli3, Noto, Ptprc, Scx, Sox2 and Zscan10 with fluorescent RNA in situ hybridization (FL-RISH) and confocal microscopy. This permits sub-cellular transcript localization and the addition of quantitative single-cell derived values of mRNA expression levels to our previous analysis. Lastly, we used a Gaussian mixture modeling approach for the exploratory analysis of IVD cells. This work complements our earlier cell population proportion-based study, confirms the previously proposed biomarkers and indicates even further heterogeneity of cells in the outer AF and NP of a mature IVD.Severe and chronic low back pain is often associated with intervertebral disc (IVD) degeneration. While imposing a considerable socio-economic burden worldwide, IVD degeneration is also severely impacting on the quality of life of affected individuals. Cell-based regenerative medicine approaches have moved into clinical trials, yet IVD cell identities in the mature disc remain to be fully elucidated and tissue heterogeneity exists, requiring a better characterization of IVD cells. The bovine coccygeal IVD is an accepted research model to study IVD mechano-biology and disc homeostasis. Recently, we identified novel IVD biomarkers in the outer annulus fibrosus (AF) and nucleus pulposus (NP) of the mature bovine coccygeal IVD through RNA in situ hybridization (AP-RISH) and z-proportion test. Here we follow up on  Cell-based tissue regeneration approaches to address degeneration of intervertebral discs (IVD) are a glimpse of hope for a large percentage of the population suffering from severe and chronic lower back pain due to age or injury related degenerative disc disease (DDD). The IVD is a tissue of strength, resilience and capable of reducing the impact of movement on the rigid vertebral bodies that stabilize our spine . In thisMus musculus, have long been extremely helpful as model organisms to study human development and genetic mutations underlying congenital diseases [Bos Taurus. Respecting the 3R guidelines in research—replacement, reduction, and refinement—bovine tails are an ideal IVD source, as abattoirs often discard them. Bovine coccygeal discs provide a very suitable research model to study cell populations of the mature healthy IVD  domain containing) is a TF and proposed multipotency marker in mouse [In need for further characterization of resident cells in the mature IVD, we recently proposed a set of novel IVD biomarkers based on the proportion of cells within the outer AF and NP tissue of bovine coccygeal IVDs being either positive or negative for the proposed biomarker transcript : Lamininin mouse . Tyrosinin mouse ,37.Analyzing these genes with RNA in situ hybridization (RISH), we point to heterogeneity among cells within the outer AF or NP, which is typically not accounted for by methods involving cell pooling for RNA extraction, such as qRT-PCR, microarray expression profiling or non-single-cell RNA sequencing ,3,38. HeAll procedures were performed according to ethical standards of Clarkson University . No human material was included in this study. TMHistobondR glass slides  [Tails of skeletally mature bovine animals were retrieved fresh from local abattoirs, transported on ice and processed within two hours. All procedures were carried out strictly under ribonuclease free conditions . CoccygePA, USA) .IVDs were fixed overnight using 2.5% (v/v) glutaraldehyde  in 0.1 M sodium cacodylate solution (EMS) at 4 °C, followed by 0.1 M sodium cacodylate incubation at 4 °C overnight. Then the IVDs were gently dehydrated in 50%, 60%, 70%, 80%, 90%, and 100% ethanol baths. Initial air-drying was followed by freeze-drying overnight before the IVDs were Au/Pd sputter coated and examined with a JEOL JSM-7400F scanning electron microscope  at 1500× magnification.Templates for RNA probes were amplified by polymerase chain reaction (PCR) from bovine genomic DNA as described . The enzMus musculus [Col1a1 in the outer AF and Acan in the NP. Of those 18 genes, two were novel biomarkers in the outer AF (Lam1 and Thy1) and eight in NP tissue ) [Previously we had investigated 50 genes based on their occurrence in IVD related literature ,42,43,44musculus ,48,49,50Col2a1 and LOC101904175 [For transcript quantification of each proposed biomarker we chose 20 random fields of view within the outer AF and NP of three IVDs to capture fluorescent signal intensities, similar to the approach taken for 01904175 . QuantitThe Kernel density estimates of the data were graphed in R using a log2 transformation of the total fluorescence intensity for each transcriptionally active cell. The Shapiro–Wilk test was employed to assess the validity of a normality assumption for the data collected. When the data was not normally distributed, k-means clustering was performed to see if the data could be fit to a mixture of Gaussian populations using the expectation-maximization (EM) algorithm. Subsequently, if cells were found to be normally distributed within the sub-clusters, no further subdivision was pursued and the resulting Gaussian mixture model (GMM) was kept. Of note, we have excluded the possibility of artificial sub-clustering due to technical errors through natural data clustering. That is, we found those clusters to be uncorrelated with the frame number or individual IVD sections .Cells of the mature AF and NP reside in a large amount of ECM. Fibers of structural molecules in the ECM appear aligned in a linear manner in the outer AF and show a more crisscross pattern in the NP . NP cellThy1, Ptprc and Sox2 in cells of the outer AF), some were found predominantly in the cytoplasm  and others were typically found in both cellular compartments   . The intpearance .Lam1 and Thy1) and NP tissue  using fluorescent tagging of the transcripts (FL-RISH) and confocal imaging  [www.sciencellonline.com), however their original fate and gene expression patterns might change in vitro without appropriate ECM and 3D-culture systems in place, as seen for primary bovine cells derived from IVD tissue and maintained in monolayer culture [Discogenic, severe and chronic lower back pain due to disc trauma and degeneration is a debilitating condition that patients, once affected, often have to endure for a significant part of their life. So far, partial alleviation of symptoms but no complete cure or full restoration of athletic abilities or lifestyle choices is available ,52. Cellals.gov) ,10,11,53als.gov) . DDD is als.gov) ,56,57,58als.gov) , while oals.gov) . With reals.gov) ,20,61,62als.gov) ,63,64. N culture ,22,23. KRT19 and T (brachyury) as a population [T expression in cells of the AF and NP, however, with no significant difference in cell population proportions, indicating that assessment of heterogeneity within a cell population remains important to address the question of NP cell origin and heterogeneity [Lam1, Thy1) or NP . Other biomarkers previously proposed by others in the AF, like Col1a1 or in the NP, like Acan, Col1a2, Col2a1, Krt18, Krt19, Shh and Ca12 were also confirmed with our approach, while some did not show any significant difference in the proportion of positive cells between the outer AF and NP, for example Foxf1, Hif1a, Krt8, Snap25, Sox5, Sox6, Sox9, Pax1, T and Tmnd. Since our approach to analyze cell population proportions had differed from the common practice of cell pooling and expression profiling of cell population averages which uses methods like microarray, RNAseq or qRT-PCR [Lam1 and Thy1 as potential AF and Gli1, Gli3, Noto, Scx, Ptprc, Sox2 and Zscan10 as potential NP biomarkers. To demonstrate that the observed transcriptional heterogeneity cannot simply be attributed to cells leaving the active phase of the cell cycle, we used the widely accepted cell proliferation marker Ki67 [Thy1, Gli1, Gli3, Scx, Sox2 and Zscan10) or the outer AF , additional heterogeneity based on fluorescent intensities and hence transcript levels. While neither Gli3, Noto, nor Zscan10 are considered AF-specific, neither is Thy1 considered a NP biomarker, the indication of further heterogeneity could point to mixed cell sub-populations of shared developmental origin.Aside from their exposure to mechanical, physical and chemical constraints ,66,67,68pulation ,37. We hogeneity ,77. Thesogeneity ,77,78,79ogeneity ,68,73. Sogeneity ,61,80,81 qRT-PCR ,43,44,weker Ki67 ,83 in coKrt8, Krt18 and Krt19 positive cells in both outer AF and NP tissue of mature bovine IVDs by AP-RISH, yet only Krt18 and Krt19 were expressed by a significantly larger proportion of cells in the NP [OVOS2, GDF10, GPC3, HBB or NCAM1, which were identified as human NP-specific over articular cartilage (AC) were not part of our initial panel of 50 genes and not investigated in our studies [Col2a1, Acan and Sox9 have often been used to identify mature NP cells [Sox9 was not detected in a significantly higher proportion of cells in the NP over the AF in our previous study [CLDN11, TMEFF2, CA12, ANAX2, CD44, EFNA1, NETO2 and SLC2A1 as NP-specific cell surface markers to assess cellular heterogeneity of NP cells in vivo and suggested CHIC1, COLEC12, LPAR1, LRP4, LRP5 and FZD2 as markers to define cellular heterogeneity in AF cells. The immortalized NP cell lines were previously employed by this group to identify human NP subpopulations through qRT-PCR based expression profiling, pointing to FOXF1 and CA12 as useful markers with significant difference between clonal subtypes [CD24, STMN2, RTN1, PRPH, CXC12, IGF1, ISL1, CLDN1, THBS2 and MAP1B were mostly down regulated in adult NP cells, with the exception of the latter. Using cell pooling for RNA extraction and genome wide microarray analysis another recent study also focused on the molecular discrimination between human AF and NP tissue suggesting six novel NP markers: CDKN2B, ARAP2, ERFE, DSC3, DEFB1, SPTLC3 and five novel AF markers: OLFML2A, ANKRD29, EMCN, ADGRL4 and LDB2 with a significant difference in expression levels between the two tissue types [Ca12 overlapped with our initial panel of 50 investigated genes [Lam1, Thy1, Gli1, Gli3, Noto, Ptprc, Scx, Sox2 and Zscan10 presented here. While we cannot draw any further conclusions at this point, it would be interesting to investigate the novel markers proposed in the studies above in the context of cellular heterogeneity going forward.Despite strong evidence pointing to heterogeneity of outer AF and NP cells in the mature IVD, currently most expression profiling data available for the IVD is based on cell pooling and population averaging technologies ,44,81,84n the NP . Other m studies ,62,87,88NP cells ,89, yet subtypes . The appsubtypes , howeversubtypes . A diffeue types . While wSox2 (NP), Zscan10  or Gli3  could point to the proximity of such functional nuclear domains and possibly indicate active transcription and processing of transcripts. The novel markers Lam1, Thy1, Gli1, Gli3, Noto, Ptprc, Scx, Sox2 and Zscan10 suggested here in our study, should be considered as addition to a growing repertoire of biomarker panels for future characterization of outer AF and NP cells along with morphological and cell behavior data, like cell movement, velocity and clustering ability [Lastly, the combination of FL-RISH and the high resolution of confocal imaging allows for a glimpse at sub-cellular transcript location. It is known for some transcripts, like non-coding RNAs, that transcript location could point to regulatory functions . In caseLam1, Thy1, Gli1, Gli3, Noto, Ptprc, Scx, Sox2 and Zscan10. We believe that a combination of the many biomarkers that have been established so far and those that will be determined in the future will be helpful to clarify the molecular identity of cells in the mature IVD, however, data re-assessment from a cell-by-cell perspective taking heterogeneity into account might become necessary. Future regenerative cell-based therapies are of great potential if a safe outcome is predictable. Whole genome transcriptome analysis is a powerful screening tool to identify novel biomarkers, however phenotyping and genotyping of heterogeneous cell populations with single-cell assessment is an important quality control measure in achieving this predictability. Animal research models like the bovine IVD are invaluable tools to better characterize resident cells within a healthy IVD environment. FL-RISH in combination with confocal microscopy and statistical data analysis can provide both, transcript analysis through population averaging and on a single-cell level. Both were used here to confirm our previously proposed biomarkers


Ferriphaselus amnicola is a freshwater, neutrophilic, iron-oxidizing bacterium that produces extracellular twisted-ribbon-like iron biominerals called stalks. Here, we report the 2.72-Mb closed genome sequence of F. amnicola strain OYT1, which was isolated from iron oxide deposits at a groundwater stream in Japan. Ferriphaselus amnicola is a freshwater, neutrophilic, iron-oxidizing bacterium that produces extracellular twisted-ribbon-like iron biominerals called stalks. Here, we report the 2.72-Mb closed genome sequence of F. amnicola strain OYT1, which was isolated from iron oxide deposits at a groundwater stream in Japan. Gallionella ferruginea, was described , from a groundwater seep in Japan  of the strain was already determined by 454 pyrosequencing and Ion PGM sequencing, which indicated the presence of putative genes involved in carbon fixation, iron oxidation, and stalk formation , nce then , 3; howeF. amnicola strain OYT1. The cultivation of the strain and the DNA extraction from the culture have been reported previously  source at pH 6.2 and 25°C. Using the same DNA extract, we resequenced its genome on a MiSeq platform  and on a MinION device  with an R9.4 flow cell (ONT). Sequencing libraries were constructed using a QIAseq FX DNA library kit  for the Illumina sequencing and a rapid sequencing kit  for the ONT sequencing. We obtained 9,621,832 Illumina paired-end short reads  with a total of 4,295,964,156 bp and 610,696 ONT long reads  with a total of 1,048,892,817 bp. De novo assembly of the genome using both the short and long reads was performed using Unicycler version 0.3.0b , 3 copies of rRNA gene operons , and 50 coding regions of tRNAs. In addition to the rRNA genes, 4 copies of CDSs for transposase  and 7 copies of CDSs for integrase  were encoded in the genome. These CDSs probably caused the previous failure of the finished genome assembly, which used only short reads (<400 bp) produced by 454 pyrosequencing and Ion PGM sequencing  using MaAP018738, which is linked to the BioProject accession no. PRJDB3480.The complete genome sequence determined in the present study has been deposited in DDBJ/ENA/GenBank under the accession no.


MAPK interacting kinase (MNK), a downstream effector of mitogen-activated protein kinase (MAPK) pathways, activates eukaryotic translation initiation factor 4E (eIF4E) and plays a key role in the mRNA translation of mitogenic and antiapoptotic genes in acute myeloid leukemia (AML) cells. We examined the antileukemic properties of a novel MNK inhibitor, SEL201. Our studies provide evidence that SEL201 suppresses eIF4E phosphorylation on Ser209 in AML cell lines and in primary patient-derived AML cells. Such effects lead to growth inhibitory effects and leukemic cell apoptosis, as well as suppression of leukemic progenitor colony formation. Combination of SEL201 with 5’-azacytidine or rapamycin results in synergistic inhibition of AML cell growth. Collectively, these results suggest that SEL201 has significant antileukemic activity and further underscore the relevance of the MNK pathway in leukemogenesis. Acute myeloid leukemia (AML) is an aggressive hematological malignancy with relatively limited therapeutic options . Abnorma50) of 10.8 nM and 5.4 nM, respectively, in in vitro kinase assays [in vitro and in vivo models [in vitro.Recently, a new ATP-competitive inhibitor of MNK1/2, SEL201, has been reported to selectively inhibit MNK1 and MNK2 activity, with a half maximal inhibitory concentration  assays  assays .In addition to blocking tumor cell viability and proliferation, induction of programmed cell death (apoptosis) is an important effect of many antitumor agents . We examMany patients with AML either do not respond to therapy or often relapse and develop resistance mechanisms to currently used therapies , 29, undIn subsequent experiments we examined whether MNK1/2 inhibition by SEL201 could enhance the antileukemic properties of 5′-azacytidine, a hypomethylating agent with major clinical activity in AML and myelodysplastic syndromes (MDS) , 36. Thein vitro and in vivo [MAPK pathways have been previously shown to be constitutively activated in malignant hematopoietic cells and control malignant cell proliferation, via downstream effectors, including activation of MNKs , 38. Whe in vivo , 46–48. in vivo, small-molecule inhibitor of MNK1/2 activity [in situ [+ progenitor cells. Previous studies have shown that eIF4E activation promotes tumorigenesis by inducing expression of anti-apoptotic proteins, such as MCL-1 and survivin [In the current study, we examined the anti-leukemic effects of SEL201, a novel, orally bioavailable, well tolerated and safe activity , 26. SELactivity , and to [in situ . Our stu[in situ , 47. In survivin , 39, 49.in vitro and in vivo models [TP53 mutated, cells. In another study, ribavirin treatment was shown to increase 5′-azacytidine-induced suppression of colony formation of primary AML specimens [Cytarabine, an antimetabolic agent currently used for the treatment of AML, was previously shown to induce phosphorylation of eIF4E on serine 209, which could constitute a potential anti-cancer resistance mechanism activated during administration of this therapy . Consisto models . Additioo models . Furthero models , 31. Thuo models , 50, 51.o models , 51, 52.U937 cells were grown in RPMI 1640 medium with 10% fetal bovine serum (FBS) and antibiotics. MV4-11 cells were cultured in IMDM medium with 10% FBS and antibiotics. MM6 cells were grown in RPMI 1640 medium supplemented with 10% FBS, 10 μg/ml human insulin, 1 mM sodium pyruvate, 1mM nonessential amino acids, and antibiotics. Peripheral blood or bone marrow from patients with AML were collected after obtaining informed consent as approved by the institutional review board of Northwestern University. Mononuclear cells were isolated following Histopaque density gradient separation (Sigma-Aldrich). For immunoblotting analysis the mononuclear cells were cultured overnight in IMDM medium supplemented with 20% FBS prior to drug treatment. SEL201 was provided by Selvita S. A. (Ryvu Therapeutics S. A.). 5′-azacytidine and rapamycin were purchased from Sigma-Aldrich .2, 1 mM EDTA pH 8.0, 100 μM NaF, 100 μM Na4P2O7, 0.5% Triton X-100, and 10% glycerol) supplemented with protease and phosphatase inhibitors. Equal amounts of total cell lysates were resolved by SDS-PAGE and processed for immunoblotting essentially as in our previous studies [For immunoblotting experiments, cells were treated with either vehicle-DMSO (control) or SEL201 at indicated doses and time points. Cells were lysed in lysis buffer  , 56. For+ cells (ATCC) were used to assess CFU-GM colony formation in clonogenic assays in methylcellulose (Stemcell Technologies) in the presence or absence of SEL201 at the indicated doses.This assay was performed as described in previous studies . PeripheMV4-11 and MM6 cells were treated with either vehicle-DMSO (control) or SEL201 at the indicated times and doses. U937 were treated with vehicle-DMSO (control) or SEL201 and/or 5′-azacytidine for 48 and 72 hours. Samples were processed and analyzed as previously described , 56.All statistical analyses were performed using GraphPad Prism 6.0 software as described previously , 56.


Levels of miR-134-5p and miR-320a-3p were significantly down-regulated (p < 0.001) in melanoma samples (n = 96) compared to healthy controls (n = 28). Differentially expressed protein-encoding mRNA 5′-fragments were enriched for the angiopoietin, p21-activated kinase (PAK), and EIF2 pathways. Levels of ATM1, AMFR, SOS1, and CD109 gene fragments were up-regulated (p < 0.001) in melanoma samples (n = 144) compared to healthy controls (n = 41) (AUC = 0.825). Over 40% of mapped reads were YRNAs, a class of non-coding RNAs that to date has been little explored. Expression levels of RNY3P1, RNY4P1, and RNY4P25 were significantly higher in patients with stage 0 disease than either healthy controls or more advanced stage disease (p < 0.001). In conclusion, we have identified a number of novel RNA biomarkers, which, most importantly, we validated in multi-center retrospective and prospective cohorts, suggesting potential diagnostic use of these RNA species.The circulating transcriptome is a valuable source of cancer biomarkers, which, with the exception of microRNAs (miRNAs), remains relatively unexplored. To elucidate which RNAs are present in plasma from melanoma patients and which could be used to distinguish cancer patients from healthy individuals, we used next generation sequencing (NGS), and validation was carried out by qPCR and/or ddPCR. We identified 442 different microRNAs in samples, eleven of which were differentially expressed ( Although malignant melanoma accounts for ~4% of skin cancer cases, it accounts for ~75% of all associated mortalities. In the US alone, it is estimated there were 87,000 new cases and nearly 10,000 deaths due to melanoma in 2017 .Non-invasive diagnostics, or liquid biopsies, represent a major advance towards earlier diagnosis and disease monitoring of cancer patients, including those with melanoma. As a consequence, there has been a great deal of interest in recent years in the potential of circulating nucleic acids, and in particular circulating microRNAs (miRNAs) ,5. In meRNY1, RNY3, RNY3, RNY5) involved in Ro60 inhibition, DNA replication, and quality control of non-coding RNAs [We identified not only circulating miRNAs with biomarker potential, but also mRNA gene fragments and non-coding YRNAs. YRNAs (Ro-associated Y) are poorly characterized, non-coding RNAs, which were initially identified in the blood of rheumatic autoimmune disease patients . They aring RNAs ,12,13. OWe optimized library construction by comparing several protocols, including different ribodepletion methodologies, using plasma from healthy controls in a pilot study, before settling on the protocol described in materials and methods . It shouDue to the low quantity of cfRNA in plasma, we decided to pool plasma samples according to clinical stage, as depicted in 5 and 3.14 × 105 reads per sample. The most abundant miRNAs were members of the let-7 family, which accounted for >70% of mapped miRNAs reads, followed by miR-423 and miR-320a-3p. Eleven miRNAs were identified by ANOVA as being differentially expressed between the different disease stages and healthy controls . Receiver operating characteristic (ROC) analysis gave area under curve (AUC) values of 0.798 (miR-320a-3p) and 0.788 (miR-134-5p), with a higher sensitivity (90%) for miR-320a-3p and a higher specificity for miR-134-5p (96%)  .Because mRNA is degraded by RNase activity in the blood into fragments with an average size of 200 bases , rather p < 0.05; ATM, ARHGAP, AMFR, CD109, and SOS1 genes)  using the predictive algorithms TargetScan and miRDB [Seventy of the probe sets were identified as being differentially expressed between samples (1 genes) . We werend miRDB . The fouATM, AMFR, CD109, and SOS1 were all significantly higher (p < 0.001) in plasma samples from either stage 0, stage I/II, or stage III/IV melanoma patients than in healthy controls   j.RNY1, RNY3, and RNY4) representing an average of 26.1% of reads, 30 YRNA pseudogenes representing an average of 48.4% of reads, 69 7SK sequences (average 0.05% of reads), and 194 Rfam predicted YRNA sequences representing an average of 25.5% of reads , selected on the basis of fold-change and read count. We measured levels of the YRNAs in a validation cohort of 80 samples  and high-stage disease , and identified five differentially expressed YRNA fragments  in plasma from all stages of melanoma patients when compared to samples from healthy controls. MiR-320a has also been found to be down-regulated in melanoma tumor cells when compared to heathy skin samples [miR-320a has been observed in the blood of several cancers including colorectal cancer [miR-320a is up-regulated in melanoma cells after treatment with bevacizumab or rapamycin + bevacizumab [miR-134 has been characterized as a tumor suppressor, acting to regulate proliferation, apoptosis, and invasion and migration in a wide range of cancer types, including melanoma [miR-320a miRNA had a sensitivity of 90%, whereas miR-134 had a specificity of 96%, suggesting these two miRNAs in combination could be useful biomarkers for melanoma.Based on our sequencing results, we measured the expression of  samples . Furtherl cancer , and retl cancer . Moreoveacizumab . Furthermelanoma . ROC anaEven though circulating extracellular mRNA was first detected in 1999 (in melanoma) , as the SOS1 and ATM1, which were the third and fourth most differentially expressed probe sets in our analysis, form part of the angiopoietin, PAK, and EIF2 pathways. We measured levels of SOS1, ATM1, CD109, and AMFR mRNA fragments in plasma samples from 173 melanoma patients and 47 healthy controls. With the exception of CD109, these mRNA fragments mapped to regions corresponding to the 5′-terminus of the reference gene transcript and included the initiation codon. Consistent with the NGS data , and has also been found to be down-regulated in more advanced stage hepatocellular carcinoma [AMFR gene, gp78, also regulates EMT, and increasing levels of AMFR are associated with metastatic melanoma [CD109 is a predicted target of miR-134 by the Targetscan algorithm; we are currently carrying out experiments to confirm this. ATM1 is a serine/threonine kinase induced by DNA damage and associated with risk in many cancer types [CD109 and AMFR were higher in plasma from stage 0 disease than more advanced stage disease, suggesting that these biomarkers maybe non-tumoral in origin. Consistent with this hypothesis, the release of CD109 by bone marrow mesenchymal stem cells has recently been shown to attenuate EMT in skin squamous cell carcinoma [AMFR plays an important role in regulation of the anti-cancer immune Stimulator of interferon genes (STING) pathway [Pathway analysis of the genes corresponding to differentially-expressed mRNA fragments showed significant enrichment in the angiopoietin, p21-activated kinase (PAK) and Eukaryotic Initiation Factor 2 (EIF2) pathways. It has been previously reported that circulating level of Angiopoietin-2 (Ang-2) protein in melanoma patient sera closely correlates with disease progression . SimilarNGS data , levels disease. b–e. CD10arcinoma . The promelanoma ,42. Intrer types . SOS1 iser types . Interesarcinoma , and AMF pathway .SOS1) to 0.767 (ATM1). In contrast, a combination of ATM1, SOS1, and AMFR resulted in an AUC value of 0.825 with a sensitivity of 75% and specificity of 92%. Although these findings need to be confirmed independently, this combination compares very favorably with existing sera markers such as LDH and S100B with reported sensitivities/specificities of 41.6/84.2% and 36.3/96.5%, respectively [To test the potential diagnostic ability of these biomarkers, we carried out ROC analysis, however the results from individual mRNA fragments were poor  and prospectively (n = 289). Retrospective samples were obtained from the John Radcliffe Hospital, Oxford , and the AVAST-M multi-center phase 3 clinical trial  [n = 67) or the Onkologikoa Cancer Hospital and Donostia University Hospital of San Sebastián : a total of 327 melanoma patients  were obtained from the Basque Biobank for Research O+EHUN. Plasma preparation was carried out within 1 h of phlebotomy, with blood collected in EDTA-coated tubes followed by centrifugation for 1000× g for 15 min at 4 °C.Patient plasma samples were collected both retrospectively ( n = 89) . Samplespatients . The cliWith the exception of the 37 prospectively collected samples used for NGS , only a For the plasma samples used for NGS (5–8 mL), cfRNA was purified using the plasma RNA purification kit from Norgen Biotek , and for validation studies (1 mL samples) the miRCURY™ RNA Isolation Kit Biofluids from Exiqon  was used.The samples used for NGS were pooled according to disease stage, as shown in Sequencing reads were quality filtered using the fastx_artifacts_filter tool, and ligation adapters were removed using the AdRec.jar program )). Reads were mapped to the GRCh37 build of the human genome using the Bowtie 2.0 algorithm. A custom annotated probe set was built by combining probes from GENCODE version 8 , supplem® Assay Design Tool from Applied Biosystems , using the sequences corresponding to the respective probe sets (mRNA was reverse transcribed (RT) using random primers with the High Capacity cDNA Reverse Transcription Kit from Applied Biosystems following the manufacturers’ protocol with DNase treatment. Due to the difficulty in quantifying cfRNA reliably, we used fixed volumes in reactions ,62. For obe sets . The refmiR-24, miR-16 and miR-191) [n = 22), stage I/II (n = 26), stage III/IV (n = 15)). Using the NormFinder algorithm we identified miR-24 and miR-191 as the most stable combination of reference genes in our samples  ,65, in a samples .® Small RNA Assay Design Tool from Applied Biosystems. We performed ddPCR using QX200TM Droplet DigitalTM PCR system , following the manufacturers’ protocol. Data analysis was performed by QuantaSoft analysis software from Bio-Rad. Expression levels were compared using the Kruskal–Wallis multiple comparison test, and the Mann–Whitney independent t-test to carry out a pairwise comparison between individual groups . ROC analysis and comparisons were carried out using the method of DeLong et al., as implemented in MedCalc v. 14.8 software [Custom primers and Taqman probes for Y3P1, Y4P1 and Y4P25 were designed using the Custom Taqmansoftware .We have carried out a comprehensive, non-biased elucidation of the circulating transcriptome of melanoma patients and identified a number of promising candidate biomarker RNA species, not only miRNAs. These candidates were validated in independent cohorts by ourselves, however it is clear that further studies should be carried out by independent research groups in order to strengthen our findings and facilitate the translation of this knowledge into the clinic.What is obvious is that many virtually unexplored classes of the circulating transcriptome are yet to be fully assessed for their ability to serve as useful cancer biomarkers. As a consequence, while the discovery of circulating miRNAs represented an important event in the history of the liquid biopsy field, it is clear that there is much that we have still to explore.