Additional file 3: of Integrative analysis and machine learning on cancer genomics data using the Cancer Systems Biology Database (CancerSysDB)

Figure S2 Interactive workflow of mitochondrial pathways. Shown is the Tricarboxylic acid cycle (TCA) pathway for KIRP cancer patients. The central view of this workflow is a bee-swarm scatterplot, which contains the averaged log2-fold changes of patient groups according to either tumor stage, gender or vital status. Each dot is represents the averaged log2-fold change of one gene that has been assigned to the chosen function. Functions can be selected on the right-hand side of the scatter plot. The dashboard below the scatter plot can be used to change the averaging according to a different feature ((a), which shows averaging according to stage), to display information on the composition of the selected feature ((b), which informs the user that all individuals of stage II, which was hovered over in this case, are male and that one individual is dead, while three of the patients are alive); or to further select individual patients and thus modify the averaging shown in the scatter plot ((c), where only female patients were chosen for stage-dependent averaging; as female patient data are only available for two stages (I and III), the scatter plot is changed accordingly). (PNG 679 kb

Additional file 1: of The founder-cell transcriptome in the Arabidopsis apetala1 cauliflower inflorescence meristem

Comparison of log2-transformed expression from qRT-PCR for a subset of 18 up- or downregulated genes from the transcriptome dataset normalised to ACTIN2 expression and the log2 (relative expression) from RNA-seq. (DOC 150 kb

Additional file 2: of Integrative analysis and machine learning on cancer genomics data using the Cancer Systems Biology Database (CancerSysDB)

Figure S1 Overall success rate of the prediction of tumor types by random forests depending on (a) the number of samples per stratum in the random forest, (b) the number of variables picked randomly for each tree in the forest and (c) the number of trees learned in the forest. Importantly, the accuracy is increasing monotonically with the number of samples, indicating that the overall strategy is suitable, in particular, for a database with continuously growing amounts of data. In contrast, the success rate does not so much depend on the parameters chosen for the training phase of the random forest. (PNG 34 kb

Additional file 2: of The founder-cell transcriptome in the Arabidopsis apetala1 cauliflower inflorescence meristem

Primer sequences and list of genes used for real-time PCR expression analysis. (DOCX 147 kb

ZNF395 acts through ISREI and ISREII to stimulate the ISG56 promoter.

<p>(<b>A</b>) Sequential deletions starting from the 5´ end of the ISG56 upstream regulatory region were introduced into the ISG56-Luc construct as indicated in the figure. The corresponding luciferase reporter constructs were co-transfected with 5, 10 and 20ng of the FLAG-ZNF395 expression vector. The relative luciferase activity of the full length ISG56-Luc (=ISG56-654) construct was set as 1. The numbers above each set represent the fold activations induced by ZNF395 with the relative activity of each mutated reporter construct set as 1. (<b>B</b>) The construct ISG56Δ117-93 contains a deletion of the two ISREs within the context of the full length ISG56-Luc construct which harbors the upstream region up to -654bp while in ISG56-mtISRE I/II a T in each ISRE has been changed into G, as indicated beneath the graph. All reporter constructs were co-transfected again with 5, 10 or 20ng of the expression vector for FLAG-ZNF395. The sequence of the two ISREs present in the ISG56 promoter with the point mutations that have been introduced is provided. (<b>C</b>) Transient transfections with ISG56-Luc reporter constructs that were modified to contain either two copies of ISRE I (ISG56-2x ISRE I) or two copies of ISRE II (ISG56-2x ISRE II) and 5ng of expression vector for ZNF395 or IRF3-5D, respectively. (<b>D</b>) ChIP-assay. RTS3b-TR-FLAG-ZNF395 cells were grown in the absence or presence of Dox, cross-linked and subjected to a ChIP assay with antibody against the FLAG-tag and control mouse IgG. The precipitated DNA segments were amplified with a LightCycler using primers flanking the ISREs of the ISG56 promoter. The ISG56-Luc reporter construct was included as standard to allow a quantification. The copy number obtained for the input was set as one for each extract and the fold enrichment was calculated. The PCRs were performed in triplicate (* p=0.05). (<b>E</b>) Gel shift analysis. Bacterially expressed his-tagged purified ΔN-ZNF395 (lacking amino acids 1-114) was incubated with 200pg ISREI-wt (lanes 1-4) or ISRE-mut oligonucleotide (lanes 5-7), both radioactively labeled with ³²P-γ-ATP and the binding was analyzed with a native PAA gel. In lanes 3 and 6, a 250-fold excess of unlabeled ISRE-wt and in lanes 4 and 7, of ISRE-mut oligonucleotide were added as competitors. In the gel shift shown on the right, nuclear extracts prepared from RTS3b-TR-FLAG-ZNF395 cells, either incubated in the absence or presence of Dox and polyI:C, as indicated, were incubated with labeled ISRE-wt oligonucleotide and a 250-fold excess of unlabeled ISRE-wt or ISRE-mut oligonucleotide. The position of the putative ZNF395-ISRE complex is indicated by an arrow.</p

ZNF395 activates innate immune response and cancer-associated genes.

<p>(<b>A</b>) Stably transfected RTS3b cells expressing the tet repressor and FLAG-tagged ZNF395 under control of the tet inducible promoter (lanes 3, 4) or the empty vector pcDNA4/TO (lanes 1, 2) were either grown in the absence (lanes 1, 3) or presence of Dox (lanes 2, 4) for 24h. Extracts were used for ImmunoBlot (IB) which was developed with the FLAG antibody and an anti-actin antibody as control. ns (non specific band) (<b>B</b>) Total RNA isolated from RTS3b TR-FLAG-ZNF395 cells, either grown with or without Dox was used for qRT-PCR to analyze the expression of the factors shown in the graph. The corresponding values were normalized to the values for the housekeeping gene hypoxanthine guanine phosphoribosyl transferase (HPRT) and those obtained from cells grown in the absence of Dox were set as 1 for each factor. The graph represents the means of two independent experiments each performed in duplicate. The error bars represent the standard deviations. (<b>C</b>, <b>D</b>) RTS3b and U87-MG cells were transfected with control siRNA or siRNA targeting ZNF395 in duplicate. One set of samples was treated with solvent and the other with IFN-α, before total RNA was isolated. QRT-PCR was performed with the specific primer to amplify ISG56, IFI44, IFI16 and ZNF395 transcripts. CP-values obtained for the various factors were normalized against those for the housekeeping gene HPRT. The value with RNA from solvent treated cells transfected with siControl was set as 1 in each case. The fold activations were calculated according to the comparative threshold method described in Pfaffl et al. [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0074911#B64" target="_blank">64</a>]. QPCRs were performed four times and the standard deviations are given. The values provided in the figure reflect the non-induced basal expression level in the absence of ZNF395 (** p <0.01).</p

ZNF395 activates the ISG56 promoter and requires its DNA-binding domain and CR1.

<p>(<b>A</b>) RTS3b cells were seeded in six-well plates and transiently transfected with 500ng of the ISG56-Luc reporter construct and increasing amounts (5, 10, 20ng) of expression vector for FLAG-ZNF395 or the different mutants per well, as indicated. The structure of ZNF395 with its conserved regions CR1, CR2 and CR3 is depicted beneath the graphs including the sequence of the C-terminal 25 amino acids, which are conserved to the E-tail of TCF-1E and TCF-4E [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0074911#B52" target="_blank">52</a>]. The M at pos. 169 and 172 were changed to A in mtNES while in ΔCR1 the amino acids from 165 to 188 were deleted. The amino acids that were mutated in mtCR3 and leading to loss of DNA-binding are indicated. (<b>B</b>) RTS3b and C33A cells were first transfected with siControl or siZNF395 and 24h later with the ISG56-Luc reporter construct. All graphs represent the results of at least three independent experiments. The standard deviations are given. (<b>C</b>) RTS3b cells were transiently transfected with the Luciferase reporter construct containing the IFI44-promoter including 560bp bases upstream of the initiation site. The segment harbors two overlapping ISREs, which have been shown to mediate the IFN-dependent induction of IFI44. The expression vector for ZNF395 and ZNF395mtNES were co-transfected as in A.</p

ZNF395 induced during hypoxia is modified by IKK.

<p>(<b>A</b>) U937 and U87-MG cells were either kept under normoxic or under hypoxic conditions (2% O₂ atmosphere) for 12h before preparing total cell extracts or RNA. RNA was used for qRT-PCR to analyze the expression of ZNF395, which was normalized to the expression of HPRT. The fold induction was calculated according the comparative threshold cycle [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0074911#B64" target="_blank">64</a>]. 50µg of protein extracts were used for an IB with the anti-ZNF395. Actin served as the loading control. (<b>B</b>) U87-MG cells were grown in ambient or 2% O₂ atmosphere and either treated with BMS-345541 or left untreated. Fifty µg of total cell extracts were used in an IB to detect ZNF395. In lanes 7, 9 and 10, these extracts were incubated with λ-phosphatase, as indicated. (<b>C</b>) 15µg of extracts from RTS3b-TR-FLAG-ZNF395 cells grown in the absence or presence of Dox, hypoxia and TNFα, as indicated in the figure, were analyzed in a IB for the expression of ZNF395, and actin. α.</p

Active IKK marks ZNF395 for degradation.

<p>(<b>A</b>) RTS3b cells were transiently transfected with 5ng (+) and 10ng (++) of the expression vector for FLAG-ZNF395 and in the experiments shown in the right graph, 5ng (+) or 10ng (++) of the vector for ZNF395mtNES was included. The transfected cells were treated either with IFN-α (left graph) or with polyI:C (right graph) as indicated. The bars represent the fold activations calculated from three independent experiments and the standard deviations are included. (<b>B</b>) Cells were transiently transfected with expression vector for FLAG-ZNF395 (lanes 4-8) or the empty vector (lanes 1-3) and treated either with polyI:C (lanes 2, 5), IFN-α (lanes 3, 6), TNFα (lane 8) or solvent (lanes 1, 4, 7). An IB with the anti-ZNF395 antibody and the anti-actin antibody was performed. (<b>C</b>) Cells transiently transfected with the FLAG-ZNF395 vector or the empty vector (in lanes 7, 10, 11) were treated with TNFα (lanes 1, 2), poly I:C (lanes 3, 4) or MG132 (lanes 9, 11, 13). BMS-345541 was added to the cells used in lanes 1, 3, 5 and the solvent DMSO in lanes 2, 4, 6, 7, 8. The analysis of ZNF395 expression was done by IB using the anti-FLAG and anti-actin antibody. In lanes 10–13, FLAG-ZNF395 was precipitated by M2-FLAG-agarose and the IB was performed with an antibody against ubiquitin. (<b>D</b>) RTS3b (lanes 2, 3), U937 (lanes 4, 5) or U87-MG cells (lanes 6, 7) were incubated in medium containing BMS-345541 (+) or DMSO (-) and analyzed for ZNF395 expression by an IB developed with the anti-ZNF395 antibody. In lane 1, extracts prepared from RTS3b TR-FLAG-ZNF395 cells used in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0074911#pone-0074911-g001" target="_blank">Figure 1</a> were used as a control.</p

Additional file 1: of Integrative analysis and machine learning on cancer genomics data using the Cancer Systems Biology Database (CancerSysDB)

The source code of the database queries and workflow scripts for the three use cases reported in the paper. The results can be reproduced using the query results and analysis scripts provided. File query1.csv contains the barcodes of all samples for which mutation data do exist. File query2.csv contains the barcodes of all samples which carry a mutation in the gene of interest. Finally, query3.csv contains the survival data (according to Fig. 1a), a list of all mutations of patients in the cohort of interest (according to Fig. 1b), or a list of all genomic segments with aberrant copy number in the cohort of interest (according to Fig. 1c). There are small discrepancies between the number of patients with mutation data and the number of patients with survival data (Fig. 1a) and copy number data (Fig. 1c). (ZIP 4981 kb