Better Agreement of Human Transcriptomic and Proteomic Cancer Expression Data at the Molecular Pathway Activation Level.

Previously, we have shown that the aggregation of RNA-level gene expression profiles into quantitative molecular pathway activation metrics results in lesser batch effects and better agreement between different experimental platforms. Here, we investigate whether pathway level of data analysis provides any advantage when comparing transcriptomic and proteomic data. We compare the paired proteomic and transcriptomic gene expression and pathway activation profiles obtained for the same human cancer biosamples in The Cancer Genome Atlas (TCGA) and the NCI Clinical Proteomic Tumor Analysis Consortium (CPTAC) projects, for a total of 755 samples of glioblastoma, breast, liver, lung, ovarian, pancreatic, and uterine cancers. In a CPTAC assay, expression levels of 15,112 protein-coding genes were profiled using the Thermo QE series of mass spectrometers. In TCGA, RNA expression levels of the same genes were obtained using the Illumina HiSeq 4000 engine for the same biosamples. At the gene level, absolute gene expression values are compared, whereas pathway-grade comparisons are made between the pathway activation levels (PALs) calculated using average sample-normalized transcriptomic and proteomic profiles. We observed remarkably different average correlations between the primary RNA- and protein expression data for different cancer types: Spearman Rho between 0.017 (p = 1.7 × 10−13) and 0.27 (p < 2.2 × 10−16). However, at the pathway level we detected overall statistically significantly higher correlations: averaged Rho between 0.022 (p < 2.2 × 10−16) and 0.56 (p < 2.2 × 10−16). Thus, we conclude that data analysis at the PAL-level yields results of a greater similarity when comparing high-throughput RNA and protein expression profiles.

RNA Sequencing Data for FFPE Tumor Blocks Can Be Used for Robust Estimation of Tumor Mutation Burden in Individual Biosamples.

Tumor mutation burden (TMB) is a well-known efficacy predictor for checkpoint inhibitor immunotherapies. Currently, TMB assessment relies on DNA sequencing data. Gene expression profiling by RNA sequencing (RNAseq) is another type of analysis that can inform clinical decision-making and including TMB estimation may strongly benefit this approach, especially for the formalin-fixed, paraffin-embedded (FFPE) tissue samples. Here, we for the first time compared TMB levels deduced from whole exome sequencing (WES) and RNAseq profiles of the same FFPE biosamples in single-sample mode. We took TCGA project data with mean sequencing depth 23 million gene-mapped reads (MGMRs) and found 0.46 (Pearson)-0.59 (Spearman) correlation with standard mutation calling pipelines. This was converted into low (<10) and high (>10) TMB per megabase classifier with area under the curve (AUC) 0.757, and application of machine learning increased AUC till 0.854. We then compared 73 experimental pairs of WES and RNAseq profiles with lower (mean 11 MGMRs) and higher (mean 68 MGMRs) RNA sequencing depths. For higher depth, we observed ~1 AUC for the high/low TMB classifier and 0.85 (Pearson)-0.95 (Spearman) correlation with standard mutation calling pipelines. For the lower depth, the AUC was below the high-quality threshold of 0.7. Thus, we conclude that using RNA sequencing of tumor materials from FFPE blocks with enough coverage can afford for high-quality discrimination of tumors with high and low TMB levels in a single-sample mode.

Human blood serum can donor-specifically antagonize effects of EGFR-targeted drugs on squamous carcinoma cell growth.

Many patients fail to respond to EGFR-targeted therapeutics, and personalized diagnostics is needed to identify putative responders. We investigated 1630 colorectal and lung squamous carcinomas and 1357 normal lung and colon samples and observed huge variation in EGFR pathway activation in both cancerous and healthy tissues, irrespectively on EGFR gene mutation status. We investigated whether human blood serum can affect squamous carcinoma cell growth and EGFR drug response. We demonstrate that human serum antagonizes the effects of EGFR-targeted drugs erlotinib and cetuximab on A431 squamous carcinoma cells by increasing IC50 by about 2- and 20-fold, respectively. The effects on clonogenicity varied significantly across the individual serum samples in every experiment, with up to 100% differences. EGF concentration could explain many effects of blood serum samples, and EGFR ligands-depleted serum showed lesser effect on drug sensitivity.

Mutation Enrichment and Transcriptomic Activation Signatures of 419 Molecular Pathways in Cancer.

Carcinogenesis is linked with massive changes in regulation of gene networks. We used high throughput mutation and gene expression data to interrogate involvement of 278 signaling, 72 metabolic, 48 DNA repair and 47 cytoskeleton molecular pathways in cancer. Totally, we analyzed 4910 primary tumor samples with individual cancer RNA sequencing and whole exome sequencing profiles including ~1.3 million DNA mutations and representing thirteen cancer types. Gene expression in cancers was compared with the corresponding 655 normal tissue profiles. For the first time, we calculated mutation enrichment values and activation levels for these pathways. We found that pathway activation profiles were largely congruent among the different cancer types. However, we observed no correlation between mutation enrichment and expression changes both at the gene and at the pathway levels. Overall, positive median cancer-specific activation levels were seen in the DNA repair, versus similar slightly negative values in the other types of pathways. The DNA repair pathways also demonstrated the highest values of mutation enrichment. However, the signaling and cytoskeleton pathways had the biggest proportions of representatives among the outstandingly frequently mutated genes thus suggesting their initiator roles in carcinogenesis and the auxiliary/supporting roles for the other groups of molecular pathways.

Structural basis of the high thermal stability of the histone-like HU protein from the mollicute Spiroplasma melliferum KC3.

The three-dimensional structure of the histone-like HU protein from the mycoplasma Spiroplasma melliferum KC3 (HUSpm) was determined at 1.4 Å resolution, and the thermal stability of the protein was evaluated by differential scanning calorimetry. A detailed analysis revealed that the three-dimensional structure of the HUSpm dimer is similar to that of its bacterial homologues but is characterized by stronger hydrophobic interactions at the dimer interface. This HUSpm dimer interface lacks salt bridges but is stabilized by a larger number of hydrogen bonds. According to the DSC data, HUSpm has a high denaturation temperature, comparable to that of HU proteins from thermophilic bacteria. To elucidate the structural basis of HUSpm thermal stability, we identified amino acid residues potentially responsible for this property and modified them by site-directed mutagenesis. A comparative analysis of the melting curves of mutant and wild-type HUSpm revealed the motifs that play a key role in protein thermal stability: non-conserved phenylalanine residues in the hydrophobic core, an additional hydrophobic loop at the N-terminal region of the protein, the absence of the internal cavity present at the dimer interface of some HU proteins, and the presence of additional hydrogen bonds between the monomers that are missing in homologous proteins.

Expression, purification, crystallization and preliminary X-ray crystallographic analysis of the histone-like HU protein from Spiroplasma melliferum KC3.

HU proteins belong to the nucleoid-associated proteins (NAPs) that are involved in vital processes such as DNA compaction and reparation, gene transcription etc. No data are available on the structures of HU proteins from mycoplasmas. To this end, the HU protein from the parasitic mycoplasma Spiroplasma melliferum KC3 was cloned, overexpressed in Escherichia coli and purified to homogeneity. Prismatic crystals of the protein were obtained by the vapour-diffusion technique at 4°C. The crystals diffracted to 1.36 Šresolution (the best resolution ever obtained for a HU protein). The diffraction data were indexed in space group C2 and the structure of the protein was solved by the molecular-replacement method with one monomer per asymmetric unit.

DNA repair in Mycoplasma gallisepticum.

BACKGROUND: DNA repair is essential for the maintenance of genome stability in all living beings. Genome size as well as the repertoire and abundance of DNA repair components may vary among prokaryotic species. The bacteria of the Mollicutes class feature a small genome size, absence of a cell wall, and a parasitic lifestyle. A small number of genes make Mollicutes a good model for a "minimal cell" concept. RESULTS: In this work we studied the DNA repair system of Mycoplasma gallisepticum on genomic, transcriptional, and proteomic levels. We detected 18 out of 22 members of the DNA repair system on a protein level. We found that abundance of the respective mRNAs is less than one per cell. We studied transcriptional response of DNA repair genes of M. gallisepticum at stress conditions including heat, osmotic, peroxide stresses, tetracycline and ciprofloxacin treatment, stationary phase and heat stress in stationary phase. CONCLUSIONS: Based on comparative genomic study, we determined that the DNA repair system M. gallisepticum includes a sufficient set of proteins to provide a cell with functional nucleotide and base excision repair and mismatch repair. We identified SOS-response in M. gallisepticum on ciprofloxacin, which is a known SOS-inducer, tetracycline and heat stress in the absence of established regulators. Heat stress was found to be the strongest SOS-inducer. We found that upon transition to stationary phase of culture growth transcription of DNA repair genes decreases dramatically. Heat stress does not induce SOS-response in a stationary phase.