Big genes are big mutagen targets: A connection to cancerous, spherical cells?

Chemical complementarity between immune receptors and cancer mutants, independent of antigen presentation protein binding, is associated with increased survival rates

•

Establishment of an immunological distinction between endometrioid and serous uterine cancers.

•

High priority CDR3s, mutant amino acids (AA) for endometrioid cancer prognosis, therapy tools.

•

Further understanding of CDR3-mutant AA complementarity scoring factors, such as HLA binding.

Uterine cancer has been associated with a T-cell immune response that leads to increased survival. Therefore, we used several bioinformatics approaches to explore specific interactions between T-cell receptor (TCR) and tumor mutant peptide sequences. Using endometrioid uterine cancer exome files from the The Cancer Genome Atlas database, we obtained tumor resident V-J recombinations for the T-Cell Receptor alpha gene (TRA). The charged-based, chemical complementarity for each patient's LRP2 or TTN mutant amino acids (AAs) and the recovered, TRA complementarity determining region-3 (CDR3) sequences was calculated, allowing a division of patients into complementary and noncomplementary groups. Complementary groups with TTN mutants had increased disease-free survival and increased expression of complement genes. Furthermore, the survival distinction based on CDR3-mutant peptide complementarity was independent of programmatically assessed HLA class II binding and was not observable based on the CDR3 AA chemical features alone. The above approach provides a potential, highly efficient method for identifying TCR targets in uterine cancer and may aid in the development of novel prognostic tools.

Classification of Homo sapiens gene behavior using linear discriminant analysis fused with minimum entropy mapping

Classification of Homo sapiens gene behavior employing computational biology is a recent research trend. But monitoring gene activity profile and genetic behavior from the alphabetic DNA sequence using a non-invasive method is a tremendous challenge in functional genomics. The present paper addresses such issue and attempts to differentiate Homo sapiens genes using linear discriminant analysis (LDA) method. Annotated protein coding sequences of Homo sapiens genes, collected from NCBI, are taken as test samples. Minimum entropy-based mapping (MEM) technique assists to extract highest information from the numerical DNA sequences. The proposed LDA technique has successfully classified Homo sapiens genes based on the following features: composition of hydrophilic amino acids, dominance of arginine amino acid, and magnitude and size of individual amino acids. The proposed algorithm is successfully tested on 84 Homo sapiens healthy and cancer genes of the prostate and breast cells. Classification performance of the proposed LDA technique is judged by sensitivity (89.12%), specificity (91.9%), accuracy (90.87%), F1 score (92.03%), Matthews' correlation coefficients (81.04%), and miss rate (9.12%), and it outperforms other four existing classifiers. The results are cross-validated through Rayleigh PDF and mutual information technique. Fisher test, 2-sample T-test, and relative entropy test are considered to verify the efficacy of the present classifier.

A multi-omics study on cutaneous and uveal melanoma

AIM

To present the multi-omics landscape of cutaneous melanoma (CM) and uveal melanoma (UM) from The Cancer Genome Atlas (TCGA).

METHODS

The differentially expressed genes (DEGs) between CM and UM were found and integrated into a gene ontology enrichment analysis. Besides, the differentially expressed miRNAs were also identified. We also compared the methylation level of CM with UM and identified the differentially methylated regions to integrate with the DEGs to display the relationship between the gene expression and DNA methylation. The differentially expressed transcription factors (TFs) were identified.

RESULTS

Though CM had more mutational burden than UM, they shared several similarities such as the same rankings in diverse variant types. Except GNAQ and GNA11, the other top 18 mutated genes of the combined group were mostly detected in CM instead of UM. On the transcriptomic level, 4610 DEGs were found and integrated into a gene ontology enrichment analysis. We also identified 485 differentially expressed miRNAs. The methylation analysis showed that UM had a significantly higher methylation level than CM. The integration of differentially methylated regions and DEGs demonstrated that most DEGs were downregulated in UM and the hypo- and hypermethylation presented no obvious difference within these DEGs. Finally, 116 hypermethylated TFs and 114 hypomethylated TFs were identified as differentially expressed TFs in CM when compared with UM.

CONCLUSION

This multi-omics study on comparing CM with UM confirms that they differ in all analyzed levels. Of notice, the results also offer new insights with implications for elucidating certain unclear problems such as the distinct role of epithelial mesenchymal transition in two melanomas, the different metastatic routes of CM and UM and the liver tropism of metastatic UM.

Matrix-Metalloprotease Resistant Mucin-16 (MUC16) Peptide Mutants Represent a Worse Lung Adenocarcinoma Outcome

PURPOSE

The relationship of lung adenocarcinoma (LUAD)-specific proteases and the mutant profile of cytoskeletal and extracellular matrix proteins (CECMPs) are examined.

EXPERIMENTAL DESIGN

Mutant CECMPs are assessed with an automated application of a protease binding, amino acid-based, scoring database.

RESULTS

MUC16 (Human Genome Organization symbol for mucin-16 gene) mutants in particular are, more often than not, resistant to matrix-metalloproteases (MMPs) commonly secreted by LUAD cells, and LUAD cases representing the MUC16, MMP resistant mutants have a worse outcome. Similar results are obtained for MUC16 mutants resistant to cathepsins, also commonly secreted by LUAD cells. Analyses also show that MUC16, MMP resistant peptide mutants have greater binding affinities to HLA-A and HLA-B when compared to MUC16, MMP nonresistant peptide mutants.

CONCLUSION

These results provide a potential, novel biomarker for lung cancer progression, in particular, protease resistant MUC16 peptides; and suggest a possible mechanism of immune escape entailing the reduction of mutant peptides available for HLA class I binding.

MMP7 sensitivity of mutant ECM proteins: An indicator of melanoma survival rates and T-cell infiltration

OBJECTIVE

To assess the potential impact of mutant ECM amino acids (AA) on melanoma-related matrix metalloproteinase-7 (MMP7) activity.

DESIGN AND METHODS

We applied a novel scripted algorithm, based on the MEROPS database, to reveal mutant-dependent sensitivity changes across the cancer genome atlas, melanoma dataset.

RESULTS

This approach revealed a strong bias in favor of mutant AA dependent protease sensitivity increases. Thus, melanoma specimens with relatively few mutations had only MMP7 mutant sensitive, ECM peptides. As mutations increased, melanoma specimens included mutant AA representing mostly increased sensitivity and a small but increasing number of mutant AA representing decreased MMP7 sensitivity. There was no detection of melanoma specimens with only decreases in MMP7 sensitivity. Furthermore, melanoma specimens with exclusively increased sensitivity and thereby only a few overall mutations represented reduced T-cell infiltrates and worse outcomes.

CONCLUSIONS

Overall, the results indicated that changes in MMP7 sensitivity, attributable to mutant AA, have the potential of identifying patients with distinct survival outcomes as well as patients with cancer specimen immune activity.

Analysis of cancer gene attributes using electrical sensor

Prediction of cancer gene attributes by their primary structure (long amino acid sequence) is instrumental in large-scale genomics projects, especially in the field of genomics. Various methods are proposed to predict gene characteristics from its primary structure, but accurate prediction of it is still very challenging task. Here we introduce an electrical network based sensor or detector to discriminate cancer and non-cancer cells based on two features i.e. amino acid sequence length, and hydrophilic/hydrophobic property. The electrical circuit consists of resistors, capacitors and inductors, is used for modeling individual amino acid and cascaded to form gene system. Corresponding electrical responses are judged using Bode and Nyquist analyzers and achieve 89.55% accuracy with 87.06% True Positive rate and 95.42% True Negative rate, demonstrate that proposed electrical sensor model is very promising for predicting the cancer gene attributes as well as non-cancer gene in the field of large-scale genomics study.

Mutant cytoskeletal and ECM peptides sensitive to the ST14 protease are associated with a worse outcome for glioblastoma multiforme

We previously identified a set of the most frequently mutated cytoskeleton- and extracellular matrix-related proteins (CECMPs) in numerous cancer datasets. In this report, we used a bioinformatics approach to assess the impact of amino acid (AA) substitutions on the sensitivity of CECMPs to the ST14 protease (matriptase I), a transmembrane serine protease previously implicated in cancer development. Results indicated that AA substitutions in glioblastoma multiforme (GBM) CECMPs are skewed toward increased resistance to the ST14 protease, in comparison to the wild-type peptide sequence. Furthermore, the protease resistant AA substitutions represent relatively high binding affinities to HLA class I proteins, when assessing the binding specificities using HLA class I alleles matched to the source of the mutant AA. Moreover, samples representing AA substitutions that increased protease sensitivity also represented reduced overall and disease-free survival periods for patients with glioblastoma. To assess tumor specimen immunogenicity, we identified T-cell receptor (TCR) V(D)J recombinations in GBM exome files. The overlap between ST14 protease sensitive mutant barcodes and the TCR V(D)J recombination read positive barcodes represented significantly reduced survival.

The human, F-actin-based cytoskeleton as a mutagen sensor

Background

Forty years ago the actin cytoskeleton was determined to be disrupted in fibroblasts from persons with DNA repair-defective, hereditary colon cancer, with no clear connection between the cytoskeleton and DNA repair defects at that time. Recently, the large number of sequenced genomes has indicated that mammalian mutagenesis has a large stochastic component. As a result, large coding regions are large mutagen targets. Cytoskeletal protein-related coding regions (CPCRs), including extra-cellular matrix proteins, are among the largest coding regions in the genome and are indeed very commonly mutated in cancer.

Methods

To determine whether mutagen sensitivity of the actin cytoskeleton could be assessed experimentally, we treated tissue culture cells with 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanone and quantified overall cytoskeleton integrity with rhodamine-phalloidin stains for F-actin.

Results

The above approach indicated cytoskeletal degradation with increasing mutagen exposure, consistent with increased mutagenesis of CPCRs in TCGA, smoker samples, where overall mutation rates correlate with CPCR mutation rates (R² = 0.8694; p < 0.00001). In addition, mutagen exposure correlated with a decreasing cell perimeter to area ratio, raising questions about potential decreasing, intracellular diffusion and concentrations of chemotherapy drugs, with increasing mutagenesis and decreasing cytoskeleton integrity.

Conclusion

Determination of cytoskeletal integrity may provide the opportunity to assess mutation burdens in nonclonal cell populations, such as in intact tissues, where DNA sequencing for heterogeneous mutation burdens can be challenging.

Smoking correlates with increased cytoskeletal protein-related coding region mutations in the lung and head and neck datasets of the cancer genome atlas

Cancer from smoking tobacco is considered dependent on mutagens, but significant molecular aspects of smoking‐specific, cancer development remain unknown. We defined sets of coding regions for oncoproteins, tumor suppressor proteins, and cytoskeletal‐related proteins that were compared between nonsmokers and smokers, for mutation occurrences, in the lung adenocarcinoma (LUAD), head and neck squamous carcinoma (HNSC), bladder carcinoma (BLCA), and pancreatic adenocarcinoma ( PAAD) datasets from the cancer genome atlas (TCGA). We uncovered significant differences in overall mutation rates, and in mutation rates in cytoskeletal protein‐related coding regions (CPCRs, including extracellular matrix protein coding regions), between nonsmokers and smokers in LUAD and HNSC (P < 0.001), raising the question of whether the CPCR mutation differences lead to different clinical courses for nonsmoker and smoker cancers. Another important question inspired by these results is, whether high smoker cancer mutation rates would facilitate genotoxicity or neoantigen‐based therapies. No significant, mutation‐based differences were found in the BLCA or PAAD datasets, between nonsmokers and smokers. However, a significant difference was uncovered for the average number of overall cancer mutations, in LUAD, for persons who stopped smoking more than 15 years ago, compared with more recent smokers (P < 0.032).

Protected cytoskeletal-related proteins: Towards a resolution of contradictions regarding the role of the cytoskeleton in cancer

Initial reports of the role of the cytoskeleton in cancer indicated that tumor cells with a more disorganized cytoskeleton were more tumorigenic. These reports were based on stains for the F-actin cytoskeleton, for example, using phalloidin or anti-F-actin antibody reagents, and gave a basic impression of F-actin-based cytoskeletal integrity. Later developments emphasized the significance of the cytoskeletal elements in cell migration, presumably associated with either basement membrane invasion or metastasis, or both, with several specific proteins implicated in the formation of cell invadopodia. With the advent of genomics approaches, it has become clear that cytoskeletal related proteins are indeed common targets of mutagenesis in cancer and commonly rank among the most mutated proteins in cancers, presumably due to large coding region sizes and the significant stochastic component to human mutagenesis. This cytoskeletal genomics result is consistent with the loss of cytoskeleton integrity as a hallmark of tumor development, but raises the question of whether such mutational sensitivity relates to the migration and invadopodia aspects of tumor progression. In the present study, the authors report that it is possible to identify a set of cytoskeletal related proteins protected from mutation, in comparison to the commonly mutated cytoskeleton related proteins in certain, but not all cancer, datasets.

Identification of Sets of Cytoskeletal Related and Adhesion-related Coding Region Mutations in the TCGA Melanoma Dataset that Correlate with a Negative Outcome

BACKGROUND

Relatively little cancer genome atlas data has been associated with clinically relevant stratifications of individual cancers.

RESULTS

Mutations in two subsets of a cytoskeletal related and adhesion-related protein coding region set (CAPCRs) were determined to have strong associations with a negative outcome for melanoma, in-cluding a subset constituted by: DSCAM, FAT3, MUC17 and PCDHGC5 (p < 0.0001).

CONCLUSION

Roles for CAPCR mutations in cancer progression raise a question about the potential dominant negative impact of these mutations for multi-meric subcellular and extra-cellular protein struc-tures.

De novo, systemic, deleterious amino acid substitutions are common in large cytoskeleton-related protein coding regions

Human mutagenesis is largely random, thus large coding regions, simply on the basis of probability, represent relatively large mutagenesis targets. Thus, we considered the possibility that large cytoskeletal-protein related coding regions (CPCRs), including extra-cellular matrix (ECM) coding regions, would have systemic nucleotide variants that are not present in common SNP databases. Presumably, such variants arose recently in development or in recent, preceding generations. Using matched breast cancer and blood-derived normal datasets from the cancer genome atlas, CPCR single nucleotide variants (SNVs) not present in the All SNPs(142) or 1000 Genomes databases were identified. Using the Protein Variation Effect Analyzer internet-based tool, it was discovered that apparent, systemic mutations (not shared among others in the analysis group) in the CPCRs, represented numerous deleterious amino acid substitutions. However, no such deleterious variants were identified among the (cancer blood-matched) variants shared by other members of the analysis group. These data indicate that private SNVs, which potentially have a medical consequence, occur de novo with significant frequency in the larger, human coding regions that collectively impact the cytoskeleton and ECM.

Stratifying melanoma and breast cancer TCGA datasets on the basis of the CNV of transcription factor binding sites common to proliferation- and apoptosis-effector genes

Transcription factors that activate both proliferation- and apoptosis-effector genes, along with a number of related observations, have led to a proposal for a feed forward mechanism of activating the two gene classes, whereby a certain concentration of a transcription factor activates the proliferation-effector genes and a higher concentration of the transcription factor activates the apoptosis-effector genes. We reasoned that this paradigm of regulation could lead to, in the cancer setting, a selection for relatively reduced copy numbers of apoptosis-effector gene, transcription factor binding sites (TFBS). Thus, the aim of this investigation was to examine the DNA sequencing read depths of TFBS for a set of proliferation- and apoptosis-effector genes, normalized to the read depths found in matching blood samples, as provided by the cancer genome atlas (TCGA); and thereby document copy number differences among these TFBS. We determined that the melanoma and breast cancer, TCGA datasets could be divided into three categories: (i) no detectable copy number variation for the proliferation- and apoptosis-effector, shared TFBS; (ii) a relative increase in the copy number of proliferation-effector gene TFBS, compared with the copy number of the apoptosis-effector gene TFBS; and (iii) a relative decrease in the number of proliferation-effector gene TFBS. Thus, we conclude that changes in the relative copies of the shared TFBS, for proliferation- and apoptosis-effector genes, have the potential of impacting tumor cell proliferative and apoptotic capacities.

Overlap of the cancer genome atlas and the immune epitope database

Mutant peptides resulting from cancer drivers or passenger mutations are expected to have the potential to serve as a basis for cancer vaccines. However, a number of parameters regulate vaccine-associated immunogenicity, including the suitability of a peptide for binding to an antigen-presenting molecule or antibody. In order to obtain a basic indication of the prospect of human cancer epitope identification via current database development strategies, an overlap of the mutant Homo sapiens epitopes listed on the Immune Epitope Database (IEDB) and the mutant peptides indicated by The Cancer Genome Atlas (TCGA) somatic mutation database was obtained. No putative TCGA mutant peptides were detected among the 8,890 14-18 amino acid (AA) IEDB peptides available. In total, 3 IEDB mutant epitopes that encompassed a TCGA mutant AA position, but did not overlap the exact position of the TCGA mutant AA, were detected. The results of the present analysis confirm that verification of certain aspects of cancer epitope function can be obtained via the continued and systematic expansion of databases representing human protein epitopes. However, the analysis also indicates that there is relatively limited systematic information available regarding antigen-presenting molecule epitopes and cancer-related mutant peptides.

TCGA: Increased oncoprotein coding region mutations correlate with a greater expression of apoptosis-effector genes and a positive outcome for stomach adenocarcinoma

Oncogene mutations are primarily thought to facilitate uncontrolled cell growth. However, overexpression of oncoproteins likely leads to apoptosis in a feed forward mechanism, whereby a certain level of oncoprotein leads to the activation of pro-proliferation effector genes and higher levels lead to activation of pro-apoptotic effector genes. TCGA STAD barcodes having no oncoprotein coding region mutations represented reduced expression of the apoptosis-effector genes compared with barcodes with multiple oncoprotein coding region mutations. Furthermore, STAD barcodes in a "no-subsequent tumor" group, representing 224 samples, and in a "positive outcome" group, had more oncoprotein coding regions mutated, on average, than barcodes of the new tumor and negative outcome groups, respectively. BRAF, CTNNB1, KRAS and MTOR coding region mutations (as a group) had the strongest association with the no-subsequent tumor group. Tumor suppressor coding region mutations were also correlated with no-subsequent tumor. These results are consistent with an oncoprotein-mediated, feed-forward mechanism of apoptosis in patients. Importantly, the no-subsequent tumor group also had more overall mutations. This result leads to considerations of unhealthy cells or cells with more neo-antigens for immune rejection. However, a probabilistic aspect of mutagenesis is also consistent with more oncoprotein and tumor suppressor protein mutations, in cases of more overall mutations, and thus a higher likelihood of activation of feed forward apoptosis pathways.

Modeling of Cancer Classifier to Predict Site of Origin

Cancer classification based on site of origin is very significant research issue for prediction and treatment of cancer. This paper is addressing the problem of cancer classification for Homo Sapiens genes composed of amino acid chain. Cancer gene network is realized by equivalent electrical circuits based on hydrophilic/ hydrophobic property of amino acid and a classifier is modeled to determine the cancer origin. The phase value, peak gain value and shape of Nyquist curve of network model are investigated to characterize different types of cancer gene origins. The model achieves 81.09% of classification accuracy and proves to be more sensitive and simple, since it shows 69% better performance compare to the existing nucleotide based method. The proposed classifier successfully predicts the site of origin of 93 cancer gene samples.

Flat cells come full sphere: Are mutant cytoskeletal-related proteins oncoprotein-monsters or useful immunogens?

Osteogenesis imperfecta is inherited as a dominant disease because if one allele is mutated, it contributes a mutant, destructive subunit polypeptide to collagen, which requires many subunits to form normal, polymeric, collagenous structures. Recent cancer genome atlas (TCGA) data indicate that cytoskeletal-related proteins are among the most commonly mutated proteins in human cancers, in distinct mutation frequency groups, i.e., including low mutation frequency groups. Part of the explanation for this observation is likely to be the fact that many of the coding regions for these proteins are very large, and indeed, it is likely these coding regions are mutated in many cells that never become cancerous. However, it would not be surprising if mutations in cytoskeletal proteins, when combined with oncoprotein or tumor suppressor protein mutations, had significant impacts on cancer development, for a number of reasons, including results obtained almost 5 decades ago indicating that well-spread cells in tissue culture, with well-formed cytoskeletons, were less tumorigenic than spherical cells with disrupted cytoskeletons. This raises the question, are mutant cytoskeletal proteins, which would likely interfere with polymer formation, a new class of oncoproteins, in particular, dominant negative oncoproteins? If these proteins are so commonly mutant, could they be the bases for common cancer vaccines?