In a 2012 study on the topology of the human and mouse m6A RNA methylomes Gene Ontology (GO) analysis of differentially expressed genes (DEG's) indicated a noteworthy enrichment of the p53 signaling pathway: 22/23 genes had differentially expressed splice variants, of which 18 were methylated. Moreover, 15 other members of the signaling pathway, which were not significant DEG's, exhibited significant differential isoform expressions. For example, isoforms of MDM4, needed for p53 inactivation were downregulated. Similar pro-apoptotic effects were observed in other pathway genes including MDM2, FAS and BAX. Higher apoptosis rate in HaCaT-T cells resulted with knockdown of m6A subunit METTL3, which also reversed a significant decrease in p53 activity. Modulation of p53 signaling through splicing may be relevant to induction of apoptosis by silencing of METTL3.
Then, in a 2019 study of arsenite-induced human keratinocyte transformation knockdown of METTL3 significantly decreased m6A level, restored p53 activation and inhibited cellular transformation phenotypes in the arsenite-transformed cells. Further, it was demonstrated that m6A downregulated the expression of the positive p53 regulator, PRDM2, through the YTHDF2-promoted decay of PRDM2 mRNAs. Further, m6A upregulated the expression of negative p53 regulator, YY1 and MDM2 through YTHDF1-stimulated translation of YY1 and MDM2 mRNA.
Downregulation of METTL3, which in spinal cord contributes with YTHDF2 to modulate inflammatory pain may upregulate differentially expressed p53 network splice variants that oppose YTHDF2 induced downregulation of p53, via PRDM2 leading to apoptotic or diseased cells. In diseased environments cytokines may upregulate YTHDF2 in NK cells leading to downregulation of p53 and cytoskeletal transformation that may be sufficient, at an immune synapse to advance cytolysis.
p53 signals may inform selections of cells and tissue that prime NK cells for advanced, personalized immune therapy.
The first intron of a gene, regardless of tissue or species is conserved as a site of downstream methylation with an inverse relationship to transcription and gene expression. Therefore, it is an informative gene feature regarding the relationship between DNA methylation and gene expression. But, expression in induced pluripotent stem cells (iPSC's) has been a major challenge to the stem cell industry, because by comparison these cells have not yet reached the state of natural pluripotent or embryonic stem cells (ESC's).
In mice two X chromosomes (XC) are active in the epiblasts of blastocysts as well as in pluripotent stem cells. One XC is inactivated triggered by Xist (non coding) RNA transcripts coating it to become silent. Designer transcription factor (dTF) repressors, binding the Xist intron 1 enhancer region caused higher H3K9me3 methylation and led to XC's opening and X-linked gene repression in MEFs. This substantially improved iPSC production and somatic cell nuclear transfer (SCNT) preimplantation embryonic development. This also correlated with much fewer abnormally expressed genes frequently associated with SCNT, even though it did not affect Xist expression. In stark contrast, the dTF activator targeting the same enhancer region drastically decreased both iPSC generation and SCNT efficiencies and induced ESC differentiation.
A genome-wide, tissue-independent quasi-linear, inverse relationship exists between DNA methylation of the first intron and gene expression. More tissue-specific, differentially methylated regions exist in the first intron than in any other gene feature. These have positive or negative correlation with gene expression, indicative of distinct mechanisms of tissue-specific regulation. CpGs in transcription factor binding motifs are enriched in the first intron and methylation tends to increase with distance from the first exon–first intron boundary, with a concomitant decrease in gene expression.
Since the relationship between sequence, methylation, repression and transcription is determinative in ESC differentiation it may also suggest a broader link to differential translation. Translation is required for miRNA-dependent transcript destabilization that alters levels of coding and noncoding transcripts. But, steady-state abundance and decay rates of cytosolic long non-coding RNA's (lncRNAs) are insensitive to miRNA loss. Instead lncRNAs fused to protein-coding reporter sequences become susceptible to miRNA-mediated decay.
In this model, first intron DNA sequences that are differentially methylated, bind transcription factors that effect transcription, impact splicing, expressions of coding or non-coding transcripts and transcript destabilizations resulting in differential rates and possible variations in translation. This bottom-up, dynamic view of the classical process may elevate the first intron from 'junk' to a DNA 'brain' because it plays a more extensive role, heading the process toward translation of any gene or switching it off entirely.
For this reason, among others Codondex uses first intron k-mers relative to the transcripts mRNA as the basis for comparing same gene transcripts in diseased cells or tissue samples. Further, p53 and BRCA1 miRNA key sequences, discovered using Codondex iScore algorithm, when transfected into HeLa cells resulted in significantly reduced proliferation that may result from this accelerated, transfected miRNA dependent decay.
Relationships exist between short sequences of proximal DNA (SSPD) of a gene that when transcribed into RNA present stronger or weaker binding attractions to RNA binding proteins (RBP'S) that settle, edit, splice and resolve messenger RNA (mRNA). Responsive to epigenetic stimuli on Histones and DNA, mRNA are constantly transcribed in different quantity, at different times such that different mRNA strands are transported from the nucleus to cytoplasm where they are translated into and produce any of more than 30,000 different proteins.
Single nucleotide polymorphisms and DNA mutations can alter SSPD combinations in different diseased cells thus altering sequence proximity, ordering that affects transcribed RNA's attraction and optimal binding of RBP's. This may result in modified splicing of RNA, assembly of mRNA and slight or major variations in some or all translated protein derived from that gene.
The specific effects of these DNA variations, on the multitude of proteins produced are generally unknown. However, it remains important to understand their effects in disease, diagnosis and therapy. Typically these have historically been researched by large scale analysis of RBP on RNA as opposed to the more fundamental, yet underrepresented massive array of diseased variant DNA to mRNA transitions.
Most pharmaceutical research is directed to a molecular interference targeting an aberrant protein to cure widely represented or highly impactful disease conditions of society. Economic assessments generally influence government decisions to support research based on loss of GDP contribution by a specific disease in a patient cohort. However, in the modern multi-omics era top down research into protein-RNA activity is descending deeper into the cell to include RNA-mRNA and mRNA-DNA customizable therapies that will eventually resolve individually assessed diseases at a price that addresses much larger array of patient needs.
SNP's and other mutations can vary considerably in cells. These variations can cause instability during division and lead to translated differences that can ultimately drive cancerous cell growth to escape patient immunity. Like a 'whack-a-mole' game, pattern variation and mechanistic persistence eventually beat the player. Without effective immune clearance these cells can replicate into tumors and contribute to microenvironments that support their existence.
We thought to analyze DNA and mRNA transcripts from cells in tumors and their microenvironments to see if we could expose the SSPD disordered combinations that may have promoted sub-optimal RBP attractions and led to sustained immune escape. Given the complexity of DNA to mRNA transcription, for any given gene many distortions in gene data sets have to be filtered. To do that we focused on p53, the most mutated gene in cancer. We designed a method to compare sequences arrays of DNA and mRNA Ensembl transcripts, from the consensus of healthy patients to multiple cell samples extracted from different sections of a patients tumor and tumor microenvironment.
We previously identified and measured different levels of Natural Killer (NK) cell cytotoxicity, produced from cocultures with the extracted samples of each of the multiple sites of a biopsy. We will measure the different p53 transcript SSPD combinations associated with each sample and determine whether disordered SSPD's corelate with NK cytotoxicity from each coculture. We expect to identify whether biopsied tumor cells, ranked by SSPD's predict the cytotoxicity resulting from NK cell cocultures. We will narrow our research to identify the varied expressions of receptor combinations associated with degrees of cytotoxicity. We will test immune efficacy to lyse and destroy tumor cells. Finally we will test for adaptive immune response.
Our vision is for per-patient, predictable cell co-culture pairings, for innate immune cell education based on ranking DNA-mRNA combinations to lead to multiple effective therapies. The falling cost of sequencing and sophistication of GMP laboratories presently servicing oncologists may support a successful use of this analytical approach to laboratory assisted disease management.