p53 Direct Mechanisms In Immunity

Never in the field of molecular oncology have so many sites of posttranslational modification in one protein (p53) been modified by so many different enzymes, but direct response mechanisms that increase immune receptors are rarely discovered and have important implications.  

In the tumor microenvironment (TME), cancer associated fibroblasts (CAFs) display an activated phenotype and can physically remodel the extracellular matrix (ECM). Silencing p53 in the CAFs strongly compromised this activity, implicating p53 as a key contributor to a distinctive CAF feature. Here, the non-autonomous, tumor-suppressive activity of non-mutant p53 cDNA is rewired to become a significant contributor to the CAFs’ tumor-supportive activities. This surprising role for p53 in CAFs suggests that, during tumor progression p53 functionality is altered, not only in the cancer cells, but also in their adjacent stroma.

Although p53 is not mutated in the human placenta, it has become functionally incompetent. Why and how p53 is functionally incompetent in cytotrophoblast cells might well be the key to understanding trophoblast invasion. Vascular remodeling for placentation is controlled by small populations of conventional Natural Killer cells, distinct from much larger populations of uterine NK cells, that acidify the ECM with a2V-ATPase, that activates MMP9, degrades the ECM and releases stored pro-angiogenesis growth factors. Similarly hypoxic TME's that in NK cells sustain excessive mitochondrial fission resulting in fragmentation could cause a2V-ATP activated MMP9 to similarly degrade ECM and promote angiogenesis in the early TME.  

Another MMP protein, MMP2 is a ligand for the Toll-like receptor 2 (Tlr2). Expression of Tlr2 and Tlr4 in the TME is important for the promotion of tumor growth, and when both of these receptors are absent, growth is compromised. Furthermore, the expression of Tlr2 and Tlr4 in both hematopoietic and stromal compartments appears to support MMP2-driven tumor growth.

The integration of the TLR gene family into the p53 regulatory network is unique to primates. p53 promoter response elements that are targeted by this DNA damage and stress-responsive regulator suggest a general p53 role in the control of human TLR gene expression. TLR genes show responses to DNA damage, and most are p53-mediated. TLR's mediate innate immunity to a wide variety of threats through recognition of conserved pathogen-associated molecular motifs. Expression of all TLR genes, in blood lymphocytes and alveolar macrophages from healthy volunteers can be induced by DNA metabolic stressors with considerable inter-individual variability. Most TLR genes respond to p53 via canonical as well as noncanonical promoter binding sites.

A polymorphism in a TLR8 response element provided the first human example of a p53 target sequence specifically responsible for endogenous gene induction. These findings—demonstrating that the human innate immune system, including downstream induction of cytokines, can be modulated by DNA metabolic stress—have many implications for health and disease, as well as for understanding the evolution of DNA damage and p53 responsive networks. That p53 can directly increase an inflammatory response differs from the generally held view relating to the antagonistic affect of p53 on inflammation directed by NF-κB. However, the direct mechanism here is different in that it involves another p53-mediated increase in a receptor that translates ligand interactions into cytokine responses.

First Intron DNA - Site for a Genetic Brain?

DNA Methylation

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.

 

Non-Coding DNA Key Sequences

DNA Structural Inherency

Wind two strands of elastic, eventually it will knot, ultimately it will double up on itself. Separate the strands. From the point of unwinding, forces will be directed to different regions and the separation will approximately return to the wound state of the band. Do the same with each of 10 different bands or strings of any type, they will all behave in much the same way. For a given section of DNA being transcribed, the effect of separation will be much the same. For a given gene, there will be sequences that can tolerate force to greater or lesser degrees. For different transcripts, of a gene variation at those sequences may be crucial to the integrity of transcription machinery that separates DNA strands to initiate replication to RNA and for the outcome.

Cellular biology is enormously complex in all regards. The physics of molecular interaction, fluid dynamics, and chemistry combine in a system where cause and effect is near impossible to predict. At the most elementary level we hypothesize some non-coding DNA (ncDNA) possess structural inherencies that can be deployed to direct gene proteins and cell function for diagnosis or therapy.

Coding DNA and its regulatory, non-coding gene compliment is transcribed and spliced from a transcribed gene. Transcription to RNA, edited mRNA, spliced non-coding RNA and ultimately mRNA translation to protein can produce wide ranging, variable outcomes that may not be re-captured experimentally. 

A single nucleotide polymorphism (SNP) or SNP combinations within a gene may affect the finely tuned balance that results. Under different environmental conditions this could be material to the protein produced. Additionally other mutations of the gene could add complexity to the environment and/or the  resulting protein translation. 

At this level of cellular biology, genetic DNA stores instruction for protein assemblies to produce new protein required for the fully functional cell. However, DNA's stored mutations can lead to different functional or non-functional versions of protein depending on many different factors. Relationships between ncDNA, including mutations and the transcripts' edited, protein coding mRNA may represent unexplored inherencies that can regulate the gene's mRNA or translated protein.

We built an algorithm to elaborately compare ncDNA sequences of multiple protein coding transcripts of the same gene. For each transcript it steps through every variable length ncDNA sequence (kmer) (specifically intron1), computes a signature for each and indexes it to the constant of the transcripts' mRNA signature. For each step these signatures order the kmers for each of the transcript's. The order is represented in a vector of all the transcripts being compared.  

At millions of successive steps (depending on total intron 1 length's) transcripts mostly retain their vector ordering except, as expected at a kmer length change. Mostly transcript order in the vector does not change, occasionally a few positions change, vary rarely do all positions change. Position changes that cause another, like a domino effect are filtered out. For the rarest positions changes at a step, we look to the root causes in the kmer (sequence). We call this a Key Sequence because it is identified by the significance of changes to transcript positions in the vector compared to the vector at the next step. 

Therefore, Key Sequences cause the most position changes between transcripts being compared by the algorithm. This relative measure is step dependent and Key Sequences are discovered by comparing transcript positions in the vector at the next step location. Logically, this infers a genes structural inherency discovered through ncDNA Key Sequence relationships to mRNA, to other transcripts, error in gene alignments, sequenced reads or the algorithm. 

In assay testing we were able to predict and synthesize non-coding RNA Key Sequences that significantly reduced proliferation of HeLa cells. In our pre-clinical work, based on comparisons to transcripts of the TP53 we will be predicting the efficacy of cell and tissue selections that educate and activate Natural Killer cells.

If Key Sequences are inherent they could open a new frontier for diagnosis and therapy.