CSF H3F3A K27M circulating tumor DNA copy number quantifies tumor growth and in vitro treatment response

https://deepblue.lib.umich.edu/bitstream/2027.42/145434/1/40478_2018_Article_580.pd

Cancer Biomarker Discovery: The Entropic Hallmark

Background: It is a commonly accepted belief that cancer cells modify their transcriptional state during the progression of the disease. We propose that the progression of cancer cells towards malignant phenotypes can be efficiently tracked using high-throughput technologies that follow the gradual changes observed in the gene expression profiles by employing Shannon's mathematical theory of communication. Methods based on Information Theory can then quantify the divergence of cancer cells' transcriptional profiles from those of normally appearing cells of the originating tissues. The relevance of the proposed methods can be evaluated using microarray datasets available in the public domain but the method is in principle applicable to other high-throughput methods. Methodology/Principal Findings: Using melanoma and prostate cancer datasets we illustrate how it is possible to employ Shannon Entropy and the Jensen-Shannon divergence to trace the transcriptional changes progression of the disease. We establish how the variations of these two measures correlate with established biomarkers of cancer progression. The Information Theory measures allow us to identify novel biomarkers for both progressive and relatively more sudden transcriptional changes leading to malignant phenotypes. At the same time, the methodology was able to validate a large number of genes and processes that seem to be implicated in the progression of melanoma and prostate cancer. Conclusions/Significance: We thus present a quantitative guiding rule, a new unifying hallmark of cancer: the cancer cell's transcriptome changes lead to measurable observed transitions of Normalized Shannon Entropy values (as measured by high-throughput technologies). At the same time, tumor cells increment their divergence from the normal tissue profile increasing their disorder via creation of states that we might not directly measure. This unifying hallmark allows, via the the Jensen-Shannon divergence, to identify the arrow of time of the processes from the gene expression profiles, and helps to map the phenotypical and molecular hallmarks of specific cancer subtypes. The deep mathematical basis of the approach allows us to suggest that this principle is, hopefully, of general applicability for other diseases

Standardization of the liquid biopsy for pediatric diffuse midline glioma using ddPCR.

Diffuse midline glioma (DMG) is a highly morbid pediatric brain tumor. Up to 80% of DMGs harbor mutations in histone H3-encoding genes, associated with poor prognosis. We previously showed the feasibility of detecting H3 mutations in circulating tumor DNA (ctDNA) in the liquid biome of children diagnosed with DMG. However, detection of low levels of ctDNA is highly dependent on platform sensitivity and sample type. To address this, we optimized ctDNA detection sensitivity and specificity across two commonly used digital droplet PCR (ddPCR) platforms (RainDance and BioRad), and validated methods for detecting H3F3A c.83A > T (H3.3K27M) mutations in DMG CSF, plasma, and primary tumor specimens across three different institutions. DNA was extracted from H3.3K27M mutant and H3 wildtype (H3WT) specimens, including H3.3K27M tumor tissue (n = 4), CSF (n = 6), plasma (n = 4), and human primary pediatric glioma cells (H3.3K27M, n = 2; H3WT, n = 1). ctDNA detection was enhanced via PCR pre-amplification and use of distinct custom primers and fluorescent LNA probes for c.83 A > T H3F3A mutation detection. Mutation allelic frequency (MAF) was determined and validated through parallel analysis of matched H3.3K27M tissue specimens (n = 3). We determined technical nuances between ddPCR instruments, and optimized sample preparation and sequencing protocols for H3.3K27M mutation detection and quantification. We observed 100% sensitivity and specificity for mutation detection in matched DMG tissue and CSF across assays, platforms and institutions. ctDNA is reliably and reproducibly detected in the liquid biome using ddPCR, representing a clinically feasible, reproducible, and minimally invasive approach for DMG diagnosis, molecular subtyping and therapeutic monitoring

Genome-wide association study of homocysteine levels in Filipinos provides evidence for CPS1 in women and a stronger MTHFR effect in young adults

Plasma homocysteine (Hcy) level is associated with cardiovascular disease and may play an etiologic role in vascular damage, a precursor for atherosclerosis. We performed a genome-wide association study for Hcy in 1786 unrelated Filipino women from the Cebu Longitudinal Health and Nutrition Survey (CLHNS). The most strongly associated single-nucleotide polymorphism (SNP) (rs7422339, P = 4.7 × 10−13) encodes Thr1405Asn in the gene CPS1 and explained 3.0% of variation in the Hcy level. The widely studied MTHFR C677T SNP (rs1801133) was also highly significant (P = 8.7 × 10−10) and explained 1.6% of the trait variation. We also genotyped these two SNPs in 1679 CLHNS young adult offspring. The MTHFR C677T SNP was strongly associated with Hcy (P = 1.9 × 10−26) and explained ∼5.1% of the variation in the offspring. In contrast, the CPS1 variant was significant only in females (P = 0.11 in all; P = 0.0087 in females). Combined analysis of all samples confirmed that the MTHFR variant was more strongly associated with Hcy in the offspring (interaction P = 1.2 × 10−5). Furthermore, although there was evidence for a positive synergistic effect between the CPS1 and MTHFR SNPs in the offspring (interaction P = 0.0046), there was no significant evidence for an interaction in the mothers (P = 0.55). These data confirm a recent finding that CPS1 is a locus influencing Hcy levels in women and suggest that genetic effects on Hcy may differ across developmental stages