Accurate Quantification of T Cells in Copy Number Stable and Unstable DNA Samples Using Multiplex Digital PCR.

An accurate T-cell quantification is prognostically and therapeutically relevant in various malignancies. We previously developed a digital PCR-based approach offering a precise T-cell enumeration in small amounts of DNA. However, it may be challenging to apply this method in malignant specimens, as genetic instability can disturb the underlying mathematical model. For example, approximately 24% of the tumors from The Cancer Genome Atlas pan-cancer data set carried a copy number alteration affecting the TRB gene T-cell marker, which would cause an underestimation or overestimation of the T-cell fraction. In this study, we introduce a multiplex digital PCR experimental setup to quantify T cells in copy number unstable DNA samples. By implementing a so-called regional corrector, genetic alterations involving the T-cell marker locus can be recognized and corrected for. This novel setup is evaluated mathematically in silico and validated in vitro by measuring T-cell presence in various samples with a known T-cell fraction. The utility of the approach is further demonstrated in copy number altered cutaneous melanomas. Our novel multiplex setup provides a simple, but accurate, DNA-based T-cell quantification in both copy number stable and unstable specimens. This approach has potential clinical and diagnostic applications, as it does not depend on availability of T-cell epitopes, has low requirements for sample quantity and quality, and can be performed in a relatively easy experiment.

Involvement of mutant and wild-type CYSLTR2 in the development and progression of uveal nevi and melanoma.

BACKGROUND: Activating Gαq signalling mutations are considered an early event in the development of uveal melanoma. Whereas most tumours harbour a mutation in GNAQ or GNA11, CYSLTR2 (encoding G-protein coupled receptor CysLT2R) forms a rare alternative. The role of wild-type CysLT2R in uveal melanoma remains unknown. METHODS: We performed a digital PCR-based molecular analysis of benign choroidal nevi and primary uveal melanomas. Publicly available bulk and single cell sequencing data were mined to further study mutant and wild-type CYSLTR2 in primary and metastatic uveal melanoma. RESULTS: 1/16 nevi and 2/120 melanomas carried the CYSLTR2 mutation. The mutation was found in a subpopulation of the nevus, while being clonal in both melanomas. In the melanomas, secondary, subclonal CYSLTR2 alterations shifted the allelic balance towards the mutant. The resulting genetic heterogeneity was confirmed in distinct areas of both tumours. At the RNA level, further silencing of wild-type and preferential expression of mutant CYSLTR2 was identified, which was also observed in two CYSLTR2 mutant primary melanomas and one metastatic lesion from other cohorts. In CYSLTR2 wild-type melanomas, high expression of CYSLTR2 correlated to tumour inflammation, but expression originated from melanoma cells specifically. CONCLUSIONS: Our findings suggest that CYSLTR2 is involved in both early and late development of uveal melanoma. Whereas the CYSLTR2 p.L129Q mutation is likely to be the initiating oncogenic event, various mechanisms further increase the mutant allele abundance during tumour progression. This makes mutant CysLT2R an attractive therapeutic target in uveal melanoma.

Quantification of DNA methylation independent of sodium bisulfite conversion using methylation-sensitive restriction enzymes and digital PCR.

Epigenetic regulation is important in human health and disease, but the exact mechanisms remain largely enigmatic. DNA methylation represents one epigenetic aspect but is challenging to quantify. In this study, we introduce a digital approach for the quantification of the amount and density of DNA methylation. We designed an experimental setup combining efficient methylation-sensitive restriction enzymes with digital polymerase chain reaction (PCR) to quantify a targeted density of DNA methylation independent of bisulfite conversion. By using a stable reference and comparing experiments treated and untreated with these enzymes, copy number instability could be properly normalized. In silico simulations demonstrated the mathematical validity of the setup and showed that the measurement precision depends on the amount of input DNA and the fraction methylated alleles. This uncertainty could be successfully estimated by the confidence intervals. Quantification of RASSF1 promoter methylation in a variety of healthy and malignant samples and in a calibration curve confirmed the high accuracy of our approach, even in minute amounts of DNA. Overall, our results indicate the possibility of quantifying DNA methylation with digital PCR, independent of bisulfite conversion. Moreover, as the context-density of methylation can also be determined, biological mechanisms can now be quantitatively assessed.