Digital PCR detection of EGFR somatic mutations in non-small-cell lung cancer formalin fixed paraffin embedded samples.

BACKGROUND: Digital PCR (dPCR) is proposed to replace real time PCR and Sanger sequencing for detection and quantification of rare mutations, frequently unnoticed in the mass of tumoral cells. Screening of endothelial growth factor receptor (EGFR) mutations is mandatory before treatment with EGFR-targeted therapy with small-molecule tyrosine kinase inhibitors, which has been approved for the treatment of advanced non-small-cell lung cancer (NSCLC). OBJECTIVE: In order to establish a cost-effective method for detection of mutations, we optimized dPCR identification of EGFR mutations in exons 18-21, and determined dPCR sensitivity, limits of detection (LoD) and quantification (LoQ). METHODS: For clinical validation, we compared the performance of dPCR and castPCR in 57 NSCL formalin fixed paraffin embedded samples and 10 lung cancer-free formalin fixed paraffin embedded samples. RESULTS: EGFR mutations DEL19, p.L858R, p.G719X, p.L861Q and p.T790 M were detected by dPCR in 27 samples versus 11 detected by castPCR (p = 0.014). LoD was determined as 100 molecules of DNA/uL and LoQ as 1%. Most of the samples (87%) identified by competitive Allele-Specific TaqMan (castPCR) as wild-type and by dPCR as mutated, presented less than 10% mutated DNA molecules (mean 4.57%). Accuracy of dPCR was 94.44%, as measured with the assay recommended by the College of American Pathologists. CONCLUSION: These results indicated higher sensibility and specificity of dPCR for screening EGFR mutations in NSCLC biopsies, compared to castPCR.

Unveiling the Diversity of Immunoglobulin Heavy Constant Gamma (IGHG) Gene Segments in Brazilian Populations Reveals 28 Novel Alleles and Evidence of Gene Conversion and Natural Selection.

Even though immunoglobulins are critical for immune responses and human survival, the diversity of the immunoglobulin heavy chain gene (IGH) is poorly known and mostly characterized only by serological methods. Moreover, this genomic region is not well-covered in genomic databases and genome-wide association studies due to particularities that impose technical difficulties for its analysis. Therefore, the IGH gene has never been systematically sequenced across populations. Here, we deliver an unprecedented and comprehensive characterization of the diversity of the IGHG1, IGHG2, and IGHG3 gene segments, which encode the constant region of the most abundant circulating immunoglobulins: IgG1, IgG2, and IgG3, respectively. We used Sanger sequencing to analyze 357 individuals from seven different Brazilian populations, including five Amerindian, one Japanese-descendant and one Euro-descendant population samples. We discovered 28 novel IGHG alleles and provided evidence that some of them may have been originated by gene conversion between common alleles of different gene segments. The rate of synonymous substitutions was significantly higher than the rate of the non-synonymous substitutions for IGHG1 and IGHG2 (p = 0.01 and 0.03, respectively), consistent with purifying selection. Fay and Wu's test showed significant negative values for most populations (p < 0.001), which indicates that positive selection in an adjacent position may be shaping IGHG variation by hitchhiking of variants in the vicinity, possibly the regions that encode the Ig variable regions. This study shows that the variation in the IGH gene is largely underestimated. Therefore, exploring its nucleotide diversity in populations may provide valuable information for comprehension of its evolution, its impact on diseases and vaccine research.