57 Background: It has been suggested that the sequential analysis of the mutational spectra at loci involved in the pathogenesis of tumors (mutational load distribution analysis [MLDA]) may reflect the biology of the tumor and/or the risk of cancer before the tumor emerges. Metrics derived from MLDA could assist quantifying risk, in early diagnosis, and in monitoring response to therapy. The aim of this study was to assess the efficacy of the NGS platform to obtain clinically relevant metrics derived from MLDA. Methods: Two sets of DNA samples were assessed: (i) 6 paired tumor/normal colorectal carcinomas and 8 colorectal adenomas; and (ii) 21 pancreatic carcinoma and 6 non-matched normal pancreas. Thirty amplicons from 6 genes (KRAS, BRAF, EGFR, CDKN2A, TP53, and PI3KCA) were sequenced using the Roche 454 GS FLX-TI platform. Data analysis was carried out by Variant Identification Pipeline (VIP) software and R (computing environment) commands. Total mutational load (TML) was calculated as the sum of all variants frequency for each sample. Results: In all, 18,626 variants were identified. Optimal filters applied to discard false positives were: (1) variants with an absolute frequency < 10x, (2) variants in homopolymer (HP) ≥ 6 nucleotides, (3) insertions and deletions (INDELs) in HP ≥ 5 nucleotides, and (4) INDELs in only one strand. Filtering yielded 870 variants from all samples remained as valid, 92 being unique. After discarding polymorphisms, variants classified as neutral by the Condel software and variants preferentially detected in normal tissues, 46 variants were used to compute TML. TML in colonic carcinomas and adenomas was higher than normal mucosa (0.83 vs. 0.607 vs. 0.128, p = 0.01). In pancreatic disease, TML for pancreatic carcinoma was higher than normal pancreas (0.716 vs. 0.135, p = 0.01). KRAS and TP53 analysis provide most of the information in both tumors, while PI3KCA adds information for colorectal carcinomas exclusively and CDKNA2 is informative in pancreatic samples. Conclusions: NGS provides a robust and quantitative measure of genetic alterations in tumor samples. MLDA is an effective tool for the classification of GI tumors.
Load Distribution Analysis Method for Cylindrical Worm Gear Teeth. 1st Report, Measurement of Deflections of Worm Gear Teeth Using Laser Holographic Interferometry.
