RAS gene mutations and histomorphometric measurements in oral squamous cell carcinoma.

Members of the RAS gene family frequently are mutated in cancers including oral squamous cell carcinoma (OSCC). We investigated the correlation of histological characteristics of OSCC with RAS gene mutations. We graded tumors and extracted genomic DNA from OSCC. The first two exons of KRAS, HRAS and NRAS genes were subjected to PCR amplification and DNA sequencing followed by bioinformatic analysis to explore the structural and functional impact of the mutations on encoding of proteins. Cellular and nuclear diameters in histological sections were varied in all grades of cancer. Using sequence analysis, we identified nonsynonymous mutations in both HRAS (G12S, G15C, D54H, Q61H, Q61L, E62D, E63D, Q70E, Q70V) and NRAS (Q22P, K88R). Stop codon mutations, however, were observed in KRAS. Spatial orientation of substituted amino acids was observed despite conservation of overall structure of variant proteins. Our findings suggest that KRAS may be mutated more frequently in OSCC compared to HRAS and NRAS. Also, the histological features of nuclear and cellular diameter differed significantly between the KRAS mutated and unmutated cases.

Application of Sigma Metrics Analysis for the Assessment and Modification of Quality Control Program in the Clinical Chemistry Laboratory of a Tertiary Care Hospital.

Sigma is a metric that quantifies the performance of a process as a rate of Defects-Per-Million opportunities. In clinical laboratories, sigma metric analysis is used to assess the performance of laboratory process system. Sigma metric is also used as a quality management strategy for a laboratory process to improve the quality by addressing the errors after identification. The aim of this study is to evaluate the errors in quality control of analytical phase of laboratory system by sigma metric. For this purpose sigma metric analysis was done for analytes using the internal and external quality control as quality indicators. Results of sigma metric analysis were used to identify the gaps and need for modification in the strategy of laboratory quality control procedure. Sigma metric was calculated for quality control program of ten clinical chemistry analytes including glucose, chloride, cholesterol, triglyceride, HDL, albumin, direct bilirubin, total bilirubin, protein and creatinine, at two control levels. To calculate the sigma metric imprecision and bias was calculated with internal and external quality control data, respectively. The minimum acceptable performance was considered as 3 sigma. Westgard sigma rules were applied to customize the quality control procedure. Sigma level was found acceptable (≥3) for glucose (L2), cholesterol, triglyceride, HDL, direct bilirubin and creatinine at both levels of control. For rest of the analytes sigma metric was found <3. The lowest value for sigma was found for chloride (1.1) at L2. The highest value of sigma was found for creatinine (10.1) at L3. HDL was found with the highest sigma values at both control levels (8.8 and 8.0 at L2 and L3, respectively). We conclude that analytes with the sigma value <3 are required strict monitoring and modification in quality control procedure. In this study application of sigma rules provided us the practical solution for improved and focused design of QC procedure.