Current clinical criteria for Lynch syndrome are not sensitive enough to identify MSH6 mutation carriers

Background: Reported prevalence, penetrance and expression of deleterious mutations in the mismatch repair (MMR) genes, MLH1, MSH2, MSH6 and PMS2, may reflect differences in the clinical criteria used to select families for DNA testing. The authors have previously reported that clinical criteria are not sensitive enough to identify MMR mutation carriers among incident colorectal cancer cases. Objective: To describe the sensitivity of the criteria when applied to families with a demonstrated MMR mutation. Methods: Families with an aggregation of colorectal cancers were examined for deleterious MMR mutations according to the Mallorca guidelines. All families with a detected MMR mutation as of November 2009 were reclassified according to the Amsterdam and Bethesda criteria. Results: Sixty-nine different DNA variants were identified in a total of 129 families. The original Amsterdam clinical criteria were met by 38%, 12%, 78% and 25% of families with mutations in MSH2, MSH6, MLH1 and PMS2, respectively. Corresponding numbers for the revised Amsterdam criteria were 62%, 48%, 87% and 38%. Similarly, each of the four clinical Bethesda criteria had low sensitivity for identifying MSH6 or PMS2 mutations. Conclusion: Amsterdam criteria and each of the Bethesda criteria were inadequate for identifying MSH6 mutation-carrying kindreds. MSH6 mutations may be more common than currently assumed, and the penetrance/expression of MSH6 mutations, as derived from families meeting current clinical criteria, may be misleading. To increase detection rate of MMR mutation carriers, all cancers in the Lynch syndrome tumour spectrum should be subjected to immunohistochemical analysis and/or analysis for microsatellite instability

A massive parallel sequencing workflow for diagnostic genetic testing of mismatch repair genes

The purpose of this study was to develop a massive parallel sequencing (MPS) workflow for diagnostic analysis of mismatch repair (MMR) genes using the GS Junior system (Roche). A pathogenic variant in one of four MMR genes, (MLH1, PMS2, MSH6, and MSH2), is the cause of Lynch Syndrome (LS), which mainly predispose to colorectal cancer. We used an amplicon‐based sequencing method allowing specific and preferential amplification of the MMR genes including PMS2, of which several pseudogenes exist. The amplicons were pooled at different ratios to obtain coverage uniformity and maximize the throughput of a single‐GS Junior run. In total, 60 previously identified and distinct variants (substitutions and indels), were sequenced by MPS and successfully detected. The heterozygote detection range was from 19% to 63% and dependent on sequence context and coverage. We were able to distinguish between false‐positive and true‐positive calls in homopolymeric regions by cross‐sample comparison and evaluation of flow signal distributions. In addition, we filtered variants according to a predefined status, which facilitated variant annotation. Our study shows that implementation of MPS in routine diagnostics of LS can accelerate sample throughput and reduce costs without compromising sensitivity, compared to Sanger sequencing

A massive parallel sequencing workflow for diagnostic genetic testing of mismatch repair genes

The purpose of this study was to develop a massive parallel sequencing (MPS) workflow for diagnostic analysis of mismatch repair (MMR) genes using the GS Junior system (Roche). A pathogenic variant in one of four MMR genes, (MLH1, PMS2, MSH6, and MSH2), is the cause of Lynch Syndrome (LS), which mainly predispose to colorectal cancer. We used an amplicon‐based sequencing method allowing specific and preferential amplification of the MMR genes including PMS2, of which several pseudogenes exist. The amplicons were pooled at different ratios to obtain coverage uniformity and maximize the throughput of a single‐GS Junior run. In total, 60 previously identified and distinct variants (substitutions and indels), were sequenced by MPS and successfully detected. The heterozygote detection range was from 19% to 63% and dependent on sequence context and coverage. We were able to distinguish between false‐positive and true‐positive calls in homopolymeric regions by cross‐sample comparison and evaluation of flow signal distributions. In addition, we filtered variants according to a predefined status, which facilitated variant annotation. Our study shows that implementation of MPS in routine diagnostics of LS can accelerate sample throughput and reduce costs without compromising sensitivity, compared to Sanger sequencing

Mucosal 5-aminosalicylic acid concentration, drug formulation and mucosal microbiome in patients with quiescent ulcerative colitis

Background 5‐aminosalicylic acid (5‐ASA) is the first‐line therapy for ulcerative colitis (UC). 5‐ASA acts locally in the colonic mucosa by numerous proposed mechanisms, and is metabolised by N‐acetyltransferase (NAT). Large variations in mucosal 5‐ASA concentrations have been reported, but the underlying mechanisms are not understood. Aim To study the relationship between 5‐ASA concentration, 5‐ASA formulation, NAT genotype and bacterial microbiome in patients with UC. Methods Patients with quiescent UC, using monotherapy of Mezavant (n = 18), Asacol (n = 14) or Pentasa (n = 10), 4.0‐4.8 g/day were included. 5‐ASA was measured in colonic mucosal biopsies and serum by ultra‐high performance liquid chromatography. NAT genotypes were determined by Sanger sequencing. Bacterial microbiome was sequenced from faeces and mucosa by 16S rRNA sequencing using Illumina Miseq. Results Mezavant provided the highest mucosal 5‐ASA levels (geometric mean 2.39 ng/mg), followed by Asacol (1.60 ng/mg, 33% lower, P = 0.50) and Pentasa (0.57 ng/mg, 76% lower, P = 0.033). Mucosal 5‐ASA concentration was not associated with NAT genotype, but serum 5‐ASA concentration and NAT1 genotype was associated (P = 0.044). Mucosal 5‐ASA concentration was positively associated with mucosal bacterial diversity (P = 0.0005) and bacterial composition. High mucosal 5‐ASA concentration was related to reduced abundance of pathogenic bacteria such as Proteobacteria, and increased abundance of several favourable bacteria such as Faecalibacterium. Conclusions Mucosal 5‐ASA concentration is positively associated with bacterial diversity and a mucosal bacterial composition that are perceived favourable in UC. Mezavant yielded higher mucosal 5‐ASA concentrations than Pentasa. 5‐ASA may have beneficial effects on the mucosal microbiome, and high concentrations possibly amend dysbiosis in UC