In this study, we generated a genetic panel for the diagnosis of Gorlin syndrome to establish a new, cost-effective, easy, and reliable method for genetic diagnosis. This gene panel has the following advantages:
High reliability. The entire exons of the three Gorlin syndrome causative genes PTCH1, PTCH2, and SUFU and exon regions of the BCC driver gene, SMO, can be sequenced with high accuracy. The reliability of the sequence obtained from this gene panel will be very high if the QC of the extracted patient DNA is good and the library purification is of high quality. The average Q30 of this panel was ≥90%, the average on-target ratio was ≥90%, and the average coverage depth was ≥1,000 (Supplementary Table S1).
Easy to handle, time-saving, and cost-effective. All the analysis pipelines can be executed with a graphical user interface using the program BaseSpace Sequence Hub, and hence, no previous experience is needed to analyze the sequences. It only requires approximately 2 days to obtain results from patients’ blood samples.
Tailorable to many diseases. This gene panel can be used to diagnose a wide range of diseases.
Regarding the high reliability of the gene panel, the standard coverage depth of WES is usually ≥ 30⋅, but that of the gene panel is ≥ 1000⋅, suggesting that the gene panel is much more reliable. Should a high-quality library is produced with a Q30 score of ≥90, the reliability of the gene sequence obtained by panel analysis is then high. NGS analysis using a custom panel limited the region of target gene analysis and provided deeper coverage than WES analysis. In this way, the gene panel is more accurate than the typical WES test; hence, it is possible to identify new mutations that cannot be identified using WES. In addition, the panel-based gene analysis method established in this study can be applied for mutation analysis of the OKC tissue; it is possible to diagnose the cyst itself and evaluate the possibility of a future recurrence.
When the causative gene mutations in patients with Gorlin syndrome were comprehensively investigated using NGS exome analysis, it was found that the proportion of patients with both PTCH1 and PTCH2 mutations was higher than expected. In many cases, the PTCH2 mutation has not been examined after patients were found to have the PTCH1 mutation; thus, the double mutation might have been possibly overlooked. The gene panel developed in this study can accurately detect mutations in PTCH1 and PTCH2 at once, eliminating the possibility of not being able to detect duplicate mutations, as described above. In addition, SMO mutations, which are relatively common in BCC and frequently occur in Gorlin syndrome, have never been identified as the causative gene mutation of the Gorlin syndrome. This gene panel can be used to discover syndromes caused by SMO gene mutations.
The gene panel is composed of multiple PCR-based gene amplifications of the entire target gene exons in one tube. Thus, each step of the examination procedure is relatively simple. As the reliability of the panel is assured, it is easy to use owing to the user-friendly analysis program BaseSpace Sequence Hub. Furthermore, NGS analysis using a custom panel can accurately obtain 15,000 bp of base information at once, which is a great advantage in terms of time, human resources, and cost. Therefore, this panel is easy to use and time- and cost-effective.
As Gorlin syndrome is caused by hyperactivation of the Hh pathway due to loss-of-function mutations in Hh suppressor genes (PTCH1, PTCH2, and SUFU), these mutations are often observed in tumors. Activation mutations in these Hh pathway genes are involved in BCC and several types of jawbone cysts . However, the relationship between mutations in these genes and pathogenesis has not been well elucidated, probably owing to the relatively difficult analysis of these causative gene mutations. In the future, a highly accurate application of this gene panel for the comprehensive diagnosis of BCC and jawbone cysts may become common . If more patients are examined using this gene panel technique, the relationship between SMO gene mutations, or even SUFU gene mutations, and pathological conditions may also be identified, along with association between SUFU and SMO gene mutations and pathological conditions.
However, clinical outcomes should never be based solely on in silico predictions. It has been reported that in silico pathogenicity predictions tend to have false positive results and low specificity [36, 37]. The accuracy of in silico tools remains low while the use of computational information in clinical practice is limited by strict guidelines . This necessitates the use of multiple in silico tools. In this study, we used the five in silico tools described in the ACMG-AMP 2015 guidelines. Variants shown as pathogenic variants using the five pathogenicity prediction tools were evaluated according to the ACMG-AMP guidelines for variant classification. As a result of this classification, some limitations were observed. First, owing to the lack of case reports, variant data for rare diseases are lacking compared to those for cancer. Variant databases for patients with Gorlin syndrome have not been prepared, and it was difficult to evaluate the data with the endpoints of the ACMG-AMP guidelines. Second, data collected was limited because the gene region to be analyzed differs depending on the research center and the analysis method. There are ethnic differences in each disease, and disease mutation databases for each ethnic group are needed. The results of the custom gene panel analysis of blood from three clinically asymptomatic natural relatives who were related to the patients with Gorlin syndrome suggest that custom gene panel testing could be clinically applied as a tool for early diagnosis and then treatment of patients with Gorlin syndrome. In particular, the patient with asymptomatic Gorlin syndrome can be diagnosed using prophylactic tests and informed about the future possibility of developing the disease.