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High frequency of mutations seems to determine a higher occurrence of neoepitope formation and, thus, tumor immunogenicity. A somatic hypermutated status could thus act as a predictive biomarker of responsiveness to immunotherapy with recent immune checkpoint inhibitors. Among several factors involved in determining the hypermutated status, such as inactivating mutations in the DNA polymerases as well as exposure to external (cigarette smoke, UV radiation, chemicals) and endogenous (reactive oxygen species) mutagens, a defective DNA mismatch repair system may give rise to genetic instability and, particularly, to microsatellite instability (MSI). The occurrence of MSI has been associated with increased load of mutations and expression of abundant peptides that serve as neoantigens to elicit an immune response within a context of a favorable tumor microenvironment. Here we describe methodological strategies to investigate for the presence of the MSI phenotype in cancer samples, through a combination of molecular approaches performed on paraffin-embedded tissues.

Table S2. The 73 somatic variants found in our study, in detail. In bold, variants classified as pathogenic/likely pathogenic mutations. (PDF 76 kb)

Additional file 1: Table S1. Sequence variations in candidate genes.

Additional file 1. Additional figures and tables.

Additional file 1. Additional tables S1 and S2. the file contains two supplementary tables depicting the exact distribution of the 543 mutations identified in RAS and BRAF genes (Table S1), as well as the distribution of the 115 PIK3CA mutations (Table S2) in our cohort.

In the context of personalized medicine, an important role will be played by enabling "omics" technologies for molecular profiling, such as genomic profiling (using approaches of next-generation sequencing, NGS), transcriptomic (using microarrays or quantitative PCR), proteomics (using mass spectrometry methods) and metabolomic (by NMR assays). The combination of these methodologies on both in vitro tumor models and, particularly, in vivo tissue samples will allow to identify biomarkers for diagnosis (associated with various clinical and pathological aspects of the disease), prediction of response and/or resistance to therapies, and prognosis. On this regard, our group has set itself to achieve the characterization of genomic (genetic mutations and polymorphisms) and proteomic profiles in different melanoma cell lines from excised lesions in patients at different stages of the disease (primary tumor; skin, lymph node, or visceral metastases). The main goal is the identification of differentially expressed proteins derived from the comparison with different genetic patterns in melanoma cells in order to identify the biochemical and cellular processes of initiation and progression of the disease and elucidate potential mechanisms involved in the development of the different melanoma genotypes. For the mutation analysis, genomic DNA was isolated from melanoma cell lines, using standard methods. Specimens were analyzed for mutations in most common genes involved in melanoma pathogenesis with a specific Panel on the Ion Torrent platform (PGM sequencer). All variants detected by NGS were confirmed through PCR-based Sanger sequencing For the proteomic analysis, the melanoma cell lines have been analyzed by MudPIT approach. Data obtained from the MudPIT analysis in the different melanoma cell lines at various stages of the disease have been investigated by using specific identification software (SEQUEST Cluster and Bioworks). All samples were analyzed in duplicate, therefore, having available a substantial number of listings protein, it was possible to compare most of them. The comparison was performed using the MAProMA software which allows the preliminary assessment of differentially expressed proteins through specific algorithms (DAVE - Differential Average- and -Differential Confidence Index-DCI). The Dave parameter is indicative of the difference in relative amounts of the same proteins found in the two samples being analyzed; the DCI parameter provides the absolute value of the differential expression confidence. These two parameters are thus used to identify proteins with a different level of abundance, which is present in the two samples in a manner significantly different. From a preliminary analysis of the data - we have just generated, a significant number of differentially expressed proteins was found to play an essential role in cancer tumorigenesis, including those involved in proliferation control, cellular motility, and resistance to apoptosis of melanoma cells. More accurate correlations and association analyses between genetic and proteomic data are ongoing.

Background: Racial and geographic factors seem to affect the incidence of cutaneous and mucosal melanoma. Objective: To investigate the occurrence of BRAF and cKIT impairments in patients with sinonasal melanoma in Southern Italy. Methods: Eleven sinonasal melanomas were screened for BRAF mutations and cKIT alterations by immunohistochemistry (CD117), fluorescence in situ hybridization and sequencing analyses. Results: A high prevalence (4/11; 36%) of BRAF mutations and lack of cKIT mutations were observed. Amplification of cKIT was found in 18% of cases; cKIT expression was detectable in 18% non-overlapping cases. No correlation between CD117 and cKIT alterations was observed. One (6%) cKIT and two (12%) BRAF mutations were detected in an additional series of 17 acral/mucosal melanomas from the same geographic areas. Conclusion: Mutations of cKIT are infrequent in sinonasal melanoma in Southern Italy.

Background Role of KRAS, BRAF and PIK3CA mutations in pathogenesis of colorectal cancer (CRC) has been recently investigated worldwide. In this population-based study, we evaluated the incidence rates and distribution of such somatic mutations in genetically isolated population from Sardinia. Methods From April 2009 to July 2011, formalin-fixed paraffin-embedded tissues (N = 478) were prospectively collected from Sardinian CRC patients at clinics across the entire island. Genomic DNA was isolated from tissue sections and screened for mutations in KRAS, BRAF, and PIK3CA genes by automated DNA sequencing. Results Overall, KRAS tumour mutation rate was 30% (145/478 positive cases). Distribution of mutation carriers was surprisingly different within the island: 87/204 (43%) in North Sardinia vs. 58/274 (21%) in Middle-South Sardinia (pBRAF gene; PIK3CA was found mutated in 67 (17%) patients. A significant inverse distribution of PIK3CA mutation rates was observed within Sardinian population: 19/183 (10%) cases from northern vs. 48/201 (24%) cases from central-southern island (pKRAS/PIK3CA somatic mutations is consistent with already-reported discrepancies in distribution of germline mutations for other malignancies within Sardinian population. Preliminary clinical evaluation of 118 KRAS wild-type patients undergoing anti-EGFR-based treatment indicated lack of role for PIK3CA in predicting response to therapy. Conclusions Our findings support the hypothesis that differences in patients’ origins and related genetic backgrounds may contribute to even determine the incidence rate of somatic mutations in candidate cancer genes.