Project description:The two most common melanoma histopathologic subtypes, superficial spreading (SSM) and nodular melanoma (NM), are believed to represent sequential phases of linear progression from radial to vertical growth. Studies suggest, however, that SSM and NM are biologically distinct. We utilized an integrative genomic approach to examine the possibility that SSM and NM are the result of independent pathways characterized by unique molecular alterations. Cell lines including SSM, NM, metastatic melanoma, and melanocyte controls were evaluated for copy number changes and differential mRNA expression using single nucleotide polymorphism array (SNP 6.0, Affymetrix) and gene array (U133A 2.0, Affymetrix). Data sets were integrated to identify copy number alterations that correlated with gene expression, and array results were validated using immunohistochemistry on human tissue microarrays (TMAs) and an external data set. The functional effect of genomic deletion was assessed by lentiviral overexpression. Integrative genomics revealed 8 genes in which NM/SSM-specific copy number alterations were correlated with NM/SSM differential gene expression (P<0.05, Spearman’s rank). Pathways analysis of differentially expressed genes (N=114) showed enrichment for metabolic-related processes. SSM-specific genomic deletions (DIS3, MTAP, G3BP2, SEC23IP, USO1) were verified in an expanded panel of cell lines, and forced overexpression of MTAP in SSM resulted in reduced cell growth. Metabolism-related gene ALDH7A1 was verified as overexpressed in NM using human TMAs.The identification of recurrent genomic deletions in SSM not present in NM challenges the linear model of melanoma progression and supports the unique molecular classification of SSM and NM. Gene expression profiling using Affymetrix U133A 2.0 arrays was performed on 18 melanoma cell lines including 2 primary superficial spreading melanoma, 2 primary nodular melanoma, 2 metastatic nodular melanoma, and 12 metastatic cell lines. Four melanocyte control lines were also evaluated including 2 immortalized melanocyte cell lines (Hermes 1 and 2B) and 2 normal melanocyte lines cultured from neonatal foreskin (HEM-N and HEM-LP).

Project description:Corneal epithelial cells derived from hPSCs provides an important cells source for the construction of the in vitro preclinical models aimed for ophthalmic drugs tests. However, the recent differentiation protocols lack the optimal culturing conditions that hinder the robustness and the quality of cells as well as the scale-up application of cells production. Here we introduce a simplified, yet efficient small molecules-based corneal induction method (SSM-CI) for the generation of corneal epithelial cells from hPSCs. SSM-CI provides the advantage of minimization the cells culturing time and steps using only two defined xenobiotic-free and serum-free culturing mediums in combination with the TGFß pathway, Wnt/ß-catenin pathway signaling chemical inhibitors, and human bFGF growth factor for a period of 25 days. Compared to both conventional human corneal epithelial cell line (HCE-T) as well as the human primary corneal epithelial cells (hPCEpC), human embryonic stem cells derived corneal epithelial cells generated by SSM-CI has highly expressed major differentiation as well as maturation markers such as PAX6 and CK12. RNA-seq analysis indicated the genuine diversion of hPSCs into the corneal epithelium lineage where corneal progenitor and adult corneal epithelial phenotypes were significantly upregulated. Furthermore, despite the inhibition of TGF-β and Wnt/β-catenin at the early stage of differentiation, an upregulation of the TGF-β and Wnt/β-catenin pathways related transcripts we noticed in the late stage which indicated the necessity of these pathways in the generation of mature corneal epithelial cells. Moreover, there was a shift in gene signatures associated with the metabolic characteristics of mature corneal epithelial cells where a decrease of glycolysis related transcripts and an increase in fatty acid oxidation related one was noticed. That was also corresponded by the overexpression of metabolic enzymes and transporters related transcripts that were mainly responsible for the metabolism of fatty acids. Thus SSM-CI provide a comprehensive method for the generation of functional corneal epithelial cells that has the potential for the employment in future preclinical models.

Project description:Spectral library search (SLS) is a major approach for peptide identification from tandem mass spectrometry data, offering a complementary approach to conventional database search. Moreover, with the emergence of spectrum prediction models, proteomics database search is progressively becoming more like spectral library search of predicted peptide spectra. The performance of peptide identification algorithms thus frequently depends on how well the underlying Spectrum-Spectrum Matching (SSM) scoring functions distinguish true and false positive matches. However, detailed comparative studies evaluating the performance of SSM scoring functions remain limited by the absence of comprehensive benchmark datasets. We propose new methods to build benchmarks that assess the effectiveness and robustness of SSM scoring functions. The resulting benchmark dataset is composed of (i) a set of 476,063 precursors used to construct 8 query spectrum sets with different levels of noise added to "ideal" and real experimental spectra, and (ii) three spectral libraries with different spectra for the same 3,065,819 precursors: experimental spectra, annotated/de-noised spectra and predicted spectra. The benchmark set was then used to evaluate 9 common spectrum preprocessing scenarios, followed by the evaluation of 3 standard SSM scoring functions, Cosine, Projected-Cosine (commonly used for the analysis of chimeric/mixture spectra), and Jensen-Shannon divergence, and 2 additional scoring functions used in state-of-the-art SLS tools: SpectraST and EntropyScore. The results revealed that scoring spectrum-spectrum matches is still an important open problem, with the best recall for typical SLS searches still assessed to be poor at just ~70% at the typical 1% error rate. Overall, SpectraST performed best for spectra with little-to-no noise, but JS-divergence performed better in some cases as it was found to be most resistant to noise. Conversely, the performance of Cosine and Entropy score was found to be generally lower than previously reported, with Projected-Cosine performing especially poorly in most cases. However, the performance of the SSM scoring functions was also found to depend quite significantly on the minimum number of matching peaks required for each SSM, with benchmark results showing that the scoring functions' performance and relative ranking can be very significantly affected by how this important parameter is set. The resulting benchmark dataset can be used to test and support the development of SSM scoring functions and the proposed benchmark construction approach, providing a foundation that can be extended for additional types of spectrum-spectrum matching.

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