RESUMO
BACKGROUND: Myxoid liposarcoma (MLS) displays a distinctive tumor microenvironment and is characterized by the FUS::DDIT3 fusion oncogene, however, the precise functional contributions of these two elements remain enigmatic in tumor development. METHODS: To study the cell-free microenvironment in MLS, we developed an experimental model system based on decellularized patient-derived xenograft tumors. We characterized the cell-free scaffold using mass spectrometry. Subsequently, scaffolds were repopulated using sarcoma cells with or without FUS::DDIT3 expression that were analyzed with histology and RNA sequencing. RESULTS: Characterization of cell-free MLS scaffolds revealed intact structure and a large variation of protein types remaining after decellularization. We demonstrated an optimal culture time of 3 weeks and showed that FUS::DDIT3 expression decreased cell proliferation and scaffold invasiveness. The cell-free MLS microenvironment and FUS::DDIT3 expression both induced biological processes related to cell-to-cell and cell-to-extracellular matrix interactions, as well as chromatin remodeling, immune response, and metabolism. Data indicated that FUS::DDIT3 expression more than the microenvironment determined the pre-adipocytic phenotype that is typical for MLS. CONCLUSIONS: Our experimental approach opens new means to study the tumor microenvironment in detail and our findings suggest that FUS::DDIT3-expressing tumor cells can create their own extracellular niche.
Assuntos
Lipossarcoma Mixoide , Proteínas de Fusão Oncogênica , Proteína FUS de Ligação a RNA , Microambiente Tumoral , Animais , Humanos , Camundongos , Linhagem Celular Tumoral , Proliferação de Células , Matriz Extracelular/metabolismo , Regulação Neoplásica da Expressão Gênica , Lipossarcoma Mixoide/patologia , Lipossarcoma Mixoide/metabolismo , Lipossarcoma Mixoide/genética , Proteínas de Fusão Oncogênica/metabolismo , Proteínas de Fusão Oncogênica/genética , Proteína FUS de Ligação a RNA/metabolismo , Proteína FUS de Ligação a RNA/genética , Alicerces Teciduais/química , Fator de Transcrição CHOP/genética , Fator de Transcrição CHOP/metabolismoRESUMO
Massively parallel sequencing (MPS) is increasingly applied in forensic short tandem repeat (STR) analysis. The presence of stutter artefacts and other PCR or sequencing errors in the MPS-STR data partly limits the detection of low DNA amounts, e.g., in complex mixtures. Unique molecular identifiers (UMIs) have been applied in several scientific fields to reduce noise in sequencing. UMIs consist of a stretch of random nucleotides, a unique barcode for each starting DNA molecule, that is incorporated in the DNA template using either ligation or PCR. The barcode is used to generate consensus reads, thus removing errors. The SiMSen-Seq (Simple, multiplexed, PCR-based barcoding of DNA for sensitive mutation detection using sequencing) method relies on PCR-based introduction of UMIs and includes a sophisticated hairpin design to reduce unspecific primer binding as well as PCR protocol adjustments to further optimize the reaction. In this study, SiMSen-Seq is applied to develop a proof-of-concept seven STR multiplex for MPS library preparation and an associated bioinformatics pipeline. Additionally, machine learning (ML) models were evaluated to further improve UMI allele calling. Overall, the seven STR multiplex resulted in complete detection and concordant alleles for 47 single-source samples at 1â¯ng input DNA as well as for low-template samples at 62.5â¯pg input DNA. For twelve challenging mixtures with minor contributions of 10â¯pg to 150â¯pg and ratios of 1-15% relative to the major donor, 99.2% of the expected alleles were detected by applying the UMIs in combination with an ML filter. The main impact of UMIs was a substantially lowered number of artefacts as well as reduced stutter ratios, which were generally below 5% of the parental allele. In conclusion, UMI-based STR sequencing opens new means for improved analysis of challenging crime scene samples including complex mixtures.