Search

Abstract Background Quality Control in any high-throughput sequencing technology is a critical step, which if overlooked can compromise an experiment and the resulting conclusions. A number of methods exist to identify biases during sequencing or alignment, yet not many tools exist to interpret biases due to outliers. Results Hence, we developed iSeqQC, an expression-based QC tool that detects outliers either produced due to variable laboratory conditions or due to dissimilarity within a phenotypic group. iSeqQC implements various statistical approaches including unsupervised clustering, agglomerative hierarchical clustering and correlation coefficients to provide insight into outliers. It can be utilized through command-line (Github: https://github.com/gkumar09/iSeqQC) or web-interface (http://cancerwebpa.jefferson.edu/iSeqQC). A local shiny installation can also be obtained from github (https://github.com/gkumar09/iSeqQC). Conclusion iSeqQC is a fast, light-weight, expression-based QC tool that detects outliers by implementing various statistical approaches.

Abstract Background Metastatic uveal melanoma is a highly fatal disease; most patients die from their hepatic metastasis within 1 year. A major drawback in the development of new treatments for metastatic uveal melanoma is the difficulty in obtaining appropriate cell lines and the lack of appropriate animal models. Patient-derived xenograft (PDX) tumor models, bearing ectopically implanted tumors at a subcutaneous site, have been developed. However, these ectopically implanted PDX models have obstacles to translational research, including a low engraftment rate, slow tumor growth, and biological changes after multiple passages due to the different microenvironment. To overcome these limitations, we developed a new method to directly transplant biopsy specimens to the liver of immunocompromised mice. Results By using two metastatic uveal melanoma cell lines, we demonstrated that the liver provides a more suitable microenvironment for tumor growth compared to subcutaneous sites and that surgical orthotopic implantation (SOI) of tumor pieces allows the creation of a liver tumor in immunocompromised mice. Subsequently, 10 of 12 hepatic metastasis specimens from patients were successfully xenografted into the immunocompromised mice (83.3% success rate) using SOI, including 8 of 10 needle biopsy specimens (80%). Additionally, four cryopreserved PDX tumors were re-implanted to new mice and re-establishment of PDX tumors was confirmed in all four mice. The serially passaged xenograft tumors as well as the re-implanted tumors after cryopreservation were similar to the original patient tumors in histologic, genomic, and proteomic expression profiles. CT imaging was effective for detecting and monitoring PDX tumors in the liver of living mice. The expression of Ki67 in original patient tumors was a predictive factor for implanted tumor growth and the success of serial passages in PDX mice. Conclusions Surgical orthotopic implantation of hepatic metastasis from uveal melanoma is highly successful in the establishment of orthotopic PDX models, enhancing their practical utility for research applications. By using CT scan, tumor growth can be monitored, which is beneficial to evaluate treatment effects in interventional studies.