Biology subjects

DiNapoli, K.

Publications and source records attributed to DiNapoli, K..

2 recordsLinked to original sources

bioRxiv2020

Evaluating the transcriptional fidelity of cancer models

BackgroundCancer researchers use cell lines, patient derived xenografts, engineered mice, and tumoroids as models to investigate tumor biology and to identify therapies. The generalizability and power of a model derives from the fidelity with which it represents the tumor type under investigation, however, the extent to which this is true is often unclear. The preponderance of models and the ability to readily generate new ones has created a demand for tools that can measure the extent and ways in which cancer models resemble or diverge from native tumors. MethodsWe developed a machine learning based computational tool, CancerCellNet, that measures the similarity of cancer models to 22 naturally occurring tumor types and 36 subtypes, in a platform and species agnostic manner. We applied this tool to 657 cancer cell lines, 415 patient derived xenografts, 26 distinct genetically engineered mouse models, and 131 tumoroids. We validated CancerCellNet by application to independent data, and we tested several predictions with immunofluorescence. ResultsWe have documented the cancer models with the greatest transcriptional fidelity to natural tumors, we have identified cancers underserved by adequate models, and we have found models with annotations that do not match their classification. By comparing models across modalities, we report that, on average, genetically engineered mice and tumoroids have higher transcriptional fidelity than patient derived xenografts and cell lines in four out of five tumor types. However, several patient derived xenografts and tumoroids have classification scores that are on par with native tumors, highlighting both their potential as faithful model classes and their heterogeneity. ConclusionsCancerCellNet enables the rapid assessment of transcriptional fidelity of tumor models. We have made CancerCellNet available as freely downloadable software and as a web application that can be applied to new cancer models that allows for direct comparison to the cancer models evaluated here.

bioinformatics↗

bioRxiv2017

Harnessing the adaptive potential of mechanoresponsive proteins to overwhelm pancreatic cancer dissemination and invasion

Metastatic disease is often characterized by altered cellular contractility and deformability, lending cells and groups of cells the flexibility to navigate through different microenvironments. This ability to change cell shape is driven in large part by the structural elements of the mechanobiome, which includes cytoskeletal proteins that sense and respond to mechanical stimuli. Here, we demonstrate that key mechanoresponsive proteins (those which accumulate in response to mechanical stress), specifically nonmuscle myosin IIA and IIC, -actinin 4, and filamin B, are highly upregulated in pancreatic ductal adenocarcinoma cancer (PDAC) and in patient-derived pancreatic cancer cell lines. Their less responsive sister paralogs (myosin IIB, -actinin 1, and filamin A) show a smaller dynamic range or disappear with PDAC progression. We demonstrate that these mechanoresponsive proteins directly impact cell mechanics using knock-down and overexpression cell lines. We further quantify the nonmuscle myosin II family members in patient-derived cell lines and identify a role for myosin IIC in the formation of transverse actin arcs in single cells and cortical actin belts in tissue spheroids. We harness the upregulation of myosin IIC and its impact of cytoskeletal architecture through the use of the mechanical modulator 4-hydroxyacetophenone (4-HAP), which increases myosin IIC assembly and stiffens cells. Here, 4-HAP decreases dissemination, induces cortical actin belts, and slows retrograde actin flow in spheroids. Finally, mice having undergone hemi-splenectomies with PDAC cells and then treated with 4-HAP have a reduction in liver metastases. Thus, increasing the activity of these mechanoresponsive proteins (in this case, by increasing myosin IIC assembly) to overwhelm the ability of cells to polarize and invade may be an effective strategy to improve the five-year survival rate of pancreatic cancer patients, currently hovering around 6%.

cancer biology↗