Enhancing structural plasticity of PC12 neurons during differentiation and neurite regeneration with a catalytically inactive mutant version of the zRICH protein.

BACKGROUND: Studies of the molecular mechanisms of nerve regeneration have led to the discovery of several proteins that are induced during successful nerve regeneration. RICH proteins were identified as proteins induced during the regeneration of the optic nerve of teleost fish. These proteins are 2',3'-cyclic nucleotide, 3'-phosphodiesterases that can bind to cellular membranes through a carboxy-terminal membrane localization domain. They interact with the tubulin cytoskeleton and are able to enhance neuronal structural plasticity by promoting the formation of neurite branches. RESULTS: PC12 stable transfectant cells expressing a fusion protein combining a red fluorescent protein with a catalytically inactive mutant version of zebrafish RICH protein were generated. These cells were used as a model to analyze effects of the protein on neuritogenesis. Differentiation experiments showed a 2.9 fold increase in formation of secondary neurites and a 2.4 fold increase in branching points. A 2.2 fold increase in formation of secondary neurites was observed in neurite regeneration assays. CONCLUSIONS: The use of a fluorescent fusion protein facilitated detection of expression levels. Two computer-assisted morphometric analysis methods indicated that the catalytically inactive RICH protein induced the formation of branching points and secondary neurites both during differentiation and neurite regeneration. A procedure based on analysis of random field images provided comparable results to classic neurite tracing methods.

SIK2 kinase synthetic lethality is driven by spindle assembly defects in FANCA-deficient cells.

The Fanconi anemia (FA) pathway safeguards genomic stability through cell cycle regulation and DNA damage repair. The canonical tumor suppressive role of FA proteins in the repair of DNA damage during interphase is well established, but their function in mitosis is incompletely understood. Here, we performed a kinome-wide synthetic lethality screen in FANCA-/- fibroblasts, which revealed multiple mitotic kinases as necessary for survival of FANCA-deficient cells. Among these kinases, we identified the depletion of the centrosome kinase SIK2 as synthetic lethal upon loss of FANCA. We found that FANCA colocalizes with SIK2 at multiple mitotic structures and regulates the activity of SIK2 at centrosomes. Furthermore, we found that loss of FANCA exacerbates cell cycle defects induced by pharmacological inhibition of SIK2, including impaired G2-M transition, delayed mitotic progression, and cytokinesis failure. In addition, we showed that inhibition of SIK2 abrogates nocodazole-induced prometaphase arrest, suggesting a novel role for SIK2 in the spindle assembly checkpoint. Together, these findings demonstrate that FANCA-deficient cells are dependent upon SIK2 for survival, supporting a preclinical rationale for targeting of SIK2 in FA-disrupted cancers.

Mitotic Errors Promote Genomic Instability and Leukemia in a Novel Mouse Model of Fanconi Anemia.

Fanconi anemia (FA) is a disease of genomic instability and cancer. In addition to DNA damage repair, FA pathway proteins are now known to be critical for maintaining faithful chromosome segregation during mitosis. While impaired DNA damage repair has been studied extensively in FA-associated carcinogenesis in vivo, the oncogenic contribution of mitotic abnormalities secondary to FA pathway deficiency remains incompletely understood. To examine the role of mitotic dysregulation in FA pathway deficient malignancies, we genetically exacerbated the baseline mitotic defect in Fancc-/- mice by introducing heterozygosity of the key spindle assembly checkpoint regulator Mad2. Fancc-/-;Mad2+/- mice were viable, but died from acute myeloid leukemia (AML), thus recapitulating the high risk of myeloid malignancies in FA patients better than Fancc-/-mice. We utilized hematopoietic stem cell transplantation to propagate Fancc-/-; Mad2+/- AML in irradiated healthy mice to model FANCC-deficient AMLs arising in the non-FA population. Compared to cells from Fancc-/- mice, those from Fancc-/-;Mad2+/- mice demonstrated an increase in mitotic errors but equivalent DNA cross-linker hypersensitivity, indicating that the cancer phenotype of Fancc-/-;Mad2+/- mice results from error-prone cell division and not exacerbation of the DNA damage repair defect. We found that FANCC enhances targeting of endogenous MAD2 to prometaphase kinetochores, suggesting a mechanism for how FANCC-dependent regulation of the spindle assembly checkpoint prevents chromosome mis-segregation. Whole-exome sequencing revealed similarities between human FA-associated myelodysplastic syndrome (MDS)/AML and the AML that developed in Fancc-/-; Mad2+/- mice. Together, these data illuminate the role of mitotic dysregulation in FA-pathway deficient malignancies in vivo, show how FANCC adjusts the spindle assembly checkpoint rheostat by regulating MAD2 kinetochore targeting in cell cycle-dependent manner, and establish two new mouse models for preclinical studies of AML.

High precision localization of pulmonary nodules on chest CT utilizing axial slice number labels.

BACKGROUND: Reidentification of prior nodules for temporal comparison is an important but time-consuming step in lung cancer screening. We develop and evaluate an automated nodule detector that utilizes the axial-slice number of nodules found in radiology reports to generate high precision nodule predictions. METHODS: 888 CTs from Lung Nodule Analysis were used to train a 2-dimensional (2D) object detection neural network. A pipeline of 2D object detection, 3D unsupervised clustering, false positive reduction, and axial-slice numbers were used to generate nodule candidates. 47 CTs from the National Lung Cancer Screening Trial (NLST) were used for model evaluation. RESULTS: Our nodule detector achieved a precision of 0.962 at a recall of 0.573 on the NLST test set for any nodule. When adjusting for unintended nodule predictions, we achieved a precision of 0.931 at a recall 0.561, which corresponds to 0.06 false positives per CT. Error analysis revealed better detection of nodules with soft tissue attenuation compared to ground glass and undeterminable attenuation. Nodule margins, size, location, and patient demographics did not differ between correct and incorrect predictions. CONCLUSIONS: Utilization of axial-slice numbers from radiology reports allowed for development of a lung nodule detector with a low false positive rate compared to prior feature-engineering and machine learning approaches. This high precision nodule detector can reduce time spent on reidentification of prior nodules during lung cancer screening and can rapidly develop new institutional datasets to explore novel applications of computer vision in lung cancer imaging.