Murine Mesenchymal Stromal Cells Retain Biased Differentiation Plasticity Towards Their Tissue of Origin.

Mesenchymal stromal/stem cells (MSCs) reside in many human tissues and comprise a heterogeneous population of cells with self-renewal and multi-lineage differentiation potential, making them useful in regenerative medicine. It remains inconclusive whether MSCs isolated from different tissue sources exhibit variations in biological features. In this study, we derived MSCs from adipose tissue (AT-MSC) and compact bone (CB-MSC). We found that early passage of MSCs was readily expandable ex vivo, whereas the prolonged culture of MSCs showed alteration of cell morphology to fibroblastoid and reduced proliferation. CB-MSCs and AT-MSCs at passage 3 were CD29+, CD44+, CD105+, CD106+, and Sca-1+; however, passage 7 MSCs showed a reduction of MSC markers, indicating loss of stem cell population after prolonged culturing. Strikingly, CB-MSC was found more efficient at undergoing osteogenic differentiation, while AT-MSC was more efficient to differentiate into adipocytes. The biased differentiation pattern of MSCs from adipogenic or osteogenic tissue source was accompanied by preferential expression of the corresponding lineage marker genes. Interestingly, CB-MSCs treated with DNA demethylation agent 5-azacytidine showed enhanced osteogenic and adipogenic differentiation, whereas the treated AT-MSCs are less competent to differentiate. Our results suggest that the epigenetic state of MSCs is associated with the biased differentiation plasticity towards its tissue of origin, proposing a mechanism related to the retention of epigenetic memory. These findings facilitate the selection of optimal tissue sources of MSCs and the ex vivo expansion period for therapeutic applications.

Constitutively nuclear FOXO3a localization predicts poor survival and promotes Akt phosphorylation in breast cancer.

BACKGROUND: The PI3K-Akt signal pathway plays a key role in tumorigenesis and the development of drug-resistance. Cytotoxic chemotherapy resistance is linked to limited therapeutic options and poor prognosis. METHODOLOGY/PRINCIPAL FINDINGS: Examination of FOXO3a and phosphorylated-Akt (P-Akt) expression in breast cancer tissue microarrays showed nuclear FOXO3a was associated with lymph node positivity (p = 0.052), poor prognosis (p = 0.014), and P-Akt expression in invasive ductal carcinoma. Using tamoxifen and doxorubicin-sensitive and -resistant breast cancer cell lines as models, we found that doxorubicin- but not tamoxifen-resistance is associated with nuclear accumulation of FOXO3a, consistent with the finding that sustained nuclear FOXO3a is associated with poor prognosis. We also established that doxorubicin treatment induces proliferation arrest and FOXO3a nuclear relocation in sensitive breast cancer cells. Induction of FOXO3a activity in doxorubicin-sensitive MCF-7 cells was sufficient to promote Akt phosphorylation and arrest cell proliferation. Conversely, knockdown of endogenous FOXO3a expression reduced PI3K/Akt activity. Using MDA-MB-231 cells, in which FOXO3a activity can be induced by 4-hydroxytamoxifen, we showed that FOXO3a induction up-regulates PI3K-Akt activity and enhanced doxorubicin resistance. However FOXO3a induction has little effect on cell proliferation, indicating that FOXO3a or its downstream activity is deregulated in the cytotoxic drug resistant breast cancer cells. Thus, our results suggest that sustained FOXO3a activation can enhance hyperactivation of the PI3K/Akt pathway. CONCLUSIONS/SIGNIFICANCE: Together these data suggest that lymph node metastasis and poor survival in invasive ductal breast carcinoma are linked to an uncoupling of the Akt-FOXO3a signaling axis. In these breast cancers activated Akt fails to inactivate and re-localize FOXO3a to the cytoplasm, and nuclear-targeted FOXO3a does not induce cell death or cell cycle arrest. As such, sustained nuclear FOXO3a expression in breast cancer may culminate in cancer progression and the development of an aggressive phenotype similar to that observed in cytotoxic chemotherapy resistant breast cancer cell models.

A new presentation and exploration of human cerebral vasculature correlated with surface and sectional neuroanatomy.

The increasing complexity of human body models enabled by advances in diagnostic imaging, computing, and growing knowledge calls for the development of a new generation of systems for intelligent exploration of these models. Here, we introduce a novel paradigm for the exploration of digital body models illustrating cerebral vasculature. It enables dynamic scene compositing, real-time interaction combined with animation, correlation of 3D models with sectional images, quantification as well as 3D manipulation-independent labeling and knowledge-related meta labeling (with name, diameter, description, variants, and references). This novel exploration is incorporated into a 3D atlas of cerebral vasculature with arteries and veins along with the surrounding surface and sectional neuroanatomy derived from 3.0 Tesla scans. This exploration paradigm is useful in medical education, training, research, and clinical applications. It enables development of new generation systems for rapid and intelligent exploration of complicated digital body models in real time with dynamic scene compositing from highly parcellated 3D models, continuous navigation, and manipulation-independent labeling with multiple features.

A 3D model of human cerebrovasculature derived from 3T magnetic resonance angiography.

The human cerebrovasculature is extremely complicated and its three dimensional (3D) highly parcellated models, though necessary, are unavailable. We constructed a digital cerebrovascular model from a high resolution, 3T 3D time-of-flight magnetic resonance angiography scan. This model contains the arterial and venous systems and is 3D, geometric, highly parcellated, fully segmented, and completely labeled with name, diameter, and variants. Our approach replaces the tedious and time consuming process of checking and correcting automatic segmentation results done at 2D image level with an aggregate and faster process at 3D model level. The creation of the vascular model required vessel pre-segmentation, centerline extraction, vascular segments connection, centerline smoothing, vessel surface construction, vessel grouping, tracking, editing, labeling, setting diameter, and checking correctness and completeness. For comparison, the same scan was segmented automatically with 59.8% sensitivity and only 16.5% of vessels smaller than 1 pixel size were extracted. To check and correct this automatic segmentation requires 8 weeks. Conversely, the speedup of our approach (the number of 2D segmented areas/the number of 3D vascular segments) is 34. This cerebrovascular model can serve as a reference framework in clinical, research, and educational applications. The wealth of information aggregated with its quantification capabilities can augment or replace numerous textbook chapters. Five applications of the vascular model were described. The model is easily extendable in content, parcellation, and labeling, and the proposed approach is applicable for building a whole body vascular system.

On geometric modeling of the human intracranial venous system.

We describe a process aiming to construct a 3-D geometric model of the human normal intracranial venous system from MRA data. An analysis of geometric properties of the intracranial veins and sinuses results in proposing three models: circular, elliptic, and free-shape. We formulate a rule based on which a suitable geometric venous model can be selected. The cross-sectional shape of different parts of dural venous sinuses is found to be better approximated by ellipses and free shapes, while for veins the circular and elliptic models are comparable. An analysis of using splines for radii smoothing is also provided. The approach is useful for building venous models in education and clinical applications.