Telomerase represents an attractive target for a mechanism-based therapeutic approach because its activation has been associated with unlimited proliferation in most cancer cells. Recently, a nonnucleosidic small molecule inhibitor, BIBR1532 (2-[(E)-3-naphtalen-2-yl-but-2-enoylamino]-benzoic acid), has been identified that is highly selective for inhibition of telomerase, resulting in delayed growth arrest of tumor cells. Here we examined the effects of BIBR1532 in different leukemia cell lines as well as in primary cells from patients with acute myeloid leukemia (AML) and chronic lymphocytic leukemia (CLL) in short-term culture assays. We observed a dose-dependent direct cytotoxicity in concentrations ranging from 30 to 80 M. Interestingly, cell death was not dependent on the catalytic activity of telomerase but was delayed in cells with very long telomeres. We observed timedependent individual telomere erosion, which was associated with loss of telomeric repeat binding factor 2 (TRF2) and increased phosphorylation of p53. Importantly, the proliferative capacity of normal CD34 ؉ cells from cord blood and leukapheresis samples was not affected by treatment with BIBR1532. We conclude that using this class of telomerase inhibitor at higher concentrations exerts a direct cytotoxic effect on malignant cells of the hematopoietic system, which appears to derive from direct damage of the structure of individual telomeres and must be dissected from telomerase-suppressed overall telomere shortening. (Blood. 2005; 105:1742-1749)

Purpose: The pattern of breast cancer metastasis may be determined by interactions between CXCR4 on breast cancer cells and CXCL12 within normal tissues. Glycosaminoglycans bind chemokines for presentation to responsive cells. This study was designed to test the hypothesis that soluble heparinoid glycosaminoglycan molecules can disrupt the normal response to CXCL12, thereby reducing the metastasis of CXCR4-expressing cancer cells. Experimental Design: Inhibition of the response of CXCR4-expressing Chinese hamster ovary cells to CXCL12 was assessed by measurement of calcium flux and chemotaxis. Radioligand binding was also assessed to quantify the potential of soluble heparinoids to prevent specific receptor ligation. The human breast cancer cell line MDA-MB-231and a range of sublines were assessed for their sensitivity to heparinoid-mediated inhibition of chemotaxis. A model of hematogenous breast cancer metastasis was established, and the potential of clinically relevant doses of heparinoids to inhibit CXCL12 presentation and metastatic disease was assessed. Results: Unfractionated heparin and the low-molecular-weight heparin tinzaparin inhibited receptor ligation and the response of CXCR4-expressing Chinese hamster ovary cells and human breast cancer cell lines to CXCL12. Heparin also removed CXCL12 from its normal site of expression on the surface of parenchymal cells in the murine lung. Both heparin and two clinically relevant dose regimens of tinzaparin reduced hematogenous metastatic spread of human breast cancer cells to the lung in a murine model. Conclusions: Clinically relevant concentrations of tinzaparin inhibit the interaction between CXCL12 and CXCR4 and may be useful to prevent chemokine-driven breast cancer metastasis.Breast cancer metastases are commonly found in regional lymph nodes, bone, liver, and the lungs (1). Evidence shows that the sites of metastasis are determined not only by the characteristics of the cancer cells but also by the microenvironment of the specific organ (2). It seems that breast cancer cells are able to metastasize to specific organs in a manner that is dependent on the ability of the organ to mediate tumor cell adhesion and extravasation and to support subsequent viability and proliferation.Chemokines are members of a superfamily of chemotactic cytokines and were initially characterized because of their association with inflammatory responses. However, it is now known that they also play roles in homeostasis, cell proliferation, hematopoiesis (3), viral interactions, angiogenesis, and neovascularization (4). Four chemokine classes have been defined based on the location of the first two cysteine residues in the protein sequence (CXC, CC, C, and CX 3 C). CXCL12 (stromal cell -derived factor-1a) is a CXC chemokine and is the sole ligand for the receptor CXCR4, although CXCL12 can also signal through the orphan receptor RDC1 (CXCR7) on T lymphocytes (5). Chemokines activate members of the seven-transmembrane spanning G protein -coupled receptor family. On chemoki...

Sequencing studies of diffuse large B cell lymphoma (DLBCL) have identified hundreds of recurrently altered genes. However, it remains largely unknown whether and how these mutations may contribute to lymphomagenesis, either individually or in combination. Existing strategies to address this problem predominantly utilize cell lines, which are limited by their initial characteristics and subsequent adaptions to prolonged in vitro culture. Here, we describe a co-culture system that enables the ex vivo expansion and viral transduction of primary human germinal center B cells. Incorporation of CRISPR/Cas9 technology enables high-throughput functional interrogation of genes recurrently mutated in DLBCL. Using a backbone of BCL2 with either BCL6 or MYC, we identify co-operating genetic alterations that promote growth or even full transformation into synthetically engineered DLBCL models. The resulting tumors can be expanded and sequentially transplanted in vivo, providing a scalable platform to test putative cancer genes and to create mutation-directed, bespoke lymphoma models.

In this paper, we propose a statistical approach for mitosis detection in breast cancer histological images. The proposed algorithm models the pixel intensities in mitotic and non-mitotic regions by a Gamma-Gaussian mixture model (GGMM) and employs a context aware post-processing (CAPP) in order to reduce false positives. Experimental results demonstrate the ability of this simple, yet effective method to detect mitotic cells (MCs) in standard H & E breast cancer histology images.Context:Counting of MCs in breast cancer histopathology images is one of three components (the other two being tubule formation, nuclear pleomorphism) required for developing computer assisted grading of breast cancer tissue slides. This is very challenging since the biological variability of the MCs makes their detection extremely difficult. In addition, if standard H & E is used (which stains chromatin rich structures, such as nucleus, apoptotic, and MCs dark blue) and it becomes extremely difficult to detect the latter given the fact that former two are densely localized in the tissue sections.Aims:In this paper, a robust MCs detection technique is developed and tested on 35 breast histopathology images, belonging to five different tissue slides.Settings and Design:Our approach mimics a pathologists’ approach to MCs detections. The idea is (1) to isolate tumor areas from non-tumor areas (lymphoid/inflammatory/apoptotic cells), (2) search for MCs in the reduced space by statistically modeling the pixel intensities from mitotic and non-mitotic regions, and finally (3) evaluate the context of each potential MC in terms of its texture.Materials and Methods:Our experimental dataset consisted of 35 digitized images of breast cancer biopsy slides with paraffin embedded sections stained with H and E and scanned at × 40 using an Aperio scanscope slide scanner.Statistical Analysis Used:We propose GGMM for detecting MCs in breast histology images. Image intensities are modeled as random variables sampled from one of the two distributions; Gamma and Gaussian. Intensities from MCs are modeled by a gamma distribution and those from non-mitotic regions are modeled by a gaussian distribution. The choice of Gamma-Gaussian distribution is mainly due to the observation that the characteristics of the distribution match well with the data it models. The experimental results show that the proposed system achieves a high sensitivity of 0.82 with positive predictive value (PPV) of 0.29. Employing CAPP on these results produce 241% increase in PPV at the cost of less than 15% decrease in sensitivity.Conclusions:In this paper, we presented a GGMM for detection of MCs in breast cancer histopathological images. In addition, we introduced CAPP as a tool to increase the PPV with a minimal loss in sensitivity. We evaluated the performance of the proposed detection algorithm in terms of sensitivity and PPV over a set of 35 breast histology images selected from five different tissue slides and showed that a reasonably high value of sensitivity can be retained while ...

It has been reported that p21-activated kinase 4 (PAK4) is amplified in pancreatic cancer tissue. PAK4 is a member of the PAK family of serine/threonine kinases, which act as effectors for several small GTPases, and has been specifically identified to function downstream of HGF-mediated c-Met activation in a PI3K dependent manner. However, the functionality of PAK4 in pancreatic cancer and the contribution made by HGF signalling to pancreatic cancer cell motility remain to be elucidated. We now find that elevated PAK4 expression is coincident with increased expression levels of c-Met and the p85α subunit of PI3K. Furthermore, we demonstrate that pancreatic cancer cells have a specific motility response to HGF both in 2D and 3D physiomimetic organotypic assays; which can be suppressed by inhibition of PI3K. Significantly, we report a specific interaction between PAK4 and p85α and find that PAK4 deficient cells exhibit a reduction in Akt phosphorylation downstream of HGF signalling. These results implicate a novel role for PAK4 within the PI3K pathway via interaction with p85α. Thus, PAK4 could be an essential player in PDAC progression representing an interesting therapeutic opportunity.

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Recent advances in whole-slide imaging (WSI) technology have led to the development of a myriad of computer vision and artificial intelligence-based diagnostic, prognostic, and predictive algorithms. Computational Pathology (CPath) offers an integrated solution to utilise information embedded in pathology WSIs beyond what can be obtained through visual assessment. For automated analysis of WSIs and validation of machine learning (ML) models, annotations at the slide, tissue, and cellular levels are required. The annotation of important visual constructs in pathology images is an important component of CPath projects. Improper annotations can result in algorithms that are hard to interpret and can potentially produce inaccurate and inconsistent results. Despite the crucial role of annotations in CPath projects, there are no well-defined guidelines or best practices on how annotations should be carried out. In this paper, we address this shortcoming by presenting the experience and best practices acquired during the execution of a large-scale annotation exercise involving a multidisciplinary team of pathologists, ML experts, and researchers as part of the Pathology image data Lake for Analytics, Knowledge and Education (PathLAKE) consortium. We present a real-world case study along with examples of different types of annotations, diagnostic algorithm, annotation data dictionary, and annotation constructs. The analyses reported in this work highlight best practice recommendations that can be used as annotation guidelines over the lifecycle of a CPath project.

Multicentric Castleman disease (MCD) is a rare human herpes virus type 8 (HHV8)-associated lymphoproliferative disorder that occurs more frequently in patients infected with human immunodeficiency virus (HIV). In tissue samples, HHV8-infected plasmablasts localise to the mantle zones of the lymphoid follicles. We revisited the immunohistological features in 25 lymph node (LN) and three spleen samples of MCD. In five (20%) LN and one (33%) spleen sample, HHV8 latent nuclear antigen 1 (LANA1) staining was also noted on the follicular dendritic cells (FDC). The HHV8-positive FDC subgroup of patients had significantly higher numbers of CD3-positive T cells infiltrating the follicles when compared to the HHV8-negative FDC subgroup (P = 0.047). Furthermore, the numbers of HHV8-positive plasmablasts and serum HHV8 viral copy numbers were lower among the HHV8-positive FDC subgroup when compared to the HHV8-negative FDC subgroup (not statistically significant). Our findings show, for the first time, possible 'presentation' of an HHV8 antigen by FDCs in MCD.