Quantitative assessment of pancreatic cancer precursor lesions in IHC-stained tissue with a tissue image analysis platform.

Tissue image analysis (tIA) is emerging as a powerful tool for quantifying biomarker expression and distribution in complex diseases and tissues. Pancreatic ductal adenocarcinoma (PDAC) develops in a highly complex and heterogeneous tissue environment and, generally, has a very poor prognosis. Early detection of PDAC is confounded by limited knowledge of the pre-neoplastic disease stages and limited methods to quantitatively assess disease heterogeneity. We sought to develop a tIA approach to assess the most common PDAC precursor lesions, pancreatic intraepithelial neoplasia (PanIN), in tissues from KrasLSL-G12D/+; Trp53LSL-R172H/+; Pdx-Cre (KPC) mice, a validated model of PDAC development. tIA profiling of training regions of PanIN and tumor microenvironment (TME) cells was utilized to guide identification of PanIN/TME tissue compartment stratification criteria. A custom CellMap algorithm implementing these criteria was applied to whole-slide images of KPC mice pancreata sections to quantify p53 and Ki-67 biomarker staining in each tissue compartment as a proof-of-concept for the algorithm platform. The algorithm robustly identified a higher percentage of p53-positive cells in PanIN lesions relative to the TME, whereas no difference was observed for Ki-67. Ki-67 expression was also quantified in a human pancreatic tissue sample available to demonstrate the translatability of the CellMap algorithm to human samples. Together, our data demonstrated the utility of CellMap to enable objective and quantitative assessments, across entire tissue sections, of PDAC precursor lesions in preclinical and clinical models of this disease to support efforts leading to novel insights into disease progression, diagnostic markers, and potential therapeutic targets.

Activated tumor cell integrin αvß3 cooperates with platelets to promote extravasation and metastasis from the blood stream.

Metastasis is the main cause of death in cancer patients, and understanding mechanisms that control tumor cell dissemination may lead to improved therapy. Tumor cell adhesion receptors contribute to cancer spreading. We noted earlier that tumor cells can expressing the adhesion receptor integrin αvß3 in distinct states of activation, and found that cells which metastasize from the blood stream express it in a constitutively high affinity form. Here, we analyzed steps of the metastatic cascade in vivo and asked, when and how the affinity state of integrin αvß3 confers a critical advantage to cancer spreading. Following tumor cells by real time PCR, non-invasive bioluminescence imaging, intravital microscopy and histology allowed us to identify tumor cell extravasation from the blood stream as a rate-limiting step supported by high affinity αvß3. Successful transendothelial migration depended on cooperation between tumor cells and platelets involving the high affinity tumor cell integrin and release of platelet granules. Thus, this study identifies the high affinity conformer of integrin αvß3 and its interaction with platelets as critical for early steps during hematogenous metastasis and target for prevention of metastatic disease.

AngioMap is a novel image analysis algorithm for assessment of plasma cell distribution within bone marrow vascular niche.

The ability to characterize distribution of neoplastic hematopoietic cells and their progenitors in their native microenvironment is emerging as an important challenge and potential therapeutic target in many disease areas, including multiple myeloma. In multiple myeloma, bone marrow (BM) angiogenesis is typically increased and microvessel density is a known indicator of poor prognosis. However, the difficulty of consistently measuring 3D vessels from 2D cut sections has previously limited the study of spatial distribution of plasma cells (PC) and their interaction with BM microenvironment. The aim of the study is to report a novel method to study myeloma cells spatial distribution within their hematopoietic niche context using readily available tissue sections and standard histology approaches. We utilized a novel whole-tissue image analysis approach to identify vessels, and then applied computational grown regions extended out from each vessel at 15, 35, 55, 75, and 100 µm to identify the spatial distribution of PC on CD34/CD138 double-stained core biopsy slides. Percent PC to total cells (TC) was significantly higher at <15 µm distance compared with those at 16 to 35, 36 to 55, 56 to 75, and 76 to 100 µm distance (P=0.0001). Similarly, PC/TC at <35 µm region was significantly higher compared with 36 to 55 (P=0.0001), 56 to 75 (P≤0.0001), and 76 to 100 (P=0.0002) µm distances. The mean PC/TC differences in the spatial gradient of 36 to 55, 56 to 75, and 76 to 100 µm distance regions were not significant. Our findings suggest possible preferential advantage to neoplastic PC in the proximity of blood vessels compared with other hematopoietic marrow cells. We demonstrate the feasibility of analyzing the spatial distribution of PC, and possibly other hematopoietic/stem cells in their microenvironment, as characterized by the distance to vessels in BM using a novel image analysis approach.

Altered expression of polycomb group genes in glioblastoma multiforme.

The Polycomb group (PcG) proteins play a critical role in histone mediated epigenetics which has been implicated in the malignant evolution of glioblastoma multiforme (GBM). By systematically interrogating The Cancer Genome Atlas (TCGA), we discovered widespread aberrant expression of the PcG members in GBM samples compared to normal brain. The most striking differences were upregulation of EZH2, PHF19, CBX8 and PHC2 and downregulation of CBX7, CBX6, EZH1 and RYBP. Interestingly, changes in EZH2, PHF19, CBX7, CBX6 and EZH1 occurred progressively as astrocytoma grade increased. We validated the aberrant expression of CBX6, CBX7, CBX8 and EZH2 in GBM cell lines by Western blotting and qRT-PCR, and further the aberrant expression of CBX6 in GBM tissue samples by immunohistochemical staining. To determine if there was functional significance to the diminished CBX6 levels in GBM, CBX6 was overexpressed in GBM cells resulting in decreased proliferative capacity. In conclusion, aberrant expression of PcG proteins in GBMs may play a role in the development or maintenance of the malignancy.

Tissue pattern recognition error rates and tumor heterogeneity in gastric cancer.

The anatomic pathology discipline is slowly moving toward a digital workflow, where pathologists will evaluate whole-slide images on a computer monitor rather than glass slides through a microscope. One of the driving factors in this workflow is computer-assisted scoring, which depends on appropriate selection of regions of interest. With advances in tissue pattern recognition techniques, a more precise region of the tissue can be evaluated, no longer bound by the pathologist's patience in manually outlining target tissue areas. Pathologists use entire tissues from which to determine a score in a region of interest when making manual immunohistochemistry assessments. Tissue pattern recognition theoretically offers this same advantage; however, error rates exist in any tissue pattern recognition program, and these error rates contribute to errors in the overall score. To provide a real-world example of tissue pattern recognition, 11 HER2-stained upper gastrointestinal malignancies with high heterogeneity were evaluated. HER2 scoring of gastric cancer was chosen due to its increasing importance in gastrointestinal disease. A method is introduced for quantifying the error rates of tissue pattern recognition. The trade-off between fully sampling tumor with a given tissue pattern recognition error rate versus randomly sampling a limited number of fields of view with higher target accuracy was modeled with a Monte-Carlo simulation. Under most scenarios, stereological methods of sampling-limited fields of view outperformed whole-slide tissue pattern recognition approaches for accurate immunohistochemistry analysis. The importance of educating pathologists in the use of statistical sampling is discussed, along with the emerging role of hybrid whole-tissue imaging and stereological approaches.

Evaluating tumor heterogeneity in immunohistochemistry-stained breast cancer tissue.

Quantitative clinical measurement of heterogeneity in immunohistochemistry staining would be useful in evaluating patient therapeutic response and in identifying underlying issues in histopathology laboratory quality control. A heterogeneity scoring approach (HetMap) was designed to visualize a individual patient's immunohistochemistry heterogeneity in the context of a patient population. HER2 semiquantitative analysis was combined with ecology diversity statistics to evaluate cell-level heterogeneity (consistency of protein expression within neighboring cells in a tumor nest) and tumor-level heterogeneity (differences of protein expression across a tumor as represented by a tissue section). This approach was evaluated on HER2 immunohistochemistry-stained breast cancer samples using 200 specimens across two different laboratories with three pathologists per laboratory, each outlining regions of tumor for scoring by automatic cell-based image analysis. HetMap was evaluated using three different scoring schemes: HER2 scoring according to American Society of Clinical Oncology and College of American Pathologists (ASCO/CAP) guidelines, H-score, and a new continuous HER2 score (HER2(cont)). Two definitions of heterogeneity, cell-level and tumor-level, provided useful independent measures of heterogeneity. Cases where pathologists had disagreement over reads in the area of clinical importance (+1 and +2) had statistically significantly higher levels of tumor-level heterogeneity. Cell-level heterogeneity, reported either as an average or the maximum area of heterogeneity across a slide, had low levels of dependency on the pathologist choice of region, while tumor-level heterogeneity measurements had more dependence on the pathologist choice of regions. HetMap is a measure of heterogeneity, by which pathologists, oncologists, and drug development organizations can view cell-level and tumor-level heterogeneity for a patient for a given marker in the context of an entire patient cohort. Heterogeneity analysis can be used to identify tumors with differing degrees of heterogeneity, or to highlight slides that should be rechecked for QC issues. Tumor heterogeneity plays a significant role in disconcordant reads between pathologists.

Inducible expression of TGFß, snail and Zeb1 recapitulates EMT in vitro and in vivo in a NSCLC model.

The progression of cancer from non-metastatic to metastatic is the critical transition in the course of the disease. The epithelial to mesenchymal transition (EMT) is a mechanism by which tumor cells acquire characteristics that improve metastatic efficiency. Targeting EMT processes in patients is therefore a potential strategy to block the transition to metastatic cancer and improve patient outcome. To develop models of EMT applicable to in vitro and in vivo settings, we engineered NCI-H358 non-small cell lung carcinoma cells to inducibly express three well-established drivers of EMT: activated transforming growth factor ß (aTGFß), Snail or Zeb1. We characterized the morphological, molecular and phenotypic changes induced by each of the drivers and compared the different end-states of EMT between the models. Both in vitro and in vivo, induction of the transgenes Snail and Zeb1 resulted in downregulation of epithelial markers and upregulation of mesenchymal markers, and reduced the ability of the cells to proliferate. Induced autocrine expression of aTGFß caused marker and phenotypic changes consistent with EMT, a modest effect on growth rate, and a shift to a more invasive phenotype. In vivo, this manifested as tumor cell infiltration of the surrounding mouse stromal tissue. Overall, Snail and Zeb1 were sufficient to induce EMT in the cells, but aTGFß induced a more complex EMT, in which changes in extracellular matrix remodeling components were pronounced.

Targeting activated integrin alphavbeta3 with patient-derived antibodies impacts late-stage multiorgan metastasis.

Advanced metastatic disease is difficult to manage and specific therapeutic targets are rare. We showed earlier that metastatic breast cancer cells use the activated conformer of adhesion receptor integrin alphavbeta3 for dissemination. We now investigated if targeting this form of the receptor can impact advanced metastatic disease, and we analyzed the mechanisms involved. Treatment of advanced multi-organ metastasis in SCID mice with patient-derived scFv antibodies specific for activated integrin alphavbeta3 caused stagnation and regression of metastatic growth. The antibodies specifically localized to tumor lesions in vivo and inhibited alphavbeta3 ligand binding at nanomolar levels in vitro. At the cellular level, the scFs associated rapidly with high affinity alphavbeta3 and dissociated extremely slowly. Thus, the scFvs occupy the receptor on metastatic tumor cells for prolonged periods of time, allowing for inhibition of established cell interaction with natural alphavbeta3 ligands. Potential apoptosis inducing effects of the antibodies through interaction with caspase-3 were studied as potential additional mechanism of treatment response. However, in contrast to a previous concept, neither the RGD-containing ligand mimetic scFvs nor RGD peptides bound or activated caspase-3 at the cellular or molecular level. This indicates that the treatment effects seen in the animal model are primarily due to antibody interference with alphavbeta3 ligation. Inhibition of advanced metastatic disease by treatment with cancer patient derived single chain antibodies against the activated conformer of integrin alphavbeta3 identifies this form of the receptor as a suitable target for therapy.

Activation of tumor cell integrin alphavbeta3 controls angiogenesis and metastatic growth in the brain.

The incidence of brain metastasis is rising and poses a severe clinical problem, as we lack effective therapies and knowledge of mechanisms that control metastatic growth in the brain. Here we demonstrate a crucial role for high-affinity tumor cell integrin alpha(v)beta(3) in brain metastatic growth and recruitment of blood vessels. Although alpha(v)beta(3) is frequently up-regulated in primary brain tumors and metastatic lesions of brain homing cancers, we show that it is the alpha(v)beta(3) activation state that is critical for brain lesion growth. Activated, but not non-activated, tumor cell alpha(v)beta(3) supports efficient brain metastatic growth through continuous up-regulation of vascular endothelial growth factor (VEGF) protein under normoxic conditions. In metastatic brain lesions carrying activated alpha(v)beta(3), VEGF expression is controlled at the post-transcriptional level and involves phosphorylation and inhibition of translational respressor 4E-binding protein (4E-BP1). In contrast, tumor cells with non-activated alpha(v)beta(3) depend on hypoxia for VEGF induction, resulting in reduced angiogenesis, tumor cell apoptosis, and inefficient intracranial growth. Importantly, the microenvironment critically influences the effects that activated tumor cell alpha(v)beta(3) exerts on tumor cell growth. Although it strongly promoted intracranial growth, the activation state of the receptor did not influence tumor growth in the mammary fat pad as a primary site. Thus, we identified a mechanism by which metastatic cells thrive in the brain microenvironment and use the high-affinity form of an adhesion receptor to grow and secure host support for proliferation. Targeting this molecular mechanism could prove valuable for the inhibition of brain metastasis.

Adaptation of energy metabolism in breast cancer brain metastases.

Brain metastases are among the most feared complications in breast cancer, as no therapy exists that prevents or eliminates breast cancer spreading to the brain. New therapeutic strategies depend on specific knowledge of tumor cell properties that allow breast cancer cell growth within the brain tissue. To provide information in this direction, we established a human breast cancer cell model for brain metastasis based on circulating tumor cells from a breast cancer patient and variants of these cells derived from bone or brain lesions in immunodeficient mice. The brain-derived cells showed an increased potential for brain metastasis in vivo and exhibited a unique protein expression profile identified by large-scale proteomic analysis. This protein profile is consistent with either a selection of predisposed cells or bioenergetic adaptation of the tumor cells to the unique energy metabolism of the brain. Increased expression of enzymes involved in glycolysis, tricarboxylic acid cycle, and oxidative phosphorylation pathways suggests that the brain metastatic cells derive energy from glucose oxidation. The cells further showed enhanced activation of the pentose phosphate pathway and the glutathione system, which can minimize production of reactive oxygen species resulting from an enhanced oxidative metabolism. These changes promoted resistance of brain metastatic cells to drugs that affect the cellular redox balance. Importantly, the metabolic alterations are associated with strongly enhanced tumor cell survival and proliferation in the brain microenvironment. Thus, our data support the hypothesis that predisposition or adaptation of the tumor cell energy metabolism is a key element in breast cancer brain metastasis, and raise the possibility of targeting the functional differentiation in breast cancer brain lesions as a novel therapeutic strategy.

MAP kinase/estrogen receptor cross-talk enhances estrogen-mediated signaling and tumor growth but does not confer tamoxifen resistance.

The estrogen receptor alpha (ERalpha) signaling plays an essential role in breast cancer progression and endocrine therapy. Mitogen-activated protein kinase (MAPK/Erk1/2) has been implicated in ligand-independent activation of ER, resulting in the cross-talk between growth factor and ER mediated signaling. In this study, we examined the effect of the cross-talk on estradiol (E(2))-mediated signaling, tumor growth and its effect on anti-estrogen therapy. Our findings demonstrate that expression of constitutively activated mitogen activated kinase kinase (MEK1), an immediate upstream activator of MAPK in estrogen receptor positive MCF-7 breast cancer cells (MEK/MCF-7), showed an increase in ERalpha-driven transcriptional activation. In MEK/MCF-7 cells maximal transactivation levels were achieved in response to treatment with much lower E(2) concentrations (10(-10) M E(2)) when compared to MCF-7 control cells (10(-8) M E(2)). Furthermore, we have seen an increased association between ERalpha and its nuclear coactivators AIB1 or TIF-2, in MEK/MCF-7 cells relative to those seen in MCF-7 control cells. In addition, in vivo studies show that MEK/MCF-7 cell tumors are approximately threefold larger than those of MCF-7 cell, in the presence of E(2). Immunohistochemical staining demonstrates that progesterone receptor (PR) and pS2, two E(2)-regulated gene products, are significantly increased in MEK/MCF-7 cell tumors compared to those of MCF-7 control tumors, suggesting that activation of ERalpha by MAPK enhances the expression of E(2)-regulated genes and accelerates tumor growth. Remarkably, the antiestrogens tamoxifen and ICI 182,780, were shown both in vitro and in vivo studies to efficiently antagonize the stimulatory effects of E(2) on ER regulated transactivation and tumor growth in MEK/MCF-7 as well as MCF-7 cell lines. Taken together, these data suggest that MAPK/ER cross-talk enhances ERalpha-mediated signaling and accelerates E(2)-dependent tumor growth without diminishing sensitivity to the inhibitory effects of anti-estrogens.