Brian Laffin

The PSA−/lo Prostate Cancer Cell Population Harbors Self-Renewing Long-Term Tumor-Propagating Cells that Resist Castration

Prostate cancer (PCa) is heterogeneous and contains both differentiated and undifferentiated tumor cells, but the relative functional contribution of these two cell populations remains unclear. Here we report distinct molecular, cellular, and tumor-propagating properties of PCa cells that express high (PSA(+)) and low (PSA(-/lo)) levels of the differentiation marker PSA. PSA(-/lo) PCa cells are quiescent and refractory to stresses including androgen deprivation, exhibit high clonogenic potential, and possess long-term tumor-propagating capacity. They preferentially express stem cell genes and can undergo asymmetric cell division to generate PSA(+) cells. Importantly, PSA(-/lo) PCa cells can initiate robust tumor development and resist androgen ablation in castrated hosts, and they harbor highly tumorigenic castration-resistant PCa cells that can be prospectively enriched using ALDH(+)CD44(+)α2β1(+) phenotype. In contrast, PSA(+) PCa cells possess more limited tumor-propagating capacity, undergo symmetric division, and are sensitive to castration. Altogether, our study suggests that PSA(-/lo) cells may represent a critical source of castration-resistant PCa cells.

CD44-positive cancer stem cells expressing cellular prion protein contribute to metastatic capacity in colorectal cancer

Cancer stem cells are implicated in tumor progression, metastasis, and recurrence, although the exact mechanisms remain poorly understood. Here, we show that the expression of cellular prion protein (PrPc, PRNP) is positively correlated with an increased risk of metastasis in colorectal cancer. PrPc defines a subpopulation of CD44-positive cancer stem cells that contributes to metastatic capacity. PrPc(+)CD44(+) colorectal cancer stem cells displayed high liver metastatic capability, unlike PrPc(-)CD44(+) stem cells, that was inhibited by RNAi-mediated attenuation of PrPc. Notably, administration of PrPc monoclonal antibodies significantly inhibited tumorigenicity and metastasis of colorectal cancer stem cells in mouse models of orthotopic metastasis. PrPc promoted epithelial to mesenchymal transition (EMT) via the ERK2 (MAPK1) pathway, thereby conferring high metastatic capacity. Our findings reveal the function of PrPc in regulating EMT in cancer stem cells, and they identify PrPc as candidate therapeutic target in metastatic colorectal cancer.

Abstract 2548: Using whole slide digital image analysis to quantify leukocyte populations in tumor sections

Proceedings: AACR Annual Meeting 2014; April 5-9, 2014; San Diego, CA In recent years, the tumor microenvironment (TME) has been identified as an important factor influencing the growth and metastasis of the tumor. Multiple studies have shown that adding the “Immunoscore” assessment to the AJCC/UICC-TNM classification system improves the accuracy of outcome prediction, and in some cases outperforms traditional TNM staging. In many instances these studies have been performed utilizing 2-3 independent readers to manually quantify the cells, performed on selective high-powered fields or TMA cores rather than the entire specimen, resulting in variations in counts when different high powered fields (HPFs) or cores are chosen. A key method to increase the throughput and to decrease the variability is to utilize whole slide imaging and computerized image analysis to provide leukocyte counts. An image analysis algorithm which can automatically differentiate tumor from stroma would allow rapid quantification of endpoints in each tissue compartment across the whole specimen. To address these issues, Flagship Biosciences has designed proprietary CellMapTM image analysis algorithm tools to develop an Immunoscore-like paradigm for colorectal cancers (CRCs) to potentially provide new and more accurate TME information to aid in interpretation. Utilizing whole slide imaging (WSI) approaches, CellMap™ allows the quantitation of leukocyte populations (e.g., CD3+, CD8+, FoxP3+) automatically across whole tissue sections. Using this algorithm, leukocyte populations were quantified in sections that have been either singly or dually labeled for inflammatory markers. Our preliminary studies indicate that Immunoscore-like scoring paradigm should be established both in tumor areas and in adjacent stroma to provide the most complete information on the biology of the tumor. We compared the use of this approach in tissue microarray (TMA) cores which generally sample areas of dense tumor mass, and compared automated WSI to manual HPF approaches. Accuracy of the algorithm was demonstrated by comparing data from manual counts to algorithm derived counts using high-powered fields. These data support using CellMap™ in the prospective or retrospective assessment of leukocyte subpopulations in whole slides of clinical samples. This approach will diminish variability in counting, expand the types of endpoints determined, and improve the statistical value of these determinations, thereby facilitating robust TME measurements with clinical value. Note: This abstract was not presented at the meeting. Citation Format: Joseph S. Krueger, Brian Laffin, Holger Lange, Anthony Milici, Eric Neeley, Mirza Peljto, Mahipal Suraneni, David Young. Using whole slide digital image analysis to quantify leukocyte populations in tumor sections. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 2548. doi:10.1158/1538-7445.AM2014-2548

Abstract 2842: Evaluation of immunohistochemistry assays against c-Met and HGF to guide companion diagnostic decisions

Proceedings: AACR Annual Meeting 2014; April 5-9, 2014; San Diego, CA Establishing reagent specificity during immunohistochemistry (IHC) based biomarker or companion diagnostic (CDx) assays is challenging. Antibody specificity is dictated in part by recognition of 3D confirmation of the target binding, target activity, and and/or epitopes post-translation modifications. Fixation effects pose additional challenges to epitope recognition during IHC assay. For these reasons, different antibodies against the same target biomarker may demonstrate diversity in prevalence, range, and staining patterns over identical specimens. Thus, determining reagent specificity is a critical part of IHC and CDx assay development. Interpretation is further complicated by the pattern of biomarker expression in specific cell types (e.g. tumor v. stroma) or cell compartments (e.g. membrane v. cytosol). These factors may be critical to associate the drugs mechanism of action with efficacy. In the companion diagnostic (CDx) setting, the mechanism of the drug, epitope recognition, and staining features used to interpret and quantify the biomarker to predict patient response requires an evidence-based approach, where all features of an IHC assay are considered and tied empirically to patient response to the drug. In this study, we demonstrate these complexities in gastric cancer specimens, by comparing IHC assays using two antibodies that recognize either intracellular or extracellular domains of c-Met receptor (SP44/ C-term and EP154Y/ N-term) in the context of the ligand for c-Met, Hepatocyte Growth Factor (HGF). Therapeutic antibodies targeting c-Met [such as MetMab® (OA-5D5/ Roche)]; or HGF directly [such as Rilotumumab (AMG 102/ Amgen)], have directly linked c-Met protein expression as revealed by IHC to patient response. Thus, we hypothesized that a link between c-Met protein expression and HGF should be discernible. To test this hypothesis, we used image analysis approaches to determine the staining features of each IHC assay in comparison to each other. Surprisingly, we found little concordance between the two c-Met antibodies in evaluating c-Met and HGF expression. We found distinct populations of c-Met expressing vs HGF expressing specimens, whose HGF-c-Met association differed with the c-Met assay used. We examined the tissue and cell compartmentalization, and identified staining features of each reagent which would aid or impede in interpretation strategies for understanding the relationship between c-Met and HGF. These results suggest that the epitope-specific features of each c-Met antibody determines the relationship with HGF expression, and how quantitative image analysis endpoints can be used to make critical decisions during the development of an IHC companion diagnostic. Note: This abstract was not presented at the meeting. Citation Format: Joseph S. Krueger, Brian Laffin, Holger Lange, Eric Neeley, Mirza Peljto, Mohamed Salama, Mahipal Suraneni, David Young. Evaluation of immunohistochemistry assays against c-Met and HGF to guide companion diagnostic decisions. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 2842. doi:10.1158/1538-7445.AM2014-2842

Abstract 4981: Evaluating the contribution of heterogeneity and the tumor microenvironment in companion diagnostic approaches

Proceedings: AACR Annual Meeting 2014; April 5-9, 2014; San Diego, CA As our understanding of the factors which affect efficacy of a targeted therapy increases, the reliance on histopathological analysis of a biomarker has also increased. This is often due to the necessity to weigh the critical factors of a target or biomarker protein in tissue and cellular context. Currently, histopathologic assessment of tumors which aims to project patient clinical outcome utilize drug target response factors, such as relative expression of the drug target of the drug target or a resistance mechanism in the target (tumor) cells or the tumor microenvironment (TME ). Multiple studies have also shown that TME factors such as inflammatory cell content can be prognostic and predictive. For example, adding the Immunoscore assessment to the TNM classification systems improves the accuracy of disease prognosis. This correlation has led to the concept of predictive “immunoprofiling”, which uses an individuals immune system profile to predict that patients response to immunomodulating antibody therapy. For these reasons, it is critical to evaluate the drug target or biomarker in conjunction with TME features when defining a patient selection strategy. Critical factors such as tissue and/or cellular compartmentalization and tumor heterogeneity direct the interpretation of these measures and their predictive value. To address the need for careful, contextual interpretation of histopathological evaluations, Flagship has built CellMap™ image analysis algorithms to directly measure heterogeneity and the TME components in a whole tissue section. These approaches allow biomarker interpretation in the complex context of spatial, architectural, and morphological information to aid histological definition and quantification. In this study, we utilized a cohort of specimens from 20 colorectal cancer (CRC) patients and immunologically stained them in order to visualize c-Met, as a characteristic and biologically relevant therapy target; and CD3+ and CD8+ to visualize the inflammatory cell environment. Using these immunohistochemical markers as a prototype for a simultaneous evaluation of a molecular target and the TME, we characterized the biomarker and inflammatory content in both the tumor and stroma using our CellMap™ image analysis algorithms. This provided detailed accounting of the molecular target profile (tumor vs stroma; membrane vs cytoplasm vs nucleus), and the “immunoprofile”, which allowed us to quantitatively describe and associate these features relative to each other in the context of heterogeneity. This data demonstrated discrete patterns of association between c-met and the TME, serving as a potentially critical measure which reflects a biological process relevant to disease outcome. These studies demonstrate novel tools which can assess both the prognostic and predictive value of key measurements which reflect complex tumor biology. Citation Format: Joseph S. Krueger, Brian Laffin, Holger Lange, Anthony Milici, Mirza Peljto, Eric Neeley, Mahipal Suraneni, David Young. Evaluating the contribution of heterogeneity and the tumor microenvironment in companion diagnostic approaches. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 4981. doi:10.1158/1538-7445.AM2014-4981

Abstract C34: Using quantitative image analysis of a putative immunohistochemistry assay against C-met to guide companion diagnostic decisions.

When developing an immunohistochemistry (IHC) based biomarker or companion diagnostic assay, establishing reagent specificity is very challenging. Because antibodies recognize three dimensional epitopes, epitope recognition may be based on a specific confirmation (activated, receptor occupied, etc) or biological state (glycosylation, cell surface vs cytoplasmic) of the target protein. Furthermore, recognition of the epitope in Formalin-Fixed, Paraffin Embedded (FFPE) specimens imposes additional challenges due to the fixation effects. For these reasons, different antibodies against the same target biomarker may demonstrate different prevalence, range, and staining patterns in the same specimens. Determining reagent specificity is a critical part of IHC assay development; but the typical approaches utilized (such as Western Blotting, etc) do not directly prove specificity in the FFPE setting. Additionally, the presence or absence of the protein in a particular tissue (tumor vs stroma) or cell (membrane/ cytosol/ nuclear) compartment may be critical to associate the drugs mechanism of action with efficacy. In the companion diagnostic (CDx) setting, the mechanism of the drug, epitope recognition, and staining features used to interpret and quantify the biomarker to predict patient response requires an evidence-based approach, where all features of an IHC assay are considered and tied empirically to patient response to the drug. In this study, we demonstrate these complexities in gastric cancer specimens, by comparing IHC assays using two antibodies against the intracellular vs extracellular domains of c-met (SP44/ C-term and EP154Y/ N-term) in the context of the ligand for c-met, Hepatocyte Growth Factor (HGF). Therapeutic antibodies targeting c-met [such as MetMab® (OA-5D5/ Roche)]; or HGF directly [such as Rilotumumab (AMG 102/ Amgen)], have linked c-met protein expression by IHC directly to patient response. Thus, we hypothesized that a link between c-met protein expression and HGF should be discernible. To test this hypothesis, we used image analysis approaches to determine the staining features of each IHC assay in relation to each other. Surprisingly, we found little concordance between the two c-met antibodies in evaluating c-met and HGF expression. We found distinct populations of c-met expressing vs HGF expressing specimens, whose HGF-c-met association differed with the c-met assay used. We examined the tissue and cell compartmentalization, and identified staining features of each reagent which would aid or impede in interpretation strategies for understanding the relationship between c-met and HGF. These results suggest that the epitope-specific features of each c-met antibody determines the relationship with HGF expression, and how quantitative image analysis endpoints can be used to make critical decisions during the development of an IHC companion diagnostic. Citation Information: Mol Cancer Ther 2013;12(11 Suppl):C34. Citation Format: Joseph S. Krueger, Brian Laffin, Mirza Peljto, Mahipal Suraneni, Holger Lange, David Young. Using quantitative image analysis of a putative immunohistochemistry assay against C-met to guide companion diagnostic decisions. [abstract]. In: Proceedings of the AACR-NCI-EORTC International Conference: Molecular Targets and Cancer Therapeutics; 2013 Oct 19-23; Boston, MA. Philadelphia (PA): AACR; Mol Cancer Ther 2013;12(11 Suppl):Abstract nr C34.

Abstract 2872: Image analysis algorithms for whole-slide counting, regional assignment, and subtype classification of tumor-associated macrophages (TAMs).

Proceedings: AACR 104th Annual Meeting 2013; Apr 6-10, 2013; Washington, DC Tumor-associated macrophages (TAMs) regulate cancer progression on multiple levels, including angiogenesis, treatment response, and metastasis. Additionally, multiple studies have demonstrated a significant association between clinical outcome and TAM abundance, M1 vs. M2 subtype, and intratumoral distribution into stromal or epithelial compartments. However, manual counting of TAMs and assignment into tumor stroma or epithelial nests is laborious, inaccurate, subjective, and does not provide a statistically optimal sample size. These pitfalls may be limiting its utility as a diagnostic tool or an endpoint in drug efficacy studies. Using tissue sections from human breast cancers as a model, we have developed image analysis algorithms for the rapid automated counting and compartmental assignment of total TAMs (CD68+) and TAMs of the more strongly tumor-promoting M2 subtype (CD163+). Using whole slide scanning and proprietary image analysis tools called Feature Analysis on Consectutive Tissue Sections (FACTS), we have developed an approach to not only tally but also map the location of CD68+ and CD163+ macrophages in serial tissue sections, align those sections, and provide information about regional distribution of these macrophages. These outcomes can also be aligned with other serial sections containing relevant biomarkers associated with macrophage infiltration such as hypoxia or angiongenesis, using our proprietary multivariate correlation analysis tool Multivariatemap. Additionally, we have begun investigations into the association of these regional macrophage densities with clinical outcome using patient data available for the model set. These approaches represent a powerful toolkit for elucidating significant quantitative associations between TAMs and tumor vasculature, hypoxia, or other relevant features or markers, for the determination of prognostic or drug efficacy endpoints. Citation Format: Brian E. Laffin, Joseph Krueger, Mohamed Salama. Image analysis algorithms for whole-slide counting, regional assignment, and subtype classification of tumor-associated macrophages (TAMs). [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr 2872. doi:10.1158/1538-7445.AM2013-2872

Abstract C68: Phenotypic and functional heterogeneity of prostate cancer stem cells

Abstract Recent evidence in many tumor systems suggests that there may exist several or even many tumorigenic subpopulations in each tumor. Utilizing 4 xenograft human prostate cancer (PCa) models, including two AR+/PSA+ (LAPC9 and LAPC4) and two AR-/PSA- (Du145 and PC3) xenografts, and by performing exhaustive limiting-dilution tumor regeneration assays in NOD/SCID mice using purified PCa cells based on functional properties (i.e., side population and Aldefluor assays) or preferential expression of surface markers (ABCG2, CD44, or integrin α2β1), we provide evidence for both the phenotypic and functional heterogeneity of PCa stem cells (i.e., PCa cell subpopulations with enhanced tumor-regeneration activity). Our results show that no single marker or assay seems to be able to capture all tumorigenic subsets in all 4 xenografts. We further show that different tumor-initiating subpopulations appear to co-exist in a common tumorigenic pool. We also demonstrate that some tumorigenic PCa cells overexpress stem cell-associated gene expression profiles. Finally, we provide evidence that primary prostate tumors possess subsets of tumor cells that bear similar phenotypic features to those in xenografts. Our results raise the possibility that different PCa patient tumors may harbor CSCs with distinct phenotypic and functional properties. Note: This abstract was not presented at the conference because the presenter was unable to attend. Citation Format: Xin Liu, Xin Chen, Brian Laffin, Binglan Yin, Tammy Calhoun-Davis, Feng Wang-Johanning, Dean G. Tang. Phenotypic and functional heterogeneity of prostate cancer stem cells [abstract]. In: Proceedings of the AACR Special Conference on Advances in Prostate Cancer Research; 2012 Feb 6-9; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2012;72(4 Suppl):Abstract nr C68.

Abstract 476: Defining two populations of prostate cancer cells with distinct molecular, biological, and tumor-propagating properties

Prostate cancer (PCa) is a heterogeneous malignancy containing different types of tumor cells. The cellular basis underlying PCa cell heterogeneity and functional importance of different PCa cell populations in maintaining tumor homeostasis and mediating castration-resistant progression remain poorly understood. By whole-genome microarray analysis, time-lapse videomicroscopy, serial tumor transplantations, and other functional assays, here we report the distinct molecular, cell biological, and tumor-propagating properties of PCa cells that express high (i.e., PSA + ) and low (PSA −/lo ) levels of PSA. PSA −/lo PCa cells are relatively quiescent and resistant to multiple stresses, exhibit high clonogenic potential, and possess long-term tumor-propagating capacity in intact male mice. They preferentially express stem cell-associated genes and epigenetic profiles and can generate PSA + cells by either asymmetric or symmetric cell division. Of great clinic significance, PSA −/lo PCa cells can initiate robust tumor development in fully castrated hosts and survive experimental androgen-deprivation therapy. In contrast, PSA + PCa cells, despite being highly tumorigenic in androgen-proficient hosts, possess more limited tumor-propagating capacity, mainly undergo symmetric division, and are sensitive to castration. Our data together suggest that the two populations of PCa cells appear to play differential roles in tumor maintenance and PSA −/lo cells may represent an important source of castration-resistant PCa cells. Our findings have important implications in understanding PCa cell heterogeneity, tumor response to the mainstay antiandrogen therapies, and emergence of castration-resistant PCa. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 102nd Annual Meeting of the American Association for Cancer Research; 2011 Apr 2-6; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2011;71(8 Suppl):Abstract nr 476. doi:10.1158/1538-7445.AM2011-476