Signature maps for automatic identification of prostate cancer from colorimetric analysis of H&E- and IHC-stained histopathological specimens.

Prostate cancer (PCa) is a major cause of cancer death among men. The histopathological examination of post-surgical prostate specimens and manual annotation of PCa not only allow for detailed assessment of disease characteristics and extent, but also supply the ground truth for developing of computer-aided diagnosis (CAD) systems for PCa detection before definitive treatment. As manual cancer annotation is tedious and subjective, there have been a number of publications describing methods for automating the procedure via the analysis of digitized whole-slide images (WSIs). However, these studies have focused only on the analysis of WSIs stained with hematoxylin and eosin (H&E), even though there is additional information that could be obtained from immunohistochemical (IHC) staining. In this work, we propose a framework for automating the annotation of PCa that is based on automated colorimetric analysis of both H&E and IHC WSIs stained with a triple-antibody cocktail against high-molecular weight cytokeratin (HMWCK), p63, and α-methylacyl CoA racemase (AMACR). The analysis outputs were then used to train a regression model to estimate the distribution of cancerous epithelium within slides. The approach yielded an AUC of 0.951, sensitivity of 87.1%, and specificity of 90.7% as compared to slide-level annotations, and generalized well to cancers of all grades.

Sleeping Beauty Insertional Mutagenesis Reveals Important Genetic Drivers of Central Nervous System Embryonal Tumors.

Medulloblastoma and central nervous system primitive neuroectodermal tumors (CNS-PNET) are aggressive, poorly differentiated brain tumors with limited effective therapies. Using Sleeping Beauty (SB) transposon mutagenesis, we identified novel genetic drivers of medulloblastoma and CNS-PNET. Cross-species gene expression analyses classified SB-driven tumors into distinct medulloblastoma and CNS-PNET subgroups, indicating they resemble human Sonic hedgehog and group 3 and 4 medulloblastoma and CNS neuroblastoma with FOXR2 activation. This represents the first genetically induced mouse model of CNS-PNET and a rare model of group 3 and 4 medulloblastoma. We identified several putative proto-oncogenes including Arhgap36, Megf10, and Foxr2. Genetic manipulation of these genes demonstrated a robust impact on tumorigenesis in vitro and in vivo. We also determined that FOXR2 interacts with N-MYC, increases C-MYC protein stability, and activates FAK/SRC signaling. Altogether, our study identified several promising therapeutic targets in medulloblastoma and CNS-PNET. SIGNIFICANCE: A transposon-induced mouse model identifies several novel genetic drivers and potential therapeutic targets in medulloblastoma and CNS-PNET.

Genetically engineered minipigs model the major clinical features of human neurofibromatosis type 1.

Neurofibromatosis Type 1 (NF1) is a genetic disease caused by mutations in Neurofibromin 1 (NF1). NF1 patients present with a variety of clinical manifestations and are predisposed to cancer development. Many NF1 animal models have been developed, yet none display the spectrum of disease seen in patients and the translational impact of these models has been limited. We describe a minipig model that exhibits clinical hallmarks of NF1, including café au lait macules, neurofibromas, and optic pathway glioma. Spontaneous loss of heterozygosity is observed in this model, a phenomenon also described in NF1 patients. Oral administration of a mitogen-activated protein kinase/extracellular signal-regulated kinase inhibitor suppresses Ras signaling. To our knowledge, this model provides an unprecedented opportunity to study the complex biology and natural history of NF1 and could prove indispensable for development of imaging methods, biomarkers, and evaluation of safety and efficacy of NF1-targeted therapies.

Safe and Effective Sarcoma Therapy through Bispecific Targeting of EGFR and uPAR.

Sarcomas differ from carcinomas in their mesenchymal origin. Therapeutic advancements have come slowly, so alternative drugs and models are urgently needed. These studies report a new drug for sarcomas that simultaneously targets both tumor and tumor neovasculature. eBAT is a bispecific angiotoxin consisting of truncated, deimmunized Pseudomonas exotoxin fused to EGF and the amino terminal fragment of urokinase. Here, we study the drug in an in vivo "ontarget" companion dog trial as eBAT effectively kills canine hemangiosarcoma and human sarcoma cells in vitro We reasoned the model has value due to the common occurrence of spontaneous sarcomas in dogs and a limited lifespan allowing for rapid accrual and data collection. Splenectomized dogs with minimal residual disease were given one cycle of eBAT followed by adjuvant doxorubicin in an adaptive dose-finding, phase I-II study of 23 dogs with spontaneous, stage I-II, splenic hemangiosarcoma. eBAT improved 6-month survival from <40% in a comparison population to approximately 70% in dogs treated at a biologically active dose (50 µg/kg). Six dogs were long-term survivors, living >450 days. eBAT abated expected toxicity associated with EGFR targeting, a finding supported by mouse studies. Urokinase plasminogen activator receptor and EGFR are targets for human sarcomas, so thorough evaluation is crucial for validation of the dog model. Thus, we validated these markers for human sarcoma targeting in the study of 212 human and 97 canine sarcoma samples. Our results support further translation of eBAT for human patients with sarcomas and perhaps other EGFR-expressing malignancies. Mol Cancer Ther; 16(5); 956-65. ©2017 AACR.

Constitutive activation of alternative nuclear factor kappa B pathway in canine diffuse large B-cell lymphoma contributes to tumor cell survival and is a target of new adjuvant therapies.

Activation of the classical nuclear factor kappa-light-chain-enhancer of activated B cells (NFκB) pathway is a common molecular event observed in both human and canine diffuse large B-cell lymphoma (DLBCL). Although the oncogenic potential of the alternative NFκB pathway (ANFκBP) has also been recently identified in DLBCL, its precise role in tumor pathogenesis and potential as a treatment target is understudied. We hypothesized that up-regulation of the ANFκBP plays an important role in the proliferation and survival of canine DLBCL cells, and we demonstrate that the ANFκBP is constitutively active in primary canine DLBCL samples and a cell line (CLBL1). We further demonstrate that a small interfering RNA inhibits the activation of the NFκB pathway and induces apoptosis in canine DLBCL cells. In conclusion, the ANFκBP facilitates survival of canine DLBCL cells, and thus, dogs with spontaneous DLBCL can provide a useful large animal model to study therapies targeting the ANFκBP.

Quantitative comparison and reproducibility of pathologist scoring and digital image analysis of estrogen receptor ß2 immunohistochemistry in prostate cancer.

BACKGROUND: Digital image analysis offers advantages over traditional pathologist visual scoring of immunohistochemistry, although few studies examining the correlation and reproducibility of these methods have been performed in prostate cancer. We evaluated the correlation between digital image analysis (continuous variable data) and pathologist visual scoring (quasi-continuous variable data), reproducibility of each method, and association of digital image analysis methods with outcomes using prostate cancer tissue microarrays (TMAs) stained for estrogen receptor-ß2 (ERß2). METHODS: Prostate cancer TMAs were digitized and evaluated by pathologist visual scoring versus digital image analysis for ERß2 staining within tumor epithelium. Two independent analysis runs were performed to evaluate reproducibility. Image analysis data were evaluated for associations with recurrence-free survival and disease specific survival following radical prostatectomy. RESULTS: We observed weak/moderate Spearman correlation between digital image analysis and pathologist visual scores of tumor nuclei (Analysis Run A: 0.42, Analysis Run B: 0.41), and moderate/strong correlation between digital image analysis and pathologist visual scores of tumor cytoplasm (Analysis Run A: 0.70, Analysis Run B: 0.69). For the reproducibility analysis, there was high Spearman correlation between pathologist visual scores generated for individual TMA spots across Analysis Runs A and B (Nuclei: 0.84, Cytoplasm: 0.83), and very high correlation between digital image analysis for individual TMA spots across Analysis Runs A and B (Nuclei: 0.99, Cytoplasm: 0.99). Further, ERß2 staining was significantly associated with increased risk of prostate cancer-specific mortality (PCSM) when quantified by cytoplasmic digital image analysis (HR 2.16, 95 % CI 1.02-4.57, p = 0.045), nuclear image analysis (HR 2.67, 95 % CI 1.20-5.96, p = 0.016), and total malignant epithelial area analysis (HR 5.10, 95 % CI 1.70-15.34, p = 0.004). After adjusting for clinicopathologic factors, only total malignant epithelial area ERß2 staining was significantly associated with PCSM (HR 4.08, 95 % CI 1.37-12.15, p = 0.012). CONCLUSIONS: Digital methods of immunohistochemical quantification are more reproducible than pathologist visual scoring in prostate cancer, suggesting that digital methods are preferable and especially warranted for studies involving large sample sizes.

Trp53 haploinsufficiency modifies EGFR-driven peripheral nerve sheath tumorigenesis.

Malignant peripheral nerve sheath tumors (MPNSTs) are genetically diverse, aggressive sarcomas that occur sporadically or in association with neurofibromatosis type 1 syndrome. Reduced TP53 gene expression and amplification/overexpression of the epidermal growth factor receptor (EGFR) gene occur in MPNST formation. We focused on determining the cooperativity between reduced TP53 expression and EGFR overexpression for Schwann cell transformation in vitro (immortalized human Schwann cells) and MPNST formation in vivo (transgenic mice). Human gene copy number alteration data, microarray expression data, and TMA analysis indicate that TP53 haploinsufficiency and increased EGFR expression co-occur in human MPNST samples. Concurrent modulation of EGFR and TP53 expression in HSC1λ cells significantly increased proliferation and anchorage-independent growth in vitro. Transgenic mice heterozygous for a Trp53-null allele and overexpressing EGFR in Schwann cells had a significant increase in neurofibroma and grade 3 PNST (MPNST) formation compared with single transgenic controls. Histological analysis of tumors identified a significant increase in pAkt expression in grade 3 PNSTs compared with neurofibromas. Array comparative genome hybridization analysis of grade 3 PNSTs identified recurrent focal regions of chromosomal gains with significant enrichment in genes involved in extracellular signal-regulated kinase 5 signaling. Collectively, altered p53 expression cooperates with overexpression of EGFR in Schwann cells to enhance in vitro oncogenic properties and tumorigenesis and progression in vivo.

Evaluation of protein biomarkers of prostate cancer aggressiveness.

BACKGROUND: Prognostic multibiomarker signatures in prostate cancer (PCa) may improve patient management and provide a bridge for developing novel therapeutics and imaging methods. Our objective was to evaluate the association between expression of 33 candidate protein biomarkers and time to biochemical failure (BF) after prostatectomy. METHODS: PCa tissue microarrays were constructed representing 160 patients for whom clinicopathologic features and follow-up data after surgery were available. Immunohistochemistry for each of 33 proteins was quantified using automated digital pathology techniques. Relationships between clinicopathologic features, staining intensity, and time to BF were assessed. Predictive modeling using multiple imputed datasets was performed to identify the top biomarker candidates. RESULTS: In univariate analyses, lymph node positivity, surgical margin positivity, non-localized tumor, age at prostatectomy, and biomarkers CCND1, HMMR, IGF1, MKI67, SIAH2, and SMAD4 in malignant epithelium were significantly associated with time to BF. HMMR, IGF1, and SMAD4 remained significantly associated with BF after adjusting for clinicopathologic features while additional associations were observed for HOXC6 and MAP4K4 following adjustment. In multibiomarker predictive models, 3 proteins including HMMR, SIAH2, and SMAD4 were consistently represented among the top 2, 3, 4, and 5 most predictive biomarkers, and a signature comprised of these proteins best predicted BF at 3 and 5 years. CONCLUSIONS: This study provides rationale for investigation of HMMR, HOXC6, IGF1, MAP4K4, SIAH2, and SMAD4 as biomarkers of PCa aggressiveness in larger cohorts.

Elevated hyaluronan and hyaluronan-mediated motility receptor are associated with biochemical failure in patients with intermediate-grade prostate tumors.

BACKGROUND: The clinical course of prostate cancer (PCa) measured by biochemical failure (BF) after prostatectomy remains unpredictable in many patients, particularly in intermediate Gleason score (GS) 7 tumors, suggesting that identification of molecular mechanisms associated with aggressive PCa biology may be exploited for improved prognostication or therapy. Hyaluronan (HA) is a high molecular weight polyanionic carbohydrate produced by synthases (HAS1 through HAS3) and fragmented by oxidative/nitrosative stress and hyaluronidases (HYAL1 through HYAL4, SPAM1) common in PCa microenvironments. HA and HA fragments interact with receptors CD44 and hyaluronan-mediated motility receptor (HMMR), resulting in increased tumor aggressiveness in experimental PCa models. This study evaluated the association of HA-related molecules with BF after prostatectomy in GS7 tumors. METHODS: Tissue microarrays were constructed from a 96-patient cohort. HA histochemistry and HAS2, HYAL1, CD44, CD44v6, and HMMR immunohistochemistry were quantified using digital pathology techniques. RESULTS: HA in tumor-associated stroma and HMMR in malignant epithelium were significantly and marginally significantly associated with time to BF in univariate analysis, respectively. After adjusting for clinicopathologic features, both HA in tumor-associated stroma and HMMR in malignant epithelium were significantly associated with time to BF. Although not significantly associated with BF, HAS2 and HYAL1 positively correlated with HMMR in malignant epithelium. Cell culture assays demonstrated that HMMR bound native and fragmented HA, promoted HA uptake, and was required for a promigratory response to fragmented HA. CONCLUSIONS: HA and HMMR are factors associated with time to BF in GS7 tumors, suggesting that increased HA synthesis and fragmentation within the tumor microenvironment stimulates aggressive PCa behavior through HA-HMMR signaling.

Canonical Wnt/ß-catenin signaling drives human schwann cell transformation, progression, and tumor maintenance.

Genetic changes required for the formation and progression of human Schwann cell tumors remain elusive. Using a Sleeping Beauty forward genetic screen, we identified several genes involved in canonical Wnt signaling as potential drivers of benign neurofibromas and malignant peripheral nerve sheath tumors (MPNSTs). In human neurofibromas and MPNSTs, activation of Wnt signaling increased with tumor grade and was associated with downregulation of ß-catenin destruction complex members or overexpression of a ligand that potentiates Wnt signaling, R-spondin 2 (RSPO2). Induction of Wnt signaling was sufficient to induce transformed properties in immortalized human Schwann cells, and downregulation of this pathway was sufficient to reduce the tumorigenic phenotype of human MPNST cell lines. Small-molecule inhibition of Wnt signaling effectively reduced the viability of MPNST cell lines and synergistically induced apoptosis when combined with an mTOR inhibitor, RAD-001, suggesting that Wnt inhibition represents a novel target for therapeutic intervention in Schwann cell tumors.

Quantitative comparison of immunohistochemical staining measured by digital image analysis versus pathologist visual scoring.

Immunohistochemical (IHC) assays performed on formalin-fixed paraffin-embedded (FFPE) tissue sections traditionally have been semi-quantified by pathologist visual scoring of staining. IHC is useful for validating biomarkers discovered through genomics methods as large clinical repositories of FFPE specimens support the construction of tissue microarrays (TMAs) for high throughput studies. Due to the ubiquitous availability of IHC techniques in clinical laboratories, validated IHC biomarkers may be translated readily into clinical use. However, the method of pathologist semi-quantification is costly, inherently subjective, and produces ordinal rather than continuous variable data. Computer-aided analysis of digitized whole slide images may overcome these limitations. Using TMAs representing 215 ovarian serous carcinoma specimens stained for S100A1, we assessed the degree to which data obtained using computer-aided methods correlated with data obtained by pathologist visual scoring. To evaluate computer-aided image classification, IHC staining within pathologist annotated and software-classified areas of carcinoma were compared for each case. Two metrics for IHC staining were used: the percentage of carcinoma with S100A1 staining (%Pos), and the product of the staining intensity (optical density [OD] of staining) multiplied by the percentage of carcinoma with S100A1 staining (OD*%Pos). A comparison of the IHC staining data obtained from manual annotations and software-derived annotations showed strong agreement, indicating that software efficiently classifies carcinomatous areas within IHC slide images. Comparisons of IHC intensity data derived using pixel analysis software versus pathologist visual scoring demonstrated high Spearman correlations of 0.88 for %Pos (p < 0.0001) and 0.90 for OD*%Pos (p < 0.0001). This study demonstrated that computer-aided methods to classify image areas of interest (e.g., carcinomatous areas of tissue specimens) and quantify IHC staining intensity within those areas can produce highly similar data to visual evaluation by a pathologist. VIRTUAL SLIDES: The virtual slide(s) for this article can be found here: http://www.diagnosticpathology.diagnomx.eu/vs/1649068103671302.

Development of multigene expression signature maps at the protein level from digitized immunohistochemistry slides.

Molecular classification of diseases based on multigene expression signatures is increasingly used for diagnosis, prognosis, and prediction of response to therapy. Immunohistochemistry (IHC) is an optimal method for validating expression signatures obtained using high-throughput genomics techniques since IHC allows a pathologist to examine gene expression at the protein level within the context of histologically interpretable tissue sections. Additionally, validated IHC assays may be readily implemented as clinical tests since IHC is performed on routinely processed clinical tissue samples. However, methods have not been available for automated n-gene expression profiling at the protein level using IHC data. We have developed methods to compute expression level maps (signature maps) of multiple genes from IHC data digitized on a commercial whole slide imaging system. Areas of cancer for these expression level maps are defined by a pathologist on adjacent, co-registered H&E slides, allowing assessment of IHC statistics and heterogeneity within the diseased tissue. This novel way of representing multiple IHC assays as signature maps will allow the development of n-gene expression profiling databases in three dimensions throughout virtual whole organ reconstructions.