MultiPathGAN: Structure Preserving Stain Normalization using Unsupervised Multi-domain Adversarial Network with Perception Loss

Histopathology relies on the analysis of microscopic tissue images to diagnose disease. A crucial part of tissue preparation is staining whereby a dye is used to make the salient tissue components more distinguishable. However, differences in laboratory protocols and scanning devices result in significant confounding appearance variation in the corresponding images. This variation increases both human error and the inter-rater variability, as well as hinders the performance of automatic or semi-automatic methods. In the present paper we introduce an unsupervised adversarial network to translate (and hence normalize) whole slide images across multiple data acquisition domains. Our key contributions are: (i) an adversarial architecture which learns across multiple domains with a single generator-discriminator network using an information flow branch which optimizes for perceptual loss, and (ii) the inclusion of an additional feature extraction network during training which guides the transformation network to keep all the structural features in the tissue image intact. We: (i) demonstrate the effectiveness of the proposed method firstly on H\&E slides of 120 cases of kidney cancer, as well as (ii) show the benefits of the approach on more general problems, such as flexible illumination based natural image enhancement and light source adaptation

Heterogeneity Mapping of Protein Expression in Tumors using Quantitative Immunofluorescence

Morphologic heterogeneity within an individual tumor is well-recognized by histopathologists in surgical practice. While this often takes the form of areas of distinct differentiation into recognized histological subtypes, or different pathological grade, often there are more subtle differences in phenotype which defy accurate classification (Figure 1). Ultimately, since morphology is dictated by the underlying molecular phenotype, areas with visible differences are likely to be accompanied by differences in the expression of proteins which orchestrate cellular function and behavior, and therefore, appearance. The significance of visible and invisible (molecular) heterogeneity for prognosis is unknown, but recent evidence suggests that, at least at the genetic level, heterogeneity exists in the primary tumor1,2, and some of these sub-clones give rise to metastatic (and therefore lethal) disease

Multiscale genomic, transcriptomic and proteomic analysis of colorectal cancer cell lines to identify novel biomarkers

Introduction: Resistance to colorectal cancer (CRC) therapies is a significant cause of treatment failure. We used an in vitro model to identify novel therapeutic targets, explain mechanisms of carcinogenesis and resistance to therapy, and ultimately aid patient stratification for therapy. Methods: A panel of 15 CRC cell lines was profiled by comparative genomic hybridisation, gene expression profiling, reverse phase protein array analysis, and chemosensitivity assays with respect to 5fluorouracil, oxaliplatin, and BEZ235. As proof of concept, fluorescence in situ hybridization and automated quantitative protein analysis were employed to investigate a candidate biomarker in a CRC patient cohort (n=n8).peer-reviewe

Evaluation of Carbonic Anhydrase IX as a Therapeutic Target for Inhibition of Breast Cancer Invasion and Metastasis Using a Series of in vitro Breast Cancer Models

This research was financed in part by a Grant of the 7th Framework Program of the European Union (METOXIA project; HEALTH‐F2‐2009‐222741) and the NGI Pre- Seed grant (NWO n° 93613002).Triple negative, resistant or metastatic disease are major factors in breast cancer mortality, warranting novel approaches. Carbonic anhydrase IX (CAIX) is implicated in survival, migration and invasion of breast cancer cells and inhibition provides an innovative therapeutic strategy. The efficacy of 5 novel ureido-substituted sulfamate CAIX inhibitors were assessed in increasingly complex breast cancer models, including cell lines in normoxia and hypoxia, 3D spheroids and an ex-vivo explant model utilizing fresh biopsy tissue from different breast cancer subtypes. CAIX expression was evaluated in a tissue microarray (TMA) of 92 paired lymph node and primary breast cancers and 2 inhibitors were appraised in vivo using MDA-MB-231 xenografts. FC11409B, FC9398A, FC9403, FC9396A and S4 decreased cell proliferation and migration and inhibited 3D spheroid invasion. S4, FC9398A and FC9403A inhibited or prevented invasion into collagen. FC9403A significantly reversed established invasion whilst FC9398A and DTP348 reduced xenograft growth. TMA analysis showed increased CAIX expression in triple negative cancers. These data establish CAIX inhibition as a relevant therapeutic goal in breast cancer, targeting the migratory, invasive, and metastatic potential of this disease. The use of biopsy tissue suggests efficacy against breast cancer subtypes, and should provide a useful tool in drug testing against invasive cancers.Publisher PDFPeer reviewe

Multi-scale genomic, transcriptomic and proteomic analysis of colorectal cancer cell lines to identify novel biomarkers

This work was partially funded by the Strategic Educational Pathways Scholarship (Malta). The scholarship is part-financed by the European Union – European Social Fund (ESF) under Operational Programme II – Cohesion Policy 2007-2013, “Empowering People for More Jobs and a Better Quality of Life”. This project was additionally funded by Medical Research Scotland.Selecting colorectal cancer (CRC) patients likely to respond to therapy remains a clinical challenge. The objectives of this study were to establish which genes were differentially expressed with respect to treatment sensitivity and relate this to copy number in a panel of 15 CRC cell lines. Copy number variations of the identified genes were assessed in a cohort of CRCs. IC50’s were measured for 5-fluorouracil, oxaliplatin, and BEZ-235, a PI3K/mTOR inhibitor. Cell lines were profiled using array comparative genomic hybridisation, Illumina gene expression analysis, reverse phase protein arrays, and targeted sequencing of KRAS hotspot mutations. Frequent gains were observed at 2p, 3q, 5p, 7p, 7q, 8q, 12p, 13q, 14q, and 17q and losses at 2q, 3p, 5q, 8p, 9p, 9q, 14q, 18q, and 20p. Frequently gained regions contained EGFR, PIK3CA, MYC, SMO, TRIB1, FZD1, and BRCA2, while frequently lost regions contained FHIT and MACROD2. TRIB1 was selected for further study. Gene enrichment analysis showed that differentially expressed genes with respect to treatment response were involved in Wnt signalling, EGF receptor signalling, apoptosis, cell cycle, and angiogenesis. Stepwise integration of copy number and gene expression data yielded 47 candidate genes that were significantly correlated. PDCD6 was differentially expressed in all three treatment responses. Tissue microarrays were constructed for a cohort of 118 CRC patients and TRIB1 and MYC amplifications were measured using fluorescence in situ hybridisation. TRIB1 and MYC were amplified in 14.5% and 7.4% of the cohort, respectively, and these amplifications were significantly correlated (p≤0.0001). TRIB1 protein expression in the patient cohort was significantly correlated with pERK, Akt, and Caspase 3 expression. In conclusion, a set of candidate predictive biomarkers for 5-fluorouracil, oxaliplatin, and BEZ235 are described that warrant further study. Amplification of the putative oncogene TRIB1 has been described for the first time in a cohort of CRC patients.Publisher PDFPeer reviewe

Phosphoprotein pathway profiling of ovarian carcinoma for the identification of potential new targets for therapy

Advances in predicting responses to therapies in ovarian cancer have not matched progress seen in other solid-organ tumours: ovarian cancer remains a poor-prognosis disease. There has been a paradigm shift in molecular therapeutics away from targeting individual molecules to whole biological pathways. The aim of this study was to quantitatively measure the activation state of druggable oncogenic pathways by generating a phosphoprotein profile in cancer tissues, in order to establish associations with clinicopathological parameters and to identify treatment groups for targeted therapy. In total we analysed the expression of ten phosphoproteins within eight signalling pathways (PI3K, MAPK, beta-catenin, STAT, NF kappa B, ER, cell cycle and DNA damage response), proliferation (phospho-histone H3 and Ki67) and apoptosis (activated caspase 3), in two independent cohorts of ovarian cancers using quantitative immunofluorescence image analysis. Data were analysed by unsupervised and K-means clustering to determine new biologically relevant groups. Expression of markers of the five main pathways deregulated by mutation or copy number changes was different between histological subtypes. Four main clusters with distinct phosphoprotein profiles were identified, which were significantly associated with survival in univariate analysis, and which had distinct patterns of pathway expression reproducible between clinical cohorts. These pathway profiles suggest novel therapeutic regimens for the treatment of ovarian cancer, such as MAPK-inhibition in serous or clear cell carcinomas, or combined inhibition of STAT, NF kappa B and WNT signalling. (C) 2011 Elsevier Ltd. All rights reserved.</p

Predicting response to the anti-estrogen fulvestrant in recurrent ovarian cancer

Anti-estrogen therapy appears to have efficacy in a subset of ovarian cancers, as demonstrated in multiple phase II studies. Identifying sensitive patients early in treatment may allow for targeted, low-toxicity primary therapy or prevention of recurrence. We have previously demonstrated that the likelihood of response to letrozole could be improved by patient selection based on estrogen-pathway marker expression. We sought to identify ovarian cancer biomarkers that might indicate sensitivity to fulvestrant, an estrogen receptor antagonist

Additional file 3: of Dynamic modulation of phosphoprotein expression in ovarian cancer xenograft models

Differential protein expression. Log fold changes of differentially expressed proteins over 14 days are shown in 4 worksheets, each for a xenograft-treatment condition: carboplatin treated OV1002; carboplatin treated HOX424; carboplatin-paclitaxel treated OV1002; carboplatin-paclitaxel treated HOX424. (XLS 57 kb