Tuan Zea Tan

Epithelial-mesenchymal transition spectrum quantification and its efficacy in deciphering survival and drug responses of cancer patients

Epithelial‐mesenchymal transition (EMT) is a reversible and dynamic process hypothesized to be co‐opted by carcinoma during invasion and metastasis. Yet, there is still no quantitative measure to assess the interplay between EMT and cancer progression. Here, we derived a method for universal EMT scoring from cancer‐specific transcriptomic EMT signatures of ovarian, breast, bladder, lung, colorectal and gastric cancers. We show that EMT scoring exhibits good correlation with previously published, cancer‐specific EMT signatures. This universal and quantitative EMT scoring was used to establish an EMT spectrum across various cancers, with good correlation noted between cell lines and tumours. We show correlations between EMT and poorer disease‐free survival in ovarian and colorectal, but not breast, carcinomas, despite previous notions. Importantly, we found distinct responses between epithelial‐ and mesenchymal‐like ovarian cancers to therapeutic regimes administered with or without paclitaxel in vivo and demonstrated that mesenchymal‐like tumours do not always show resistance to chemotherapy. EMT scoring is thus a promising, versatile tool for the objective and systematic investigation of EMT roles and dynamics in cancer progression, treatment response and survival.

Functional genomics identifies five distinct molecular subtypes with clinical relevance and pathways for growth control in epithelial ovarian cancer

Epithelial ovarian cancer (EOC) is hallmarked by a high degree of heterogeneity. To address this heterogeneity, a classification scheme was developed based on gene expression patterns of 1538 tumours. Five, biologically distinct subgroups — Epi‐A, Epi‐B, Mes, Stem‐A and Stem‐B — exhibited significantly distinct clinicopathological characteristics, deregulated pathways and patient prognoses, and were validated using independent datasets. To identify subtype‐specific molecular targets, ovarian cancer cell lines representing these molecular subtypes were screened against a genome‐wide shRNA library. Focusing on the poor‐prognosis Stem‐A subtype, we found that two genes involved in tubulin processing, TUBGCP4 and NAT10, were essential for cell growth, an observation supported by a pathway analysis that also predicted involvement of microtubule‐related processes. Furthermore, we observed that Stem‐A cell lines were indeed more sensitive to inhibitors of tubulin polymerization, vincristine and vinorelbine, than the other subtypes. This subtyping offers new insights into the development of novel diagnostic and personalized treatment for EOC patients.

An EMT spectrum defines an anoikis-resistant and spheroidogenic intermediate mesenchymal state that is sensitive to e-cadherin restoration by a src-kinase inhibitor, saracatinib (AZD0530)

The phenotypic transformation of well-differentiated epithelial carcinoma into a mesenchymal-like state provides cancer cells with the ability to disseminate locally and to metastasise. Different degrees of epithelial–mesenchymal transition (EMT) have been found to occur in carcinomas from breast, colon and ovarian carcinoma (OC), among others. Numerous studies have focused on bona fide epithelial and mesenchymal states but rarely on intermediate states. In this study, we describe a model system for appraising the spectrum of EMT using 43 well-characterised OC cell lines. Phenotypic EMT characterisation reveals four subgroups: Epithelial, Intermediate E, Intermediate M and Mesenchymal, which represent different epithelial–mesenchymal compositions along the EMT spectrum. In cell-based EMT-related functional studies, OC cells harbouring an Intermediate M phenotype are characterised by high N-cadherin and ZEB1 expression and low E-cadherin and ERBB3/HER3 expression and are more anoikis-resistant and spheroidogenic. A specific Src-kinase inhibitor, Saracatinib (AZD0530), restores E-cadherin expression in Intermediate M cells in in vitro and in vivo models and abrogates spheroidogenesis. We show how a 33-gene EMT Signature can sub-classify an OC cohort into four EMT States correlating with progression-free survival (PFS). We conclude that the characterisation of intermediate EMT states provides a new approach to better define EMT. The concept of the EMT Spectrum allows the utilisation of EMT genes as predictive markers and the design and application of therapeutic targets for reversing EMT in a selective subgroup of patients.

Epithelial-to-mesenchymal transition and autophagy induction in breast carcinoma promote escape from T-cell-mediated lysis.

Epithelial-to-mesenchymal transition (EMT) mediates cancer cell invasion, metastasis, and drug resistance, but its impact on immune surveillance has not been explored. In this study, we investigated the functional consequences of this mode of epithelial cell plasticity on targeted cell lysis by cytotoxic T lymphocytes (CTL). Acquisition of the EMT phenotype in various derivatives of MCF-7 human breast cancer cells was associated with dramatic morphologic changes and actin cytoskeleton remodeling, with CD24(-)/CD44(+)/ALDH(+) stem cell populations present exhibiting a higher degree of EMT relative to parental cells. Strikingly, acquisition of this phenotype also associated with an inhibition of CTL-mediated tumor cell lysis. Resistant cells exhibited attenuation in the formation of an immunologic synapse with CTLs along with the induction of autophagy in the target cells. This response was critical for susceptibility to CTL-mediated lysis because siRNA-mediated silencing of beclin1 to inhibit autophagy in target cells restored their susceptibility to CTL-induced lysis. Our results argue that in addition to promoting invasion and metastasis EMT also profoundly alters the susceptibility of cancer cells to T-cell-mediated immune surveillance. Furthermore, they reveal EMT and autophagy as conceptual realms for immunotherapeutic strategies to block immune escape.

A novel cognitive interpretation of breast cancer thermography with complementary learning fuzzy neural memory structure

Abstract Early detection of breast cancer is the key to improve survival rate. Thermogram is a promising front-line screening tool as it is able to warn women of breast cancer up to 10 years in advance. However, analysis and interpretation of thermogram are heavily dependent on the analysts, which may be inconsistent and error-prone. In order to boost the accuracy of preliminary screening using thermogram without incurring additional financial burden, Complementary Learning Fuzzy Neural Network (CLFNN), FALCON-AART is proposed as the Computer-Assisted Intervention (CAI) tool for thermogram analysis. CLFNN is a neuroscience-inspired technique that provides intuitive fuzzy rules, human-like reasoning, and good classification performance. Confluence of thermogram and CLFNN offers a promising tool for fighting breast cancer.

Epithelial–mesenchymal status renders differential responses to cisplatin in ovarian cancer

Chemoresistance to platinums, such as cisplatin, is of critical concern in the treatment of ovarian cancer. Recent evidence has linked epithelial–mesenchymal transition (EMT) as a contributing mechanism. The current study explored the connection between cellular responses to cisplatin and EMT in ovarian cancer. Expression microarrays were utilized to estimate the EMT status as a binary phenotype, and the transcriptional responses of 46 ovarian cancer cell lines to cisplatin were measured at dosages equivalent to 50% growth inhibition. Phenotypic responses to cisplatin were quantified with respect to cell number, proliferation rate and apoptosis, and then compared with the epithelial or mesenchymal status. Ovarian cancer cell lines with an epithelial status exhibited higher resistance to cisplatin treatment in the MTS assay than those with a mesenchymal status. Pathway analyses revealed the induction of G1/S- and S-phase genes (P=0.001) and the activation of multiple NF-κB (nuclear factor kappa-light-chain-enhancer of activated B cells) downstream genes (P=0.0016) by cisplatin selectively in epithelial-like cell lines. BrdU incorporation and Caspase-3/7 release assays confirmed impaired apoptosis in epithelial-like ovarian cancer cells. In clinical samples, we observed resistance to single platinum treatment and the selective activation of the NF-κB pathway by platinum in ovarian cancers with an epithelial status. Overall, our results suggest that, in epithelial-like ovarian cancer cells, NF-κB activation by cisplatin may lead to defective apoptosis, preferential proliferation arrest and a consequential decreased sensitivity to cisplatin.

Ovarian cancer diagnosis with complementary learning fuzzy neural network

DNA microarray is an emerging technique in ovarian cancer diagnosis. However, very often, microarray data is ultra-huge and difficult to analyze. Thus, it is desirable to utilize fuzzy neural network (FNN) approach for assisting the diagnosis and analysis process. Amongst FNN, complementary learning FNN is able to rapidly derive fuzzy sets and formulate fuzzy rules. Complementary learning FNN uses positive and negative learning, and hence it subsides the effect of curse of dimension and is capable of modeling the dynamics of problem space with relative good classification performance. Furthermore, FALCON-AART has human-like reasoning that allows physician to examine its computation in a familiar way. FALCON-AART can generate intuitive fuzzy rule to justify its reasoning, which is important to generate trust among the users of the system. Hence, FALCON-AART is applied in ovarian cancer diagnosis as a clinical decision support system in this work. Its experimental results are encouraging.

FZD7 drives in vitro aggressiveness in Stem-A subtype of ovarian cancer via regulation of non-canonical Wnt/PCP pathway

Ovarian cancer (OC) can be classified into five biologically distinct molecular subgroups: epithelial-A (Epi-A), Epi-B, mesenchymal (Mes), Stem-A and Stem-B. Among them, Stem-A expresses genes relating to stemness and is correlated with poor clinical prognosis. In this study, we show that frizzled family receptor 7 (FZD7), a receptor for Wnt signalling, is overexpressed in the Stem-A subgroup. To elucidate the functional roles of FZD7, we used an RNA interference gene knockdown approach in three Stem-A cell lines: CH1, PA1 and OV-17R. Si-FZD7 OC cells showed reduced cell proliferation with an increase in the G0/G1 sub-population, with no effect on apoptosis. The cells also displayed a distinctive morphologic change by colony compaction to become more epithelial-like and polarised with smaller internuclear distances and increased z-axis height. Immunofluorescence (IF) staining patterns of pan-cadherin and β-catenin suggested an increase in cadherin-based cell–cell adhesion in si-FZD7 cells. We also observed a significant rearrangement in the actin cytoskeleton and an increase in tensile contractility in si-FZD7 OC cells, as evident by the loss of stress fibres and the redistribution of phospho-myosin light chain (pMLC) from the sites of cell–cell contacts to the periphery of cell colonies. Furthermore, there was reciprocal regulation of RhoA (Ras homolog family member A) and Rac1 (Ras-related C3 botulinum toxin substrate 1 (Rho family, small GTP-binding protein Rac1)) activities upon FZD7 knockdown, with a significant reduction in RhoA activity and a concomitant upregulation in Rac1 activity. These changes in pMLC and RhoA, as well as the increased TopFlash reporter activities in si-FZD7 cells, suggested involvement of the non-canonical Wnt/planar cell polarity (PCP) pathway. Selected PCP pathway genes (cadherin EGF LAG seven-pass G-type receptor 3 (CELSR3), prickle homolog 4 (Drosophila) (PRICKLE4), dishevelled-associated activator of morphogenesis 1 (DAAM1), profilin 2 (PFN2), protocadherin 9 (PCDH9), protocadherin α1 (PCDHA1), protocadherin β17 pseudogene (PCDHB17), protocadherin β3 (PCDHB3), sprouty homolog 1 (SPRY1) and protein tyrosine kinase 7 (PTK7)) were found to be more highly expressed in Stem-A than non Stem-A subgroup of OC. Taken together, our results suggest that FZD7 might drive aggressiveness in Stem-A OC by regulating cell proliferation, cell cycle progression, maintenance of the Mes phenotype and cell migration via casein kinase 1ɛ-mediated non-canonical Wnt/PCP pathway.

2005 Special Issue: Ovarian cancer diagnosis by hippocampus and neocortex-inspired learning memory structures

Early detection and accurate staging of ovarian cancer are the keys to improving survival rate. However, at present there is no single diagnosis modality that is sufficiently sensitive. DNA microarray analysis is an emerging technique that has potential for ameliorating the hardship in early detection and staging of ovarian disease. However, microarray data is ultra-huge and difficult to analyze. Hence, computational intelligence methods are often utilized to assist in the diagnosis and analysis process. Fuzzy Neural Networks (FNN) are more suitable for this task as FNN provides not only the accuracy, but also the interpretability of its reasoning process. Hippocampus-inspired Complementary Learning FNN (CLFNN) is able to rapidly derive fuzzy sets and formulate fuzzy rules. CLFNN uses positive and negative learning, and hence it reduces the effect of the curse of dimensionality and is capable of modeling the dynamics of the problem space with relatively good classification performance. One of its successors, a hybrid of complementary hippocampal learning and associative neocortical learning called Pseudo Associative Complementary Learning (PACL), is a structure that seeks to functionally model the memory consolidation process. Both PACL and CLFNN have human-like reasoning that allows physicians to examine their computation using familiar terms. They can construct intuitive fuzzy rules autonomously to justify their reasoning, which is important to generate trust among the users. Hence, CLFNN and PACL are applied as a diagnostic decision support system in ovarian cancer diagnosis. The experimental results are encouraging.

GRHL2-miR-200-ZEB1 maintains the epithelial status of ovarian cancer through transcriptional regulation and histone modification

Epithelial-mesenchymal transition (EMT), a biological process by which polarized epithelial cells convert into a mesenchymal phenotype, has been implicated to contribute to the molecular heterogeneity of epithelial ovarian cancer (EOC). Here we report that a transcription factor—Grainyhead-like 2 (GRHL2) maintains the epithelial phenotype. EOC tumours with lower GRHL2 levels are associated with the Mes/Mesenchymal molecular subtype and a poorer overall survival. shRNA-mediated knockdown of GRHL2 in EOC cells with an epithelial phenotype results in EMT changes, with increased cell migration, invasion and motility. By ChIP-sequencing and gene expression microarray, microRNA-200b/a is identified as the direct transcriptional target of GRHL2 and regulates the epithelial status of EOC through ZEB1 and E-cadherin. Our study demonstrates that loss of GRHL2 increases the levels of histone mark H3K27me3 on promoters and GRHL2-binding sites at miR-200b/a and E-cadherin genes. These findings support GRHL2 as a pivotal gatekeeper of EMT in EOC via miR-200-ZEB1.