Quantitative and systems pathology for therapeutic response prediction

The measurement of tissue biomarkers for therapeutic response prediction in cancer patients has become standard pathological practice, but only for a very limited number of targets. This is in spite of massive intellectual and financial investment in molecular pathology for translational cancer research. A re-evaluation of current approaches, and the testing of new ones, is required in order to meet the challenges of predicting responses to existing and novel therapeutics, and individualising therapy.Herein I critique the current state of tissue biomarker analysis and quantification in cancer pathology and the reasons why so few novel biomarkers have entered the clinic. In particular, we examine the central role of signalling pathway biology in sensitivity and resistance to targeted therapy. I discuss how accurate quantification, and the ability to simulate biological responses over time and space, may lead to more accurate prediction of therapeutic response. I propose that different mathematical techniques used in the nascent field of systems biology (ordinary differential equation-based, S-systems, and Bayesian approaches) may provide promising new avenues to improve prediction in clinical and pathological practice. I also discuss the challenges and opportunities for quantification in pathological research and practice.I have examined the role of cellular signalling pathways in therapeutic sensitivity and resistance in three different ways. Firstly, I have taken a hypothesis-driven and reductionist approach and shown that decreased Sprouty 2, a feedback inhibitor of MAPK and PI3K signalling, is associated with trastuzumab-resistance in vitro and in a cohort of breast cancer patients treated with trastuzumab. Secondly, I have characterised the activation state of ten growth and survival pathways across different histological subtypes of ovarian cancer using quantitative fluorescence microscopy. I have shown that unsupervised clustering of phosphoprotein expression profiles results in new subgroups with distinct biological properties (in terms of proliferation and apoptosis), and which predict therapeutic response to chemotherapy. Thirdly, I have developed a new mathematical model of PI3K signalling, parameterised using quantitative phosphoprotein expression data from cancer cell lines using reverse-phase protein microarrays, and shown that quantitative PTEN protein expression is the key determinant of resistance to anti-HER2 therapy in silico. Furthermore, the quantitative measurement of PTEN is more predictive of response than other pathway components taken in isolation and when tested by multivariate analysis in a cohort of breast cancers treated with trastuzumab. For the first time, a systems biology approach has successfully been used to stratify patients for personalised therapy in cancer, and is further compelling evidence that PTEN, appropriately measured in the clinical setting, refines clinical decision-making in patients treated with anti-HER2 therapies

Compensatory effects in the PI3K/PTEN/AKT signaling network following receptor tyrosine kinase inhibition

Overcoming de novo and acquired resistance to anticancer drugs that target signaling networks is a formidable challenge for drug design and effective cancer therapy. Understanding the mechanisms by which this resistance arises may offer a route to addressing the insensitivity of signaling networks to drug intervention and restore the efficacy of anticancer therapy. Extending our recent work identifying PTEN as a key regulator of Herceptin sensitivity, we present an integrated theoretical and experimental approach to study the compensatory mechanisms within the PI3K/PTEN/AKT signaling network that afford resistance to receptor tyrosine kinase (RTK) inhibition by anti-HER2 monoclonal antibodies. In a computational model representing the dynamics of the signaling network, we define a single control parameter that encapsulates the balance of activities of the enzymes involved in the PI3K/PTEN/AKT cycle. By varying this control parameter we are able to demonstrate both distinct dynamic regimes of behavior of the signaling network and the transitions between those regimes. We demonstrate resistance, sensitivity, and suppression of RTK signals by the signaling network. Through model analysis we link the sensitivity-to-resistance transition to specific compensatory mechanisms within the signaling network. We study this transition in detail theoretically by variation of activities of PTEN, PI3K, AKT enzymes, and use the results to inform experiments that perturb the signaling network using combinatorial inhibition of RTK, PTEN, and PI3K enzymes in human ovarian carcinoma cell lines. We find good alignment between theoretical predictions and experimental results. We discuss the application of the results to the challenges of hypersensitivity of the signaling network to RTK signals, suppression of drug resistance, and efficacy of drug combinations in anticancer therapy

Features of the reversible sensitivity-resistance transition in PI3K/PTEN/AKT signalling network after HER2 inhibition

Systems biology approaches that combine experimental data and theoretical modelling to understand cellular signalling network dynamics offer a useful platform to investigate the mechanisms of resistance to drug interventions and to identify combination drug treatments. Extending our work on modelling the PI3K/PTEN/AKT signalling network (SN), we analyse the sensitivity of the SN output signal, phospho-AKT, to inhibition of HER2 receptor. We model typical aberrations in this SN identified in cancer development and drug resistance: loss of PTEN activity, PI3K and AKT mutations, HER2 overexpression, and overproduction of GSK3β and CK2 kinases controlling PTEN phosphorylation. We show that HER2 inhibition by the monoclonal antibody pertuzumab increases SN sensitivity, both to external signals and to changes in kinetic parameters of the proteins and their expression levels induced by mutations in the SN. This increase in sensitivity arises from the transition of SN functioning from saturation to non-saturation mode in response to HER2 inhibition. PTEN loss or PIK3CA mutation causes resistance to anti-HER2 inhibitor and leads to the restoration of saturation mode in SN functioning with a consequent decrease in SN sensitivity. We suggest that a drug-induced increase in SN sensitivity to internal perturbations, and specifically mutations, causes SN fragility. In particular, the SN is vulnerable to mutations that compensate for drug action and this may result in a sensitivity-to-resistance transition. The combination of HER2 and PI3K inhibition does not sensitise the SN to internal perturbations (mutations) in the PI3K/PTEN/AKT pathway: this combination treatment provides both synergetic inhibition and may prevent the SN from acquired mutations causing drug resistance. Through combination inhibition treatments, we studied the impact of upstream and downstream interventions to suppress resistance to the HER2 inhibitor in the SN with PTEN loss. Comparison of experimental results of PI3K inhibition in the PTEN upstream pathway with PDK1 inhibition in the PTEN downstream pathway shows that upstream inhibition abrogates resistance to pertuzumab more effectively than downstream inhibition. This difference in inhibition effect arises from the compensatory mechanism of an activation loop induced in the downstream pathway by PTEN loss. We highlight that drug target identification for combination anti-cancer therapy needs to account for the mutation effects on the upstream and downstream pathways

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

The relationship between oestrogen receptor-alpha phosphorylation and the tumour microenvironment in patients with primary operable ductal breast cancer

Aims: Although the role of phosphorylation of oestrogen receptor (ER) at serines 118 (p-S118) and 167 (p-S167) has been studied, the relationship between p-S118, p-S167 and the tumour microenvironment in ER-positive primary operable ductal breast cancers have not been investigated. The aims of this study are to investigate (i) the relationship between p-S118/p-S167 and the tumour microenvironment, and (ii) the effect of p-S118/167 on survival and recurrence in ER-positive primary operable ductal breast cancers. Methods and results: Patients presenting at three Glasgow hospitals between 1995 and 1998 with invasive ductal ER-positive primary breast cancers were studied (n = 294). Immunohistochemical staining of p-S118 and p-S167 was performed and their association with clinicopathological characteristics, cancer-specific survival (CSS) and recurrence-free interval (RFI) were examined. In the whole cohort, tumour size (P < 0.05) and microvessel density (P < 0.05) were associated with high p-S118 while increased micovessel density (P < 0.05), apoptosis (P < 0.05), general inflammatory infiltrate measured using the Klintrup–Makinen score (P < 0.05) and macrophage infiltrate (P < 0.05) were found to be associated with high p-S167. Only high p-S167 was associated with shorter CSS (P < 0.005) and shorter RFI in the whole cohort (P = 0.001) and separately in the luminal A (P < 0.05) and B tumours (P < 0.05). Conclusions: This study showed that both p-S118 and p-S167 were associated with several microenvironmental factors, including increased microvessel density. In particular, p-S167 was associated with reduced RFI and CSS in the whole cohort and RFI in luminal A and B tumours and could possibly be employed to predict response to kinase inhibitors

The use of automated quantitative analysis to evaluate epithelial-to-mesenchymal transition associated proteins in clear cell renal cell carcinoma.

BACKGROUND: Epithelial-to-mesenchymal transition (EMT) has recently been implicated in the initiation and progression of renal cell carcinoma (RCC). Some mRNA gene expression studies have suggested a link between the EMT phenotype and poorer clinical outcome from RCC. This study evaluated expression of EMT-associated proteins in RCC using in situ automated quantitative analysis immunofluorescence (AQUA) and compared expression levels with clinical outcome. METHODS/PRINCIPAL FINDINGS: Unsupervised hierarchical cluster analysis of pre-existing RCC gene expression array data (GSE16449) from 36 patients revealed the presence of an EMT transcriptional signature in RCC [E-cadherin high/SLUG low/SNAIL low]. As automated immunofluorescence technology is dependent on accurate definition of the tumour cells in which measurements take place is critical, extensive optimisation was carried out resulting in a novel pan-cadherin based tumour mask that distinguishes renal cancer cells from stromal components. 61 patients with ccRCC and clinical follow-up were subsequently assessed for expression of EMT-associated proteins (WT1, SNAIL, SLUG, E-cadherin and phospho-β-catenin) on tissue microarrays. Using Kaplan-Meier analysis both SLUG (p = 0.029) and SNAIL (p = 0.024) (log rank Mantel-Cox) were significantly associated with prolonged progression free survival (PFS). Using Cox regression univariate and multivariate analysis none of the biomarkers were significantly correlated with outcome. 14 of the 61 patients expressed the gene expression analysis predicted EMT-protein signature [E-cadherin high/SLUG low/SNAIL low], which was not found to be associated to PFS when measured at the protein level. A combination of high expression of SNAIL and low stage was able to stratify patients with greater significance (p = 0.001) then either variable alone (high SNAIL p = 0.024, low stage p = 0.029). CONCLUSIONS: AQUA has been shown to have the potential to identify EMT related protein targets in RCC allowing for stratification of patients into high and low risk groups, as well the ability to assess the association of reputed EMT signatures to progression of the disease

C35 overexpression defines subsets of human breast cancer and its immunoreceptor tyrosine-based activation motif represents a novel treatment target

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Evaluation of the dual mTOR / PI3K inhibitors Gedatolisib (PF-05212384) and PF-04691502 against ovarian cancer xenograft models

We are grateful to Wyeth/Pfizer (ONC-EU-150) and to the Scottish Funding Council (SRDG HR07005) for support of this study.This study investigated the antitumour effects of two dual mTOR/PI3K inhibitors, gedatolisib (WYE-129587/PKI-587/PF-05212384) and PF-04691502 against a panel of six human patient derived ovarian cancer xenograft models. Both dual mTOR/PI3K inhibitors demonstrated antitumour activity against all xenografts tested. The compounds produced tumour stasis during the treatment period and upon cessation of treatment, tumours re-grew. In several models, there was an initial rapid reduction of tumour volume over the first week of treatment before tumour stasis. No toxicity was observed during treatment. Biomarker studies were conducted in two xenograft models; phospho-S6 (Ser235/236) expression (as a readout of mTOR activity) was reduced over the treatment period in the responding xenograft but expression increased to control (no treatment) levels on cessation of treatment. Phospho-AKT (Ser473) expression (as a readout of PI3K) was inhibited by both drugs but less markedly so than phospho-S6 expression. Initial tumour volume reduction on treatment and regrowth rate after treatment cessation was associated with phospho-S6/total S6 expression ratio. Both drugs produced apoptosis but minimally influenced markers of proliferation (Ki67, phospho-histone H3). These results indicate that mTOR/PI3K inhibition can produce broad spectrum tumour growth stasis in ovarian cancer xenograft models during continuous chronic treatment and this is associated with apoptosis.Publisher PDFPeer reviewe

A Novel Method for Simulating Insulin Mediated GLUT4 Translocation

Glucose transport in humans is a vital process which is tightly regulated by the endocrine system. Specifically, the insulin hormone triggers a cascade of intracellular signals in target cells mediating the uptake of glucose. Insulin signaling triggers cellular relocalization of the glucose transporter protein GLUT4 to the cell surface, which is primarily responsible for regulated glucose import. Pathology associated with the disruption of this pathway can lead to metabolic disorders, such as type II diabetes mellitus, characterized by the failure of cells to appropriately uptake glucose from the blood. We describe a novel simulation tool of the insulin intracellular response, incorporating the latest findings regarding As160 and GEF interactions. The simulation tool differs from previous computational approaches which employ algebraic or differential equations; instead, the tool incorporates statistical variations of kinetic constants and initial molecular concentrations which more accurately mimic the intracellular environment. Using this approach, we successfully recapitulate observed in vitro insulin responses, plus the effects of Wortmannin- like inhibition of the pathway. The developed tool provides insight into transient changes in molecule concentrations throughout the insulin signaling pathway, and may be employed to identify or evaluate potentially critical components of this pathway, including those associated with insulin resistance. In the future, this highly tractable platform may be useful for simulating other complex cell signaling pathways