Manuela Salvucci

BCL-2 system analysis identifies high-risk colorectal cancer patients

Objective The mitochondrial apoptosis pathway is controlled by an interaction of multiple BCL-2 family proteins, and plays a key role in tumour progression and therapy responses. We assessed the prognostic potential of an experimentally validated, mathematical model of BCL-2 protein interactions (DR_MOMP) in patients with stage III colorectal cancer (CRC). Design Absolute protein levels of BCL-2 family proteins were determined in primary CRC tumours collected from n=128 resected and chemotherapy-treated patients with stage III CRC. We applied DR_MOMP to categorise patients as high or low risk based on model outputs, and compared model outputs with known prognostic factors (T-stage, N-stage, lymphovascular invasion). DR_MOMP signatures were validated on protein of n=156 patients with CRC from the Cancer Genome Atlas (TCGA) project. Results High-risk stage III patients identified by DR_MOMP had an approximately fivefold increased risk of death compared with patients identified as low risk (HR 5.2, 95% CI 1.4 to 17.9, p=0.02). The DR_MOMP signature ranked highest among all molecular and pathological features analysed. The prognostic signature was validated in the TCGA colon adenocarcinoma (COAD) cohort (HR 4.2, 95% CI 1.1 to 15.6, p=0.04). DR_MOMP also further stratified patients identified by supervised gene expression risk scores into low-risk and high-risk categories. BCL-2-dependent signalling critically contributed to treatment responses in consensus molecular subtypes 1 and 3, linking for the first time specific molecular subtypes to apoptosis signalling. Conclusions DR_MOMP delivers a system-based biomarker with significant potential as a prognostic tool for stage III CRC that significantly improves established histopathological risk factors.

A Stepwise Integrated Approach to Personalized Risk Predictions in Stage III Colorectal Cancer

Purpose: Apoptosis is essential for chemotherapy responses. In this discovery and validation study, we evaluated the suitability of a mathematical model of apoptosis execution (APOPTO-CELL) as a stand-alone signature and as a constituent of further refined prognostic stratification tools. Experimental Design: Apoptosis competency of primary tumor samples from patients with stage III colorectal cancer (n = 120) was calculated by APOPTO-CELL from measured protein concentrations of Procaspase-3, Procaspase-9, SMAC, and XIAP. An enriched APOPTO-CELL signature (APOPTO-CELL-PC3) was synthesized to capture apoptosome-independent effects of Caspase-3. Furthermore, a machine learning Random Forest approach was applied to APOPTO-CELL-PC3 and available molecular and clinicopathologic data to identify a further enhanced signature. Association of the signature with prognosis was evaluated in an independent colon adenocarcinoma cohort (TCGA COAD, n = 136). Results: We identified 3 prognostic biomarkers (P = 0.04, P = 0.006, and P = 0.0004 for APOPTO-CELL, APOPTO-CELL-PC3, and Random Forest signatures, respectively) with increasing stratification accuracy for patients with stage III colorectal cancer. The APOPTO-CELL-PC3 signature ranked highest among all features. The prognostic value of the signatures was independently validated in stage III TCGA COAD patients (P = 0.01, P = 0.04, and P = 0.02 for APOPTO-CELL, APOPTO-CELL-PC3, and Random Forest signatures, respectively). The signatures provided further stratification for patients with CMS1-3 molecular subtype. Conclusions: The integration of a systems-biology–based biomarker for apoptosis competency with machine learning approaches is an appealing and innovative strategy toward refined patient stratification. The prognostic value of apoptosis competency is independent of other available clinicopathologic and molecular factors, with tangible potential of being introduced in the clinical management of patients with stage III colorectal cancer. Clin Cancer Res; 23(5); 1200–12. ©2016 AACR.

Guidelines on experimental methods to assess mitochondrial dysfunction in cellular models of neurodegenerative diseases

Neurodegenerative diseases are a spectrum of chronic, debilitating disorders characterised by the progressive degeneration and death of neurons. Mitochondrial dysfunction has been implicated in most neurodegenerative diseases, but in many instances it is unclear whether such dysfunction is a cause or an effect of the underlying pathology, and whether it represents a viable therapeutic target. It is therefore imperative to utilise and optimise cellular models and experimental techniques appropriate to determine the contribution of mitochondrial dysfunction to neurodegenerative disease phenotypes. In this consensus article, we collate details on and discuss pitfalls of existing experimental approaches to assess mitochondrial function in in vitro cellular models of neurodegenerative diseases, including specific protocols for the measurement of oxygen consumption rate in primary neuron cultures, and single-neuron, time-lapse fluorescence imaging of the mitochondrial membrane potential and mitochondrial NAD(P)H. As part of the Cellular Bioenergetics of Neurodegenerative Diseases (CeBioND) consortium (www.cebiond.org), we are performing cross-disease analyses to identify common and distinct molecular mechanisms involved in mitochondrial bioenergetic dysfunction in cellular models of Alzheimer’s, Parkinson’s, and Huntington’s diseases. Here we provide detailed guidelines and protocols as standardised across the five collaborating laboratories of the CeBioND consortium, with additional contributions from other experts in the field.

Patient-derived glioblastoma cells show significant heterogeneity in treatment responses to the inhibitor-of-apoptosis-protein antagonist birinapant.

Background:Resistance to temozolomide (TMZ) greatly limits chemotherapeutic effectiveness in glioblastoma (GBM). Here we analysed the ability of the Inhibitor-of-apoptosis-protein (IAP) antagonist birinapant to enhance treatment responses to TMZ in both commercially available and patient-derived GBM cells.Methods:Responses to TMZ and birinapant were analysed in a panel of commercial and patient-derived GBM cell lines using colorimetric viability assays, flow cytometry, morphological analysis and protein expression profiling of pro- and antiapoptotic proteins. Responses in vivo were analysed in an orthotopic xenograft GBM model.Results:Single-agent treatment experiments categorised GBM cells into TMZ-sensitive cells, birinapant-sensitive cells, and cells that were insensitive to either treatment. Combination treatment allowed sensitisation to therapy in only a subset of resistant GBM cells. Cell death analysis identified three principal response patterns: Type A cells that readily activated caspase-8 and cell death in response to TMZ while addition of birinapant further sensitised the cells to TMZ-induced cell death; Type B cells that readily activated caspase-8 and cell death in response to birinapant but did not show further sensitisation with TMZ; and Type C cells that showed no significant cell death or moderately enhanced cell death in the combined treatment paradigm. Furthermore, in vivo, a Type C patient-derived cell line that was TMZ-insensitive in vitro and showed a strong sensitivity to TMZ and TMZ plus birinapant treatments.Conclusions:Our results demonstrate remarkable differences in responses of patient-derived GBM cells to birinapant single and combination treatments, and suggest that therapeutic responses in vivo may be greatly affected by the tumour microenvironment.

Simulating and predicting cellular and in vivo responses of colon cancer to combined treatment with chemotherapy and IAP antagonist Birinapant/TL32711

Apoptosis resistance contributes to treatment failure in colorectal cancer (CRC). New treatments that reinstate apoptosis competency have potential to improve patient outcome but require predictive biomarkers to target them to responsive patient populations. Inhibitor of apoptosis proteins (IAPs) suppress apoptosis, contributing to drug resistance; IAP antagonists such as TL32711 have therefore been developed. We developed a systems biology approach for predicting response of CRC cells to chemotherapy and TL32711 combinations in vitro and in vivo. CRC cells responded poorly to TL32711 monotherapy in vitro; however, co-treatment with 5-fluorouracil (5-FU) and oxaliplatin enhanced TL32711-induced apoptosis. Notably, cells from genetically identical populations responded highly heterogeneously, with caspases being activated both upstream and downstream of mitochondrial outer membrane permeabilisation (MOMP). These data, combined with quantities of key apoptosis regulators were sufficient to replicate in vitro cell death profiles by mathematical modelling. In vivo, apoptosis protein expression was significantly altered, and mathematical modelling for these conditions predicted higher apoptosis resistance that could nevertheless be overcome by combination of chemotherapy and TL32711. Subsequent experimental observations agreed with these predictions, and the observed effects on tumour growth inhibition correlated robustly with apoptosis competency. We therefore obtained insights into intracellular signal transduction kinetics and their population-based heterogeneities for chemotherapy/TL32711 combinations and provide proof-of-concept that mathematical modelling of apoptosis competency can simulate and predict responsiveness in vivo. Being able to predict response to IAP antagonist-based treatments on the background of cell-to-cell heterogeneities in the future might assist in improving treatment stratification approaches for these emerging apoptosis-targeting agents.

The BAX/BAK-like protein BOK is a prognostic marker in colorectal cancer

The intrinsic or mitochondrial apoptosis pathway is controlled by the interaction of antiapoptotic and pro-apoptotic members of the BCL-2 protein family. Activation of this death pathway plays a crucial role in cancer progression and chemotherapy responses. The BCL-2-related ovarian killer (BOK) possesses three BCL-2 homology domains and has been proposed to act in a similar pro-apoptotic pathway as the pro-apoptotic proteins BAX and BAK. In this study, we showed that stage II and III colorectal cancer patients possessed decreased levels of BOK protein in their tumours compared to matched normal tissue. BOK protein levels in tumours were also prognostic of clinical outcome but increased BOK protein levels surprisingly associated with earlier disease recurrence and reduced overall survival. We found no significant association of BOK protein tumour levels with ER stress markers GRP78 or GRP94 or with cleaved caspase-3. In contrast, BOK protein levels correlated with Calreticulin. These data indicate BOK as a prognostic marker in colorectal cancer and suggest that different activities of BOK may contribute to cancer progression and prognosis.

Abstract 4924: Retrospective evaluation of a system model of the BCL2 family of proteins as a predictive and prognostic biomarker for the clinical outcome of stage II-IV colorectal cancer patients

Proceedings: AACR 107th Annual Meeting 2016; April 16-20, 2016; New Orleans, LA With 1.4 million new cases every year, colorectal cancer (CRC) is the fourth most common cancer worldwide [Globocan 2012, WHO]. Despite therapeutic advances and improvements in overall care, TNM staging remains the best prognostic indicator for CRC patients’ clinical outcomes and is pivotal for deciding on use of adjuvant chemotherapy after resection of the tumour. Adjuvant chemotherapy is not recommended for many stage II patients and mostly high-risk patients receive chemotherapy. However, there is a lack of robust biomarkers for identifying patient response to chemotherapy, recurrence and mortality risk. We developed a system model of the BCL2 family of proteins (DR\_MOMP) to assess the sensitivity of cells to genotoxic stress and to induce apoptosis triggered by chemotherapy. It calculates the stress dose required to induce mitochondrial outer membrane permeabilization (MOMP) based on absolute protein levels and the interaction of pro- and anti-apoptotic BCL2 family proteins. Cells predicted to require a high stress dose showed decreased cell death rates after being exposed to 5FU and Oxaliplatin. Profiles of BAK, BAX, BCL2, BCL(X)L and MCL1 were determined by Reverse Phase Protein Array (RPPA) technology in FFPE primary tumours collected from two distinct cohorts: stage III CRC patients who underwent adjuvant 5FU-based chemotherapy (n = 128), and stage II CRC patients from a completed clinical trial with patients randomised to adjuvant 5FU-based chemotherapy or observation only (n = 138). Protein profiles were inputted into DR\_MOMP to determine chemotherapy sensitivity and to classify patients into high- or low risk categories. Findings were validated on the TCGA COAD cohort using both protein (RPPA) and mRNA (SeqV2 RSEM) expression data. Stage II patients classified as high-risk by DR\_MOMP and randomised to observation only had approximately 2-fold increased risk of death from CRC compared to those classified as low-risk or received chemotherapy (HR 2.4; 95% CI 1.2-4.8; p-value = 0.0199). Among stage III patients treated with FOLFOX, those classified as high- versus low-risk had a more than 10-fold increased risk of death from CRC (HR 10.6; 95% CI 2.4-46.3; p-value < 0.0001). We validated this finding in 261 stage II-IV patients of the TCGA COAD cohort (HR 10.6; 95% CI 1.2-12.5; p-value = 0.0125). DR\_MOMP predicted mortality risk independent of TNM staging and KRAS mutation status. Our system delivers a novel predictive and prognostic biomarker that could be combined with TNM staging when assessing initial risk and subsequent clinical management of CRC patients. Citation Format: Andreas U. Lindner, Manuela Salvucci, Mattia Cremona, Naser Monsefi, Sarah Curry, Clare Morgan, Alexa Resler, Robert O’Byrne, Orna Bacon, Michael Stuehler, Lorna Flanagan, Richard Wilson, Patrick G. Johnston, Manuel Salto-Tellez, Sophie Camilleri-Broet, Deborah A. McNamara, Bryan T. Hennessy, Elaine W. Kay, Pierre Laurent-Puig, Sandra Van Schaeybroeck, Jochen H.M. Prehn. Retrospective evaluation of a system model of the BCL2 family of proteins as a predictive and prognostic biomarker for the clinical outcome of stage II-IV colorectal cancer patients. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 4924.

Abstract 1012: Systems analysis of colon cancer cell metabolism rewired by p53 and KRAS mutations

Introduction. Somatic mutations in proto-oncogenes and tumour-suppressor genes contribute to rewire the already deregulated metabolic network in cancer cells, resulting in uncontrolled proliferation and oncogenesis. In this study, we set out to establish a dynamic mathematical model of bioenergetics and to exploit it to explore the multifaceted cross-talk between bioenergetics, somatic gene mutations in KRAS and p53, and cell proliferation and survival. Model Development. We have developed an ordinary differential equations-based model of central carbon metabolism in cancer cells which includes glycolysis, pentose phosphate pathway, citric acid cycle and respiratory chain, based on our previous work and published models. The model describes how nutrients (glucose, glutamine, lactate, pyruvate, serine and glycine) from the extracellular micro-environment affect bioenergetics parameters. The resulting model predictions are linked to cell proliferation via a heuristic function. Enzymatic activities regulated by p53 and KRAS mutations were obtained by mining publically available datasets and their regulation by the mutational status was modelled by adapting the corresponding kinetic parameters. To estimate the kinetic parameters, model simulation outputs were fitted to a portfolio of experimental data both generated de novo in house and gathered from the literature in HCT-116 colon cancer cells. Experiments were performed on parental HCT-116 (p53 competent; harbouring a KRAS mutation on exon 2 of codon G13) and three derived mutant cell lines covering all four combinations of p53 and KRAS mutational status to isolate their relative and joint effect on bioenergetics signatures. HCT-116-derived cell lines included: p53 proficient cells with the KRAS allelic mutation silenced by homologous recombination in the presence or absence of p53 knockout by lentiviral shRNA. Results. The model was calibrated against ATP concentrations measured via single-cell microscopy (ATeam probe and TMRM dye) following pharmacological inhibition of respiratory chain complexes (rotenone, sodium azide and oligomycin) as a function of nutrients availability (glucose, lactate, pyruvate). Modelling results revealed that p53 and KRAS mutations drive a shift in metabolic signatures and L-lactate emerged as a pivotal metabolite to stratify the different phenotypes. Systems analysis revealed that in KRAS mutated cells p53 deficiency leads to an increase in glucose uptake and flux through the pentose phosphate pathway and a decrease in lactate production. Indeed, p53 deficient HCT-116 cells showed a decrease in extracellular lactate with respect to p53 proficient cells in validation experiments. Conclusions. The computational model developed can be used to benchmark mechanistic hypotheses by which tumour suppressors and/or oncogenic mutations rewire metabolism and to identify putative targets for therapeutic intervention. Citation Format: Manuela Salvucci, Robert O’Byrne, Natalia Niewidok, Sean Kilbride, Caoimhin G. Concannon, Heiko Dussmann, Heinrich H. Huber, Jochen HM Prehn. Systems analysis of colon cancer cell metabolism rewired by p53 and KRAS mutations. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 1012.