Andreas U. Lindner

Systems Analysis of BCL2 Protein Family Interactions Establishes a Model to Predict Responses to Chemotherapy

Apoptotic desensitization is a hallmark of cancer cells, but present knowledge of molecular systems controlling apoptosis has yet to provide significant prognostic insights. Here, we report findings from a systems study of the intrinsic pathway of apoptosis by BCL2 family proteins and clinical translation of its findings into a model with applications in colorectal cancer (CRC). By determining absolute protein quantifications in CRC cells and patient tumor samples, we found that BAK and BAX were expressed more highly than their antiapoptotic inhibitors. This counterintuitive finding suggested that sole inhibition of effector BAX and BAK could not be sufficient for systems stability in nonstressed cells. Assuming a model of direct effector activation by BH3-only proteins, we calculated that the amount of stress-induced BH3-only proteins required to activate mitochondrial apoptosis could predict individual death responses of CRC cells to 5-fluorouracil/oxaliplatin. Applying this model predictor to protein profiles in tumor and matched normal tissue samples from 26 patients with CRCs, we found that differences in protein quantities were sufficient to model the increased tumor sensitivity to chemotherapy compared with normal tissue. In addition, these differences were sufficient to differentiate clinical responders from nonresponders with high confidence. Applications of our model, termed DR_MOMP, were used to assess the impact of apoptosis-sensitizing drugs in lowering the necessary dose of state-of-the-art chemotherapy in individual patients. Together, our findings offer a ready clinical tool with the potential to tailor chemotherapy to individual patients.

Systems analysis of cancer cell heterogeneity in caspase-dependent apoptosis subsequent to mitochondrial outer membrane permeabilization.

Background: Computational systems models may allow understanding of progression and impairment of apoptosis based on quantitative protein profiles. Results: We found apoptosis to be impaired in some cell lines after MOMP, which can be understood by our systems model “APOPTO-CELL”. Conclusion: APOPTO-CELL helps to understand heterogeneity in apoptosis execution after MOMP. Significance: APOPTO-CELL may help to assess cancer-specific efficacy of chemotherapeutics that induce apoptosis. Deregulation of apoptosis is a hallmark of carcinogenesis. We here combine live cell imaging and systems modeling to investigate caspase-dependent apoptosis execution subsequent to mitochondrial outer membrane permeabilization (MOMP) in several cancer cell lines. We demonstrate that, although most cell lines that underwent MOMP also showed robust and fast activation of executioner caspases and apoptosis, the colorectal cancer cell lines LoVo and HCT-116 Smac−/−, similar to X-linked inhibitor of apoptosis protein (XIAP)-overexpressing HeLa (HeLa XIAPAdv) cells, only showed delayed and often no caspase activation, suggesting apoptosis impairment subsequent to MOMP. Employing APOPTO-CELL, a recently established model of apoptosis subsequent to MOMP, this impairment could be understood by studying the systemic interaction of five proteins that are present in the apoptosis pathway subsequent to MOMP. Using APOPTO-CELL as a tool to study detailed molecular mechanisms during apoptosis execution in individual cell lines, we demonstrate that caspase-9 was the most important regulator in DLD-1, HCT-116, and HeLa cells and identified additional cell line-specific co-regulators. Developing and applying a computational workflow for parameter screening, systems modeling identified that apoptosis execution kinetics are more robust against changes in reaction kinetics in HCT-116 and HeLa than in DLD-1 cells. Our systems modeling study is the first to draw attention to the variability in cell specific protein levels and reaction rates and to the emergent effects of such variability on the efficiency of apoptosis execution and on apoptosis impairment subsequent to MOMP.

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.

Systems modeling accurately predicts responses to genotoxic agents and their synergism with BCL-2 inhibitors in triple negative breast cancer cells.

Triple negative breast cancer (TNBC) is an aggressive form of breast cancer which accounts for 15–20% of this disease and is currently treated with genotoxic chemotherapy. The BCL2 (B-cell lymphoma 2) family of proteins controls the process of mitochondrial outer membrane permeabilization (MOMP), which is required for the activation of the mitochondrial apoptosis pathway in response to genotoxic agents. We previously developed a deterministic systems model of BCL2 protein interactions, DR_MOMP that calculates the sensitivity of cells to undergo mitochondrial apoptosis. Here we determined whether DR_MOMP predicts responses of TNBC cells to genotoxic agents and the re-sensitization of resistant cells by BCL2 inhibitors. Using absolute protein levels of BAX, BAK, BCL2, BCL(X)L and MCL1 as input for DR_MOMP, we found a strong correlation between model predictions and responses of a panel of TNBC cells to 24 and 48 h cisplatin (R2 = 0.96 and 0.95, respectively) and paclitaxel treatments (R2 = 0.94 and 0.95, respectively). This outperformed single protein correlations (best performer BCL(X)L with R2 of 0.69 and 0.50 for cisplatin and paclitaxel treatments, respectively) and BCL2 proteins ratio (R2 of 0.50 for cisplatin and 0.49 for paclitaxel). Next we performed synergy studies using the BCL2 selective antagonist Venetoclax /ABT199, the BCL(X)L selective antagonist WEHI-539, or the MCL1 selective antagonist A-1210477 in combination with cisplatin. In silico predictions by DR_MOMP revealed substantial differences in treatment responses of BCL(X)L, BCL2 or MCL1 inhibitors combinations with cisplatin that were successfully validated in cell lines. Our findings provide evidence that DR_MOMP predicts responses of TNBC cells to genotoxic therapy, and can aid in the choice of the optimal BCL2 protein antagonist for combination treatments of resistant cells.

Low cleaved caspase-7 levels indicate unfavourable outcome across all breast cancers

Elevated levels of the anti-apoptotic BCL2 protein associate with favourable outcome in breast cancer. We investigated whether executioner caspase activation downstream of mitochondrial apoptosis was associated with, or independent, of BCL2’s prognostic signature in breast cancer. Levels of pro- and anti-apoptotic BCL2 family proteins were quantified in triple negative breast cancer (TNBC) samples and utilised to calculate BCL2 profiles of 845 breast cancer patients. Biomarkers including single apoptosis proteins and network-enriched apoptosis system signatures were evaluated using uni- and multi-variate Cox-models. In both TNBC and non-TNBC breast cancer, the anti-apoptotic BCL2 protein was particularly abundant when compared to other solid tumours. High BCL2 protein levels were prognostic of favourable outcome across all breast cancers (HR 0.4, 95% CI 0.2–0.6, Wald p < 0.0001). Although BCL2 and cleaved caspase-7 levels were negatively correlated, levels of cleaved caspase-7 were also associated with favourable outcome (HR 0.4, 95% CI 0.3–0.7, Wald p = 0.001). A combination of low BCL2 and low cleaved caspase-7 protein levels was highly prognostic of unfavourable outcome across all breast cancers (HR 11.29, 95% CI 2.20–58.23, Wald p = 0.01). A combination of BCL2 and cleaved caspase-7 levels is a promising prognostic biomarker in breast cancer patients.Key messageBCL2 levels are elevated in breast cancer where they are marker of good prognosis.BCL2 and active caspase levels correlate negatively; yet, active caspases indicate good outcome.Low BCL2 and low caspase-7 are highly prognostic of unfavourable outcome across all breast cancers.BCL2 levels indicate molecular subtype and tumour proliferation status in breast cancer.

Erratum to: Calnexin, an ER stress-induced protein, is a prognostic marker and potential therapeutic target in colorectal cancer

© 2016 The Author(s). This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/ publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. Erratum to: J Transl Med (2016) 14:196 DOI 10.1186/s12967‐016‐0948‐z Unfortunately, the original version of this article [1] contained an error. The title was included incorrectly. The correct can be found here. The title has been corrected in the original article and is also included correctly in this erratum.

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 3557: System-based BCL2 family protein signatures as predictive biomarkers in triple-negative breast cancer

Breast cancer is a heterogeneous disease. More recently, the molecular basis for this heterogeneity has started to be analysed at the genomic, transcriptomic and proteomic level, allowing for the development of more personalized therapies. Cancer cells showing resistance to therapy frequently have an intrinsic deficiency in their ability to initiate or execute apoptosis [1]. The BCL2 (B-cell lymphoma 2) family of proteins controls the process of Mitochondrial Outer Membrane Permeabilization (MOMP), which is required for the activation of the mitochondrial apoptosis pathway [2]. We developed a deterministic systems model of BCL2 protein interactions, DR_MOMP that calculates the sensitivity of cells to undergo mitochondrial apoptosis [3]. Here we applied DR_MOMP in the context of triple negative breast cancer to determine whether this systems model can be used as a prognostic biomarker or patient stratification tool. To analyze the contribution of BCL2 proteins in modulating apoptosis in breast cancer we validated DR_MOMP in a panel of Triple Negative Breast Cancer (TNBC) cell lines. Using quantitative Western blotting we determined the absolute protein levels of pro-apoptotic BAX and BAK and anti-apoptotic BCL2, BCL(X)L and MCL1. We found a significant correlation between cell survival and BCL(X)L levels (ρ = 0.76) after Cisplatin/Paclitaxel treatment, but protein levels of BCL2, MCL-1, BAX and BAK did not correlate with cell survival. Using absolute protein levels as input for DR_MOMP, we found a strongly improved correlation between model predictions and cells’ responses to Cisplatin (ρ = 0.93) and Paclitaxel treatments (ρ = 0.97). Next we performed synergy studies using the selective BCL2 antagonist ABT-199 or the selective BCL(X)L antagonist WEHI-539 in combination with cisplatin. We observed differential effects of BCL(X)L and BCL-2 inhibition in individual cell lines that were remodelled by DR_MOMP. Modelling also suggested additional effects of BCL2 antagonists independent of MOMP regulation. BCL2 profiling was also performed in primary tumours of 16 TBNC patients in order to predict the patients’ risk prospectively. DR_MOMP predicted a high risk in 37.5% of patients which is in line with 5-year recurrence rates in the literature [4]. Our findings provide evidence that DR_MOMP can be deployed to predict the response of TNBC breast cancer to genotoxic therapy, and can aid in the choice of the optimal BCL2 antagonists. This work is supported by Irish Cancer Society Collaborative Cancer Research Centre BREAST-PREDICT [1] Pillai et al. Am J Cancer Res. 2013 Jun 20;3(3):312-22. PubMed PMID: 23841030. [2] Lee et al. BMC Cancer. 2007 Apr 12;7:63. PubMed PMID: 17430582. [3] Lindner et al. Cancer Res. 2013 Jan 15;73(2):519-28. PubMed PMID: 23329644 [4] Haffty et al. J Clin Oncol. 2006 Dec 20;24(36):5652-7. PubMed PMID: 17116942 Citation Format: Federico Lucantoni, Andreas U. Lindner, Norma O’Donovan, Damir Vareslija, Lance Hudson, Arnold DK Hill, Michael Kerin, Roisin Dwyer, Leonie Young, Jochen HM Prehn. System-based BCL2 family protein signatures as predictive biomarkers in triple-negative breast cancer. [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 3557.

Combining systems biology models of apoptosis provides superior predictions of the responsiveness of melanoma cells to cell death inducing drugs

Background Key to the clinical management of melanoma is the development of new diagnostic tools that predict individual patient prognosis and select from potential treatments those which may be effective. Identifying individual biomarkers in tumour cells to predict susceptibility to apoptotic cell death has thus far been largely unsuccessful, as apoptosis pathways show a high degree of signalling redundancy.