Boolean network-based model of the Bcl-2 family mediated MOMP regulation

Mitochondrial outer membrane permeabilization (MOMP) is one of the most important points, in majority of apoptotic signaling cascades. Decision mechanism controlling whether the MOMP occurs or not, is formed by an interplay between members of the Bcl-2 family. To understand the role of individual members of this family within the MOMP regulation, we constructed a boolean network-based mathematical model of interactions between the Bcl-2 proteins. Results of computational simulations reveal the existence of the potentially malign configurations of activities of the Bcl-2 proteins, blocking the occurrence of MOMP, independently of the incoming stimuli. Our results suggest role of the antiapoptotic protein Mcl-1 in relation to these configurations. We demonstrate here, the importance of the Bid and Bim according to activation of effectors Bax and Bak, and the irreversibility of this activation. The model further shows the distinct requirements for effectors activation, where the antiapoptic protein Bcl-w is seemingly a key factor preventing the Bax activation. We believe that this work may help to describe the functioning of the Bcl-2 regulation of MOMP better, and hopefully provide some contribution regarding the anti-cancer drug development research

An HLA-G/SPAG9/STAT3 axis promotes brain metastases

Brain metastases (BM) are the most common brain neoplasm in adults. Current BM therapies still offer limited efficacy and reduced survival outcomes, emphasizing the need for a better understanding of the disease. Herein, we analyzed the transcriptional profile of brain metastasis initiating cells (BMICs) at two distinct stages of the brain metastatic cascade-the "premetastatic" or early stage when they first colonize the brain and the established macrometastatic stage. RNA sequencing was used to obtain the transcriptional profiles of premetastatic and macrometastatic (non-premetastatic) lung, breast, and melanoma BMICs. We identified that lung, breast, and melanoma premetastatic BMICs share a common transcriptomic signature that is distinct from their non-premetastatic counterparts. Importantly, we show that premetastatic BMICs exhibit increased expression of HLA-G, which we further demonstrate functions in an HLA-G/SPAG9/STAT3 axis to promote the establishment of brain metastatic lesions. Our findings suggest that unraveling the molecular landscape of premetastatic BMICs allows for the identification of clinically relevant targets that can possibly inform the development of preventive and/or more efficacious BM therapies

Failed immune responses across multiple pathologies share pan-tumor and circulating lymphocytic targets

Tumor-infiltrating lymphocytes (TILs) are widely associated with positive outcomes, yet carry key indicators of a systemic failed immune response against unresolved cancer. Cancer immunotherapies can reverse their tolerance phenotypes while preserving tumor reactivity and neoantigen specificity shared with circulating immune cells. We performed comprehensive transcriptomic analyses to identify gene signatures common to circulating and TILs in the context of clear cell renal cell carcinoma. Modulated genes also associated with disease outcome were validated in other cancer types. Through comprehensive bioinformatics analyses, we identified practical diagnostic markers and actionable targets of the failed immune response. On circulating lymphocytes, 3 genes (LEF1, FASLG, and MMP9) could efficiently stratify patients from healthy control donors. From their associations with resistance to cancer immunotherapies and microbial infections, we uncovered not only pan-cancer, but pan-pathology, failed immune response profiles. A prominent lymphocytic matrix metallopeptidase cell migration pathway is central to a panoply of diseases and tumor immunogenicity, correlates with multi-cancer recurrence, and identifies a feasible noninvasive approach to pan-pathology diagnoses. The differentially expressed genes we have identified warrant future investigation into the development of their potential in noninvasive precision diagnostics and precision pan-disease immunotherapeutics. - 2019, American Society for Clinical Investigation.We thank all study participants and patients; The Cancer Genome Atlas; Mathieu Latour and Roula Albadine and supporting staff of the CHUM pathology department; Manon de Ladurantaye and Anne-Marie Mes-Masson from the CRCHUM for RNA quality profiling, Geneviève Cormier and Fred Saad from the CRCHUM for drawing blood from control donors; Gilles Corbeil of the CRCHUM genomics department for RNA quality testing and microarray profiling; Francois Harvey of the CRCHUM bioinformatics department; Peter Graf and Patrick Sabourin from Affymetrix for providing reagents and technical assistance; Zeeshan Farroq and Ofir Goldberger from Fluidigm; Erika Diaz from StemCell; Andrew Mouland from McGill University; Simon Turcotte from University of Montreal; and Sascha Ring from Biostars for their advice. This work was partially performed at the Institut du Cancer de Montréal CRCHUM and University of Montreal, in Montreal, Quebec, Canada. This work was supported by a Canadian Cancer Society Research Institute grant (CCSRI) (702036, to RL and IJ) and a Biomedical Research Grant from the Kidney Foundation of Canada (KFOC130019 to RL). RL is supported by the Quebec Cell, Tissue and Gene Therapy Network—ThéCell (a thematic network supported by the Fonds de recherche du Québec–Santé [FRQS]), the FRQS, and the Immunotherapy Network (iTNT) from the Terry Fox Research Institute (TFRI), A. Monette is supported by Mitacs, Merck, l’Institut du cancer de Montréal (ICM), the Society for Immunotherapy of Cancer, and the Lady Davis Institute for Medical Research. NAB is supported by the FRQS post-doctoral award and Qatar University. JBL is supported by l’Institut du Cancer de Montréal. JPR holds the Louis Lowenstein Chair, McGill University. DEK is supported by an FRQS Research Scholar Award (grant 31035), CIHR 377124, NHLBI RO1-HL-092565, and the Canada Foundation for Innovation (CFI) (grant 31756). IJ and computational analysis were supported by the Canada Research Chair Program (CRC) (grant 225404), Ontario Research Fund (grant 34876), the Natural Sciences Research Council (NSERC) (grant 203475), the CFI (grants 203373 and 30865), the Krembil Foundation, and IBM.Scopu

The mathematical model of the Bcl-2 family mediated MOMP regulation can perform a non-trivial pattern recognition.

Interactions between individual members of the B-cell lymphoma 2 (Bcl-2) family of proteins form a regulatory network governing mitochondrial outer membrane permeabilization (MOMP). Bcl-2 family initiated MOMP causes release of the inter-membrane pro-apoptotic proteins to cytosol and creates a cytosolic environment suitable for the executionary phase of apoptosis. We designed the mathematical model of this regulatory network where the synthesis rates of the Bcl-2 family members served as the independent inputs. Using computational simulations, we have then analyzed the response of the model to up-/downregulation of the Bcl-2 proteins. Under several assumptions, and using estimated reaction parameters, a non-linear stimulus-response emerged, whose characteristics are associated with bistability and switch-like behavior. Interestingly, using the principal component analysis (PCA) we have shown that the given model of the Bcl-2 family interactions classifies the random combinations of inputs into two distinct classes, and responds to these by one of the two qualitatively distinct outputs. As we showed, the emergence of this behavior requires specific organization of the interactions between particular Bcl-2 proteins

Steady-state concentration of the MAC () is plotted as a function of the production rate of tBid (kptBid).

<p> is increasing with increasing value of . The remains at very low levels (pro-survival – the blue solid curve), until the production rate exceeds the threshold (right vertical dashed line). Exceeding the threshold value causes sudden increase of the (onset of MOMP – red solid curve). The subsequent decrease of the production of tBid cause only slow decrease of , until the another threshold is crossed (left vertical dashed line). Then the suddenly drops back to very low levels. Vertical dashed lines are enclosing the bistable region. Within this region system can persist in one of the two stable steady-states (solid curves), which are separated by unstable steady-states (dashed curve).</p

List of reactions of the model of the Bcl–2 family of proteins.

<p>Reactions no. 46–61 denote production of the correspondent species, while the reaction no. 62 denotes degradation of all the species of the model.</p

List of parameters of the model of the Bcl–2 family of proteins.

<p>Default values of parameters are listed using model-specific units (left column) as appear in the PySCes model definition file and using common units (right column). Values were recalculated assuming 1 nM = 600 molecules per abstract reaction volume (similarly to work of Eissing et al. <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0081861#pone.0081861-Eissing1" target="_blank">[49]</a>). Units differ between parameters as these corresponds to reactions of different order. Default values of the production rates were calculated as respective fractions of production rates which were estimated from references and which apply to respective Bcl-2 protein classes.</p

Point-biserial correlation coefficients () as the measure of correlation between the values of the production rates and the model's response.

<p>Point-biserial correlation coefficients () as the measure of correlation between the values of the production rates and the model's response.</p

Steady-state concentration of the MAC is plotted as a function of the production rate of Noxa.

<p>Hyperbolic curve indicates a response sensitivity to even a small levels of stimulation.</p