Integrative Systems Biology Approach Research Articles

Integrative Multiomics in the Lung Reveals a Protective Role of Asporin in Pulmonary Arterial Hypertension.

Integrative multiomics can elucidate pulmonary arterial hypertension (PAH) pathobiology, but procuring human PAH lung samples is rare. We leveraged transcriptomic profiling and deep phenotyping of the largest multicenter PAH lung biobank to date (96 disease and 52 control) by integration with clinicopathologic data, genome-wide association studies, Bayesian regulatory networks, single-cell transcriptomics, and pharmacotranscriptomics. We identified 2 potentially protective gene network modules associated with vascular cells, and we validated ASPN, coding for asporin, as a key hub gene that is upregulated as a compensatory response to counteract PAH. We found that asporin is upregulated in lungs and plasma of multiple independent PAH cohorts and correlates with reduced PAH severity. We show that asporin inhibits proliferation and transforming growth factor-β/phosphorylated SMAD2/3 signaling in pulmonary artery smooth muscle cells from PAH lungs. We demonstrate in Sugen-hypoxia rats that ASPN knockdown exacerbated PAH and recombinant asporin attenuated PAH. Our integrative systems biology approach to dissect the PAH lung transcriptome uncovered asporin as a novel protective target with therapeutic potential in PAH.

Dissecting the lung transcriptome of pulmonary fibrosis-associated pulmonary hypertension.

Integrative multiomics can help elucidate the pathophysiology of pulmonary fibrosis (PF)-associated pulmonary hypertension (PH) (PF-PH). Weighted gene coexpression network analysis (WGCNA) was performed on a transcriptomic dataset of explanted lung tissue from 116 patients with PF. Patients were stratified by pulmonary vascular resistance (PVR), and differential gene expression analysis was conducted. Gene modules were correlated with hemodynamics at the time of transplantation and tested for enrichment in the lung transcriptomics signature of an independent pulmonary arterial hypertension (PAH) cohort. We found 1,250 differentially expressed genes between high and low PVR groups. WGCNA identified that black and yellowgreen modules negatively correlated with PVR, whereas the tan and darkgrey modules are positively correlated with PVR in PF-PH. In addition, the tan module showed the strongest enrichment for an independent PAH gene signature, suggesting shared gene expression patterns between PAH and PF-PH. Pharmacotranscriptomic analysis using the Connectivity Map implicated the tan and darkgrey modules as potentially pathogenic in PF-PH, given their combined module signature demonstrated a high negative connectivity score for treprostinil, a medication used in the treatment of PF-PH, and a high positive connectivity score for bone morphogenetic protein (BMP) loss of function. Pathway enrichment analysis revealed that inflammatory pathways and oxidative phosphorylation were downregulated, whereas epithelial-mesenchymal transition was upregulated in modules associated with increased PVR. Our integrative systems biology approach to the lung transcriptome of PF with and without PH identified several PH-associated coexpression modules and gene targets with shared molecular features with PAH warranting further investigation to uncover potential new therapies for PF-PH.NEW & NOTEWORTHY An integrative systems biology approach that included transcriptomic analysis of explanted lung tissue from patients with pulmonary fibrosis (PF) with and without pulmonary hypertension (PH) undergoing lung transplantation, combined with hemodynamic correlation and pharmacotranscriptomics, identified modules of genes associated with pulmonary vascular disease severity. Comparison with an independent pulmonary arterial hypertension (PAH) dataset identified shared gene expression patterns between PAH and PF-PH.

Discovery of a Therapeutic Agent for Glioblastoma Using a Systems Biology-Based Drug Repositioning Approach.

Glioblastoma (GBM), a highly malignant tumour of the central nervous system, presents with a dire prognosis and low survival rates. The heterogeneous and recurrent nature of GBM renders current treatments relatively ineffective. In our study, we utilized an integrative systems biology approach to uncover the molecular mechanisms driving GBM progression and identify viable therapeutic drug targets for developing more effective GBM treatment strategies. Our integrative analysis revealed an elevated expression of CHST2 in GBM tumours, designating it as an unfavourable prognostic gene in GBM, as supported by data from two independent GBM cohorts. Further, we pinpointed WZ-4002 as a potential drug candidate to modulate CHST2 through computational drug repositioning. WZ-4002 directly targeted EGFR (ERBB1) and ERBB2, affecting their dimerization and influencing the activity of adjacent genes, including CHST2. We validated our findings by treating U-138 MG cells with WZ-4002, observing a decrease in CHST2 protein levels and a reduction in cell viability. In summary, our research suggests that the WZ-4002 drug candidate may effectively modulate CHST2 and adjacent genes, offering a promising avenue for developing efficient treatment strategies for GBM patients.

Abstract 450: GCN2 protects cancer cells from hypertranslation and metabolic crisis

Abstract It is widely assumed that cancer cells rely on high levels of protein synthesis to support growth and proliferation. However, protein synthesis, including ribosome biogenesis, is a highly resource- and energy-demanding process that needs to be coordinated with protein degradation and metabolic programs. GCN2 is an evolutionarily conserved kinase that is primarily activated by uncharged tRNAs when amino acid levels drop and activates the Integrated Stress Response (ISR), which encompasses a global reduction in translation and increased amino acid uptake and generation. GCN2 has been shown to support cancer cell survival under conditions of nutrient scarcity. Here, we used an integrated systems biology approach to delineate the multifaceted role of GCN2 in cancer cells that do not suffer from nutrient shortages. We carried out a broad array of multiomic analyses (RNA-seq, TMT-labelling based proteomics, Ribo-seq, LC-MS metabolomics) of melanoma cells in which GCN2 was inhibited (GCN2iB) or genetically depleted (constitutive and inducible shRNA) in cell culture and in vivo in murine xenografts, supplemented by puromycinylation-based quantification of global protein synthesis. GCN2 inhibition in A375 cells triggered a transcriptome and proteome response that was dominated by the induction of processes linked to protein and ribosome synthesis while suppressing metabolic pathways such as glycolysis and the proteasome. We confirmed these observations in vivo via RNA-seq of tumor samples from mice xenografted with A375 cells in which GCN2 was knocked down by induced shRNA expression and from xenografted mice that were treated orally with GCN2iB. Ribo-seq further demonstrated that, upon GCN2 inhibition, A375 cells expand their translational machinery. Notably, we identified 50 ribosomal genes that were translated at higher rate in GCN2-inhibited cells and whose expression was regulated exclusively at the translational level. GCN2 inhibition/depletion also resulted in an approximately 1.8-fold increase in global protein synthesis and altered the druggable proteome. Moreover, metabolite profiling of GCN2iB-treated cells revealed a loss of metabolic homeostasis including substantial alterations in glycolysis and both amino acid and lipid metabolism. In addition, we observed a significant decrease in ATP levels despite increased translation of mitochondrial ETC complex proteins. Proteomic and translatomic analyses revealed a failure of cells to increase proteasomal subunits and to maintain the production of ECM proteins. Last, but not least, we did not observe a role of GCN2 in preventing or resolving ribosome collisions. Taken together, our findings reveal GCN2 as a master regulator of translation in cancer cells that do not suffer from nutrient scarcity that keeps protein synthesis in check to maintain metabolic homeostasis. Citation Format: Monica Roman-Trufero, Istvan T. Kleijn, Kevin Blighe, Paula Saavedra-Garcia, Jinglin Zhou, Abigail Gaffar, Marilena Christoforou, Mariia Yuneva, Audrey M. Michel, Glenn R. Masson, Vahid Shahrezaei, Holger W. Auner. GCN2 protects cancer cells from hypertranslation and metabolic crisis [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 450.

Prediction of Essential Proteins of Klebsiella pneumoniae using Integrative Bioinformatics and Systems Biology Approach: Unveiling New Avenues for Drug Discovery.

Klebsiella pneumoniae is an opportunistic multidrug-resistant bacterial pathogen responsible for various health care-associated infections. The prediction of proteins that are essential for the survival of bacterial pathogens can greatly facilitate the drug development and discovery pipeline toward target identification. To this end, the present study reports a comprehensive computational approach integrating bioinformatics and systems biology-based methods to identify essential proteins of K. pneumoniae involved in vital processes. From the proteome of this pathogen, we predicted a total of 854 essential proteins based on sequence, protein-protein interaction (PPI) and genome-scale metabolic model methods. These predicted essential proteins are involved in vital processes for cellular regulation such as translation, metabolism, and biosynthesis of essential factors, among others. Cluster analysis of the PPI network revealed the highly connected modules involved in the basic functionality of the organism. Further, the predicted consensus set of essential proteins of K. pneumoniae was evaluated by comparing them with existing resources (NetGenes and PATHOgenex) and literature. The findings of this study offer guidance toward understanding cell functionality, thereby facilitating the understanding of pathogen systems and providing a way forward to shortlist potential therapeutic candidates for developing novel antimicrobial agents against K. pneumoniae. In addition, the research strategy presented herein is a fusion of sequence and systems biology-based approaches that offers prospects as a model to predict essential proteins for other pathogens.

Abstract IA019: Multiscale systems approach to target tumor ecosystem responses for therapeutic benefit

Abstract Breast tumors arise and progress via processes that involve intrinsic deregulation of epithelial cells and that also alter the composition and function of associated stromal and immune cells. Together, these tumor-intrinsic and microenvironmental changes enable malignant epithelial cells in the tumor to acquire key cancer hallmarks, including proliferation, migration, immune evasion and further evolution. The resulting collection of cancer and stromal cells comprise a complex, adaptive tumor ecosystem. Long-term therapeutic success will require that drugs attack malignant cells, favorably activate the immune system, and create a tumor microenvironment that does not support tumor (re)growth. Creating a process for treatment selection will require an integrated systems biology approach to develop, test and refine a robust computational framework that takes into account the states, signaling relationships, and spatial organization that determine the emergent properties inherent in complex interacting systems. Toward this goal, we have developed a coordinated experimental-computational approach designed to enable identification of effective treatment strategies. To examine therapeutic responses of diverse aspects of the tumor ecosystem, we have deployed a novel drug delivery microdevice that enables rapid, high-throughput assessment of the effects of multiple therapies on tumor cells and the surrounding microenvironment. When coupled with multiplex tissue imaging, this platform provides a comprehensive assessment of the state and spatial organization of the tumor ecosystem as it adapts to therapy. Initial studies demonstrated that many drugs designed to target malignant epithelial cells strongly impact stromal and immune cells, providing new insights into the importance of considering multiple aspects of the tumor ecosystem when designing effective therapeutic strategies. The resultant data are being used to guide development of a multiscale computational model that considers the functional relationships between different tumor components and can be used to predict the effects of therapies on diverse aspects of tumor ecosystems. In total, our approach has the potential to transform cancer treatments through rational identification of effective therapeutic strategies that lead to long-term durable control of tumors. Citation Format: Laura M. Heiser. Multiscale systems approach to target tumor ecosystem responses for therapeutic benefit [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Translating Cancer Evolution and Data Science: The Next Frontier; 2023 Dec 3-6; Boston, Massachusetts. Philadelphia (PA): AACR; Cancer Res 2024;84(3 Suppl_2):Abstract nr IA019.

Integrated systems biology approach identifies gene targets for endothelial dysfunction.

Endothelial dysfunction (ED) is critical in the development and progression of cardiovascular (CV) disorders, yet effective therapeutic targets for ED remain elusive due to limited understanding of its underlying molecular mechanisms. To address this gap, we employed a systems biology approach to identify potential targets for ED. Our study combined multi omics data integration, with siRNA screening, high content imaging and network analysis to prioritise key ED genes and identify a pro- and anti-ED network. We found 26 genes that, upon silencing, exacerbated the ED phenotypes tested, and network propagation identified a pro-ED network enriched in functions associated with inflammatory responses. Conversely, 31 genes ameliorated ED phenotypes, pointing to potential ED targets, and the respective anti-ED network was enriched in hypoxia, angiogenesis and cancer-related processes. An independent screen with 17 drugs found general agreement with the trends from our siRNA screen and further highlighted DUSP1, IL6 and CCL2 as potential candidates for targeting ED. Overall, our results demonstrate the potential of integrated system biology approaches in discovering disease-specific candidate drug targets for endothelial dysfunction.

Integrative Systems Biology Approach to Identify Metastatic Biomarkers in PCOS-associated Reproductive Cancers

Integrative Systems Biology Approach to Identify Metastatic Biomarkers in PCOS-associated Reproductive Cancers

An integrated systems biology approach reveals differences in formate metabolism in the genus Methanothermobacter

Methanogenesis allows methanogenic archaea to generate cellular energy for their growth while producing methane. Thermophilic hydrogenotrophic species of the genus Methanothermobacter have been recognized as robust biocatalysts for a circular carbon economy and are already applied in power-to-gas technology with biomethanation, which is a platform to store renewable energy and utilize captured carbon dioxide. Here, we generated curated genome-scale metabolic reconstructions for three Methanothermobacter strains and investigated differences in the growth performance of these same strains in chemostat bioreactor experiments with hydrogen and carbon dioxide or formate as substrates. Using an integrated systems biology approach, we identified differences in formate anabolism between the strains and revealed that formate anabolism influences the diversion of carbon between biomass and methane. This finding, together with the omics datasets and the metabolic models we generated, can be implemented for biotechnological applications of Methanothermobacter in power-to-gas technology, and as a perspective, for value-added chemical production.

Systems biology based miRNA–mRNA expression pattern analysis of Emodin in breast cancer cell lines

Breast cancer has been among the most prominent cancers with high mortality. Currently most of the offered therapeutics are toxic; hence, less toxic therapeutic intervention is required. Here, we studied the molecular mechanisms of the effect of a phytoestrogen Emodin on estrogen receptor positive MCF-7 and negative MDA-MB-231 cells by carrying out a comprehensive network assessment. Differentially expressed microRNAs along with their previously identified differentially expressed mRNAs were analyzed through microarrays by using integrative systems biology approach. For each cell line miRNA-target gene networks were built, gene ontology and pathway enrichment analyses were performed, enrichment maps were constructed and the potential key genes, miRNAs and miRNA-gene interactions were studied.

Integrated systems biology approach to identify key candidate genes, signaling pathways and therapeutic targets of oral squamous cell carcinoma

Abstract Background: This research aims to uncover gene signatures associated with oral squamous cell carcinoma (OSCC), the sixth most prevalent cancer globally, constituting about 5% of all malignant tumors. The study focuses on biomarker screening and identifying therapeutic targets, addressing a significant global issue. Materials and Methods: The study involved a comprehensive analysis of publicly available gene expression datasets, namely GSE30784 and GSE74530. The researchers conducted gene ontology (GO) and pathway analyses on genes that displayed differential expression (DEGs). They utilized the Database for Annotation, Visualization, and Integrated Discovery database to accomplish this. The String database also established a protein–protein interaction (PPI) network. This network was visualized through Cytoscape, and further exploration was carried out using Molecular Complex Detection and CytoHubba plugins. These steps aimed to identify crucial hub genes and functional modules. Furthermore, the study investigated transcription factor-gene regulatory networks focusing on the identified hub genes. The researchers employed the Gene Expression Profiling Interactive Analysis 2 tool to evaluate these hub genes’ expression levels and prognostic significance. Results: A comparison between OSCC and normal oral mucosa revealed 1210 DEGs across two databases. The obtained DEG list was cross-referenced with the DisGeNET disease database, identifying 205 potential DEG candidates. These DEGs exhibited enrichments in various biological functions, including angiogenesis, protein binding, focal adhesion, cell surface interactions, and extracellular matrix components. Among the enriched pathways, the interleukin (IL)-17 and tumor necrosis factor signaling pathways related to viral protein interactions showed significant enrichment. Further exploration involved extracting the top five hub genes from intricate PPI networks. These selected hub genes were subsequently verified in clinical samples, paving the way for subsequent in-depth analysis. Conclusion: In the study context, IL-6, chemokine (C-C motif) ligand 2, C-X-C Motif Chemokine Ligand 8, IL-1beta, and prostaglandin-endoperoxide synthase 2 emerged as the leading hub genes linked to the IL-10 signaling pathway in OSCC. These findings offer valuable insights into the potential mechanisms underlying the advancement of OSCC. However, it is essential to underscore that further research must validate these findings conclusively. The study’s outcomes have broadened our understanding of oral cancer’s molecular intricacies by identifying differentially expressed and pivotal hub genes. This newfound knowledge has the potential to catalyze the development of novel biomarkers, thereby enhancing the efficacy of both diagnostic and therapeutic strategies.

FN1 and cancer-associated fibroblasts markers influence immune microenvironment in clear cell renal cell carcinoma.

Altered tumor microenvironment (TME) is characterized in clear cell renal cell carcinoma (ccRCC) as a result of the heterogeneity observed in the TME. Modulations in TME have shown tumor metastasis promotion; hence, identifying TME-based biomarkers can be critical for theranostics application. Here, we performed an integrated systems biology approach utilizing differential gene expression, network metrics and clinical samples cohorts to prioritize the major deregulated genes and their associated pathways specific for metastasis. The gene expression profiling of 140 ccRCC samples resulted in 3657 differentially expressed genes, from which a network of 1867 up-regulated genes were further computed using network metrics for screening hub-genes. The specific pathways of ccRCC entailed through functional enrichment analysis of the hub-gene clusters indicated the role of the identified hub-genes in the enriched pathways, further validating the functional significance of the hub-genes. The positive correlation of TME cells, namely cancer-associated fibroblasts (CAFs) and its biomarkers (FAP and S100A4) with FN1, signified the role of hub-gene signaling for promoting metastasis in ccRCC. Thereafter, comparative expression, differential methylation, genetic alteration and overall survival analysis were analyzed to validate the screened hub-genes. The hub-genes were validated and prioritized by correlating with expression-based parameters, including histological grades, tumor, metastatic and pathological stages (based on median transcript per million; analysis of variance [ANOVA], P ≤ 0.05) from a clinically curated ccRCC dataset to further substantiate the translational benefits of the screened hub-genes as potential diagnostic biomarkers for ccRCC.

RETRACTED: Dual targeting of TGF-β and PD-L1 inhibits tumor growth in TGF-β/PD-L1-driven colorectal carcinoma

Immunosuppressive factors within the tumor microenvironment (TME), such as Transforming growth factor beta (TGF-β), constitute a crucial hindrance to immunotherapeutic approaches in colorectal cancer (CRC). Furthermore, immune checkpoint factors (e.g., programmed death-ligand 1 [PD-L1]) inhibit T-cell proliferation and activation. To cope with the inhibitory effect of immune checkpoints, the therapeutic value of dual targeting PD-L1 and TGF-β pathways via M7824 plus 5-FU in CRC has been evaluated. Integrative-systems biology approaches and RNAseq were used to assess the differential level of genes associated with 88 metastatic-CRC patients. The level of PD-L1 and TGF-β was evaluated in a validation cohort. The anti-proliferative, migratory, and apoptotic effects of PD-L1/TGF-β inhibitor, M7824, were assessed by MTT, wound-healing assay, and flow cytometry. Anti-tumor activity was assessed in a xenograft model, followed by biochemical studies and histological staining, and gene/protein expression analyses by RT-PCR and ELISA/IHC. The result of differentially expressed genes (DEGs) analysis showed 1268 upregulated and 1074 downregulated genes in CRC patients. Among the highest scoring genes and dysregulated pathways associated with CRC, PD-L1, and TGF-β were identified and further validated in 92 CRC patients. Targeting of PD-L1-TGF-β inhibited cell growth and migration, associated with modulation of CyclinD1 and MMP9. Furthermore, M7824 inhibited tumor growth via targeting TGF-β and PD-L1 pathways, resulting in modulation of inflammatory response and fibrosis via TNF-α/IL6/CD4–8 and COL1A1/1A2, respectively. In conclusion, our data illustrated that co-targeting PD-L1 and TGF-β pathways increased the effect of Fluorouracil (5-FU) and reduced the tumor growth in PD-L1/TGF-β expressing tumors, providing a new therapeutic option in the treatment of CRC.

Exploration of Blood Metabolite Signatures of Colorectal Cancer and Polyposis through Integrated Statistical and Network Analysis

Colorectal cancer (CRC), one of the most prevalent and deadly cancers worldwide, generally evolves from adenomatous polyps. The understanding of the molecular mechanisms underlying this pathological evolution is crucial for diagnostic and prognostic purposes. Integrative systems biology approaches offer an optimal point of view to analyze CRC and patients with polyposis. The present study analyzed the association networks constructed from a publicly available array of 113 serum metabolites measured on a cohort of 234 subjects from three groups (66 CRC patients, 76 patients with polyposis, and 92 healthy controls), which concentrations were obtained via targeted liquid chromatography-tandem mass spectrometry. In terms of architecture, topology, and connectivity, the metabolite-metabolite association network of CRC patients appears to be completely different with respect to patients with polyposis and healthy controls. The most relevant nodes in the CRC network are those related to energy metabolism. Interestingly, phenylalanine, tyrosine, and tryptophan metabolism are found to be involved in both CRC and polyposis. Our results demonstrate that the characterization of metabolite-metabolite association networks is a promising and powerful tool to investigate molecular aspects of CRC.

Toward structural-omics of the bovine retinal pigment epithelium

The use of an integrated systems biology approach to investigate tissues and organs has been thought to be impracticable in the field of structural biology, where the techniques mainly focus on determining the structure of a particular biomacromolecule of interest. Here, we report the use of cryoelectron microscopy (cryo-EM) to define the composition of a raw bovine retinal pigment epithelium (RPE) lysate. From this sample, we simultaneously identify and solve cryo-EM structures of seven different RPE enzymes whose functions affect neurotransmitter recycling, iron metabolism, gluconeogenesis, glycolysis, axonal development, and energy homeostasis. Interestingly, dysfunction of these important proteins has been directly linked to several neurodegenerative disorders, including Huntington's disease, amyotrophic lateral sclerosis (ALS), Parkinson's disease, Alzheimer's disease, and schizophrenia. Our work underscores the importance of cryo-EM in facilitating tissue and organ proteomics at the atomic level.

Simultaneous solving high-resolution structures of various enzymes from human kidney microsomes.

The ability to investigate tissues and organs through an integrated systems biology approach has been thought to be unobtainable in the field of structural biology, where the techniques mainly focus on a particular biomacromolecule of interest. Here we report the use of cryo-electron microscopy (cryo-EM) to define the composition of a raw human kidney microsomal lysate. We simultaneously identify and solve cryo-EM structures of four distinct kidney enzymes whose functions have been linked to protein biosynthesis and quality control, biosynthesis of retinoic acid, gluconeogenesis and glycolysis, and the regulation and metabolism of amino acids. Interestingly, all four of these enzymes are directly linked to cellular processes that, when disrupted, can contribute to the onset and progression of diabetes. This work underscores the potential of cryo-EM to facilitate tissue and organ proteomics at the atomic level.

TMET-09. LOSS OF MAT2A COMPROMISES METHIONINE METABOLISM AND REPRESENTS A VULNERABILITY IN H3K27M MUTANT GLIOMAS

Abstract H3K27-mutant diffuse midline gliomas (DMGs) are defined as grade IV tumors by the World Health Organization. DMGs are inoperable and resistant to chemo/radio therapies. Median survival ranges from 8-11 months, with 2% of patients surviving beyond 5 years. H3K27M mutations lead to global epigenetic and transcriptional reprogramming driven by global loss of negative transcriptional regulator H3K27 trimethylation (H3K27me3). Loss of H3K27me3 is an initiating event in gliomagenesis. This disease lacks appropriate models to predict disease biology and response to treatment. Therefore, we developed a novel syngeneic H3K27M mouse model. An unbiased integrated systems biology approach identified that H3K27M but not isogenic controls relied on the amino acid methionine and the enzyme Methionine Adenosyltransferase 2A (MAT2A). MAT2A is a central regulator of one-carbon metabolism by converting methionine to S-adenosylmethionine (SAM), the universal methyl-donor for protein and nucleotide methylation reactions. In complementary genetic approaches, we applied these findings to patient-derived cell lines with the H3K27M mutation. We hypothesize that MAT2A abrogation, genetic/pharmacological, would alter DMG viability by disrupting the methylome. The current MAT2A sensitivity paradigm is based on Methylthioadenosine Phosphorylase (MTAP) deletion through a synthetic lethal mechanism. We provide a novel mechanism whereby H3K27M cells are sensitive to MAT2A loss, independent of MTAP and through Adenosylmethionine Decarboxylase 1 (AMD1) overexpression disrupting MAT2A regulation. This results in H3K27M cells having lower MAT2A protein levels, conferring a sensitivity by inhibiting residual MAT2A. Genetic/pharmacological aberrations to MAT2A resulted in reduced proliferation. Parallel H3K36me3 ChIP and RNA-sequencing identified loss of oncogenic and developmental transcriptional programs associated with MAT2A loss. In vivo syngeneic and patient-derived xenograft models with both inducible MAT2A knockdown or methionine restricted diets showed extended survival. These results suggest novel interactions between methionine metabolism and the epigenome of H3K27M gliomas and provide evidence that MAT2A, presents exploitable therapeutic vulnerabilities in histone mutant gliomas.

An integrative systems biology approach to overcome venetoclax resistance in acute myeloid leukemia.

The over-expression of the Bcl-2 protein is a common feature of many solid cancers and hematological malignancies, and it is typically associated with poor prognosis and resistance to chemotherapy. Bcl-2-specific inhibitors, such as venetoclax, have recently been approved for the treatment of chronic lymphocytic leukemia and small lymphocytic lymphoma, and they are showing promise in clinical trials as a targeted therapy for patients with relapsed or refractory acute myeloid leukemia (AML). However, successful treatment of AML with Bcl-2-specific inhibitors is often followed by the rapid development of drug resistance. An emerging paradigm for overcoming drug resistance in cancer treatment is through the targeting of mitochondrial energetics and metabolism. In AML in particular, it was recently observed that inhibition of mitochondrial translation via administration of the antibiotic tedizolid significantly affects mitochondrial bioenergetics, activating the integrated stress response (ISR) and subsequently sensitizing drug-resistant AML cells to venetoclax. Here we develop an integrative systems biology approach to acquire a deeper understanding of the molecular mechanisms behind this process, and in particular, of the specific role of the ISR in the commitment of cells to apoptosis. Our multi-scale mathematical model couples the ISR to the intrinsic apoptosis pathway in venetoclax-resistant AML cells, includes the metabolic effects of treatment, and integrates RNA, protein level, and cellular viability data. Using the mathematical model, we identify the dominant mechanisms by which ISR activation helps to overcome venetoclax resistance, and we study the temporal sequencing of combination treatment to determine the most efficient and robust combination treatment protocol.

Mathematical Model of the Immunopathological Progression of Tuberculosis

Tuberculosis is a worldwide persistent infectious disease. It is caused by bacteria from the Mycobacterium tuberculosis complex that mainly affects the lungs and can be fatal. Using an integrative systems biology approach, we study the immunopathological progression of this disease, analyzing the key interactions between the cells involved in the different phases of the infectious process. We integrated multiple in vivo and in vitro data from immunohistochemical, serological, molecular biology, and cell count assays into a mechanistic mathematical model. The ordinary differential equation (ODE) model captures the regulatory interplay between the phenotypic variation of the main cells involved in the disease progression and the inflammatory microenvironment. The model reproduces in vivo time course data of an experimental model of progressive pulmonary TB in mouse, accurately reflecting the functional adaptations of the host–pathogen interactions as the disease progresses through three phenotypically different phases. We used the model to assess the effect of genotypic variations (encoded as changes in parameters) on disease outcomes. For all genotypes, we found an all-or-nothing response, where the virtual mouse either completely clears the infection or suffers uncontrolled Tb growth. Results show that it is 84% probable that a mouse submitted to a progressive pulmonary TB assay will end up with an uncontrolled infection. The simulations also showed how the genotypic variations shape the transitions across phases, showing that 100% of the genotypes evaluated eventually progress to phase two of the disease, suggesting that adaptive immune response activation was unavoidable. All the genotypes of the network that avoided progressing to phase 3 cleared the infection. Later, by analyzing the three different phases separately, we saw that the anti-inflammatory genotype of phase 3 was the one with the highest probability of leading to uncontrolled bacterial growth, and the proinflammatory genotype associated with phase 2 had the highest probability of bacterial clearance. Forty-two percent of the genotypes evaluated showed a bistable response, with one stable steady state corresponding to infection clearance and the other one to bacteria reaching its carrying capacity. Our mechanistic model can be used to predict the outcomes of different experimental conditions through in silico assays.

Systems biochemistry to “deorphanize” human mitochondrial proteome

Rensvold, Shishkova, etal. (2022) apply an integrated systems biology approach spanning proteomics, lipidomics, and metabolomics to a collection of CRISPR knockout cells targeting 116 distinct human mitochondrial proteins, revealing new mitochondrial biology and guiding orphan disease diagnosis.