Quantitative systems pharmacology (QSP) models and spatial agent-based (ABM) are powerful efficient approaches for the analysis of biological clinical applications. Although QSP becoming essential in discovering predictive biomarkers developing combination therapies through silico virtual trials, they inadequate to capture heterogeneity randomness that characterize complex systems, specifically tumor microenvironment. Here, we extend our recently developed (spQSP) model analyze growth...

Although immune checkpoint blockade therapies have shown evidence of clinical effectiveness in many types cancer, the outcome trials shows that very few patients with colorectal cancer benefit from treatments inhibitors. Bispecific T cell engagers (TCEs) are gaining popularity because they can improve patients' immunological responses by promoting activation. The possibility combining TCEs inhibitors to increase tumor response and patient survival has been highlighted preclinical outcomes....

The low response rate of immune checkpoint blockade in breast cancer has highlighted the need for predictive biomarkers to identify responders. While a number clinical trials are ongoing, testing all possible combinations is not feasible. In this study, quantitative systems pharmacology model built integrate immune-cancer cell interactions patients with cancer, including central, peripheral, tumour-draining lymph node (TDLN) and tumour compartments. can describe suppression evasion both TDLN...

Background Immune checkpoint blockade therapy has clearly shown clinical activity in patients with triple-negative breast cancer, but less than half of the benefit from treatments. While a number ongoing trials are investigating different combinations inhibitors and chemotherapeutic agents, predictive biomarkers that identify most likely to remains one major challenges. Here we present modular quantitative systems pharmacology (QSP) platform for immuno-oncology incorporates detailed...

Background Hepatocellular carcinoma (HCC) is the most common form of primary liver cancer and third-leading cause cancer-related death worldwide. Most patients with HCC are diagnosed at an advanced stage, median survival for treated modern systemic therapy less than 2 years. This leaves stage limited treatment options. Immune checkpoint inhibitors (ICIs) targeting programmed cell protein 1 (PD-1) or its ligand, widely used in associated durable responses a subset patients. ICIs cytotoxic...

Quantitative systems pharmacology (QSP) modeling is an emerging mechanistic computational approach that couples drug pharmacokinetics/pharmacodynamics and the course of disease progression. It has begun to play important roles in development for complex diseases such as cancer, including triple-negative breast cancer (TNBC). The combination anti-PD-L1 antibody atezolizumab nab-paclitaxel shown clinical activity advanced TNBC with PD-L1-positive tumor-infiltrating immune cells. As...

Triple-negative breast cancer (TNBC), a highly metastatic subtype, has limited treatment options. While small number of patients attain clinical benefit with single-agent checkpoint inhibitors, identifying these before the therapy remains challenging. Here, we developed transcriptome-informed quantitative systems pharmacology model TNBC by integrating heterogenous tumors. In silico trial an anti–PD-1 drug, pembrolizumab, predicted that several features, such as density antigen-presenting...

Generating realistic virtual patients from a limited amount of patient data is one the major challenges for quantitative systems pharmacology modeling in immuno-oncology. Quantitative (QSP) mathematical methodology that integrates mechanistic knowledge biological to investigate dynamics whole system during disease progression and drug treatment. In present analysis, we parameterized our previously published QSP model cancer-immunity cycle non-small cell lung cancer (NSCLC) generated cohort...

Due to the lack of treatment options, there remains a need advance new therapeutics in hepatocellular carcinoma (HCC). The traditional approach moves from initial molecular discovery through animal models human trials novel systemic therapies that improve outcomes for patients with cancer. Computational methods simulate tumors mathematically describe cellular and interactions are emerging as promising tools impact therapy entirely silico, potentially greatly accelerating delivery patients....

Understanding the intricate interactions of cancer cells with tumor microenvironment (TME) is a pre-requisite for optimization immunotherapy. Mechanistic models such as quantitative systems pharmacology (QSP) provide insights into TME dynamics and predict efficacy immunotherapy in virtual patient populations/digital twins but require vast amounts multimodal data parameterization. Large-scale datasets characterizing are available due to recent advances bioinformatics multi-omics data. Here,...

The survival rate of patients with breast cancer has been improved by immune checkpoint blockade therapies, and the efficacy their combinations epigenetic modulators shown promising results in preclinical studies. In this prospective study, we propose an ordinary differential equation (ODE)-based quantitative systems pharmacology (QSP) model to conduct silico virtual clinical trial analyze potential predictive biomarkers improve anti-tumor response HER2-negative cancer. is comprised four...

T cells have been recognized as core effectors for cancer immunotherapy. How to restore the anti-tumor ability of suppressed or improve lethality cytotoxic has become main focus in Bispecific antibodies, especially bispecific cell engagers (TCEs), shown their unique enhance patient's immune response tumors by stimulating activation and cytokine production an MHC-independent manner. Antibodies targeting checkpoint inhibitory molecules such programmed death protein 1 (PD-1), PD-ligand (PD-L1)...

Immunotherapy has shown great potential in the treatment of cancer; however, only a fraction patients respond to treatment, and many experience autoimmune-related side effects. The pharmaceutical industry relied on mathematical models study behavior candidate drugs more recently, complex, whole-body, quantitative systems pharmacology (QSP) have become increasingly popular for discovery development. QSP modeling discover novel predictive biomarkers as well test efficacy plans combination...

Cold atmospheric plasma (CAP) has exhibited exciting potential for cancer treatment. Reactive oxygen and nitrogen species (RONS), the primary constituents in CAP, contribute to cell death by elevating oxidative stress cells. However, several intrinsic cellular antioxidant defense systems exist, such as glutathione peroxidase 4 (GPX4) enzyme, which dampens cell-killing efficacy of CAP. RAS-selective lethal 3 (RSL3), also known a ferroptosis inducer, is synthetic GPX4 inhibitor. Therefore, we...

Abstract Hypertrophic scar (HS) is one of the most common complications skin injuries, with a lack effective therapeutic approaches to date. Most current research has focused on dysfunction hypertrophic fibroblasts (HSFBs) and dermal vascular endothelial cells (HDVECs), neglecting crucial role inflammatory microenvironment that causes them be abnormal. In this study, we first discovered validated S100A8/9 specific inhibitor Paquinimod could inhibit macrophage polarization toward M1, further...

Abstract Cancer immunotherapy has recently drawn remarkable attention as promising results in the clinic have shown its ability to improve overall survival, and T cells are considered be one of primary effectors for cancer immunotherapy. Enhanced restored cell tumoricidal activity great potential killing cells. Bispecific engagers (TCEs) a growing class molecules that designed bind two different antigens on surface bring them close proximity selectively activate effector kill target New...

Response to cancer immunotherapies depends on the complex and dynamic interactions between T cell recognition killing of cells that are counteracted through immunosuppressive pathways in tumor microenvironment. Therefore, while measurements such as mutational burden provide biomarkers select patients for immunotherapy, they neither universally predict patient response nor implicate mechanisms underlie immunotherapy resistance. Recent advances single-cell RNA sequencing technology measure...

Keloid is a pathological dermatological condition that manifests as an overgrowth scar secondary to skin trauma. This study endeavored excavate immune-related signatures of keloid based on single-cell RNA (scRNA) sequencing data and bulk data.The keloid-relevant scRNA dataset GSE163973 GSE113619 were mined from the GEO database. The "Seurat" R package was utilized for quality control, cell clustering, investigation marker genes each cluster. "SingleR" helped match corresponding cluster...

Abstract Conditionally activated molecules, such as Probody therapeutics (PbTx), have recently been investigated to improve antitumoral response while reducing systemic toxicity. PbTx are engineered be proteolytically by proteases that preferentially active locally in the tumor microenvironment (TME). Here, we perform an exploratory study using our published quantitative systems pharmacology model, previously validated for other drugs, evaluate effectiveness and targeting specificity of...

Immune checkpoint inhibitors remained the standard-of-care treatment for advanced non-small cell lung cancer (NSCLC) past decade. In unselected patients, anti-PD-(L)1 monotherapy achieved an overall response rate of about 20%. this analysis, we developed a pharmacokinetic and pharmacodynamic module our previously calibrated quantitative systems pharmacology model (QSP) to simulate effectiveness macrophage-targeted therapies in combination with PD-L1 inhibition NSCLC. By conducting silico...

Patients with metastatic triple-negative breast cancer (TNBC) show variable responses to PD-1 inhibition. Efficient patient selection by predictive biomarkers would be desirable but is hindered the limited performance of existing biomarkers. Here, we leveraged in silico cohorts generated using a quantitative systems pharmacology model TNBC, informed transcriptomic and clinical data, explore potential ways improve selection. We evaluated quantified 90 biomarker candidates, including various...