Novel methods to analyze the tumor microenvironment (TME) are urgently needed to stratify melanoma patients for adjuvant immunotherapy. Tumor-infiltrating lymphocyte (TIL) analysis, by conventional pathologic methods, is predictive but is insufficiently precise for clinical application. Quantitative multiplex immunofluorescence (qmIF) allows for evaluation of the TME using multiparameter phenotyping, tissue segmentation, and quantitative spatial analysis (qSA). Given that CD3CD8 cytotoxic lymphocytes (CTLs) promote antitumor immunity, whereas CD68 macrophages impair immunity, we hypothesized that quantification and spatial analysis of macrophages and CTLs would correlate with clinical outcome. We applied qmIF to 104 primary stage II to III melanoma tumors and found that CTLs were closer in proximity to activated (CD68HLA-DR) macrophages than nonactivated (CD68HLA-DR) macrophages ( < 0.0001). CTLs were further in proximity from proliferating SOX10 melanoma cells than nonproliferating ones ( < 0.0001). In 64 patients with known cause of death, we found that high CTL and low macrophage density in the stroma ( = 0.0038 and = 0.0006, respectively) correlated with disease-specific survival (DSS), but the correlation was less significant for CTL and macrophage density in the tumor ( = 0.0147 and = 0.0426, respectively). DSS correlation was strongest for stromal HLA-DR CTLs ( = 0.0005). CTL distance to HLA-DR macrophages associated with poor DSS ( = 0.0016), whereas distance to Ki67 tumor cells associated inversely with DSS ( = 0.0006). A low CTL/macrophage ratio in the stroma conferred a hazard ratio (HR) of 3.719 for death from melanoma and correlated with shortened overall survival (OS) in the complete 104 patient cohort by Cox analysis ( = 0.009) and merits further development as a biomarker for clinical application. .

BackgroundChemoradiotherapy (CRT) remains one of the most common cancer treatment modalities, and recent data suggest that CRT is maximally effective when there is generation of an anti-tumoral immune response. However, CRT has also been shown to promote immunosuppressive mechanisms which must be blocked or reversed to maximize its immune stimulating effects.MethodsTherefore, using a preclinical model of human papillomavirus (HPV)-associated head and neck squamous cell carcinoma (HNSCC), we developed a clinically relevant therapy combining CRT and two existing immunomodulatory drugs: cyclophosphamide (CTX) and the small molecule inducible nitric oxide synthase (iNOS) inhibitor L-n6-(1-iminoethyl)-lysine (L-NIL). In this model, we treated the syngeneic HPV-HNSCC mEER tumor-bearing mice with fractionated (10 fractions of 3 Gy) tumor-directed radiation and weekly cisplatin administration. We compared the immune responses induced by CRT and those induced by combinatory treatment (CRT + CTX/L-NIL) with flow cytometry, quantitative multiplex immunofluorescence and by profiling immune-related gene expression changes.ResultsWe show that combination treatment favorably remodels the tumor myeloid immune microenvironment including an increase in anti-tumor immune cell types (inflammatory monocytes and M1-like macrophages) and a decrease in immunosuppressive granulocytic myeloid-derived suppressor cells (MDSCs). Intratumoral T cell infiltration and tumor antigen specificity of T cells were also improved, including a 31.8-fold increase in the CD8+ T cell/ regulatory T cell ratio and a significant increase in tumor antigen-specific CD8+ T cells compared to CRT alone. CTX/LNIL immunomodulation was also shown to significantly improve CRT efficacy, leading to rejection of 21% established tumors in a CD8-dependent manner.ConclusionsOverall, these data show that modulation of the tumor immune microenvironment with CTX/L-NIL enhances susceptibility of treatment-refractory tumors to CRT. The combination of tumor immune microenvironment modulation with CRT constitutes a translationally relevant approach to enhance CRT efficacy through enhanced immune activation.Electronic supplementary materialThe online version of this article (10.1186/s40425-018-0485-9) contains supplementary material, which is available to authorized users.

Genome-Wide Association Studies (GWAS), whole genome sequencing, and high-throughput omics techniques have generated vast amounts of genotypic and molecular phenotypic data. However, these data have not yet been fully explored to improve the effectiveness and efficiency of drug discovery, which continues along a one-drug-one-target-one-disease paradigm. As a partial consequence, both the cost to launch a new drug and the attrition rate are increasing. Systems pharmacology and pharmacogenomics are emerging to exploit the available data and potentially reverse this trend, but, as we argue here, more is needed. To understand the impact of genetic, epigenetic, and environmental factors on drug action, we must study the structural energetics and dynamics of molecular interactions in the context of the whole human genome and interactome. Such an approach requires an integrative modeling framework for drug action that leverages advances in data-driven statistical modeling and mechanism-based multiscale modeling and transforms heterogeneous data from GWAS, high-throughput sequencing, structural genomics, functional genomics, and chemical genomics into unified knowledge. This is not a small task, but, as reviewed here, progress is being made towards the final goal of personalized medicines for the treatment of complex diseases.

Background Immune checkpoint inhibitors (ICIs) for solid tumors, including those targeting programmed cell death 1 (PD-1) and cytotoxic T lymphocyte-associated antigen 4 (CTLA-4), have shown impressive clinical efficacy, however, most patients do not achieve durable responses. One major therapeutic obstacle is the immunosuppressive tumor immune microenvironment (TIME). Thus, we hypothesized that a strategy combining tumor-directed radiation with TIME immunomodulation could improve ICI response rates in established solid tumors. Methods Using a syngeneic mouse model of human papillomavirus (HPV)-associated head and neck cancer, mEER, we developed a maximally effective regimen combining PD-1 and CTLA-4 inhibition, tumor-directed radiation, and two existing immunomodulatory drugs: cyclophosphamide (CTX) and a small-molecule inducible nitric oxide synthase (iNOS) inhibitor, L-n6-(1-iminoethyl)-lysine (L-NIL). We compared the effects of the various combinations of this regimen on tumor growth, overall survival, establishment of immunologic memory, and immunologic changes with flow cytometry and quantitative multiplex immunofluorescence. Results We found PD-1 and CTLA-4 blockade, and radiotherapy alone or in combination, incapable of clearing established tumors or reversing the unfavorable balance of effector to suppressor cells in the TIME. However, modulation of the TIME with cyclophosphamide (CTX) and L-NIL in combination with dual checkpoint inhibition and radiation led to rejection of over 70% of established mEER tumors and doubled median survival in the B16 melanoma model. Anti-tumor activity was CD8 + T cell-dependent and led to development of immunologic memory against tumor-associated HPV antigens. Immune profiling revealed that CTX/L-NIL induced remodeling of myeloid cell populations in the TIME and tumor-draining lymph node and drove subsequent activation and intratumoral infiltration of CD8 + effector T cells. Conclusions Overall, this study demonstrates that modulation of the immunosuppressive TIME is required to unlock the benefits of ICIs and radiotherapy to induce immunologic rejection of treatment-refractory established solid tumors. Electronic supplementary material The online version of this article (10.1186/s40425-019-0698-6) contains supplementary material, which is available to authorized users.

Introduction The conventional one-drug-one-target-one-disease drug discovery process has been less successful in tracking multi-genic, multi-faceted complex diseases. Systems pharmacology has emerged as a new discipline to tackle the current challenges in drug discovery. The goal of systems pharmacology is to transform huge, heterogeneous, and dynamic biological and clinical data into interpretable and actionable mechanistic models for decision making in drug discovery and patient treatment. Thus, big data technology and data science will play an essential role in systems pharmacology. Areas covered This paper critically reviews the impact of three fundamental concepts of data science on systems pharmacology: similarity inference, overfitting avoidance, and disentangling causality from correlation. The authors then discuss recent advances and future directions in applying the three concepts of data science to drug discovery, with a focus on proteome-wide context-specific quantitative drug target deconvolution and personalized adverse drug reaction prediction. Expert opinion Data science will facilitate reducing the complexity of systems pharmacology modeling, detecting hidden correlations between complex data sets, and distinguishing causation from correlation. The power of data science can only be fully realized when integrated with mechanism-based multi-scale modeling that explicitly takes into account the hierarchical organization of biological systems from nucleic acid to proteins, to molecular interaction networks, to cells, to tissues, to patients, and to populations.

Metformin, a drug prescribed to treat type-2 diabetes, exhibits anti-cancer effects in a portion of patients, but the direct molecular and genetic interactions leading to this pleiotropic effect have not yet been fully explored. To repurpose metformin as a precision anti-cancer therapy, we have developed a novel structural systems pharmacology approach to elucidate metformin’s molecular basis and genetic biomarkers of action. We integrated structural proteome-scale drug target identification with network biology analysis by combining structural genomic, functional genomic, and interactomic data. Through searching the human structural proteome, we identified twenty putative metformin binding targets and their interaction models. We experimentally verified the interactions between metformin and our top-ranked kinase targets. Notably, kinases, particularly SGK1 and EGFR were identified as key molecular targets of metformin. Subsequently, we linked these putative binding targets to genes that do not directly bind to metformin but whose expressions are altered by metformin through protein-protein interactions, and identified network biomarkers of phenotypic response of metformin. The molecular targets and the key nodes in genetic networks are largely consistent with the existing experimental evidence. Their interactions can be affected by the observed cancer mutations. This study will shed new light into repurposing metformin for safe, effective, personalized therapies.

BackgroundImmunotherapy, in particular checkpoint blockade, has changed the clinical landscape of metastatic melanoma. Nonetheless, the majority of patients will either be primary refractory or progress over follow up. Management of patients progressing on first-line immunotherapy remains challenging. Expanded treatment options with combination immunotherapy has demonstrated efficacy in patients previously unresponsive to single agent or alternative combination therapy.Case presentationWe describe the case of a patient with diffusely metastatic melanoma, including brain metastases, who, despite being treated with stereotactic radiosurgery and dual CTLA-4/PD-1 blockade (ipilimumab/nivolumab), developed systemic disease progression and innumerable brain metastases. This patient achieved a complete CNS response and partial systemic response with standard whole brain radiation therapy (WBRT) combined with Talimogene laherparepvec (T-Vec) and pembrolizumab.ConclusionPatients who do not respond to one immunotherapy combination may respond during treatment with an alternate combination, even in the presence of multiple brain metastases. Biomarkers are needed to assist clinicians in evidence based clinical decision making after progression on first line immunotherapy to determine whether response can be achieved with second line immunotherapy.

: lxie@iscb.org.