Epilogue to the Gerald Maggiora Festschrift: a tribute to an exemplary mentor, colleague, collaborator, and innovator.

In May 2022, JCAMD published a Special Issue in honor of Gerald (Gerry) Maggiora, whose scientific leadership over many decades advanced the fields of computational chemistry and chemoinformatics for drug discovery. Along the way, he has impacted many researchers in both academia and the pharmaceutical industry. In this Epilogue, we explain the origins of the Festschrift and present a series of first-hand vignettes, in approximate chronological sequence, that together paint a picture of this remarkable man. Whether they highlight Gerry's endless curiosity about molecular life sciences or his willingness to challenge conventional wisdom or his generous support of junior colleagues and peers, these colleagues and collaborators are united in their appreciation of his positive influence. These tributes also reflect key trends and themes during the evolution of modern drug discovery, seen through the lens of people who worked with a visionary leader. Junior scientists will find an inspiring roadmap for creative collegiality and collaboration.

Treatment with a VEGFR-2 antibody results in intra-tumor immune modulation and enhances anti-tumor efficacy of PD-L1 blockade in syngeneic murine tumor models.

Prolonged activation of vascular endothelial growth factor receptor-2 (VEGFR-2) due to mis-regulation of the VEGF pathway induces aberrant blood vessel expansion, which supports growth and survival of solid tumors. Therapeutic interventions that inhibit the VEGFR-2 pathway have therefore become a mainstay of cancer treatment. Non-clinical studies have recently revealed that blockade of angiogenesis can modulate the tumor microenvironment and enhance the efficacy of concurrent immune therapies. Ramucirumab is an FDA-approved anti-angiogenic antibody that inhibits VEGFR-2 and is currently being evaluated in clinical studies in combination with anti-programmed cell death (PD-1) axis checkpoint inhibitors (pembrolizumab, durvalumab, or sintilimab) across several cancer types. The purpose of this study is to establish a mechanistic basis for the enhanced activity observed in the combined blockade of VEGFR-2 and PD-1-axis pathways. Pre-clinical studies were conducted in murine tumor models known to be responsive to anti-PD-1 axis therapy, using monoclonal antibodies that block mouse VEGFR-2 and programmed death-ligand 1 (PD-L1). Combination therapy resulted in enhanced anti-tumor activity compared to anti-PD-L1 monotherapy. VEGFR-2 blockade at early timepoints post-anti-PD-L1 therapy resulted in a dose-dependent and transient enhanced infiltration of T cells, and establishment of immunological memory. VEGFR-2 blockade at later timepoints resulted in enhancement of anti-PD-L1-driven immune cell infiltration. VEGFR-2 and PD-L1 monotherapies induced both unique and overlapping patterns of immune gene expression, and combination therapy resulted in an enhanced immune activation signature. Collectively, these results provide new and actionable insights into the mechanisms by which concurrent VEGFR-2 and PD-L1 antibody therapy leads to enhanced anti-tumor efficacy.

Relationship between gene expression patterns from nasopharyngeal swabs and serum biomarkers in patients hospitalized with COVID-19, following treatment with the neutralizing monoclonal antibody bamlanivimab.

BACKGROUND: A thorough understanding of a patient's inflammatory response to Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) infection is crucial to discerning the associated, underlying immunological processes and to the selection and implementation of treatment strategies. Defining peripheral blood biomarkers relevant to SARS-CoV-2 infection is fundamental to detecting and monitoring this systemic disease. This safety-focused study aims to monitor and characterize the immune response to SARS-CoV-2 infection via analysis of peripheral blood and nasopharyngeal swab samples obtained from patients hospitalized with Coronavirus disease 2019 (COVID-19), in the presence or absence of bamlanivimab treatment. METHODS: 23 patients hospitalized with COVID-19 were randomized to receive a single dose of the neutralizing monoclonal antibody, bamlanivimab (700 mg, 2800 mg or 7000 mg) or placebo, at study initiation (Clinical Trial; NCT04411628). Serum samples and nasopharyngeal swabs were collected at multiple time points over 1 month. A Proximity Extension Array was used to detect inflammatory profiles from protein biomarkers in the serum of hospitalized COVID-19 patients relative to age/sex-matched healthy controls. RNA sequencing was performed on nasopharyngeal swabs. A Luminex serology assay and Elecsys® Anti-SARS-CoV-2 immunoassay were used to detect endogenous antibody formation and to monitor seroconversion in each cohort over time. A mixed model for repeated measures approach was used to analyze changes in serology and serum proteins over time. RESULTS: Levels of IL-6, CXCL10, CXCL11, IFNγ and MCP-3 were > fourfold higher in the serum of patients with COVID-19 versus healthy controls and linked with observations of inflammatory and viral-induced interferon response genes detected in nasopharyngeal swab samples from the same patients. While IgA and IgM titers peaked around 7 days post-dose, IgG titers remained high, even after 28 days. Changes in biomarkers over time were not significantly different between the bamlanivimab and placebo groups. CONCLUSIONS: Similarities observed between nasopharyngeal gene expression patterns and peripheral blood biomarker profiles reveal a connection between the circulation and processes in the nasopharyngeal cavity, reinforcing the potential utility of systemic blood biomarker profiling for therapeutic monitoring of patient response. Serological antibody responses in patients correlated closely with reductions in the COVID-19 inflammatory protein biomarker signature. Bamlanivimab did not affect the biomarker dynamics in this hospitalized patient population.

A Phase I Study of an IDO-1 Inhibitor (LY3381916) as Monotherapy and in Combination With an Anti-PD-L1 Antibody (LY3300054) in Patients With Advanced Cancer.

LY3381916 is an orally available, highly selective, potent inhibitor of indoleamine 2,3-dioxygenase 1. This study explored the safety, tolerability, pharmacokinetics, pharmacodynamics, and antitumor activity of LY3381916 monotherapy and in combination with a programmed death-ligand 1 (PD-L1) inhibitor (LY3300054) in patients with advanced solid tumors. During dose escalation, patients received escalating doses of LY3381916 at 60-600 mg once daily (qd) and 240 mg twice daily in monotherapy (n=21) and in combination with PD-L1 inhibitor at 700 mg every 2 weeks (n=21). A modified toxicity probability interval method was used to guide dose escalation. Dose-limiting toxicities occurred in 3 patients; 1 at LY3381916 240 mg twice daily (alanine aminotransferase/aspartate aminotransferase increase and systemic inflammatory response syndrome) and 2 at LY3381916 240 mg qd in combination with PD-L1 inhibitor (fatigue and immune-related hepatitis). LY3381916, at the recommended phase II dose, 240 mg qd, in combination with PD-L1 inhibitor, produced maximal inhibition of indoleamine 2,3-dioxygenase 1 activity in plasma and tumor tissue, and led to an increase of CD8 T cells in tumor tissue. In the combination dose expansion cohorts, 14 triple-negative breast cancer and 4 non-small cell lung cancer patients were enrolled. Treatment-related liver toxicity (grade ≥2 alanine aminotransferase/aspartate aminotransferase increase or immune-related hepatitis) was the most prominent adverse event in triple-negative breast cancer patients (n=5, 35.7%). Best response was stable disease. These preliminary data suggest an alternative dose level of LY3381916 is needed for the combination with PD-L1 inhibitor. The combination clinical activity was limited in this study.

Immunomodulatory Activity of a Colony-stimulating Factor-1 Receptor Inhibitor in Patients with Advanced Refractory Breast or Prostate Cancer: A Phase I Study.

PURPOSE: Tumor-associated macrophages correlate with increased invasiveness, growth, and immunosuppression. Activation of the colony-stimulating factor-1 receptor (CSF-1R) results in proliferation, differentiation, and migration of monocytes/macrophages. This phase I study evaluated the immunologic and clinical activity, and safety profile of CSF-1R inhibition with the mAb LY3022855. PATIENTS AND METHODS: Patients with advanced refractory metastatic breast cancer (MBC) or metastatic castration-resistant prostate cancer (mCRPC) were treated with LY3022855 intravenously in 6-week cycles in cohorts: (A) 1.25 mg/kg every 2 weeks (Q2W); (B) 1.0 mg/kg on weeks 1, 2, 4, and 5; (C) 100 mg once weekly; (D)100 mg Q2W. mCRPC patients were enrolled in cohorts A and B; patients with MBC were enrolled in all cohorts. Efficacy was assessed by RECIST and Prostate Cancer Clinical Trials Working Group 2 criteria. RESULTS: Thirty-four patients (22 MBC; 12 mCRPC) received ≥1 dose of LY3022855. At day 8, circulating CSF-1 levels increased and proinflammatory monocytes CD14DIMCD16BRIGHT decreased. Best RECIST response was stable disease in five patients with MBC (23%; duration, 82-302 days) and three patients with mCRPC (25%; duration, 50-124 days). Two patients with MBC (cohort A) had durable stable disease >9 months and a third patient with MBC had palpable reduction in a nontarget neck mass. Immune-related gene activation in tumor biopsies posttreatment was observed. Common any grade treatment-related adverse events were fatigue, decreased appetite, nausea, asymptomatic increased lipase, and creatine phosphokinase. CONCLUSIONS: LY3022855 was well tolerated and showed evidence of immune modulation. Clinically meaningful stable disease >9 months was observed in two patients with MBC.

The Folate Pathway Inhibitor Pemetrexed Pleiotropically Enhances Effects of Cancer Immunotherapy.

PURPOSE: Combination strategies leveraging chemotherapeutic agents and immunotherapy have held the promise as a method to improve benefit for patients with cancer. However, most chemotherapies have detrimental effects on immune homeostasis and differ in their ability to induce immunogenic cell death (ICD). The approval of pemetrexed and carboplatin with anti-PD-1 (pembrolizumab) for treatment of non-small cell lung cancer represents the first approved chemotherapy and immunotherapy combination. Although the clinical data suggest a positive interaction between pemetrexed-based chemotherapy and immunotherapy, the underlying mechanism remains unknown. EXPERIMENTAL DESIGN: Mouse tumor models (MC38, Colon26) and high-content biomarker studies (flow cytometry, Quantigene Plex, and nCounter gene expression analysis) were deployed to obtain insights into the mechanistic rationale behind the efficacy observed with pemetrexed/anti-PD-L1 combination. ICD in tumor cell lines was assessed by calreticulin and HMGB-1 immunoassays, and metabolic function of primary T cells was evaluated by Seahorse analysis. RESULTS: Pemetrexed treatment alone increased T-cell activation in mouse tumors in vivo, robustly induced ICD in mouse tumor cells and exerted T-cell-intrinsic effects exemplified by augmented mitochondrial function and enhanced T-cell activation in vitro. Increased antitumor efficacy and pronounced inflamed/immune activation were observed when pemetrexed was combined with anti-PD-L1. CONCLUSIONS: Pemetrexed augments systemic intratumor immune responses through tumor intrinsic mechanisms including immunogenic cell death, T-cell-intrinsic mechanisms enhancing mitochondrial biogenesis leading to increased T-cell infiltration/activation along with modulation of innate immune pathways, which are significantly enhanced in combination with PD-1 pathway blockade.See related commentary by Buque et al., p. 6890.

Bottom-up, integrated -omics analysis identifies broadly dosage-sensitive genes in breast cancer samples from TCGA.

The massive genomic data from The Cancer Genome Atlas (TCGA), including proteomics data from Clinical Proteomic Tumor Analysis Consortium (CPTAC), provides a unique opportunity to study cancer systematically. While most observations are made from a single type of genomics data, we apply big data analytics and systems biology approaches by simultaneously analyzing DNA amplification, mRNA and protein abundance. Using multiple genomic profiles, we have discovered widespread dosage compensation for the extensive aneuploidy observed in TCGA breast cancer samples. We do identify 11 genes that show strong correlation across all features (DNA/mRNA/protein) analogous to that of the well-known oncogene HER2 (ERBB2). These genes are generally less well-characterized regarding their role in cancer and we advocate their further study. We also discover that shRNA knockdown of these genes has an impact on cancer cell growth, suggesting a vulnerability that could be used for cancer therapy. Our study shows the advantages of systematic big data methodologies and also provides future research directions.

Identification of druggable cancer driver genes amplified across TCGA datasets.

The Cancer Genome Atlas (TCGA) projects have advanced our understanding of the driver mutations, genetic backgrounds, and key pathways activated across cancer types. Analysis of TCGA datasets have mostly focused on somatic mutations and translocations, with less emphasis placed on gene amplifications. Here we describe a bioinformatics screening strategy to identify putative cancer driver genes amplified across TCGA datasets. We carried out GISTIC2 analysis of TCGA datasets spanning 16 cancer subtypes and identified 486 genes that were amplified in two or more datasets. The list was narrowed to 75 cancer-associated genes with potential "druggable" properties. The majority of the genes were localized to 14 amplicons spread across the genome. To identify potential cancer driver genes, we analyzed gene copy number and mRNA expression data from individual patient samples and identified 42 putative cancer driver genes linked to diverse oncogenic processes. Oncogenic activity was further validated by siRNA/shRNA knockdown and by referencing the Project Achilles datasets. The amplified genes represented a number of gene families, including epigenetic regulators, cell cycle-associated genes, DNA damage response/repair genes, metabolic regulators, and genes linked to the Wnt, Notch, Hedgehog, JAK/STAT, NF-KB and MAPK signaling pathways. Among the 42 putative driver genes were known driver genes, such as EGFR, ERBB2 and PIK3CA. Wild-type KRAS was amplified in several cancer types, and KRAS-amplified cancer cell lines were most sensitive to KRAS shRNA, suggesting that KRAS amplification was an independent oncogenic event. A number of MAP kinase adapters were co-amplified with their receptor tyrosine kinases, such as the FGFR adapter FRS2 and the EGFR family adapters GRB2 and GRB7. The ubiquitin-like ligase DCUN1D1 and the histone methyltransferase NSD3 were also identified as novel putative cancer driver genes. We discuss the patient tailoring implications for existing cancer drug targets and we further discuss potential novel opportunities for drug discovery efforts.

3D QSAR methods: Phase and Catalyst compared.

The programs Phase and Catalyst HypoGen are compared for their performance in determining three-dimensional quantitative structure-activity relationships. Eight sets of compounds with measured activity were collected from the public literature and partitioned into suitable training and test sets by an automated procedure. A range of models is built with each program, and suggested parameter variations are investigated. The models are assessed by their ability to predict the activity of compounds in the test set, and it is demonstrated that the performance of Phase is better than or equal to that of Catalyst HypoGen, with the data sets and parameters used here. Additionally, compounds in two of the data sets are overlaid on crystallographic structures of similar ligands in complex with the target receptor, in order to guide pharmacophore generation by the two programs, but the resulting models do not perform better.

High-throughput assays for promiscuous inhibitors.

High-throughput screening (HTS) searches large libraries of chemical compounds for those that can modulate the activity of a particular biological target; it is the dominant technique used in early-stage drug discovery. A key problem in HTS is the prevalence of nonspecific or 'promiscuous' inhibitors. These molecules have peculiar properties, act on unrelated targets and can dominate the results from screening campaigns. Several explanations have been proposed to account for promiscuous inhibitors, including chemical reactivity, interference in assay read-out, high molecular flexibility and hydrophobicity. The diversity of these models reflects the apparently unrelated molecules whose behaviors they seek to explain. However, a single mechanism may explain the effects of many promiscuous inhibitors: some organic molecules form large colloid-like aggregates that sequester and thereby inhibit enzymes. Hits from HTS, leads for drug discovery and even several drugs appear to act through this mechanism at micromolar concentrations. Here, we report two rapid assays for detecting promiscuous aggregates that we tested against 1,030 'drug-like' molecules. The results from these assays were used to test two preliminary computational models of this phenomenon and as benchmarks to develop new models.

Identification and prediction of promiscuous aggregating inhibitors among known drugs.

Some small molecules, often hits from screening, form aggregates in solution that inhibit many enzymes. In contrast, drugs are thought to act specifically. To investigate this assumption, 50 unrelated drugs were tested for promiscuous inhibition via aggregation. Each drug was tested against three unrelated model enzymes: beta-lactamase, chymotrypsin, and malate dehydrogenase, none of which are considered targets of these drugs. To be judged promiscuous, the drugs had to inhibit all three enzymes, do so in a time-dependent manner, be sensitive to detergent and to enzyme concentration, and form particles detectable by light scattering. Of the 50 drugs tested, 43 were nonpromiscuous by these criteria. Surprisingly, four of the drugs showed promiscuous, aggregation-based inhibition at concentrations below 100 microM: clotrimazole, benzyl benzoate, nicardipine, and delavirdine. Three other drugs also behaved as aggregation-based inhibitors, but only at high concentrations (about 400 microM). To investigate possible structure-activity relationships among promiscuous drugs, five analogues of the antifungal clotrimazole were studied. Three of these, miconazole, econazole, and sulconazole, were promiscuous but the other two, fluconazole and ketoconazole, were not. Using recursive partitioning, these experimental results were used to develop a model for predicting aggregate-based promiscuity. This model correctly classified 94% of 111 compounds-47 aggregators and 64 nonaggregators-that have been studied for this effect. To evaluate the model, it was used to predict the behavior of 75 drugs not previously investigated for aggregation. Several preliminary points emerge. Most drugs are not promiscuous, even at high concentrations. Nevertheless, at high enough concentrations (20-400 microM), some drugs can aggregate and act promiscuously, suggesting that aggregation may be common among small molecules at micromolar concentrations, at least in biochemical buffers.

Molecular docking and high-throughput screening for novel inhibitors of protein tyrosine phosphatase-1B.

High-throughput screening (HTS) of compound libraries is used to discover novel leads for drug development. When a structure is available for the target, computer-based screening using molecular docking may also be considered. The two techniques have rarely been used together on the same target. The opportunity to do so presented itself in a project to discover novel inhibitors for the enzyme protein tyrosine phosphatase-1B (PTP1B), a tyrosine phosphatase that has been implicated as a key target for type II diabetes. A corporate library of approximately 400 000 compounds was screened using high-throughput experimental techniques for compounds that inhibited PTP1B. Concurrently, molecular docking was used to screen approximately 235 000 commercially available compounds against the X-ray crystallographic structure of PTP1B, and 365 high-scoring molecules were tested as inhibitors of the enzyme. Of approximately 400 000 molecules tested in the high-throughput experimental assay, 85 (0.021%) inhibited the enzyme with IC50 values less than 100 microM; the most active had an IC50 value of 4.2 microM. Of the 365 molecules suggested by molecular docking, 127 (34.8%) inhibited PTP1B with IC50 values less than 100 microM; the most active of these had an IC50 of 1.7 microM. Structure-based docking therefore enriched the hit rate by 1700-fold over random screening. The hits from both the high-throughput and docking screens were dissimilar from phosphotyrosine, the canonical substrate group for PTP1B; the two hit lists were also very different from each other. Surprisingly, the docking hits were judged to be more druglike than the HTS hits. The diversity of both hit lists and their dissimilarity from each other suggest that docking and HTS may be complementary techniques for lead discovery.