Final results of urelumab, an anti-CD137 agonist monoclonal antibody, in combination with cetuximab or nivolumab in patients with advanced solid tumors.

BACKGROUND: Resistance to immune checkpoint inhibitors and targeted treatments for cancer is common; thus, novel immunotherapy agents are needed. Urelumab is a monoclonal antibody agonist that binds to CD137 receptors expressed on T cells. Here, we report two studies that evaluated urelumab in combination with cetuximab or nivolumab in patients with select, advanced solid tumors. METHODS: CA186-018: Patients with metastatic colorectal cancer or metastatic squamous cell carcinoma of the head and neck (SCCHN) were treated in a dose-evaluation phase with urelumab 0.1 mg/kg (urelumab-0.1) every 3 weeks (Q3W)+cetuximab 250 mg/m2 (cetuximab-250) weekly; and in a dose-expansion phase with urelumab 8 mg flat dose (urelumab-8) Q3W+cetuximab-250 weekly. CA186-107: The dose-escalation phase included patients with previously treated advanced solid tumors (or treated or treatment-naive melanoma); patients received urelumab 3 mg flat dose (urelumab-3) or urelumab-8 every 4 weeks+nivolumab 3 mg/kg (nivolumab-3) or 240 mg (nivolumab-240) every 2 weeks. In the expansion phase, patients with melanoma, non-small cell lung cancer, or SCCHN were treated with urelumab-8+nivolumab-240. Primary endpoints were safety and tolerability, and the secondary endpoint included efficacy assessments. RESULTS: CA186-018: 66 patients received study treatment. The most frequent treatment-related adverse events (TRAEs) were fatigue (75%; n=3) with urelumab-0.1+cetuximab-250 and dermatitis (45%; n=28) with urelumab-8+cetuximab-250. Three patients (5%) discontinued due to TRAE(s) (with urelumab-8+cetuximab-250). One patient with SCCHN had a partial response (objective response rate (ORR) 5%, with urelumab-8+cetuximab-250).CA186-107: 134 patients received study treatment. Fatigue was the most common TRAE (32%; n=2 with urelumab-3+nivolumab-3; n=1 with urelumab-8+nivolumab-3; n=40 with urelumab-8+nivolumab-240). Nine patients (7%) discontinued due to TRAE(s) (n=1 with urelumab-3+nivolumab-3; n=8 with urelumab-8+nivolumab-240). Patients with melanoma naive to anti-PD-1 therapy exhibited the highest ORR (49%; n=21 with urelumab-8+nivolumab-240). Intratumoral gene expression in immune-related pathways (CD3, CD8, CXCL9, GZMB) increased on treatment with urelumab+nivolumab. CONCLUSIONS: Although the addition of urelumab at these doses was tolerable, preliminary response rates did not indicate an evident additive benefit. Nevertheless, the positive pharmacodynamics effects observed with urelumab and the high response rate in treatment-naive patients with melanoma warrant further investigation of other anti-CD137 agonist agents for treatment of cancer. TRIAL REGISTRATION NUMBERS: NCT02110082; NCT02253992.

Cancer-associated fibroblasts are the main contributors to epithelial-to-mesenchymal signatures in the tumor microenvironment.

Epithelial-to-mesenchymal transition (EMT) is associated with tumor initiation, metastasis, and drug resistance. However, the mechanisms underlying these associations are largely unknown. We studied several tumor types to identify the source of EMT gene expression signals and a potential mechanism of resistance to immuno-oncology treatment. Across tumor types, EMT-related gene expression was strongly associated with expression of stroma-related genes. Based on RNA sequencing of multiple patient-derived xenograft models, EMT-related gene expression was enriched in the stroma versus parenchyma. EMT-related markers were predominantly expressed by cancer-associated fibroblasts (CAFs), cells of mesenchymal origin which produce a variety of matrix proteins and growth factors. Scores derived from a 3-gene CAF transcriptional signature (COL1A1, COL1A2, COL3A1) were sufficient to reproduce association between EMT-related markers and disease prognosis. Our results suggest that CAFs are the primary source of EMT signaling and have potential roles as biomarkers and targets for immuno-oncology therapies.

Rapid single cell evaluation of human disease and disorder targets using REVEAL: SingleCell™.

BACKGROUND: Single-cell (sc) sequencing performs unbiased profiling of individual cells and enables evaluation of less prevalent cellular populations, often missed using bulk sequencing. However, the scale and the complexity of the sc datasets poses a great challenge in its utility and this problem is further exacerbated when working with larger datasets typically generated by consortium efforts. As the scale of single cell datasets continues to increase exponentially, there is an unmet technological need to develop database platforms that can evaluate key biological hypotheses by querying extensive single-cell datasets. Large single-cell datasets like Human Cell Atlas and COVID-19 cell atlas (collection of annotated sc datasets from various human organs) are excellent resources for profiling target genes involved in human diseases and disorders ranging from oncology, auto-immunity, as well as infectious diseases like COVID-19 caused by SARS-CoV-2 virus. SARS-CoV-2 infections have led to a worldwide pandemic with massive loss of lives, infections exceeding 7 million cases. The virus uses ACE2 and TMPRSS2 as key viral entry associated proteins expressed in human cells for infections. Evaluating the expression profile of key genes in large single-cell datasets can facilitate testing for diagnostics, therapeutics, and vaccine targets, as the world struggles to cope with the on-going spread of COVID-19 infections. MAIN BODY: In this manuscript we describe REVEAL: SingleCell, which enables storage, retrieval, and rapid query of single-cell datasets inclusive of millions of cells. The array native database described here enables selecting and analyzing cells across multiple studies. Cells can be selected using individual metadata tags, more complex hierarchical ontology filtering, and gene expression threshold ranges, including co-expression of multiple genes. The tags on selected cells can be further evaluated for testing biological hypotheses. One such example includes identifying the most prevalent cell type annotation tag on returned cells. We used REVEAL: SingleCell to evaluate the expression of key SARS-CoV-2 entry associated genes, and queried the current database (2.2 Million cells, 32 projects) to obtain the results in < 60 s. We highlighted cells expressing COVID-19 associated genes are expressed on multiple tissue types, thus in part explains the multi-organ involvement in infected patients observed worldwide during the on-going COVID-19 pandemic. CONCLUSION: In this paper, we introduce the REVEAL: SingleCell database that addresses immediate needs for SARS-CoV-2 research and has the potential to be used more broadly for many precision medicine applications. We used the REVEAL: SingleCell database as a reference to ask questions relevant to drug development and precision medicine regarding cell type and co-expression for genes that encode proteins necessary for SARS-CoV-2 to enter and reproduce in cells.

Genome-wide association analysis identifies genetic correlates of immune infiltrates in solid tumors.

Therapeutic options for the treatment of an increasing variety of cancers have been expanded by the introduction of a new class of drugs, commonly referred to as checkpoint blocking agents, that target the host immune system to positively modulate anti-tumor immune response. Although efficacy of these agents has been linked to a pre-existing level of tumor immune infiltrate, it remains unclear why some patients exhibit deep and durable responses to these agents while others do not benefit. To examine the influence of tumor genetics on tumor immune state, we interrogated the relationship between somatic mutation and copy number alteration with infiltration levels of 7 immune cell types across 40 tumor cohorts in The Cancer Genome Atlas. Levels of cytotoxic T, regulatory T, total T, natural killer, and B cells, as well as monocytes and M2 macrophages, were estimated using a novel set of transcriptional signatures that were designed to resist interference from the cellular heterogeneity of tumors. Tumor mutational load and estimates of tumor purity were included in our association models to adjust for biases in multi-modal genomic data. Copy number alterations, mutations summarized at the gene level, and position-specific mutations were evaluated for association with tumor immune infiltration. We observed a strong relationship between copy number loss of a large region of chromosome 9p and decreased lymphocyte estimates in melanoma, pancreatic, and head/neck cancers. Mutations in the oncogenes PIK3CA, FGFR3, and RAS/RAF family members, as well as the tumor suppressor TP53, were linked to changes in immune infiltration, usually in restricted tumor types. Associations of specific WNT/beta-catenin pathway genetic changes with immune state were limited, but we noted a link between 9p loss and the expression of the WNT receptor FZD3, suggesting that there are interactions between 9p alteration and WNT pathways. Finally, two different cell death regulators, CASP8 and DIDO1, were often mutated in head/neck tumors that had higher lymphocyte infiltrates. In summary, our study supports the relevance of tumor genetics to questions of efficacy and resistance in checkpoint blockade therapies. It also highlights the need to assess genome-wide influences during exploration of any specific tumor pathway hypothesized to be relevant to therapeutic response. Some of the observed genetic links to immune state, like 9p loss, may influence response to cancer immune therapies. Others, like mutations in cell death pathways, may help guide combination therapeutic approaches.

A glycoprotein hormone expressed in corticotrophs exhibits unique binding properties on thyroid-stimulating hormone receptor.

Corticotroph-derived glycoprotein hormone (CGH), also referred to as thyrostimulin, is a noncovalent heterodimer of glycoprotein hormone alpha 2 (GPHA2) and glycoprotein hormone beta 5 (GPHB5). Here, we demonstrate that both subunits of CGH are expressed in the corticotroph cells of the human anterior pituitary, as well as in skin, retina, and testis. CGH activates the TSH receptor (TSHR); (125)I-CGH binding to cells expressing TSHR is saturable, specific, and of high affinity. In competition studies, unlabeled CGH is a potent competitor for (125)I-TSH binding, whereas unlabeled TSH does not compete for (125)I-CGH binding. Binding and competition analyses are consistent with the presence of two binding sites on the TSHR transfected baby hamster kidney cells, one that can interact with either TSH or CGH, and another that binds CGH alone. Transgenic overexpression of GPHB5 in mice produces elevations in serum T(4) levels, reductions in body weight, and proptosis. However, neither transgenic overexpression of GPHA2 nor deletion of GPHB5 produces an overt phenotype in mice. In vivo administration of CGH to mice produces a dose-dependent hyperthyroid phenotype including elevation of T(4) and hypertrophy of cells within the inner adrenal cortex. However, the distinctive expression patterns and binding characteristics of CGH suggest that it has endogenous biological roles that are discrete from those of TSH.

Walking tree heuristics for comparative genomic alignments.

Genomic sequence data is available for an ever-increasing number of organisms, but the full meaning of this data remains an enigma. String alignment is one approach for deciphering the information contained in genetic strings. Sequences which are conserved across species will help identify genes and other important structures. Similarity between species can be scored by measuring how well their sequences align. The walking tree method is an approximate string alignment method that can handle insertions, deletions, substitutions, translocations, and more than one level of inversion. We will describe this method and recent improvements which allow fast alignment of megabase strings. We will show examples in which the method located or discovered genes. We show how the method can be used to construct phylogenetic trees. We also show that the method can be used to identify essential regions for protein function.