No abstract

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.

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.

The nuclear receptor protein superfamily is a large group of transcription factors involved in many aspects of animal development, tissue differentiation, and homeostasis in the higher eukaryotes. A subfamily of receptors, ERRalpha and beta (estrogen receptor-related receptor alpha and beta), closely related to the ER, were among the first orphan nuclear receptors identified. These receptors can bind DNA as monomers and are thought to activate transcription constitutively, unaffected by beta-estradiol. Studies of the expression patterns of ERRalpha and gene disruption experiments of ERRbeta indicate that they play an important role in the development and differentiation of specific tissues in the mouse. In this work we demonstrate the existence in humans of a third member of this subfamily of receptors, termed ERRgamma, which is highly expressed in a number of diverse fetal and adult tissues including brain, kidney, pancreas, and placenta. The ERRgamma mRNA is highly alternatively spliced at the 5'-end, giving rise to a number of tissue-specific RNA species, some of which code for protein isoforms differing in the N-terminal region. Like ERRalpha and beta, ERRgamma binds as a monomer to an ERRE. A GAL4-ERRgamma fusion protein activates transcription in a ligand-independent manner in transfected HEK293 cells to a greater degree than either the GAL4-ERRalpha or -beta fusion proteins.

The development of efficient methods for amplifying random DNA sequences by the polymerase chain reaction has created the basis for mapping virtually unlimited numbers of mixed-phase dominant DNA markers in one population. Although dominant markers can be efficiently mapped using many different kinds of matings, recombination frequencies and locus orders are often mis-estimated from repulsion F2 matings. The major problem with these matings, apart from excessive sampling errors of recombination frequency (θ) estimates, is the bias of the maximum-likelihood estimator (MLE) of θ (θ ML). [Formula: see text] when the observed frequency of double-recessive phenotypes is 0 and the observed frequency of double-dominant phenotypes is less than 2/3 - the bias for those samples is - θ. We used simulation to estimate the mean bias of θ ML. Mean bias is a function of n and θ and decreases as n increases. Valid maps of dominant markers can be built by using sub-sets of markers linked in coupling, thereby creating male and feamle coupling maps, as long as the maps are fairly dense (about 5 cM) - the sampling errors of θ increase as θ increases for coupling linkages and are equal to those for backcross matings when θ=0. The use of F2 matings for mapping dominant markers is not necessarily proscribed because they yield twice as many useful markers as a backcross population, albeit in two maps, for the same number of DNA extractions and PCR assays; however, dominant markers can be more effeciently exploited by using doubled-haploid, recombinant-inbred, or other inbred populations.