Psoriasis is a chronic inflammatory skin disease driven by aberrant signals from the immune system. In this issue, Li et al. present the first large RNA-seq analysis of gene expression in normal skin and psoriasis lesions, providing a more comprehensive view of mRNA expression than earlier microarray studies. This study's size enables gene co-expression analysis, a method illustrating which pathways are altered by the presence of disease.

As epithelial tumors grow from single cells to a malignant mass of invasive tissue, they must exploit the innate inflammatory response, while evading the adaptive immune system. Prognosis of solid tumors has historically focused on macroscopic features such as size, grade, and mitotic index. It is now clear that prognosis assessment must also consider the stromal and immune cells that surround and infiltrate the tumor. Tumors promote growth, angiogenesis, and tissue remodeling by subverting the normal functions of macrophages and other cells of the innate immune system that inhabit their microenvironment. Simultaneously, tumor cells escape from and inactivate the adaptive immune system by exploiting the mechanisms preventing damaging auto-immune responses in cytotoxic T cells. The presence of CD8(+) T cells within epithelial tumors is now a well-supported marker of better prognosis in many tumor types. However, this benefit is counterbalanced by immune regulatory cell populations that promote tumor escape from immune surveillance and metastasis. Therapeutic approaches that kill tumor cells selectively by re-activating immune checkpoints are becoming an established therapeutic option, but it is not yet clear how to identify which patients will benefit from this treatment modality. Evidence is accumulating that identifying the presence of T cell-activating neoantigens, produced by mutated proteins in tumors, will play an important role in checkpoint inhibitor prognosis. This review provides an overview of the evidence that lymphocytic infiltration of tumors has prognostic value in many epithelial tumor types and is linked to the success of chemical and immune checkpoint therapeutic strategies.

SUMMARY: Resistance to two classes of FDA-approved therapies that target DNA repair-deficient tumors is caused by mutations that restore the tumor cells DNA repair function. Identifying these reversion mutations currently requires manual annotation of patient tumor sequence data. Here we present AARDVARK, an R package that automatically identifies reversion mutations from DNA sequence data. AVAILABILITY AND IMPLEMENTATION: AARDVARK is implemented in R (≥3.5). It is available on GitHub at https://github.com/davidquigley/aardvark. It is licensed under the MIT license.

Nucleation and crystal growth are important in material synthesis, climate modeling, biomineralization, and pharmaceutical formulation. Despite tremendous efforts, the mechanisms and kinetics of nucleation remain elusive to both theory and experiment. Here we investigate sodium chloride (NaCl) nucleation from supersaturated brines using seeded atomistic simulations, polymorph-specific order parameters, and elements of classical nucleation theory. We find that NaCl nucleates via the common rock salt structure. Ion desolvation-not diffusion-is identified as the limiting resistance to attachment. Two different analyses give approximately consistent attachment kinetics: diffusion along the nucleus size coordinate and reaction-diffusion analysis of approach-to-coexistence simulation data from Aragones et al. ( J. Chem. Phys. 2012, 136, 244508 ). Our simulations were performed at realistic supersaturations to enable the first direct comparison to experimental nucleation rates for this system. The computed and measured rates converge to a common upper limit at extremely high supersaturation. However, our rate predictions are between 15 and 30 orders of magnitude too fast. We comment on possible origins of the large discrepancy.

Homeodomain-interacting protein kinase 2 (Hipk2) has previously been implicated in the control of several transcription factors involved in embryonic development, apoptosis, cell proliferation, and tumor development, but very little is understood about the exact mechanisms through which Hipk2 influences these processes. Analysis of gene expression in normal tissues from genetically heterogeneous mouse or human populations can reveal network motifs associated with the structural or functional components of the tissue, and may predict roles for genes of unknown function. Here we have applied this network strategy to uncover a role for the Hipk2 gene in the transcriptional system controlling adipogenesis. Both in vitro and in vivo models were used to show that knockdown or loss of Hipk2 specifically inhibits white adipose cell differentiation and tissue development. In addition, loss of Hipk2 leads to induction of pockets of multilocular brown fat-like cells in remaining white adipose depots, which express markers of brown and beige fat such as uncoupling protein 1 and transmembrane protein 26. These changes are accompanied by increased insulin sensitivity in Hipk2 knockout mice and reduced high-fat diet-induced weight gain, highlighting a potential role for this kinase in diseases such as diabetes and obesity. Our study underscores the versatility and power of a readily available tissue, such as skin, for network modeling of systemic transcriptional programs involved in multiple pathways, including lipid metabolism and adipogenesis.

Background

Body mass index (BMI) has been implicated as a primary factor influencing cancer development. However, understanding the relationship between these two complex traits has been confounded by both environmental and genetic heterogeneity.

Methods

In order to gain insight into the genetic factors linking BMI and cancer, we performed chemical carcinogenesis on a genetically heterogeneous cohort of interspecific backcross mice ((Mus Spretus × FVB/N) F1 × FVB/N). Using this cohort, we performed quantitative trait loci (QTL) analysis to identify regions linked to BMI. We then performed an integrated analysis incorporating gene expression, sequence comparison between strains, and gene expression network analysis to identify candidate genes influencing both tumor development and BMI.

Results

Analysis of QTL linked to tumorigenesis and BMI identified several loci associated with both phenotypes. Exploring these loci in greater detail revealed a novel relationship between the Pannexin 3 gene (Panx3) and both BMI and tumorigenesis. Panx3 is positively associated with BMI and is strongly tied to a lipid metabolism gene expression network. Pre-treatment Panx3 gene expression levels in normal skin are associated with tumor susceptibility and inhibition of Panx function strongly influences inflammation.

Conclusions

These studies have identified several genetic loci that influence both BMI and carcinogenesis and implicate Panx3 as a candidate gene that links these phenotypes through its effects on inflammation and lipid metabolism.

Germline polymorphisms in model organisms and humans influence susceptibility to complex trait diseases such as inflammation and cancer. Mice of the Mus spretus species are resistant to tumour development, and crosses between M. spretus and susceptible Mus musculus strains have been used to map locations of genetic variants that contribute to skin cancer susceptibility. We have integrated germline polymorphisms with gene expression in normal skin from a M. musculus x M. spretus backcross to generate a network view of the gene expression architecture of mouse skin. Here we demonstrate how this approach identifies expression motifs that contribute to tissue organization and biological functions related to inflammation, haematopoiesis, cell cycle control and tumour susceptibility. Motifs associated with inflammation, epidermal barrier function and proliferation are differentially regulated in backcross mice susceptible or resistant to tumour development. The intestinal stem cell marker Lgr5 is identified as a candidate master regulator of the hair follicle, and the vitamin D receptor (Vdr) is linked to coordinated control of epidermal barrier function, inflammation and tumour susceptibility.

Chronic inflammation promotes breast tumor growth and invasion by accelerating angiogenesis and tissue remodeling in the tumor microenvironment. There is a complex relationship between inflammation and estrogen, which drives the growth of 70 percent of breast tumors. While low levels of estrogen exposure stimulate macrophages and other inflammatory cell populations, very high levels are immune suppressive. Breast tumor incidence is increased by obesity and age, which interact to influence inflammatory cell populations in normal breast tissue. To characterize the impact of these factors on tumors and the tumor microenvironment, we measured gene expression in 195 breast adenocarcinomas and matched adjacent normal breast tissue samples collected at Akershus University Hospital (AHUS). Age and Body Mass Index (BMI) were independently associated with inflammation in adjacent normal tissue but not tumors. Estrogen Receptor (ER)-negative tumors had elevated macrophage expression compared with matched normal tissue, but ER-positive tumors showed an unexpected decrease in macrophage expression. We found an inverse relationship between the increase in tumor estrogen pathway expression compared with adjacent normal tissue and tumor macrophage score. We validated this finding in 126 breast tumor-normal pairs from the previously published METABRIC cohort. We developed a novel statistic, the Rewiring Coefficient, to quantify the rewiring of gene co-expression networks at the level of individual genes. Differential correlation analysis demonstrated distinct pathways were rewired during tumorigenesis. Our data support an immune suppressive effect of high doses of estrogen signaling in breast tumor microenvironment, suggesting that this effect contributes to the greater presence of prognostic and therapeutically relevant immune cells in ER-negative tumors.