Developmental expression of claudins in the mammary gland

Claudins are a large family of membrane proteins whose classic function is to regulate the permeability of tight junctions in epithelia. They are tetraspanins, with four alpha-helices crossing the membrane, two extracellular loops, a short cytoplasmic N-terminus and a longer and more variable C-terminus. The extracellular ends of the helices are known to undergo side-to-side (cis) interactions that allow the formation of claudin polymers in the plane of the membrane. The extracellular loops also engage in head-to-head (trans) interactions thought to mediate the formation of tight junctions. However, claudins are also present in intracellular structures, thought to be vesicles, with less well-characterized functions. Here, we briefly review our current understanding of claudin structure and function followed by an examination of changes in claudin mRNA and protein expression and localization through mammary gland development. Claudins-1, 3, 4, 7, and 8 are the five most prominent members of the claudin family in the mouse mammary gland, with varied abundance and intracellular localization during the different stages of post-pubertal development. Claudin-1 is clearly localized to tight junctions in mammary ducts in non-pregnant non-lactating animals. Cytoplasmic puncta that stain for claudin-7 are present throughout development. During pregnancy claudin-3 is localized both to the tight junction and basolaterally while claudin-4 is found only in sparse puncta. In the lactating mouse both claudin-3 and claudin-8 are localized at the tight junction where they may be important in forming the paracellular barrier. At involution and under challenge by lipopolysaccharide claudins -1, -3, and -4 are significantly upregulated. Claudin-3 is still colocalized with tight junction molecules but is also distributed through the cytoplasm as is claudin-4. These largely descriptive data provide the essential framework for future mechanistic studies of the function and regulation of mammary epithelial cell claudins

Genes, Education, and Labor Market Outcomes: Evidence from the Health and Retirement Study

Recent advances have led to the discovery of specific genetic variants that predict educational attainment. We study how these variants, summarized as a genetic score variable, are associated with human capital accumulation and labor market outcomes in the Health and Retirement Study (HRS). We demonstrate that the same genetic score that predicts education is also associated with higher wages, but only among individuals with a college education. Moreover, the genetic gradient in wages has grown in more recent birth cohorts, consistent with interactions between technological change and labor market ability. We also show that individuals who grew up in economically disadvantaged households are less likely to go to college when compared to individuals with the same genetic score, but from higher socioeconomic status households. Our findings provide support for the idea that childhood socioeconomic status is an important moderator of the economic returns to genetic endowments. Moreover, the finding that childhood poverty limits the educational attainment of high-ability individuals suggests the existence of unrealized human potential

SMASH: Scalable Method for Analyzing Spatial Heterogeneity of genes in spatial transcriptomics data.

In high-throughput spatial transcriptomics (ST) studies, it is of great interest to identify the genes whose level of expression in a tissue covaries with the spatial location of cells/spots. Such genes, also known as spatially variable genes (SVGs), can be crucial to the biological understanding of both structural and functional characteristics of complex tissues. Existing methods for detecting SVGs either suffer from huge computational demand or significantly lack statistical power. We propose a non-parametric method termed SMASH that achieves a balance between the above two problems. We compare SMASH with other existing methods in varying simulation scenarios demonstrating its superior statistical power and robustness. We apply the method to four ST datasets from different platforms uncovering interesting biological insights

SPOP E3 Ubiquitin Ligase Adaptor Promotes Cellular Senescence by Degrading the SENP7 deSUMOylase

The SPOP gene, which encodes an E3 ubiquitin ligase adaptor, is frequently mutated in a number of cancer types. However, the mechanisms by which SPOP functions as a tumor suppressor remain poorly understood. Here, we show that SPOP promotes senescence, an important tumor suppression mechanism, by targeting the SENP7 deSUMOylase for degradation. SPOP is upregulated during senescence. This correlates with ubiquitin-mediated degradation of SENP7, which promotes senescence by increasing HP1α sumoylation and the associated epigenetic gene silencing. Ectopic wild-type SPOP, but not its cancer-associated mutants, drives senescence. Conversely, SPOP knockdown overcomes senescence. These phenotypes correlate with ubiquitination and degradation of SENP7 and HP1α sumoylation, subcellular re-localization, and its associated gene silencing. Furthermore, SENP7 is expressed at higher levels in prostate tumor specimens with SPOP mutation (n = 13) compared to those with wild-type SPOP (n = 80). In summary, SPOP acts as a tumor suppressor by promoting senescence through degrading SENP7

The SETDB1-TRIM28 Complex Suppresses Antitumor Immunity

The tumor immune microenvironment is influenced by the epigenetic landscape of the tumor. Here, we have identified the SETDB1–TRIM28 complex as a critical suppressor of antitumor immunity. An epigenetic CRISPR-Cas9 screen of 1,218 chromatin regulators identified TRIM28 as a suppressor of PD-L1 expression. We then revealed that expression of the SETDB1–TRIM28 complex negatively correlated with infiltration of effector CD8(+) T cells. Inhibition of SETDB1–TRIM28 simultaneously upregulated PD-L1 and activated the cGAS–STING innate immune response pathway to increase infiltration of CD8(+) T cells. Mechanistically, SETDB1–TRIM28 inhibition led to micronuclei formation in the cytoplasm, which is known to activate the cGAS–STING pathway. Thus, SETDB1–TRIM28 inhibition bridges innate and adaptive immunity. Indeed, SETDB1 knockout enhanced the antitumor effects of immune checkpoint blockade with anti–PD-L1 in a mouse model of ovarian cancer in a cGAS-dependent manner. Our findings establish the SETDB1–TRIM28 complex as a regulator of antitumor immunity and demonstrate that its loss activates cGAS–STING innate immunity to boost the antitumor effects of immune checkpoint blockade

A platform-independent framework for phenotyping of multiplex tissue imaging data.

Multiplex imaging is a powerful tool to analyze the structural and functional states of cells in their morphological and pathological contexts. However, hypothesis testing with multiplex imaging data is a challenging task due to the extent and complexity of the information obtained. Various computational pipelines have been developed and validated to extract knowledge from specific imaging platforms. A common problem with customized pipelines is their reduced applicability across different imaging platforms: Every multiplex imaging technique exhibits platform-specific characteristics in terms of signal-to-noise ratio and acquisition artifacts that need to be accounted for to yield reliable and reproducible results. We propose a pixel classifier-based image preprocessing step that aims to minimize platform-dependency for all multiplex image analysis pipelines. Signal detection and noise reduction as well as artifact removal can be posed as a pixel classification problem in which all pixels in multiplex images can be assigned to two general classes of either I) signal of interest or II) artifacts and noise. The resulting feature representation maps contain pixel-scale representations of the input data, but exhibit significantly increased signal-to-noise ratios with normalized pixel values as output data. We demonstrate the validity of our proposed image preprocessing approach by comparing the results of two well-accepted and widely-used image analysis pipelines