miR-9a minimizes the phenotypic impact of genomic diversity by buffering a transcription factor.

Gene expression has to withstand stochastic, environmental, and genomic perturbations. For example, in the latter case, 0.5%-1% of the human genome is typically variable between any two unrelated individuals. Such diversity might create problematic variability in the activity of gene regulatory networks and, ultimately, in cell behaviors. Using multigenerational selection experiments, we find that for the Drosophila proneural network, the effect of genomic diversity is dampened by miR-9a-mediated regulation of senseless expression. Reducing miR-9a regulation of the Senseless transcription factor frees the genomic landscape to exert greater phenotypic influence. Whole-genome sequencing identified genomic loci that potentially exert such effects. A larger set of sequence variants, including variants within proneural network genes, exhibits these characteristics when miR-9a concentration is reduced. These findings reveal that microRNA-target interactions may be a key mechanism by which the impact of genomic diversity on cell behavior is dampened.

One-step growth of Cu-doped carbon dots in amino-modified carbon nanotube-modified electrodes for sensitive electrochemical detection of BPA.

Copper-doped carbon dots and aminated carbon nanotubes (Cu-CDs/NH2-CNTs) nanocomposites were synthesized by a one-step growth method, and the composites were characterized for their performance. An electrochemical sensor for sensitive detection of bisphenol A (BPA) was developed for using Cu-CDs/NH2-CNTs nanocomposites modified with glassy carbon electrodes (GCE). The sensor exhibited an excellent electrochemical response to BPA in 0.2 M PBS (pH 7.0) under optimally selected conditions. The linear range of the sensor for BPA detection was 0.5-160 µM, and the detection limit (S/N = 3) was 0.13 µM. Moreover, the sensor has good interference immunity, stability and reproducibility. In addition, the feasibility of the practical application of the sensor was demonstrated by the detection of BPA in bottled drinking water and Liu Yang River water.

Truncation mutations in MYRF underlie primary angle closure glaucoma.

Mutations in myelin regulatory factor (MYRF), a gene mapped to 11q12-q13.3, are responsible for autosomal dominant high hyperopia and seem to be associated with angle closure glaucoma, which is one of the leading causes of irreversible blindness worldwide. Whether there is a causal link from the MYRF mutations to the pathogenesis of primary angle-closure glaucoma (PACG) remains unclear at this time. Six truncation mutations, including five novel and one previously reported, in MYRF are identified in seven new probands with hyperopia, of whom all six adults have glaucoma, further confirming the association of MYRF mutations with PACG. Immunofluorescence microscopy demonstrates enriched expression of MYRF in the ciliary body and ganglion cell layer in humans and mice. Myrfmut/+ mice have elevated IOP and fewer ganglion cells along with thinner retinal nerve fiber layer with ganglion cell layer than wild-type. Transcriptome sequencing of Myrfmut/+ retinas shows downregulation of Dnmt3a, a gene previously associated with PACG. Co-immunoprecipitation demonstrates a physical association of DNMT3A with MYRF. DNA methylation sequencing identifies several glaucoma-related cell events in Myrfmut/+ retinas. The interaction between MYRF and DNMT3A underlies MYRF-associated PACG and provides clues for pursuing further investigation into the pathogenesis of PACG and therapeutic target.

Tolerogenic dendritic cells alleviate collagen-induced arthritis by forming microchimerism and affecting the expression of immune checkpoint molecules.

Tolerogenic dendritic cells (tolDCs) have the potential to treat rheumatoid arthritis (RA) by inducing immune tolerance. However, the mechanism of intervention needs further study. Here, we investigated whether tolDCs formed microchimerism and their effect on the expression of immune checkpoint molecules after infusion of tolDCs into rats with collagen-induced arthritis (CIA). TolDCs derived from male SD rats were labeled with fluorescence and infused into female CIA rats. The fluorescence signals as well as the sex-determining region of Y-chromosome (SRY) gene revealed that tolDCs formed microchimerism in the mesenteric lymph nodes and ankle joints. We further explored the effect of tolDCs on the expression of immune checkpoint molecules in mesenteric lymph nodes and ankle joints. For stimulatory immune checkpoint molecules, the expressions of CD86 and CD40 decreased in mesenteric lymph nodes, and the expressions of CD40, CD40L, CD28, CD80, and CD86 also decreased in rat ankle joints. In contrast, the inhibitory immune checkpoint molecule PDL1 increased in mesenteric lymph nodes, and PD1, PDL1, and CTLA4 increased in ankle joints. In conclusion, our results suggested that intervention of tolDCs in CIA is associated with the formation of microchimerism and the effect on immune checkpoints.

A flexible quasi-likelihood model for microbiome abundance count data.

In this article, we present a flexible model for microbiome count data. We consider a quasi-likelihood framework, in which we do not make any assumptions on the distribution of the microbiome count except that its variance is an unknown but smooth function of the mean. By comparing our model to the negative binomial generalized linear model (GLM) and Poisson GLM in simulation studies, we show that our flexible quasi-likelihood method yields valid inferential results. Using a real microbiome study, we demonstrate the utility of our method by examining the relationship between adenomas and microbiota. We also provide an R package "fql" for the application of our method.

Comparison of State-of-the-Art Neural Network Survival Models with the Pooled Cohort Equations for Cardiovascular Disease Risk Prediction.

BACKGROUND: The Pooled Cohort Equations (PCEs) are race- and sex-specific Cox proportional hazards (PH)-based models used for 10-year atherosclerotic cardiovascular disease (ASCVD) risk prediction with acceptable discrimination. In recent years, neural network models have gained increasing popularity with their success in image recognition and text classification. Various survival neural network models have been proposed by combining survival analysis and neural network architecture to take advantage of the strengths from both. However, the performance of these survival neural network models compared to each other and to PCEs in ASCVD prediction is unknown. METHODS: In this study, we used 6 cohorts from the Lifetime Risk Pooling Project (with 5 cohorts as training/internal validation and one cohort as external validation) and compared the performance of the PCEs in 10-year ASCVD risk prediction with an all two-way interactions Cox PH model (Cox PH-TWI) and three state-of-the-art neural network survival models including Nnet-survival, Deepsurv, and Cox-nnet. For all the models, we used the same 7 covariates as used in the PCEs. We fitted each of the aforementioned models in white females, white males, black females, and black males, respectively. We evaluated models' internal and external discrimination power and calibration. RESULTS: The training/internal validation sample comprised 23216 individuals. The average age at baseline was 57.8 years old (SD = 9.6); 16% developed ASCVD during average follow-up of 10.50 (SD = 3.02) years. Based on 10 × 10 cross-validation, the method that had the highest C-statistics was Deepsurv (0.7371) for white males, Deepsurv and Cox PH-TWI (0.7972) for white females, PCE (0.6981) for black males, and Deepsurv (0.7886) for black females. In the external validation dataset, Deepsurv (0.7032), Cox-nnet (0.7282), PCE (0.6811), and Deepsurv (0.7316) had the highest C-statistics for white male, white female, black male, and black female population, respectively. Calibration plots showed that in 10 × 10 validation, all models had good calibration in all race and sex groups. In external validation, all models overestimated the risk for 10-year ASCVD. CONCLUSIONS: We demonstrated the use of the state-of-the-art neural network survival models in ASCVD risk prediction. Neural network survival models had similar if not superior discrimination and calibration compared to PCEs.

Association of MicroRNA-10b Expression and P16 with Pathological Features in Various Stages of Cervical Precancerous Lesions.

Cervical cancer is the fourth most prevalent cancer for females with 14,100 new cases each year globally. Efficient screening and intervention at the precancerous stage is the key point to the prevention and treatment of cervical cancer. However, no widely recognized biomarkers have been discovered yet. We investigated the expression of miR-10b in cervical cells and its correlation with clinicopathological features in different pathological grades of cervical precancerous lesions. The expression of miR-10b in cervical cytology samples from 20 cases of LSIL, 22 cases of HSIL, 18 cases of early-stage cervical cancer, and 20 cases of cervicitis controls were assessed using qPCR. From the same cervical cytology samples, the human papillomavirus (HPV) load was assessed using semi-PCR and the lesion size, and gland involvement levels from the same subjects were assessed during the cervical examination. The correlation between miR-10b expression and different pathological grades of cervical lesions was analyzed. We also calculated the correlation between HPV load, lesion size, gland involvement, P16 expression, and different pathological grades. The expression of miR-10b exhibited a step-decreasing manner from cervicitis control (4.23(4.00,4.71)) to LSIL (2.67(2.52,2.90)), HSIL (1.49(1.30,1.80)) and cervical cancer group (0.65(0.55,0.80)). There is a significant difference (P<0.001) between cervicitis and HSIL, cervicitis and cervical cancer, ISIL and HSIL, as well as ISIL and cervical cancer but not between the cervicitis group and the LSIL group. In addition, more severe pathological grades were correlated with a bigger rate of gland involvement (P＜0.001). We also found that different pathological grades were correlated with the intensity of P16 expression (P=0.001), and the intensity of P16 expression is positively correlated with different pathological grades (P<0.05). Repressed expression of miR-10b is related to the progression of cervical precancerous lesions. Increased gland involvement rate and increased intensity of P16 expression are risk factors for developing cervical cancers. Our result showed that miR-10b may be a potential biomarker for the screening and ranking of cervical precancerous lesions.

Design, Preparation and Properties of Polyurethane Dispersions via Prepolymer Method.

A waterborne polyurethane dispersion for foamed synthetic leather base was designed and prepared using prepolymer method. There are many variables in the emulsification and chain-extension process of waterborne polyurethane (WPUR) dispersions prepared by prepolymer method. This work thoroughly evaluated the impacts of the steps of adding emulsified water, the temperature of the prepolymer and emulsified water, and concentration of ammonia water on WPUR dispersions by investigating the particle sizes/distributions and the mechanical stability. Changes in the temperature of the prepolymer and emulsified water, the concentration of ammonia water, and the step of adding emulsified water showed great impacts on the appearance and particle size of dispersions. Decreasing the temperature of the prepolymer and emulsified water and increasing the dilution ration of H2O to ethylenediamine (EDA) led to safe emulsification and dispersions with good appearance and narrow particle size distributions can be prepared. Surprising results were obtained by adding emulsified water in two steps, WPUR dispersions with a small particle size, narrow particle distribution and excellent tensile properties can be obtained. The optimized WPUR1 was applied to prepare water-based synthetic leather base after mechanical foaming, and the base presented the desired high performance, such as high folding resistance and peel strength.

NinimHMDA: neural integration of neighborhood information on a multiplex heterogeneous network for multiple types of human Microbe-Disease association.

MOTIVATION: Many computational methods have been recently proposed to identify differentially abundant microbes related to a single disease; however, few studies have focused on large-scale microbe-disease association prediction using existing experimentally verified associations. This area has critical meanings. For example, it can help to rank and select potential candidate microbes for different diseases at-scale for downstream lab validation experiments and it utilizes existing evidence instead of the microbiome abundance data which usually costs money and time to generate. RESULTS: We construct a multiplex heterogeneous network (MHEN) using human microbe-disease association database, Disbiome and other prior biological databases, and define the large-scale human microbe-disease association prediction as link prediction problems on MHEN. We develop an end-to-end graph convolutional neural network-based mining model NinimHMDA which can not only integrate different prior biological knowledge but also predict different types of microbe-disease associations (e.g. a microbe may be reduced or elevated under the impact of a disease) using one-time model training. To the best of our knowledge, this is the first method that targets on predicting different association types between microbes and diseases. Results from large-scale cross validation and case studies show that our model is highly competitive compared to other commonly used approaches. AVAILABILITYAND IMPLEMENTATION: The codes are available at Github https://github.com/yuanjing-ma/NinimHMDA. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Extended graphical lasso for multiple interaction networks for high dimensional omics data.

There has been a spate of interest in association networks in biological and medical research, for example, genetic interaction networks. In this paper, we propose a novel method, the extended joint hub graphical lasso (EDOHA), to estimate multiple related interaction networks for high dimensional omics data across multiple distinct classes. To be specific, we construct a convex penalized log likelihood optimization problem and solve it with an alternating direction method of multipliers (ADMM) algorithm. The proposed method can also be adapted to estimate interaction networks for high dimensional compositional data such as microbial interaction networks. The performance of the proposed method in the simulated studies shows that EDOHA has remarkable advantages in recognizing class-specific hubs than the existing comparable methods. We also present three applications of real datasets. Biological interpretations of our results confirm those of previous studies and offer a more comprehensive understanding of the underlying mechanism in disease.

One-Step Co-Electrodeposition of Copper Nanoparticles-Chitosan Film-Carbon Nanoparticles-Multiwalled Carbon Nanotubes Composite for Electroanalysis of Indole-3-Acetic Acid and Salicylic Acid.

A sensitive simultaneous electroanalysis of phytohormones indole-3-acetic acid (IAA) and salicylic acid (SA) based on a novel copper nanoparticles-chitosan film-carbon nanoparticles-multiwalled carbon nanotubes (CuNPs-CSF-CNPs-MWCNTs) composite was reported. CNPs were prepared by hydrothermal reaction of chitosan. Then the CuNPs-CSF-CNPs-MWCNTs composite was facilely prepared by one-step co-electrodeposition of CuNPs and CNPs fixed chitosan residues on modified electrode. Scanning electron microscope (SEM), transmission electron microscopy (TEM), selected area electron diffraction (SAED), energy dispersive spectroscopy (EDS), X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FT-IR), cyclic voltammetry (CV), electrochemical impedance spectroscopy (EIS), and linear sweep voltammetry (LSV) were used to characterize the properties of the composite. Under optimal conditions, the composite modified electrode had a good linear relationship with IAA in the range of 0.01-50 µM, and a good linear relationship with SA in the range of 4-30 µM. The detection limits were 0.0086 µM and 0.7 µM (S/N = 3), respectively. In addition, the sensor could also be used for the simultaneous detection of IAA and SA in real leaf samples with satisfactory recovery.

Egg Protein Transferrin-Derived Peptides Irw (Lle-Arg-Trp) and Iqw (Lle-Gln-Trp) Prevent Obesity Mouse Model Induced by a High-Fat Diet via Reducing Lipid Deposition and Reprogramming Gut Microbiota.

Egg-derived peptides play important roles in insulin secretion and sensitivity, oxidative stress, and inflammation, suggesting their possible involvement in obesity management. Hence, the aim of this study is to explore the alleviating effects of IRW (lle-Arg-Trp) and IQW (lle-Gln-Trp) on obesity via the mouse model induced by a high-fat diet. The entire experimental period lasted eight weeks. The results demonstrated that IQW prevented weight gain (6.52%), decreased the glucose, low-density lipoprotein (LDL), malonaldehyde, triglycerides, total cholesterol (TC), and leptin levels, and increased the concentration of adiponectin (p < 0.05, n = 8). Although IRW failed to prevent weight gain, it reduced the concentration of glucose, high-density lipoprotein (HDL), LDL, and leptin, and increased the concentration of adiponectin (p < 0.05, n = 8). Moreover, IRW and IQW increased glucose tolerance and insulin resistance based on the results of the intraperitoneal glucose test and insulin tolerance test (p < 0.05, n = 8). The quantitative polymerase chain reaction results revealed that IRW and IQW downregulated the mRNA expression of DGAT1 (Diacylglycerol O-Acyltransferase 1), DGAT2 (Diacylglycerol O-Acyltransferase 2), TNF-α, IL-6, and IL-1ß of liver tissue (p < 0.05, n = 8). The results of the 16S ribosomal RNA amplicon sequencing showed that IQW and IRW tended to reduce the relative abundance of Firmicutes and Parabacteroides, and that IRW enhanced the abundance of Bacteroides (p < 0.05, n = 8). Collectively, IRW and IQW supplementation could alleviate the progression of obesity due to the fact that the supplementation reduced lipid deposition, maintained energy balance, and reprogrammed gut microbiota.

Three-dimensional flower-like magnetic CoFe-LDHs/CoFe2O4 composites activating peroxymonosulfate for high efficient degradation of aniline.

In this study, 3D flower-like magnetic CoFe-LDHs/CoFe2O4 was prepared by a facile urea hydrothermal method and utilized to activate peroxymonosulfate (PMS) for degrading aniline (AN). CoFe-LDHs/CoFe2O4 was systematically characterized to explore the relationship between its structure and catalytic performance. Compared with CoFe-LDHs synthesized by co-precipitation method, CoFe-LDHs/CoFe2O4 exhibited three dimensional structure and larger specific surface, which could increase the degradation efficiency of AN markedly. 96% of 10 mg L-1 AN could be eliminated by 0.3 mM PMS and 50 mg L-1 CoFe-LDHs/CoFe2O4 at initial pH 6 within 5 min and the total organic carbon (TOC) removal efficiency could be high to 52.8% in 30 min. CoFe-LDHs/CoFe2O4 can be separated by a magnet easily due to its magnetism, which makes it avoid secondary pollution and provide convenience. After recycling six times, the degradation efficiency still maintained at 92.6%. Besides, CoFe-LDHs/CoFe2O4/PMS can degrade AN in practical water samples effectively. In addition, the possible mechanism of CoFe-LDHs/CoFe2O4/PMS system for the degradation of AN was proposed. The radical scavenging experiments confirmed that SO4·-, HO· and O2·- were involved and SO4·- played a dominant role in the degradation of AN, and it was further proved by electron Paramagnetic Resonance (EPR) as well. Our findings can provide some new insights into the efficient and skillful design and application of heterogeneous catalyst for environmental remediation.

Circadian misalignment leads to changes in cortisol rhythms, blood biochemical variables and serum miRNA profiles.

The circadian clock plays a critical role in synchronizing the inner molecular, metabolic and physiological processes to environmental cues that cycle with a period of 24 h. Non-24 h and shift schedules are commonly used in maritime operations, and both of which can disturb circadian rhythms. In this study, we first conducted an experiment in which the volunteers followed a 3-d rotary schedule with consecutive shift in sleep time (rotatory schedule), and analyzed the changes in salivary cortisol rhythms and blood variables. Next we conducted another experiment in which the volunteers followed an 8 h-on and 4-h off schedule (non-24-h schedule) to compare the changes in blood/serum variables. The rotatory schedule led to elevated levels of serum cortisol during the early stage, and the phase became delayed during the early and late stages. Interestingly, both of the schedules caused comprehensive changes in blood/serum biochemical variables and increased phosphate levels. Furthermore, transcriptomic analysis of the plasma miRNAs from the volunteers following the rotatory schedule identified a subset of serum miRNAs targeting genes involved in circadian rhythms, sleep homeostasis, phosphate transport and multiple important physiological processes. Overexpression of miRNAs targeting the phosphate transport associated genes, SLC20A1 and SLC20A2, showed altered expression due to rotary schedule resulted in attenuated cellular levels of phosphate, which might account for the changed levels in serum phosphate. These findings would further our understanding of the deleterious effects of shift schedules and help to optimize and enhance the performances and welfare of personnel working on similar schedules.

A novel normalization and differential abundance test framework for microbiome data.

MOTIVATION: Microbial communities have been proved to have close relationship with many diseases. The identification of differentially abundant microbial species is clinically meaningful for finding disease-related pathogenic or probiotic bacteria. However, certain characteristics of microbiome data have hurdled the accuracy and effectiveness of differential abundance analysis. The abundances or counts of microbiome species are usually on different scales and exhibit zero-inflation and over-dispersion. Normalization is a crucial step before the differential abundance test. However, existing normalization methods typically try to adjust counts on different scales to a common scale by constructing size factors with the assumption that count distributions across samples are equivalent up to a certain percentile. These methods often yield undesirable results when differentially abundant species are of low to medium abundance level. For differential abundance analysis, existing methods often use a single distribution to model the dispersion of species which lacks flexibility to catch a single species' distinctiveness. These methods tend to detect a lot of false positives and often lack of power when the effect size is small. RESULTS: We develop a novel framework for differential abundance analysis on sparse high-dimensional marker gene microbiome data. Our methodology relies on a novel network-based normalization technique and a two-stage zero-inflated mixture count regression model (RioNorm2). Our normalization method aims to find a group of relatively invariant microbiome species across samples and conditions in order to construct the size factor. Another contribution of the paper is that our testing approach can take under-sampling and over-dispersion into consideration by separating microbiome species into two groups and model them separately. Through comprehensive simulation studies, the performance of our method is consistently powerful and robust across different settings with different sample size, library size and effect size. We also demonstrate the effectiveness of our novel framework using a published dataset of metastatic melanoma and find biological insights from the results. AVAILABILITY AND IMPLEMENTATION: The R package 'RioNorm2' can be installed from Github athttps://github.com/yuanjing-ma/RioNorm2. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Photoinduced efficient synthesis of cyanoalkylsulfonylated oxindoles via sulfur dioxide insertion.

A visible-light-promoted radical cascade reaction of N-arylacrylamide and cyclobutanone oxime esters with sulfur dioxide insertion is established. Mainly through the exploration of the visible light wavelength, it is found that the light source has a certain influence on the formation of cyanoalkylsulfonylated oxindoles, furnishing a range of sulfones in good to excellent yields. This protocol presents good functional group compatibility and does not require transition metals, photosensitizers, external bases, or oxidants.

Effects of IQW and IRW on Inflammation and Gut Microbiota in ETEC-Induced Diarrhea.

METHODS: The mice were randomly distributed into four groups: (a) control (CTRL) group, (b) ETEC group, (c) IQW-ETEC group, and (d) IRW-ETEC group. Villus length and crypt depth were measured after hematoxylin and eosin staining. The inflammatory reaction was analyzed via inflammatory cytokines (i.e., TNF-α, IL-1ß, IL-6, and IL-10) using the enzyme-linked immunosorbent assay (ELISA). The microbiota in the colon was sequenced using 16S ribosomal RNA. RESULTS: The villus length decreased, the crypt depth decreased, and the expression of inflammatory cytokines (i.e., TNF-α, IL-1ß, IL-6, and IL-10) increased due to ETEC. In the IRW-ETEC and IQW-ETEC groups, the Shannon index decreased (P < 0.05). IQW and IRW increased the abundance of Firmicutes, Proteobacteria, Clostridiales, Lachnospiraceae, and Alloprevotella; contrastingly, it decreased the abundance of Epsilonproteobacteria, Erysipelotrichales, Prevotellaceae, and Flavobacteriaceae compared to the ETEC group (P <0.05). CONCLUSION: This study ascertained that the addition of IQW and IRW could alleviate jejunal inflammation and increase microbiota community diversity.

Degradation and effect of 6:2 fluorotelomer alcohol in aerobic composting of sludge.

Perfluoroalkyl carboxylates (PFCAs) is toxic to the environment and human health. However, the degradation characteristics of fluorotelomer alcohols (FTOHs), precursors of PFACAs biodegradation, in the sludge during aerobic composting remain unclear. In this study, the degradation characteristics of 6:2 FTOH in sewage sludge by composting were researched and the influences of 6:2 FTOH on the composting process and microbial communities of the sludge were evaluated. After 52 days of composting, 6:2 FTOH retained only 0.73% of its original concentration, and its half-life was less than 1 d; 6:2 FTOH was degraded finally to perfluorohex unsaturated acid, perfluoropentanoic acid, 5:3 polyfluorinated acid (FTCA), 4:3 FTCA, and perfluorobutanoic acid through two pathways; and 6:2 FTCA and 6:2 fluorotel unsaturated acid were the intermediate products. Notably, dosing with 6:2 FTOH affected the composting process of sewage sludge. Additionally, 50 mg/kg 6:2 FTOH resulted in a decrease in the microbial richness and diversity of sludge compost. When compared with the compost without 6:2 FTOH, the proportion of Proteobacteria had increased, and the proportion of Firmicutes had decreased as the concentration of 6:2 FTOH increased. The negative effect of a dosage of 50 mg/kg 6:2 FTOH was more obvious than the effect of other treatments. This study expanded our understanding of the risk of sludge contaminated by 6:2 FTOH being used as a fertilizer after composting.

Development of resistance to FAK inhibition in pancreatic cancer is linked to stromal depletion.

OBJECTIVE: We investigated how pancreatic cancer developed resistance to focal adhesion kinase (FAK) inhibition over time. DESIGN: Pancreatic ductal adenocarcinoma (PDAC) tumours from KPC mice (p48-CRE; LSL-KRasG12D/wt; p53flox/wt) treated with FAK inhibitor were analysed for the activation of a compensatory survival pathway in resistant tumours. We identified pathways involved in the regulation of signal transducer and activator of transcription 3 (STAT3) signalling on FAK inhibition by gene set enrichment analysis and verified these outcomes by RNA interference studies. We also tested combinatorial approaches targeting FAK and STAT3 in syngeneic transplantable mouse models of PDAC and KPC mice. RESULTS: In KPC mice, the expression levels of phosphorylated STAT3 (pSTAT3) were increased in PDAC cells as they progressed on FAK inhibitor therapy. This progression corresponded to decreased collagen density, lowered numbers of SMA+ fibroblasts and downregulation of the transforming growth factor beta (TGF-ß)/SMAD signalling pathway in FAK inhibitor-treated PDAC tumours. Furthermore, TGF-ß production by fibroblasts in vitro drives repression of STAT3 signalling and enhanced responsiveness to FAK inhibitor therapy. Knockdown of SMAD3 in pancreatic cancer cells abolished the inhibitory effects of TGF-ß on pSTAT3. We further found that tumour-intrinsic STAT3 regulates the durability of the antiproliferative activity of FAK inhibitor, and combinatorial targeting of FAK and Janus kinase/STAT3 act synergistically to suppress pancreatic cancer progression in mouse models. CONCLUSION: Stromal depletion by FAK inhibitor therapy leads to eventual treatment resistance through the activation of STAT3 signalling. These data suggest that, similar to tumour-targeted therapies, resistance mechanisms to therapies targeting stromal desmoplasia may be critical to treatment durability.

Frequency and clinicopathologic associations of DNA mismatch repair protein deficiency in ampullary carcinoma: Routine testing is indicated.

BACKGROUND: The significance of DNA mismatch repair (MMR) deficiency in ampullary cancers (ACs) has not been established. METHODS: In total, 127 ACs with invasive carcinomas measuring ≥3 mmthat had adequate tissue were analyzed immunohistochemically. RESULTS: MMR loss was detected in 18% of ACs (higher than in colorectal cancers). Twelve tumors with MLH1-PMS2 loss were negative for BRAF V600E mutation, suggesting a Lynch syndrome association. MMR-deficient tumors (n = 23), comparedwith MMR-intact tumors (n = 104), showed a striking male predominance (male:female ratio, 4.7). Although the deficient tumors had slightly larger invasion size (2.7 vs 2.1 cm), they also had more expansile growth and less invasiveness, including less perineural invasion, and they ultimately had lower tumor (T) classification and less lymph node metastasis (30% vs 53%; P = .04). More important, patients who had MMR-deficient tumors had better clinical outcomes, with a 5-year overall survival rate of 68% versus 45% (P = .03), which was even more pronounced in those who had higher Tclassification (5-year overall survival, 69% vs 34%; P = .04). MMR deficiencyhad a statistically significant association with medullary phenotype, pushing-border invasion, and tumor-infiltrating immune cells, and it occurred more frequently in ampullary-duodenal type tumors. Programed cell death-ligand 1 (PD-L1) levels analyzed in the 22 MMR-deficient ACs revealed that all medullary carcinomas were positive. Nonmedullary MMR-deficient carcinomas expressed PD-L1 in 33% of tumors cells according to the criteria for a combined positive score ≥1, but all were negative according to the tumor proportion score≥1 method. CONCLUSIONS: In ACs, MMR deficiency is even more frequent (18%) than in colon cancer and often has a Lynch-suggestive profile, thus routine testing is warranted. Male gender, pushing-border infiltration, ampullary-duodenal origin, medullary histology, and tumor-related inflammation have a significantly higher association with MMR deficiency. MMR-deficient tumors have less aggressive behavior. PD-L1 expression is common in medullary-phenotype ACs, thus immunotherapy should be considered at least for this group.