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Abstract Understanding interplay of breast cancer and microenvironment is critical. Here we identified two transcriptomic subtypes and five immune infiltration patterns from RNA-seq and multiplex immunohistochemistry from 21 ER + /HER2- ILCs. We found proliferative subtype associated with increased suppressive immune infiltration, and defined a signature associated with lower proliferative, pro-inflammatory TAM infiltration, and improved survival in ER+ breast cancer. Our work identified genes related to ILC immune microenvironment and prognosis.

Background and Aims: Necrotizing enterocolitis is a severe gastrointestinal complication of prematurity. Using small intestinal organoids derived from fetal tissue of a gestational age similar to an extremely preterm infant, this study aims to assess the effect of diet on intestinal epithelial growth and differentiation to elucidate the role nutrition type plays in intestinal development and modifies the risk for necrotizing enterocolitis. Methods: Organoids were cultured for 5 days in growth media and 5 days in differentiation media supplemented 1:40 with 4 different diets: parental milk, donor human milk, standard formula, or extensively hydrolyzed formula. Images were captured daily and organoids were quantified. Organoids were preserved for RNA sequencing and immunofluorescence staining with Ki67, cleaved caspase 3, and chromogranin-A. Media was saved for cytokine/chemokine and growth factor analysis. Results: Human milk supplementation improved growth and differentiation of intestinal organoids generating larger organoids during the growth phase and organoids with longer and wider buds during differentiation compared to formula. Ki67 staining confirmed the proliferative nature of milk-supplemented organoids and chromogranin A staining proved that MM-supplemented organoids induced highest enteroendocrine differentiation. Human milk supplementation also upregulated genes involved in Wnt signaling and fatty acid metabolism pathways and promoted a homeostatic immune landscape, including via increased secretion of tumor necrosis factor-related apoptosis-inducing ligand among other cytokines. Conversely, organoids supplemented with formula had a downregulation of cell-cycle-promoting genes and a more inflammatory immune signature, including a reduced level of leukemia inhibitory factor. Conclusion: Our results demonstrate that parental milk, and to a lesser extent donor human milk, support robust intestinal epithelial proliferation, differentiation, and homeostatic cytokine production, suggesting a critical role for factors enriched in human milk in intestinal epithelial health.

BackgroundBiopsy-based diagnosis is essential for maintaining kidney allograft longevity by ensuring prompt treatment for graft complications. Although histologic assessment remains the gold standard, it carries significant limitations such as subjective interpretation, suboptimal reproducibility, and imprecise quantitation of disease burden. It is hoped that molecular diagnostics could enhance the efficiency, accuracy, and reproducibility of traditional histologic methods.MethodsQuantitative label-free mass spectrometry analysis was performed on a set of formalin-fixed, paraffin-embedded (FFPE) biopsies from kidney transplant patients, including five samples each with diagnosis of T-cell-mediated rejection (TCMR), polyomavirus BK nephropathy (BKPyVN), and stable (STA) kidney function control tissue. Using the differential protein expression result as a classifier, three different machine learning algorithms were tested to build a molecular diagnostic model for TCMR.ResultsThe label-free proteomics method yielded 800-1350 proteins that could be quantified with high confidence per sample by single-shot measurements. Among these candidate proteins, 329 and 467 proteins were defined as differentially expressed proteins (DEPs) for TCMR in comparison with STA and BKPyVN, respectively. Comparing the FFPE quantitative proteomics data set obtained in this study using label-free method with a data set we previously reported using isobaric labeling technology, a classifier pool comprised of features from DEPs commonly quantified in both data sets, was generated for TCMR prediction. Leave-one-out cross-validation result demonstrated that the random forest (RF)-based model achieved the best predictive power. In a follow-up blind test using an independent sample set, the RF-based model yields 80% accuracy for TCMR and 100% for STA. When applying the established RF-based model to two public transcriptome datasets, 78.1%-82.9% sensitivity and 58.7%-64.4% specificity was achieved respectively.ConclusionsThis proof-of-principle study demonstrates the clinical feasibility of proteomics profiling for FFPE biopsies using an accurate, efficient, and cost-effective platform integrated of quantitative label-free mass spectrometry analysis with a machine learning-based diagnostic model. It costs less than 10 dollars per test.

Abstract Background Breast cancer is the most common malignancy to spread to the orbit and periorbit, and the invasive lobular carcinoma (ILC) histologic subtype of breast cancer has been reported to form these ophthalmic metastases (OM) more frequently than invasive ductal carcinomas (IDC). We herein report our single academic institution experience with breast cancer OM with respect to anatomical presentation, histology (lobular vs. ductal), treatment, and survival. Methods We employed the natural language processing platform, TIES (Text Information Extraction System), to search 2.3 million de-identified patient pathology and radiology records at our institution in order to identify patients with OM secondary to breast cancer. We then compared the resultant cohort, the “OM cohort,” to two other representative metastatic breast cancer patient (MBC) databases from our institution. Histological analysis of selected patients was performed. Results Our TIES search and manual refinement ultimately identified 28 patients who were diagnosed with breast cancer between 1995 and 2016 that subsequently developed OM. Median age at diagnosis was 54 (range 28–77) years of age. ER, PR, and HER2 status from the 28 patients with OM did not differ from other patients with MBC from our institution. The relative proportion of patients with ILC was significantly higher in the OM cohort (32.1%) than in other MBC patients in our institution (11.3%, p = 0.007). Median time to first OM in the OM cohort was 46.7 months, and OM were the second most frequent first metastases after bony metastases. After diagnosis of the first distant metastasis of any kind, median survival of patients with ILC (21.4 months) was significantly shorter than that of patients with IDC (55.3 months, p = 0.03). Nine patients developed bilateral OM. We observed a significant co-occurrence of OM and central nervous system metastases (p = 0.0053). The histological analysis revealed an interesting case in which the primary tumor was of a mixed ILC/IDC subtype, while only ILC was present in the OM. Conclusions OM from breast cancer are illustrative of the difference in metastatic behavior of ILC versus IDC and should be considered when treating patients with ILC, especially in those with complaints of visual acuity changes.

Sleep disturbance is common in psychiatric disease, and this may contribute to altered circadian rhythm in gene expression. Here the authors show that rhythms in gene expression in the dorsolateral prefrontal cortex in schizophrenia are different to that seen in healthy controls.

Symbiotic microbial colonization through the establishment of the intestinal microbiome is critical to many intestinal functions, including nutrient metabolism, intestinal barrier integrity, and immune regulation. Recent studies suggest that education of intestinal immunity may be ongoing in utero. However, the drivers of this process are unknown. The microbiome and its byproducts are one potential source. Whether a fetal intestinal microbiome exists is controversial, and whether microbially derived metabolites are present in utero is unknown. Here, we aimed to determine whether bacterial DNA and microbially derived metabolites can be detected in second trimester human intestinal samples. Although we were unable to amplify bacterial DNA from fetal intestines, we report a fetal metabolomic intestinal profile with an abundance of bacterially derived and host-derived metabolites commonly produced in response to microbiota. Though we did not directly assess their source and function, we hypothesize that these microbial-associated metabolites either come from the maternal microbiome and are vertically transmitted to the fetus to prime the fetal immune system and prepare the gastrointestinal tract for postnatal microbial encounters or are produced locally by bacteria that were below our detection threshold.

The progress in the field of high-dimensional cytometry has greatly increased the number of markers that can be simultaneously analyzed producing datasets with large numbers of parameters. Traditional biaxial manual gating might not be optimal for such datasets. To overcome this, a large number of automated tools have been developed to aid with cellular clustering of multi-dimensional datasets. Here were review two large categories of such tools; unsupervised and supervised clustering tools. After a thorough review of the popularity and use of each of the available unsupervised clustering tools, we focus on the top six tools to discuss their advantages and limitations. Furthermore, we employ a publicly available dataset to directly compare the usability, speed, and relative effectiveness of the available unsupervised and supervised tools. Finally, we discuss the current challenges for existing methods and future direction for the new generation of cell type identification approaches.

Sexually transmitted infection (STI) of the upper reproductive tract can result in inflammation and infertility. A biomarker of STI-induced upper tract inflammation would be significant as many women are asymptomatic and delayed treatment increases risk of sequelae. Blood mRNA from 111 women from three cohorts was profiled using microarray. Unsupervised analysis revealed a transcriptional profile that distinguished 9 cases of STI-induced endometritis from 18 with cervical STI or uninfected controls. Using a hybrid feature selection algorithm we identified 21 genes that yielded maximal classification accuracy within our training dataset. Predictive accuracy was evaluated using an independent testing dataset of 5 cases and 10 controls. Sensitivity was evaluated in a separate test set of 12 women with asymptomatic STI-induced endometritis in whom cervical burden was determined by PCR; and specificity in an additional test set of 15 uninfected women with pelvic pain due to unknown cause. Disease module preservation was assessed in 42 women with a clinical diagnosis of pelvic inflammatory disease (PID). We also tested the ability of the biomarker to discriminate STI-induced endometritis from other diseases. The biomarker was 86.7% (13/15) accurate in correctly distinguishing cases from controls in the testing dataset. Sensitivity was 83.3% (5/6) in women with high cervical Chlamydia trachomatis burden and asymptomatic endometritis, but 0% (0/6) in women with low burden. Specificity in patients with non-STI-induced pelvic pain was 86.7% (13/15). Disease modules were preserved in all 8 biomarker predicted cases. The 21-gene biomarker was highly discriminatory for systemic infections, lupus, and appendicitis, but wrongly predicted tuberculosis as STI-induced endometritis in 52.4%. A 21-gene biomarker can identify asymptomatic women with STI-induced endometritis that places them at risk for chronic disease development and discriminate STI-induced endometritis from non-STI pelvic pain and other diseases.

Detection of human genome copy number variation (CNV) is one of the most important analyses in diagnosing human malignancies. Genome CNV detection in formalin-fixed and paraffin-embedded (FFPE) tissues remains challenging due to suboptimal DNA quality and failure to use appropriate baseline controls for such tissues. Here, we report a modified method in analyzing CNV in FFPE tissues using microarray with Affymetrix Cytoscan HD chips. Gel purification was applied to select DNA with good quality and data of fresh frozen and FFPE tissues from healthy individuals were included as baseline controls in our data analysis. Our analysis showed a 91% overlap between CNV detection by microarray with FFPE tissues and chromosomal abnormality detection by karyotyping with fresh tissues on 8 cases of lymphoma samples. The CNV overlap between matched frozen and FFPE tissues reached 93.8%. When the analyses were restricted to regions containing genes, 87.1% concordance between FFPE and fresh frozen tissues was found. The analysis was further validated by Fluorescence In Situ Hybridization on these samples using probes specific for BRAF and CITED2. The results suggested that the modified method using Affymetrix Cytoscan HD chip gave rise to a significant improvement over most of the previous methods in terms of accuracy in detecting CNV in FFPE tissues. This FFPE microarray methodology may hold promise for broad application of CNV analysis on clinical samples.

Breast cancer patients have different responses to chemotherapeutic treatments. Genes associated with drug response can provide insight to understand the mechanisms of drug resistance, identify promising therapeutic opportunities, and facilitate personalized treatment. Estrogen receptor (ER) positive and ER negative breast cancer have distinct clinical behavior and molecular properties. However, to date, few studies have rigorously assessed drug response genes in them. In this study, our goal was to systematically identify genes associated with multidrug response in ER positive and ER negative breast cancer cell lines. We tested 27 human breast cell lines for response to seven chemotherapeutic agents (cyclophosphamide, docetaxel, doxorubicin, epirubicin, fluorouracil, gemcitabine, and paclitaxel). We integrated publicly available gene expression profiles of these cell lines with their in vitro drug response patterns, then applied meta-analysis to identify genes related to multidrug response in ER positive and ER negative cells separately. One hundred eighty-eight genes were identified as related to multidrug response in ER positive and 32 genes in ER negative breast cell lines. Of these, only three genes (DBI, TOP2A, and PMVK) were common to both cell types. TOP2A was positively associated with drug response, and DBI was negatively associated with drug response. Interestingly, PMVK was positively associated with drug response in ER positive cells and negatively in ER negative cells. Functional analysis showed that while cell cycle affects drug response in both ER positive and negative cells, most biological processes that are involved in drug response are distinct. A number of signaling pathways that are uniquely enriched in ER positive cells have complex cross talk with ER signaling, while in ER negative cells, enriched pathways are related to metabolic functions. Taken together, our analysis indicates that distinct mechanisms are involved in multidrug response in ER positive and ER negative breast cells.

Flat epithelial atypia (FEA) is an emerging entity of uncertain clinical significance, and outcome data are sparse. The aim of this study was to evaluate the clinicopathologic significance of this entity for proper management. All core needle biopsy (CNB) specimens diagnosed as atypical ductal hyperplasia (ADH) from January 2006 to April 2008 were retrieved. H&E-stained slides of 5 levels on each case were reviewed. The differences in upstaging in subsequent excisions in the FEA and ADH group (31/189 [16.4%]) vs the pure FEA group (5/35 [14%]) and pure FEA (5/35 [14%]) vs pure ADH (5/45 [11%]) were not statistically significant. We observed that FEA evolved into ADH at the same site at an average of 3 to 4 levels. Our study concludes that there is an association of FEA with ADH on multiple levels of CNB specimens, and follow-up surgical excision findings for FEA are clinically significant. [ABSTRACT FROM AUTHOR]