Transcriptomic Profiling of Subcutaneous Adipose Tissue in Relation to Bariatric Surgery: A Retrospective, Pooled Re-analysis.

Background: Bariatric surgery is the most effective intervention for weight loss possibly through modulating subcutaneous adipose tissue (SAT) molecular programs. The post-operative molecular and biological impacts, including gene expression, deserve in-depth investigation especially given the small sample sizes in the literature. Methods: Five existing datasets (n=237 SATs) were re-processed and corrected for batch-to-batch variation. Unsupervised approaches and robust linear mixed effect model were used to compare gene expression post- (n=126) to pre-operation (n=111). Results: Post-operative SATs showed distinct global gene expression. Forty-four and 395 genes were over- and under-expressed post-operation (all Bonferroni P<0.05). The under-expressed genes significantly enriched for 21 biological processes/pathways (all Bonferroni P<0.05), 17 (76.2%) and two (9.5%) directly involved in immunity and amino/proteo-glycan metabolism, respectively. Conclusion: Post-operative SATs might adopt distinct transcriptomic landscapes and undergo a reduction in immune-related processes and amino/proteo-glycan metabolism.

Decrease in the Size of Fat-Enlarged Axillary Lymph Nodes and Serum Lipids after Bariatric Surgery.

BACKGROUND: Ectopic fat deposition in obesity is associated with organ dysfunction; however, little is known about fat deposition within the lymphatic system and associated lymphatic dysfunction. METHODS: One hundred fifty-five women who underwent routine screening mammography before and after a Roux-en-y gastric bypass or a sleeve gastrectomy were retrospectively reviewed and after excluding women without visible nodes both before and after bariatric surgery, 84 patients were included in the final analysis. Axillary lymph node size, patient weight in kilograms, body mass index, and a diagnosis of hypertension, type 2 diabetes, and dyslipidemia were evaluated before and after surgery. Binary linear regression models and Fischer's exact test were used to evaluate the relationship between the size of fat-infiltrated axillary lymph nodes, patient age, change in patient weight, and diagnosis of hypertension, type 2 diabetes, and dyslipidemia. RESULTS: Fat-infiltrated axillary lymph nodes demonstrated a statistically significant decrease in size after bariatric surgery with a mean decrease of 4.23 mm (95% CI: 3.23 to 5.2, p < 0.001). The resolution of dyslipidemia was associated with a decrease in lymph node size independent of weight loss (p = 0.006). CONCLUSIONS: Mammographically visualized fat-infiltrated axillary lymph nodes demonstrated a statistically significant decrease in size after bariatric surgery. The decrease in lymph node size was significantly associated with the resolution of dyslipidemia, independent of weight loss, age, and type of surgery.

DNA 5-hydroxymethylcytosine in pediatric central nervous system tumors may impact tumor classification and is a positive prognostic marker.

BACKGROUND: Nucleotide-specific 5-hydroxymethylcytosine (5hmC) remains understudied in pediatric central nervous system (CNS) tumors. 5hmC is abundant in the brain, and alterations to 5hmC in adult CNS tumors have been reported. However, traditional approaches to measure DNA methylation do not distinguish between 5-methylcytosine (5mC) and its oxidized counterpart 5hmC, including those used to build CNS tumor DNA methylation classification systems. We measured 5hmC and 5mC epigenome-wide at nucleotide resolution in glioma, ependymoma, and embryonal tumors from children, as well as control pediatric brain tissues using tandem bisulfite and oxidative bisulfite treatments followed by hybridization to the Illumina Methylation EPIC Array that interrogates over 860,000 CpG loci. RESULTS: Linear mixed effects models adjusted for age and sex tested the CpG-specific differences in 5hmC between tumor and non-tumor samples, as well as between tumor subtypes. Results from model-based clustering of tumors was used to test the relation of cluster membership with patient survival through multivariable Cox proportional hazards regression. We also assessed the robustness of multiple epigenetic CNS tumor classification methods to 5mC-specific data in both pediatric and adult CNS tumors. Compared to non-tumor samples, tumors were hypohydroxymethylated across the epigenome and tumor 5hmC localized to regulatory elements crucial to cell identity, including transcription factor binding sites and super-enhancers. Differentially hydroxymethylated loci among tumor subtypes tended to be hypermethylated and disproportionally found in CTCF binding sites and genes related to posttranscriptional RNA regulation, such as DICER1. Model-based clustering results indicated that patients with low 5hmC patterns have poorer overall survival and increased risk of recurrence. Our results suggest 5mC-specific data from OxBS-treated samples impacts methylation-based tumor classification systems giving new opportunities for further refinement of classifiers for both pediatric and adult tumors. CONCLUSIONS: We identified that 5hmC localizes to super-enhancers, and genes commonly implicated in pediatric CNS tumors were differentially hypohydroxymethylated. We demonstrated that distinguishing methylation and hydroxymethylation is critical in identifying tumor-related epigenetic changes. These results have implications for patient prognostication, considerations of epigenetic therapy in CNS tumors, and for emerging molecular neuropathology classification approaches.

MethylSPWNet and MethylCapsNet: Biologically Motivated Organization of DNAm Neural Networks, Inspired by Capsule Networks.

DNA methylation (DNAm) alterations have been heavily implicated in carcinogenesis and the pathophysiology of diseases through upstream regulation of gene expression. DNAm deep-learning approaches are able to capture features associated with aging, cell type, and disease progression, but lack incorporation of prior biological knowledge. Here, we present modular, user-friendly deep-learning methodology and software, MethylCapsNet and MethylSPWNet, that group CpGs into biologically relevant capsules-such as gene promoter context, CpG island relationship, or user-defined groupings-and relate them to diagnostic and prognostic outcomes. We demonstrate these models' utility on 3,897 individuals in the classification of central nervous system (CNS) tumors. MethylCapsNet and MethylSPWNet provide an opportunity to increase DNAm deep-learning analyses' interpretability by enabling a flexible organization of DNAm data into biologically relevant capsules.

Limiting Self-Renewal of the Basal Compartment by PKA Activation Induces Differentiation and Alters the Evolution of Mammary Tumors.

Differentiation therapy utilizes our understanding of the hierarchy of cellular systems to pharmacologically induce a shift toward terminal commitment. While this approach has been a paradigm in treating certain hematological malignancies, efforts to translate this success to solid tumors have met with limited success. Mammary-specific activation of PKA in mouse models leads to aberrant differentiation and diminished self-renewing potential of the basal compartment, which harbors mammary repopulating cells. PKA activation results in tumors that are more benign, exhibiting reduced metastatic propensity, loss of tumor-initiating potential, and increased sensitivity to chemotherapy. Analysis of tumor histopathology revealed features of overt differentiation with papillary characteristics. Longitudinal single-cell profiling at the hyperplasia and tumor stages uncovered an altered path of tumor evolution whereby PKA curtails the emergence of aggressive subpopulations. Acting through the repression of SOX4, PKA activation promotes tumor differentiation and represents a possible adjuvant to chemotherapy for certain breast cancers.

Perineal reconstruction following abdominoperineal resection: Comprehensive review of the literature.

Abdominoperineal resection (APR) in patients with anorectal carcinomas may involve flap-based perineal reconstruction techniques, such as rectus abdominis, myocutaneous, gracilis, and gluteal flaps. There is no consensus on the optimal approach. We evaluated the outcomes of perineal reconstruction following APR in the literature and identified a predominance of abdominal-based approaches, though overall outcomes were similar compared with thigh or perineal-based options. Statistical power to detect small differences in outcomes is limited, however, due to the retrospective design, relatively short-term follow-up, and potential selection bias based on morbidities associated with reconstructive techniques. Lacking randomized studies to define optimum approaches to perineal reconstruction, clinicians should individualize surgical strategy.

Silencing hepatic MCJ attenuates non-alcoholic fatty liver disease (NAFLD) by increasing mitochondrial fatty acid oxidation.

Nonalcoholic fatty liver disease (NAFLD) is considered the next major health epidemic with an estimated 25% worldwide prevalence. No drugs have yet been approved and NAFLD remains a major unmet need. Here, we identify MCJ (Methylation-Controlled J protein) as a target for non-alcoholic steatohepatitis (NASH), an advanced phase of NAFLD. MCJ is an endogenous negative regulator of the respiratory chain Complex I that acts to restrain mitochondrial respiration. We show that therapeutic targeting of MCJ in the liver with nanoparticle- and GalNAc-formulated siRNA efficiently reduces liver lipid accumulation and fibrosis in multiple NASH mouse models. Decreasing MCJ expression enhances the capacity of hepatocytes to mediate ß-oxidation of fatty acids and minimizes lipid accumulation, which results in reduced hepatocyte damage and fibrosis. Moreover, MCJ levels in the liver of NAFLD patients are elevated relative to healthy subjects. Thus, inhibition of MCJ emerges as an alternative approach to treat NAFLD.

MethylNet: an automated and modular deep learning approach for DNA methylation analysis.

BACKGROUND: DNA methylation (DNAm) is an epigenetic regulator of gene expression programs that can be altered by environmental exposures, aging, and in pathogenesis. Traditional analyses that associate DNAm alterations with phenotypes suffer from multiple hypothesis testing and multi-collinearity due to the high-dimensional, continuous, interacting and non-linear nature of the data. Deep learning analyses have shown much promise to study disease heterogeneity. DNAm deep learning approaches have not yet been formalized into user-friendly frameworks for execution, training, and interpreting models. Here, we describe MethylNet, a DNAm deep learning method that can construct embeddings, make predictions, generate new data, and uncover unknown heterogeneity with minimal user supervision. RESULTS: The results of our experiments indicate that MethylNet can study cellular differences, grasp higher order information of cancer sub-types, estimate age and capture factors associated with smoking in concordance with known differences. CONCLUSION: The ability of MethylNet to capture nonlinear interactions presents an opportunity for further study of unknown disease, cellular heterogeneity and aging processes.

DNA Methylation Changes in Regional Lung Macrophages Are Associated with Metabolic Differences.

A number of pulmonary diseases occur with upper lobe predominance, including cystic fibrosis and smoking-related chronic obstructive pulmonary disease. In the healthy lung, several physiologic and metabolic factors exhibit disparity when comparing the upper lobe of the lung to lower lobe, including differences in oxygenation, ventilation, lymphatic flow, pH, and blood flow. In this study, we asked whether these regional differences in the lung are associated with DNA methylation changes in lung macrophages that could potentially lead to altered cell responsiveness upon subsequent environmental challenge. All analyses were performed using primary lung macrophages collected via bronchoalveolar lavage from healthy human subjects with normal pulmonary function. Epigenome-wide DNA methylation was examined via Infinium MethylationEPIC (850K) array and validated by targeted next-generation bisulfite sequencing. We observed 95 CpG loci with significant differential methylation in lung macrophages, comparing upper lobe to lower lobe (all false discovery rate < 0.05). Several of these genes, including CLIP4, HSH2D, NR4A1, SNX10, and TYK2, have been implicated as participants in inflammatory/immune-related biological processes. Functionally, we identified phenotypic differences in oxygen use, comparing upper versus lower lung macrophages. Our results support a hypothesis that epigenetic changes, specifically DNA methylation, at a multitude of gene loci in lung macrophages are associated with metabolic differences regionally in lung.

Multicenter, Open-Label, Phase II Study of Bendamustine and Rituximab Followed by 90-Yttrium (Y) Ibritumomab Tiuxetan for Untreated Follicular Lymphoma (Fol-BRITe).

PURPOSE: Bendamustine and rituximab (BR) has been established as a superior frontline therapy over R-CHOP in the treatment of follicular lymphoma (FL). Yttrium-90 Ibritumomab tiuxetan (90YIT) is an effective consolidation strategy after chemotherapy induction. This prospective, single-arm, multicenter, phase II trial evaluated the response rate, progression-free survival (PFS), and tolerability of BR followed by consolidation with 90YIT in patients with untreated FL. PATIENTS AND METHODS: The study included grade 1 to 3a FL patients aged ≥18 years, chemotherapy-naïve, and requiring treatment for stage II-IV disease. Study treatment included an initial rituximab treatment, followed by four cycles of BR. Patients were eligible for consolidation with 90YIT, 6 to 12 weeks after BR, if they obtained at least a partial response after induction had adequate count recovery and bone marrow infiltration < 25%. RESULTS: Thirty-nine patients were treated. Eighty-two percent had an intermediate or high-risk Follicular Lymphoma International Prognostic Index score, and 6 of 39 (15%) were grade 3a. The response rate was 94.8%, and the complete response(CR)/CR unconfirmed (CRu) rate was 77% in the intention-to-treat analysis. The conversion rate from PR to CR/Cru after 90YIT was 81%. After median follow-up of 45 months, the PFS was 0.71 (95% confidence interval, 0.57-0.89). CONCLUSIONS: This report demonstrates that four cycles of BR followed by consolidation with 90YIT achieve high response rates that are durable. In addition, consolidation with 90YIT results in a high conversion rate of PR to CR/CRu. A short course of BR followed by 90YIT is a safe and effective regimen for frontline treatment of FL.

Molecular and epigenetic profiles of BRCA1-like hormone-receptor-positive breast tumors identified with development and application of a copy-number-based classifier.

BACKGROUND: BRCA1-mutated cancers exhibit deficient homologous recombination (HR) DNA repair, resulting in extensive copy number alterations and genome instability. HR deficiency can also arise in tumors without a BRCA1 mutation. Compared with other breast tumors, HR-deficient, BRCA1-like tumors exhibit worse prognosis but selective chemotherapeutic sensitivity. Presently, patients with triple negative breast cancer (TNBC) who do not respond to hormone endocrine-targeting therapy are given cytotoxic chemotherapy. However, more recent evidence showed a similar genomic profile between BRCA1-deficient TNBCs and hormone-receptor-positive tumors. Characterization of the somatic alterations of BRCA1-like hormone-receptor-positive breast tumors as a group, which is currently lacking, can potentially help develop biomarkers for identifying additional patients who might respond to chemotherapy. METHODS: We retrained and validated a copy-number-based support vector machine (SVM) classifier to identify HR-deficient, BRCA1-like breast tumors. We applied this classifier to The Cancer Genome Atlas (TCGA) and Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) breast tumors. We assessed mutational profiles and proliferative capacity by covariate-adjusted linear models and identified differentially methylated regions using DMRcate in BRCA1-like hormone-receptor-positive tumors. RESULTS: Of the breast tumors in TCGA and METABRIC, 22% (651/2925) were BRCA1-like. Stratifying on hormone-receptor status, 13% (302/2405) receptor-positive and 69% (288/417) triple-negative tumors were BRCA1-like. Among the hormone-receptor-positive subgroup, BRCA1-like tumors showed significantly increased mutational burden and proliferative capacity (both P < 0.05). Genome-scale DNA methylation analysis of BRCA1-like tumors identified 202 differentially methylated gene regions, including hypermethylated BRCA1. Individually significant CpGs were enriched for enhancer regions (P < 0.05). The hypermethylated gene sets were enriched for DNA and chromatin conformation (all Bonferroni P < 0.05). CONCLUSIONS: To provide insights into alternative classification and potential therapeutic targeting strategies of BRCA1-like hormone-receptor-positive tumors we developed and applied a novel copy number classifier to identify BRCA1-like hormone-receptor-positive tumors and their characteristic somatic alteration profiles.

Genome-wide DNA methylation profiling shows a distinct epigenetic signature associated with lung macrophages in cystic fibrosis.

BACKGROUND: Lung macrophages are major participants in the pulmonary innate immune response. In the cystic fibrosis (CF) lung, the inability of lung macrophages to successfully regulate the exaggerated inflammatory response suggests dysfunctional innate immune cell function. In this study, we aim to gain insight into innate immune cell dysfunction in CF by investigating alterations in DNA methylation in bronchoalveolar lavage (BAL) cells, composed primarily of lung macrophages of CF subjects compared with healthy controls. All analyses were performed using primary alveolar macrophages from human subjects collected via bronchoalveolar lavage. Epigenome-wide DNA methylation was examined via Illumina MethylationEPIC (850 K) array. Targeted next-generation bisulfite sequencing was used to validate selected differentially methylated CpGs. Methylation-based sample classification was performed using the recursively partitioned mixture model (RPMM) and was tested against sample case-control status. Differentially methylated loci were identified by fitting linear models with adjustment of age, sex, estimated cell type proportions, and repeat measurement. RESULTS: RPMM class membership was significantly associated with the CF disease status (P = 0.026). One hundred nine CpG loci were differentially methylated in CF BAL cells (all FDR ≤ 0.1). The majority of differentially methylated loci in CF were hypo-methylated and found within non-promoter CpG islands as well as in putative enhancer regions and DNase hyper-sensitive regions. CONCLUSIONS: These results support a hypothesis that epigenetic changes, specifically DNA methylation at a multitude of gene loci in lung macrophages, may participate, at least in part, in driving dysfunctional innate immune cells in the CF lung.

INSM1 Is More Sensitive and Interpretable than Conventional Immunohistochemical Stains Used to Diagnose Merkel Cell Carcinoma.

Merkel cell carcinoma (MCC) is an extremely aggressive skin cancer that must be distinguished from other basaloid cutaneous neoplasms that have different treatments and prognoses. This is sometimes challenging in small shave specimens, crushed samples, lymph nodes, and core needle biopsies. Insulinoma-associated protein 1 (INSM1) immunohistochemistry is a sensitive nuclear marker of neuroendocrine differentiation. INSM1 staining was performed on 56 MCC (47 primary tumors, 9 nodal metastases), 50 skin control cases that included basal cell carcinomas, basaloid squamous cell carcinomas, Bowen disease, sebaceous neoplasms, melanoma, and B-cell lymphomas, and 28 lymph node control cases that included metastatic neuroendocrine neoplasms, melanomas, squamous cell carcinomas, lymphomas, and adenocarcinomas. Percent of staining nuclei (0, <25%, 25% to 50%, 50% to 75%, >75%) and intensity (weak, moderate, strong) were recorded for each sample. All 56 MCC expressed INSM1. By comparison, synaptophysin, CK20, and chromogranin were expressed in 96%, 92%, and 32% of MCC, respectively. While the 3 conventional markers showed significant variability in staining intensity and distribution, INSM1 stained >75% tumor nuclei in 89% of MCC and 50% to 75% of tumor nuclei in 11%. Staining intensity was strong in 85% and moderate in 15%. None of the 50 cutaneous basaloid non-MCC neoplasms in the control group stained with INSM1, and among the lymph node controls 5 of 5 neuroendocrine neoplasms expressed INSM1, confirming that INSM1 staining cannot distinguish MCC from metastatic extracutaneous neuroendocrine carcinoma. INSM1 holds promise as a neuroendocrine marker that can distinguish MCC from its mimickers in the skin and improve detection of sentinel lymph node metastases.

Concordance of DNA methylation profiles between breast core biopsy and surgical excision specimens containing ductal carcinoma in situ (DCIS).

The utility and reliability of assessing molecular biomarkers for translational applications on pre-operative core biopsy specimens assume consistency of molecular profiles with larger surgical specimens. Whether DNA methylation in ductal carcinoma in situ (DCIS), measured in core biopsy and surgical specimens are similar, remains unclear. Here, we compared genome-scale DNA methylation measured in matched core biopsy and surgical specimens from DCIS, including specific DNA methylation biomarkers of subsequent invasive cancer. DNA was extracted from guided 2mm cores of formalin fixed paraffin embedded (FFPE) specimens, bisulfite-modified, and measured on the Illumina HumanMethylation450 BeadChip. DNA methylation profiles of core biopsies exhibited high concordance with matched surgical specimens. Within-subject variability in DNA methylation was significantly lower than between-subject variability (all P<2.20E-16). In 641 CpGs whose methylation was related with increased hazard of invasive breast cancer, lower within-subject than between-subject variability was observed in 92.3% of the study participants (P<0.05). Between patient-matched core biopsy and surgical specimens, <0.6% of CpGs measured had changes in median DNA methylation >15%, and a pathway analysis of these CpGs indicated enrichment for genes related with wound healing. Our results indicate that DNA methylation measured in core biopsies are representative of the matched surgical specimens and suggest that DCIS biomarkers measured in core biopsies can inform clinical decision-making.