Zhu, Chunfang

Abstract Background. DCIS consists of a molecularly heterogeneous group of premalignant lesions, with variable risk of invasive progression. Understanding biomarkers for invasive progression could help individualize treatment recommendations based upon tumor biology. As part of the NCI Human Tumor Atlas Network (HTAN), we conducted comprehensive genomic analyses on two large DCIS case-control cohorts. Methods. We performed smart3-seq and low-pass whole genome sequencing on two independent, retrospective, longitudinally sampled DCIS case-control cohorts. TBCRC 038 was a multicenter cohort diagnosed with DCIS between 1998 and 2016 at one of the Translational Breast Cancer Research sites; the RAHBT (Resource of Archival Human Breast Tissue) cohort included women identified through the St. Louis Breast Tissue Repository, and the Women’s Health Repository diagnosed between 1997 and 2001. We studied the spectrum of molecular changes present and sought genomic predictors of subsequent ipsilateral breast events (iBEs: DCIS recurrence or invasive progression) in both DCIS epithelium and stroma in formalin fixed paraffin embedded tissue. We generated de novo tumor and stroma-centric subtypes for DCIS that represents fundamental transcriptomic organization. Copy number analysis was performed using low-pass DNA sequencing. Non-negative matrix factorization (NMF) was applied to the RNA expression of all coding genes to identify clusters. A negative-binomial regression model was used to identify differentially expressed genes. Results. We analyzed 677 DCIS samples from 481 patients with 7.1 years median follow-up. In TBCRC samples, we identified three clusters via NMF in TBCRC referred to as ER low, quiescent, and ER high. The ER-low cluster had significantly higher levels of ERBB2 and lower levels of ESR1 compared to quiescent and ER-high clusters. Quiescent cluster lesions were less proliferative and less metabolically active than ER high and ER low subtypes. These findings were replicated in the RAHBT cohort. Focusing on the stromal component of DCIS from laser capture microdissection in RAHBT samples, we identified four distinct DCIS-associated stromal clusters. A “normal-like” stromal cluster with ECM organization and PI3K-AKT signaling; a “collagen-rich” stromal cluster; a “desmoplastic” stromal cluster with high fibroblast and total myeloid abundance, mostly associated with macrophages and myeloid dendritic cells (mDC); and an “immune-dense” stromal cluster. Further, we compared differentially expressed genes in patients with or without subsequent iBEs within 5 years of diagnosis. Hypothesizing that the resulting 812 DE genes (DESeq2) represent multiple routes to subsequent iBEs, we leveraged NMF to identify paths to progression. In both TBCRC and RAHBT cohorts, poor outcome groups exhibited increased ER, MYC signaling, and oxidative phosphorylation, supporting that these pathways are important for DCIS recurrence and progression. Conclusion. Comprehensive genomic profiling in two independent DCIS cohorts with longitudinal outcomes shows distinct DCIS stromal expression patterns and immune cell composition. RNA expression profiles reveal underlying tumor biology that is associated with later iBEs in both cohorts. These studies provide new insight into DCIS biology and will guide the design of diagnostic strategies to prevent invasive progression. Citation Format: Siri H Strand, Belén Rivero-Gutiérrez, Kathleen E Houlahan, Jose A Seoane, Lorraine M King, Tyler Risom, Lunden Simpson, Sujay Vennam, Aziz Khan, Timothy Hardman, Bryan E Harmon, Fergus J Couch, Kristalyn Gallagher, Mark Kilgore, Shi Wei, Angela DeMichele, Tari King, Priscilla F McAuliffe, Julie Nangia, Joanna Lee, Jennifer Tseng, Anna Maria Storniolo, Alastair Thompson, Gaorav Gupta, Robyn Burns, Deborah J Veis, Katherine DeSchryver, Chunfang Zhu, Magdalena Matusiak, Jason Wang, Shirley X Zhu, Jen Tappenden, Daisy Yi Ding, Dadong Zhang, Jingqin Luo, Shu Jiang, Sushama Varma, Cody Straub, Sucheta Srivastava, Christina Curtis, Rob Tibshirani, Robert Michael Angelo, Allison Hall, Kouros Owzar, Kornelia Polyak, Carlo Maley, Jeffrey R Marks, Graham A Colditz, E Shelley Hwang, Robert B West. The Breast PreCancer Atlas DCIS genomic signatures define biology and correlate with clinical outcomes: An analysis of TBCRC 038 and RAHBT cohorts [abstract]. In: Proceedings of the 2021 San Antonio Breast Cancer Symposium; 2021 Dec 7-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2022;82(4 Suppl):Abstract nr GS4-07.

Glucagon-like peptide-1 receptor agonists (GLP-1RAs) are an ideal therapy for type 2 diabetes and, as of recently, for obesity. In contrast to visceral fat, subcutaneous fat appears to be protective against metabolic diseases. Here, we aimed to explore whether liraglutide, a GLP-1RA, could redistribute body fat via regulating lipid metabolism in different fat depots. After being fed a high-fat diet for 8 weeks, 50 male Wistar and Goto-Kakizaki rats were randomly divided into a normal control group, a diabetic control group, low- and high-dose liraglutide-treated groups and a diet-control group. Different doses of liraglutide (400 μg/kg/day or 1200 μg/kg/day) or an equal volume of normal saline were administered to the rats subcutaneously once a day for 12 weeks. Body composition and body fat deposition were measured by dual-energy X-ray absorptiometry and MRI. Isotope tracers were infused to explore lipid metabolism in different fat depots. Quantitative real-time PCR and Western blot analyses were conducted to evaluate the expression of adipose-related genes. The results showed that liraglutide decreased visceral fat and relatively increased subcutaneous fat. Lipogenesis was reduced in visceral white adipose tissue (WAT) but was elevated in subcutaneous WAT. Lipolysis was also attenuated, and fatty acid oxidation was enhanced. The mRNA expression levels of adipose-related genes in different tissues displayed similar trends after liraglutide treatment. In addition, the expression of browning-related genes was upregulated in subcutaneous WAT. Taken together, the results suggested that liraglutide potentially redistributes body fat and promotes browning remodeling in subcutaneous WAT to improve metabolic disorders.

Abstract Context Previous epidemiological studies had inconsistent results regarding the relationship between blood lead level (BLL) and adiposity. Objective We aimed to investigate the associations of BLL with body mass index (BMI) particularly using Mendelian randomization analyses and examine the interaction between obesity-predisposing genes and BLL on the associations. Design and Setting A total of 3922 participants were enrolled from 16 sites in East China in 2014 from the Survey on Prevalence in East China for Metabolic Diseases and Risk Factors (ChiCTR-ECS-14005052, www.chictr.org.cn). We calculated the weighted BMI genetic risk score (GRS) based on 29 variants that were identified and validated in East Asians. BLL was measured by atomic absorption spectrometry. Main Outcome Measure BMI was calculated, and BMI ≥25 kg/m2 was defined as overweight. Results Multivariable logistic regression analysis demonstrated significant associations between BMI with each unit increase in lnBLL (β = 0.24; 95% CI, 0.08 to 0.40; P < 0.001) and each 1-point increase in BMI-GRS (β = 0.08; 95% CI, 0.05 to 0.11; P < 0.001). The causal regression coefficients of genetically determined BMI for lnBLL were −0.003 (95% CI, −0.075 to 0.070), which showed no significance. The GRS modified the association of BLL with BMI and overweight (BMI ≥25 kg/m2; P for interaction = 0.031 and 0.001, respectively). Each unit of lnBLL was associated with 63% higher odds of overweight (OR 1.63; 95% CI, 1.30 to 2.05) in the highest quartile of GRS, but no significant associations were found in the lower three quartiles. Conclusions The associations of BLL with BMI and overweight (BMI ≥25 kg/m2) were significantly modulated by BMI genetic susceptibility.