Data from Individualized Breast Cancer Characterization through Single-Cell Analysis of Tumor and Adjacent Normal Cells
Manjushree AnjanappaAngelo A. CardosoLijun ChengSafa MohamadAndrea GunawanStuart A. RiceYan DongLang LiGeorge E. SanduskyEdward F. SrourHarikrishna Nakshatri
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<div>Abstract<p>There is a need to individualize assays for tumor molecular phenotyping, given variations in the differentiation status of tumor and normal tissues in different patients. To address this, we performed single-cell genomics of breast tumors and adjacent normal cells propagated for a short duration under growth conditions that enable epithelial reprogramming. Cells analyzed were either unselected for a specific subpopulation or phenotypically defined as undifferentiated and highly clonogenic ALDH<sup>+</sup>/CD49f<sup>+</sup>/EpCAM<sup>+</sup> luminal progenitors, which express both basal cell and luminal cell–enriched genes. We analyzed 420 tumor cells and 284 adjacent normal cells for expression of 93 genes that included a PAM50-intrinsic subtype classifier and stemness-related genes. ALDH<sup>+</sup>/CD49f<sup>+</sup>/EpCAM<sup>+</sup> tumor and normal cells clustered differently compared with unselected tumor and normal cells. PAM50 gene-set analyses of ALDH<sup>+</sup>/CD49f<sup>+</sup>/EpCAM<sup>+</sup> populations efficiently identified major and minor clones of tumor cells, with the major clone resembling clinical parameters of the tumor. Similarly, a stemness-associated gene set identified clones with divergent stemness pathway activation within the same tumor. This refined expression profiling technique distinguished genes truly deregulated in cancer from genes that identify cellular precursors of tumors. Collectively, the assays presented here enable more precise identification of cancer-deregulated genes, allow for early identification of therapeutically targetable tumor cell subpopulations, and ultimately provide a refinement of precision therapeutics for cancer treatment. <i>Cancer Res; 77(10); 2759–69. ©2017 AACR</i>.</p></div>Keywords:
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Limited evidence suggests that inherited predisposing risk variants might affect the disease outcome. In this study, we analyzed the effect of genome-wide association studies—identified breast cancer-risk single nucleotide polymorphisms on survival of early-stage breast cancer patients in a Chinese population. This retrospective study investigated the relationship between 21 GWAS-identified breast cancer-risk single nucleotide polymorphisms and the outcome of 1177 early stage breast cancer patients with a long median follow-up time of 174 months. Cox proportional hazards regression models were used to estimate the hazard ratios and their 95% confidence intervals. Primary endpoints were breast cancer special survival and overall survival while secondary endpoints were invasive disease free survival and distant disease free survival. Multivariate survival analysis showed only the rs2046210 GA genotype significantly decreased the risk of recurrence and death for early stage breast cancer. After grouping breast cancer subtypes, significantly reduced survival was associated with the variant alleles of rs9485372 for luminal A and rs4415084 for triple negative breast cancer. Importantly, all three single-nucleotide polymorphisms, rs889312, rs4951011 and rs9485372 had remarkable effects on survival of luminal B EBC, either individually or synergistically. Furthermore, statistically significant multiplicative interactions were found between rs4415084 and age at diagnosis and between rs3803662 and tumor grade. Our results demonstrate that breast cancer risk susceptibility loci identified by GWAS may influence the outcome of early stage breast cancer patients’ depending on intrinsic tumor subtypes in Chinese women.
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Abstract This article provides a general introduction of materials characterization and describes the principles and applications of a limited number of techniques that are most commonly used to characterize the composition and structure of metals used in engineering systems. It briefly describes the classification of materials characterization methods including, bulk elemental characterization, bulk structural characterization, microstructural characterization, and surface characterization. Further, the article reviews the selection of materials characterization methods most commonly used with metals.
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Corticosterone (CORT) and other glucocorticoids cause peripheral insulin resistance and compensatory increases in β-cell mass. A prolonged high-fat diet (HFD) induces insulin resistance and impairs β-cell insulin secretion. This study examined islet adaptive capacity in rats treated with CORT and a HFD. Male Sprague-Dawley rats (age ∼6 weeks) were given exogenous CORT (400 mg/rat) or wax (placebo) implants and placed on a HFD (60% calories from fat) or standard diet (SD) for 2 weeks (N = 10 per group). CORT-HFD rats developed fasting hyperglycemia (>11 mM) and hyperinsulinemia (∼5-fold higher than controls) and were 15-fold more insulin resistant than placebo-SD rats by the end of ∼2 weeks (Homeostatic Model Assessment for Insulin Resistance [HOMA-IR] levels, 15.08 ± 1.64 vs 1.0 ± 0.12, P < .05). Pancreatic β-cell function, as measured by HOMA-β, was lower in the CORT-HFD group as compared to the CORT-SD group (1.64 ± 0.22 vs 3.72 ± 0.64, P < .001) as well as acute insulin response (0.25 ± 0.22 vs 1.68 ± 0.41, P < .05). Moreover, β- and α-cell mass were 2.6- and 1.6-fold higher, respectively, in CORT-HFD animals compared to controls (both P < .05). CORT treatment increased p-protein kinase C-α content in SD but not HFD-fed rats, suggesting that a HFD may lower insulin secretory capacity via impaired glucose sensing. Isolated islets from CORT-HFD animals secreted more insulin in both low and high glucose conditions; however, total insulin content was relatively depleted after glucose challenge. Thus, CORT and HFD, synergistically not independently, act to promote severe insulin resistance, which overwhelms islet adaptive capacity, thereby resulting in overt hyperglycemia.
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This chapter contains sections titled: Introduction Modifications of PLA PLA Applications Characterization by FT-IR Characterization by Optical Microscopy Characterization by Electron Microscopy Characterization by Mechanical Testing Characterization of GPC Characterization of Dynamic Mechanical Thermal Analysis
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The effect of 48 h of fasting in C57B1/6J-ob/ob and +/+ mice on body weight (BW), blood glucose (BG), serum immunreactive insulin (IRI), plasma immunoreactive glucagon (IRG) and on tissue levels of cyclic adenosine monophosphate (cAMP) were studied. Both groups of mice lost weight and demonstrated a decrease in BG and IRI with fasting. However, the BG and IRI of the ob/ob animals were initially highter and remained higher than those of the 2% of their initial weight while the +/+ lost 14 %. The +/+ mice exhibited an increase in cAMP levels in skeletal muscle, fat and liver with fasting, while the ob/ob mice had increased levels of cAMP in fat, but not in muscle. They also had a paradoxical decrease in liver cAMP levels with fasting, and associated with this was the lack of stimulation of glycogenolysis. Glycogenolysis was significant in the livers of fasted +/+ mice. The plasma IRG levels of the fed ob/ob mice were significantly higher (1.8) times) than those of the fed +/+ mice. Islet cAMP levels were decreased with fasting in ob/ob mice. However, the levels were significantly higher in 48-h faster ob/ob mice compared to the fasted +/+ group. The apparent paradoxical response to fasting observed in the livers of the ob/ob mice remains unexplained.
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Materials characterization is a crucial issue in the development and application of new materials. Materials characterization aims to mine and acquire characteristic information and their evolution in the materials. It mainly includes three important topics which are microstructural characterization, properties characterization, and environmental degradation. In this paper, characterization techniques about these topics were discussed for C/SiC composites and a characterization system was preliminarily established. All these characterization research and their results further the better understanding of the relationship between microstructure and properties and of the failure mechanisms in the C/SiC composites.
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Abstract Breast cancer is a frequent female malignant tumor with high mortality and poor prognosis. Peroxidasin like (PXDNL) has many biological functions, including characteristic activity of hormone biosynthesis, host defense, and cell motility. In addition, PXDNL is closely connected with the progression of breast cancer. In this study, we found that PXDNL may be an independent prognostic biomarker of breast cancer. We tested the mRNA expression of PXDNL in breast cancer by detecting The Cancer Genome Atlas (TCGA) database. The chi-squared test was used to evaluate clinical correlation. The receiver operating characteristic (ROC) curves were drawn to evaluate diagnosis potential in breast cancer. Subsequently, survival analyses were performed to identify the relevance between the expression of PXDNL and the overall survival/relapse-free survival of patients with breast cancer. Univariate/multivariate Cox regression model was executed to detect risk factors affecting the prognosis of patients with breast cancer. PXDNL is highly expressed in breast cancer tissues and is related to survival status of patients. The ROC curve showed that PXDNL had beneficial diagnostic ability in breast cancer. Survival analysis indicated that patients with breast cancer with high PXDNL expression generally had decreased overall survival/relapse-free survival. Univariate/multivariate Cox model analyses further suggested an association between PXDNL expression and prognosis of patients with breast cancer. High PXDNL expression is a potential and independent prognostic biomarker in breast cancer.
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