Abstract Background Adiposity and skeletal muscle levels assessed on computed tomography (CT) scans are prognostic indicators for patients with breast cancer. However, the intraindividual reliability of temporal changes in body composition assessed on opportunistic CT scans is unclear. Methods This retrospective study included 50 patients newly diagnosed with breast cancer who had archived CT scans pre- and postsurgery for breast cancer. The third lumbar CT image was segmented for areas of 3 types of adipose tissues and 5 different densities of skeletal muscles. Mean and percent changes in areas pre- vs postsurgery were compared using Wilcoxon signed rank tests. Intraclass correlation coefficients (ICCs) with 95% confidence intervals were assessed. A 2-sided P less than .05 was considered statistically significant. Results Mean (SD) age at diagnosis was 58.3 (12.5) years, and the interval between CT scans was 590.6 (536.8) days. Areas for body composition components were unchanged except for intermuscular adipose tissue (mean change = 1.45 cm2, 6.74% increase, P = .008) and very high-density muscle (mean change = −0.37 cm2, 11.08% decrease, P = .01) during the interval. There was strong intraindividual reliability in adipose tissue and skeletal muscle areas on pre- vs postsurgery scans overall (ICC = 0.763-0.998) and for scans collected 3 or less years apart (ICC = 0.802-0.999; 42 patients). Conclusions Although some body composition components may change after breast cancer surgery, CT scan assessments of body composition were reliable for a 3-year interval including the surgery. These findings inform measurement characteristics of body composition on opportunistic CT scans of patients undergoing surgery for breast cancer.
<p>nANGPTL4 inhibits LAL to suppress ccRCC colony formation. <b>A–C,</b> Total intracellular lipids in the indicated CAKi-1 or 786O cells were stained with BODIPY 493/503 and the median fluorescence intensity (MFI) was determined. <b>A,</b> Representative histogram is presented for BODIPY staining of CAKi WT (gray) and A4KO (red) cells. <b>B</b> and <b>C,</b> Graph depicts the average BODIPY 493/503 MFI of the indicated CAKi-1 (<b>B</b>) and 786O (<b>C</b>) cells ± SD. Welch’s <i>t</i> test was used to determine significance. <b>D,</b> CAKi-1 WT and A4KO cells were incubated with BODIPY FL C12 and analyzed by flow cytometry to measure lipid uptake. Left: representative histogram showing BODIPY FL C12 fluorescent intensity of WT (gray) and A4KO (red) cells. Right: graph depicts the average BODIPY FL C12 MFI ± SD in the indicated 786O cells. Welch’s <i>t</i> test was done to determine significance. <b>E,</b> LAL activity was determined by incubating the indicated cells with lysolive-green and measuring the fluorescence Intensity by flow cytometry. Left: representative histogram depicting intensity of lysolive-green fluorescence in CAKi-1 WT (gray) and A4KO (red) cells. Right: graph depicts the average lysolive-green MFI as a fold change compared to WT ± SD. Welch’s <i>t</i> test was done to determine significance. <b>F,</b> Graph depicts the average lysolive-green MFI as a fold change compared to WT ± SD. Welch’s <i>t</i> test was done to determine significance. <b>G,</b> CAKi-1 A4KO cells were mock transfected or transfected with full length (FL) or N-terminus (N-term) ANGPTl4 and incubated with lysolive-green. Left representative histrogram depicting lysolive-green fluorescence intensity in the indicated cell lines. The peak fluorescence intensity in mock transfected cells is indicated by the black line. Right: Average lysolive-green MFI as a fold changed compared to mock transfected ± SD. One-way ANOVA with Dunnett’s test to correct for multiple comparisons was done to determine significance. <b>H,</b> Graph depicts the average number of colonies/well of the indicated CAKi-1 cells grown in the presence or absence of the LAL inhibitor lalistat 1. One-way ANOVA with Dunnett’s test to correct for multiple comparisons was done to determine significance. <b>I,</b> Graph depicts the average number of colonies/well of the indicated 786O cells grown in the presence or absence of the LAL inhibitor lalistat 1. One-way ANOVA with Dunnett’s test to correct for multiple comparisons was done to determine significance. <b>J,</b> CAKi-1 A4KO cells were transfected with siRNA targeting <i>LIPA</i> (gene that encodes LAL) or nontargeting control siRNA (−). Cells were plated in non-adherent conditions, cultured for 72 hours and the number of colonies was counted. Top: western blot for LAL at the indicated time point post transfection. GAPDH blot is used as a loading control. Bottom: graph depicts the average number of colonies per well ± SD. Welch’s <i>t</i> test was done to determine significance. <b>K,</b> CAKi-1 A4KO cells were transfected with a lentivirus plasmid containing CRISPR-Cas9 and one of the three guide RNAs targeting <i>LIPA</i>. After selection total lysates were collected and a Western blot for LAL and GAPDH, as a loading control, was done. Arrow indicates LAL band. <b>L,</b> The indicated CAKi-1 cells (A4KO LIPA KO cells are g2 cells from <b>K</b>) were cultured in nonadherent conditions for 72 hours and the number of colonies was counted. Graph depicts the number of colonies per well ± SD. One-way ANOVA with Dunnett’s test to correct for multiple comparisons was done to determine significance. <b>M,</b> The indicated CAKi-1 cells were cultured for 72 hours, stained with annexin V-FITC and PI and analyzed by flow cytometry. Graph depicts the % of FITC-positive cells as a percentage of single cells ± SD. One-way ANOVA with Dunnett’s test to correct for multiple comparisons was done to determine significance.</p>
4200 RANK (Receptor Activator of NFκB) is a member of TNFα receptor super family. RANKL (RANK Ligand) activates RANK and its down-stream kinase IKKα, controlling osteoclast differentiation, mammary gland development as well as breast cancer tumorigenesis. Inhibition of RANK leads to reduction in tumor colonization and growth in bones in several mouse tumor metastasis models. However, the underlying mechanism underlying is still largely unknown. The purpose of the current study is to monitor and understand the influence of RANK-signaling on step-wise tumor development and metastasis. We used orthotopic tumor transplantation models with green fluorescent protein (GFP) and red fluorescent protein (DsRed2)-labeled Her2/neu transformed tumor cells which are under the control of RANK signaling. With the aid of real-time fluorescence imaging we can measure tumor growth, and monitor invasion, trafficking and colonization of tumor cells in real-time. To understand the mechanisms involved, we employed Western-blotting, RT-PCR, cell fractionation and transient transfection reporter assays. We found RANKL stimulation increased the nuclear accumulation of IKKα and expression of a group of genes involved in inflammation. However, genes which control the cell cycle and proliferation remained unchanged. This observation is consistent with that RANKL stimulation does not influence tumor-cell proliferation tumor growth. It is of great importance to analyze how blockage of RANK and RANK down-stream effectors, including IKKα and responsive genes affect tumor behavior and tumor-host interaction.
Regulatory T cells (Tregs) are a population of T cells that exert a suppressive effect on a variety of immune cells and non-immune cells. The suppressive effects of Tregs are detrimental to anti-tumor immunity. Recent investigations into cancer-associated Tregs have identified common expression patterns for tumor-infiltration, however the functional heterogeneity in tumor-infiltrating (TI) Treg is largely unknown. We performed single-cell sequencing on immune cells derived from renal clear cell carcinoma (ccRCC) patients, isolating 160 peripheral-blood (PB) Tregs and 574 TI Tregs. We identified distinct transcriptional TI Treg cell fates, with a suppressive subset expressing CD177. We demonstrate CD177 + TI-Tregs have preferential suppressive effects in vivo and ex vivo. Gene signatures derived the CD177 + Treg subset had superior ability to predict survival in ccRCC and seven other cancer types. Further investigation into the development and regulation of TI-Treg heterogeneity will be vital to the application of tumor immunotherapies that possess minimal side effects.
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