SIRT1 and c-Myc Promote Liver Tumor Cell Survival and Predict Poor Survival of Human Hepatocellular Carcinomas

<div><p>The increased expression of SIRT1 has recently been identified in numerous human tumors and a possible correlation with c-Myc oncogene has been proposed. However, it remains unclear whether SIRT1 functions as an oncogene or tumor suppressor. We sought to elucidate the role of SIRT1 in liver cancer under the influence of c-Myc and to determine the prognostic significance of SIRT1 and c-Myc expression in human hepatocellular carcinoma. The effect of either over-expression or knock down of SIRT1 on cell proliferation and survival was evaluated in both mouse and human liver cancer cells. Nicotinamide, an inhibitor of SIRT1, was also evaluated for its effects on liver tumorigenesis. The prognostic significance of the immunohistochemical detection of SIRT1 and c-Myc was evaluated in 154 hepatocellular carcinoma patients. SIRT1 and c-Myc regulate each other via a positive feedback loop and act synergistically to promote hepatocellular proliferation in both mice and human liver tumor cells. Tumor growth was significantly inhibited by nicotinamide <em>in vivo</em> and <em>in vitro</em>. In human hepatocellular carcinoma, SIRT1 expression positively correlated with c-Myc, Ki67 and p53 expression, as well as high á-fetoprotein level. Moreover, the expression of SIRT1, c-Myc and p53 were independent prognostic indicators of hepatocellular carcinoma. In conclusion, this study demonstrates that SIRT1 expression supports liver tumorigenesis and is closely correlated with oncogenic <em>c-MYC</em> expression. In addition, both SIRT1 and c-Myc may be useful prognostic indicators of hepatocellular carcinoma and SIRT1 targeted therapy may be beneficial in the treatment of hepatocellular carcinoma.</p> </div

SIRT1 expression correlates with c-Myc expression in Tet-O-MYC cells and influence on proliferation of cells.

<p>A) SIRT1 expression directly correlates with c-MYC in a time dependent manner. When oncogenic c-Myc expression is restored over five days (Re-ON), increased SIRT1 expression returns. B and C) Quantitative real time PCR (qPCR) and Western blot. After transfection of Tet-O-MYC cells with a SIRT1 over-expression plasmid, the expression of SIRT1 mRNA and protein as well as c-Myc significantly increases compared with control vector (CV). Knock down of SIRT1 by shRNA against SIRT1 resulted in decreased expression of mRNA and protein for SIRT1 and c-Myc, as well as increased acetylation of p53 protein (ac-p53) and increased expression of p21. D) SIRT1 overexpression promotes increased proliferation. Knock-down of SIRT1 decreased proliferation as demonstrated by MTT and colony forming assay. E) Nicotinamide (NAM), a SIRT1 inhibitor, significantly decreases the proliferation of both MYC-ON and MYC-OFF cells. The MTT assay was performed after seeding of 2×10³ cells for two to three days. Colony forming assay were performed in the presence of 10 mM NAM. A colony-forming assay was performed by culture of 2×10³ cells for 7 days in 24-well culture plates. A single asterik indicates <i>P</i><0.05, two asteriks indicate <i>P</i><0.001.</p

Univariate Cox regression analysis for overall survival and disease-free survival in hepatocellular carcinoma patients.

<p>Abbreviations: OS, overall survival; DFS, disease-free survival; AFP, á-fetoprotein; HR, hazard ratio.</p

The effect of SIRT1 on the proliferation of human hepatocellular carcinoma cell lines.

<p>A) Over-expression and knock-down of SIRT1 was induced in the Huh7 and HepG2 human hepatocellular carcinoma (HCC) cell lines using constructs as described above. Over-expression of SIRT1 increased the expression of c-Myc protein. Knock-down of SIRT1 resulted in relatively decreased expression of c-Myc protein and a detectable increase in the acetylation of the p53 protein. B) qPCR for SIRT1 and c-Myc after induction of over-expression and knock-down of SIRT1. C) SIRT1 over-expression results in increased proliferation of HCC cells. The proliferation of SIRT1 knock-down HCC cells is significantly decreased compared with control cells as determined by both MTT assay and colony forming assay. D) Treatment of HCC cells with NAM results in significant decreased proliferation of both Huh7 and HepG2 cells by both MTT and colony forming assay. MTT assay was performed after seeding of 2×10³ cells for two days. A colony-forming assay was performed by culture 2×10³ cells for 7 days in 24-well culture plates. A single asterik indicates <i>P</i><0.05, two asteriks indicate <i>P</i><0.001.</p

Clinicopathologic variables and the expression status of SIRT1, c-Myc, p53, and Ki67.

<p>Abbreviations: AFP, á-fetoprotein.</p

Biological characteristics of a conditional c-Myc mouse liver tumor cell line.

<p>A) A tumor cell line derived from the bitransgenic animal containing the liver associated protein (LAP) promoter driving the tetracycline transactivating protein (tTa) and c-Myc under the control of the tetracycline-response promoter (Tet-O). Addition of doxycycline prevents tTa protein from activating the Tet-O promoter. Absence of doxycycline triggers a conformational change that enables Tet-O binding, activation, and c-Myc transcription. B) Polymerase chain reaction indicates that Tet-O-MYC cells are positive for both LAP-tTa and c-Myc transcripts. C) MYC-ON cells show higher expression of messenger RNA for c-Myc than MYC-OFF cells by quantitative real-time polymerase chain reaction. D) Western blot result shows c-Myc expression only in the MYC-ON cells. E) Morphologically, MYC-OFF cells are larger than MYC-ON cells and have larger nuclei, increased cytoplasm, inconspicuous nucleoli, decreased nuclear-cytoplasmic ratio and more cytoplasmic processes. Immunofluoresence staining demonstrates increased c-MYC expression in the nuclei of the MYC-ON cells compared to MYC-OFF cells (original magnification×63). F) The proliferative activity of Tet-O-MYC cells is controlled by c-Myc. Removal of oncogenic c-Myc expression significantly attenuates Tet-O-MYC cell proliferation.</p

Risk Prediction of Emergency Department Revisit 30 Days Post Discharge: A Prospective Study

<div><p>Background</p><p>Among patients who are discharged from the Emergency Department (ED), about 3% return within 30 days. Revisits can be related to the nature of the disease, medical errors, and/or inadequate diagnoses and treatment during their initial ED visit. Identification of high-risk patient population can help device new strategies for improved ED care with reduced ED utilization.</p><p>Methods and Findings</p><p>A decision tree based model with discriminant Electronic Medical Record (EMR) features was developed and validated, estimating patient ED 30 day revisit risk. A retrospective cohort of 293,461 ED encounters from HealthInfoNet (HIN), Maine's Health Information Exchange (HIE), between January 1, 2012 and December 31, 2012, was assembled with the associated patients' demographic information and one-year clinical histories before the discharge date as the inputs. To validate, a prospective cohort of 193,886 encounters between January 1, 2013 and June 30, 2013 was constructed. The <i>c</i>-statistics for the retrospective and prospective predictions were 0.710 and 0.704 respectively. Clinical resource utilization, including ED use, was analyzed as a function of the ED risk score. Cluster analysis of high-risk patients identified discrete sub-populations with distinctive demographic, clinical and resource utilization patterns.</p><p>Conclusions</p><p>Our ED 30-day revisit model was prospectively validated on the Maine State HIN secure statewide data system. Future integration of our ED predictive analytics into the ED care work flow may lead to increased opportunities for targeted care intervention to reduce ED resource burden and overall healthcare expense, and improve outcomes.</p></div

A Data-Driven Algorithm Integrating Clinical and Laboratory Features for the Diagnosis and Prognosis of Necrotizing Enterocolitis

<div><p>Background</p><p>Necrotizing enterocolitis (NEC) is a major source of neonatal morbidity and mortality. Since there is no specific diagnostic test or risk of progression model available for NEC, the diagnosis and outcome prediction of NEC is made on clinical grounds. The objective in this study was to develop and validate new NEC scoring systems for automated staging and prognostic forecasting.</p><p>Study design</p><p>A six-center consortium of university based pediatric teaching hospitals prospectively collected data on infants under suspicion of having NEC over a 7-year period. A database comprised of 520 infants was utilized to develop the NEC diagnostic and prognostic models by dividing the entire dataset into training and testing cohorts of demographically matched subjects. Developed on the training cohort and validated on the blind testing cohort, our multivariate analyses led to NEC scoring metrics integrating clinical data.</p><p>Results</p><p>Machine learning using clinical and laboratory results at the time of clinical presentation led to two NEC models: (1) an automated diagnostic classification scheme; (2) a dynamic prognostic method for risk-stratifying patients into low, intermediate and high NEC scores to determine the risk for disease progression. We submit that dynamic risk stratification of infants with NEC will assist clinicians in determining the need for additional diagnostic testing and guide potential therapies in a dynamic manner.</p><p>Algorithm availability</p><p><a href="http://translationalmedicine.stanford.edu/cgi-bin/NEC/index.pl" target="_blank">http://translationalmedicine.stanford.edu/cgi-bin/NEC/index.pl</a> and smartphone application upon request.</p></div

The deployment of the 30-day readmission risk model.

<p>The validated risk model was deployed via a real time provider portal that was integrated into the Maine HIE. The model and results are subject to continuous adaptation in response to EMR output on a daily basis. A screenshot: the real-time dashboard allowing for high-risk inpatient encounter identification and in support of targeted interventions is shown.</p

A prospective case study on monthly ED visits and risks for a patient.

<p>A prospective case study on monthly ED visits and risks for a patient.</p