TGF-beta reduces DNA ds-break repair mechanisms to heighten genetic diversity and adaptability of CD44+/CD24- cancer cells

Many lines of evidence have indicated that both genetic and non-genetic determinants can contribute to intra-tumor heterogeneity and influence cancer outcomes. Among the best described sub-population of cancer cells generated by non-genetic mechanisms are cells characterized by a CD44+/CD24- cell surface marker profile. Here, we report that human CD44+/CD24- cancer cells are genetically highly unstable due to intrinsic defects in their DNA repair capabilities. In fact, in CD44+/CD24- cells constitutive activation of the TGF-beta axis was both necessary and sufficient to reduce the expression of genes that are critical in coordinating DNA damage repair mechanisms. Consequently, we observed that cancer cells that reside in a CD44+/CD24- state are characterized by increased accumulation of DNA copy number alterations, greater genetic diversity and improved adaptability to drug treatment. Together, these data suggest that the transition into a CD44+/CD24- cell state can promote intra-tumor genetic heterogeneity, spur tumor evolution and increase tumor fitness

Cost-effectiveness of non-invasive methods for assessment and monitoring of liver fibrosis and cirrhosis in patients with chronic liver disease: systematic review and economic evaluation

BACKGROUND: Liver biopsy is the reference standard for diagnosing the extent of fibrosis in chronic liver disease; however, it is invasive, with the potential for serious complications. Alternatives to biopsy include non-invasive liver tests (NILTs); however, the cost-effectiveness of these needs to be established. OBJECTIVE: To assess the diagnostic accuracy and cost-effectiveness of NILTs in patients with chronic liver disease. DATA SOURCES: We searched various databases from 1998 to April 2012, recent conference proceedings and reference lists. METHODS: We included studies that assessed the diagnostic accuracy of NILTs using liver biopsy as the reference standard. Diagnostic studies were assessed using the Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) tool. Meta-analysis was conducted using the bivariate random-effects model with correlation between sensitivity and specificity (whenever possible). Decision models were used to evaluate the cost-effectiveness of the NILTs. Expected costs were estimated using a NHS perspective and health outcomes were measured as quality-adjusted life-years (QALYs). Markov models were developed to estimate long-term costs and QALYs following testing, and antiviral treatment where indicated, for chronic hepatitis B (HBV) and chronic hepatitis C (HCV). NILTs were compared with each other, sequential testing strategies, biopsy and strategies including no testing. For alcoholic liver disease (ALD), we assessed the cost-effectiveness of NILTs in the context of potentially increasing abstinence from alcohol. Owing to a lack of data and treatments specifically for fibrosis in patients with non-alcoholic fatty liver disease (NAFLD), the analysis was limited to an incremental cost per correct diagnosis. An analysis of NILTs to identify patients with cirrhosis for increased monitoring was also conducted. RESULTS: Given a cost-effectiveness threshold of £20,000 per QALY, treating everyone with HCV without prior testing was cost-effective with an incremental cost-effectiveness ratio (ICER) of £9204. This was robust in most sensitivity analyses but sensitive to the extent of treatment benefit for patients with mild fibrosis. For HBV [hepatitis B e antigen (HBeAg)-negative)] this strategy had an ICER of £28,137, which was cost-effective only if the upper bound of the standard UK cost-effectiveness threshold range (£30,000) is acceptable. For HBeAg-positive disease, two NILTs applied sequentially (hyaluronic acid and magnetic resonance elastography) were cost-effective at a £20,000 threshold (ICER: £19,612); however, the results were highly uncertain, with several test strategies having similar expected outcomes and costs. For patients with ALD, liver biopsy was the cost-effective strategy, with an ICER of £822. LIMITATIONS: A substantial number of tests had only one study from which diagnostic accuracy was derived; therefore, there is a high risk of bias. Most NILTs did not have validated cut-offs for diagnosis of specific fibrosis stages. The findings of the ALD model were dependent on assuptions about abstinence rates assumptions and the modelling approach for NAFLD was hindered by the lack of evidence on clinically effective treatments. CONCLUSIONS: Treating everyone without NILTs is cost-effective for patients with HCV, but only for HBeAg-negative if the higher cost-effectiveness threshold is appropriate. For HBeAg-positive, two NILTs applied sequentially were cost-effective but highly uncertain. Further evidence for treatment effectiveness is required for ALD and NAFLD. STUDY REGISTRATION: This study is registered as PROSPERO CRD42011001561. FUNDING: The National Institute for Health Research Health Technology Assessment programme

SAKE (Single-cell RNA-Seq Analysis and Klustering Evaluation) Identifies Markers of Resistance to Targeted BRAF Inhibitors in Melanoma Cell Populations

Single-cell RNA-Seq’s (scRNA-Seq) unprecedented cellular resolution at a genome wide scale enables us to address questions about cellular heterogeneity that are inaccessible using methods that average over bulk tissue extracts. However, scRNA-Seq datasets also present additional challenges such as high transcript dropout rates, stochastic transcription events, and complex population substructures. Here, we present SAKE (Single-cell RNA-Seq Analysis and Klustering Evaluation): a robust method for scRNA-Seq analysis that provides quantitative statistical metrics at each step of the scRNA-Seq analysis pipeline including metrics for: the determination of the number of clusters present, the likelihood that each cell belongs to a given cluster, and the association of each gene marker in determining cluster membership. Comparing SAKE to multiple single-cell analysis methods shows that most methods perform similarly across a wide range cellular contexts, with SAKE outperforming these methods in the case of large complex populations. We next applied the SAKE algorithms to identify drug-resistant cellular populations as human melanoma cells respond to targeted BRAF inhibitors. Single-cell RNA-Seq data from both the Fluidigm C1 and 10x Genomics platforms were analyzed with SAKE to dissect this problem at multiple scales. Data from both platforms indicate that BRAF inhibitor resistant cells can emerge from rare populations already present before drug application, with SAKE identifying both novel and known markers of resistance. In addition, we compare integrated genomic and transcriptomic markers to show that resistance can arise stochastically within multiple distinct clonal populations

Unresolved endoplasmic reticulum stress engenders immune-resistant, latent pancreatic cancer metastases

The majority of patients with pancreatic ductal adenocarcinoma (PDA) develop metastatic disease after resection of their primary tumor. We found that livers from patients and mice with PDA harbor single, disseminated cancer cells (DCCs) lacking expression of cytokeratin-19 (CK19) and major histocompatibility complex class I (MHCI). We created a mouse model to determine how these DCCs develop. Intra-portal injection of immunogenic PDA cells into pre-immunized mice seeded livers only with single, non-replicating DCCs that were CK19(-) and MHCI(-) The DCCs exhibited an endoplasmic reticulum (ER) stress response but, paradoxically lacked both inositol-requiring enzyme 1alpha activation and expression of the spliced form of transcription factor XBP1 (XBP1s). Inducible expression of XBP1s in DCCs, in combination with T cell-depletion, stimulated the outgrowth of macro-metastatic lesions that expressed CK19 and MHCI. Thus, unresolved ER stress enables DCCs to escape immunity and establish latent metastases

A Molecular Clock Infers Heterogeneous Tissue Age Among Patients with Barrett's Esophagus

National Institutes of Health (www.nih.gov) and the National Cancer Institute (www.cancer.gov) under grants U01CA182940 (BG-U01) (to EGL, CJW, WDH, WMG, and KC), 5P30CA015704 (to WMG and CJW), 5U01CA152756 (to WMG and CJW), 5U54CA163060 (to AC), and NIH1P50CA150964-01A1 (to JEW