Author Correction: LKB1 loss links serine metabolism to DNA methylation and tumorigenesis

Erratum for: LKB1 loss links serine metabolism to DNA methylation and tumorigenesis. [Nature. 2016

Splanchnic metabolism of nutrients and hormones in steers fed alfalfa under conditions of increased absorption of ammonia and L-arginine supply across the portal-drained viscera

Effects of increased ammonia and/or arginine absorption on net splanchnic (portal-drained viscera [PDV] plus liver) metabolism of nonnitrogenous nutrients and hormones in cattle were examined. Six Hereford × Angus steers (501 ± 1 kg BW) prepared with vascular catheters for measurements of net flux across the splanchnic bed were fed a 75% alfalfa:25% (as-fed basis) corn and soybean meal diet (0.523 MJ of ME/[kg BW0.75.d]) every 2 h without (27.0 g of N/kg of DM) and with 20 g of urea/kg of DM (35.7 g of N/kg of DM) in a split-plot design. Net flux measurements were made immediately before and after a 72-h mesenteric vein infusion of L-arginine (15 mmol/h). There were no treatment effects onPDVor hepaticO2 consumption. Dietary urea had no effect on splanchnic metabolism of glucose or L-lactate, but arginine infusion decreased net hepatic removal of L-lactate when urea was fed (P < 0.01). Net PDV appearance of n-butyrate was increased by arginine infusion (P < 0.07), and both dietary urea (P < 0.09) and arginine infusion (P < 0.05) increased net hepatic removal of n-butyrate. Dietary urea also increased total splanchnic acetate output (P < 0.06), tended to increase arterial glucagon concentration (P < 0.11), and decreased arterial ST concentration (P < 0.03). Arginine infusion increased arterial concentration (P < 0.07) and net PDV release (P < 0.10) and tended to increase hepatic removal (P < 0.11) of insulin, as well as arterial concentration (P < 0.01) and total splanchnic output (P < 0.01) of glucagon. Despite changes in splanchnic N metabolism, increased ammonia and arginine absorption had little measurable effect on splanchnic metabolism of glucose and other nonnitrogenous components of splanchnic energy metabolism

Frequent mutation of receptor protein tyrosine phosphatases provides a mechanism for STAT3 hyperactivation in head and neck cancer

The underpinnings of STAT3 hyperphosphorylation resulting in enhanced signaling and cancer progression are incompletely understood. Loss-of-function mutations of enzymes that dephosphorylate STAT3, such as receptor protein tyrosine phosphatases, which are encoded by the PTPR gene family, represent a plausible mechanism of STAT3 hyperactivation. We analyzed whole exome sequencing (n = 374) and reverse-phase protein array data (n = 212) from head and neck squamous cell carcinomas (HNSCCs). PTPR mutations are most common and are associated with significantly increased phospho-STAT3 expression in HNSCC tumors. Expression of receptor-like protein tyrosine phosphatase T (PTPRT) mutant proteins induces STAT3 phosphorylation and cell survival, consistent with a “driver” phenotype. Computational modeling reveals functional consequences of PTPRT mutations on phospho-tyrosine–substrate interactions. A high mutation rate (30%) of PTPRs was found in HNSCC and 14 other solid tumors, suggesting that PTPR alterations, in particular PTPRT mutations, may define a subset of patients where STAT3 pathway inhibitors hold particular promise as effective therapeutic agents.Fil: Lui, Vivian Wai Yan. University of Pittsburgh; Estados UnidosFil: Peyser, Noah D.. University of Pittsburgh; Estados UnidosFil: Ng, Patrick Kwok-Shing. University Of Texas Md Anderson Cancer Center;Fil: Hritz, Jozef. University of Pittsburgh at Johnstown; Estados Unidos. University of Pittsburgh; Estados Unidos. Masaryk University; República ChecaFil: Zeng, Yan. University of Pittsburgh at Johnstown; Estados Unidos. University of Pittsburgh; Estados UnidosFil: Lu, Yiling. University Of Texas Md Anderson Cancer Center;Fil: Li, Hua. University of Pittsburgh; Estados Unidos. University of Pittsburgh at Johnstown; Estados UnidosFil: Wang, Lin. University of Pittsburgh; Estados Unidos. University of Pittsburgh at Johnstown; Estados UnidosFil: Gilbert, Breean R.. University of Pittsburgh; Estados Unidos. University of Pittsburgh at Johnstown; Estados UnidosFil: General, Ignacio. University of Pittsburgh; Estados Unidos. University of Pittsburgh at Johnstown; Estados UnidosFil: Bahar, Ivet. University of Pittsburgh at Johnstown; Estados Unidos. University of Pittsburgh; Estados UnidosFil: Ju, Zhenlin. University Of Texas Md Anderson Cancer Center;Fil: Wang, Zhenghe. Case Western Reserve University; Estados UnidosFil: Pendleton, Kelsey P.. University of Pittsburgh; Estados Unidos. University of Pittsburgh at Johnstown; Estados UnidosFil: Xiao, Xiao. University of Pittsburgh at Johnstown; Estados Unidos. University of Pittsburgh; Estados UnidosFil: Du, Yu. University of Pittsburgh at Johnstown; Estados Unidos. University of Pittsburgh; Estados UnidosFil: Vries, John K.. University of Pittsburgh; Estados Unidos. University of Pittsburgh at Johnstown; Estados UnidosFil: Hammerman, Peter S.. Harvard Medical School; Estados UnidosFil: Garraway, Levi A.. Harvard Medical School; Estados UnidosFil: Mills, Gordon B.. University Of Texas Md Anderson Cancer Center;Fil: Johnson, Daniel E.. University of Pittsburgh at Johnstown; Estados Unidos. University of Pittsburgh; Estados UnidosFil: Grandis, Jennifer R.. University of Pittsburgh; Estados Unidos. University of Pittsburgh at Johnstown; Estados Unido

Integrated RNA and DNA sequencing improves mutation detection in low purity tumors

Identifying somatic mutations is critical for cancer genome characterization and for prioritizing patient treatment. DNA whole exome sequencing (DNA-WES) is currently the most popular technology; however, this yields low sensitivity in low purity tumors. RNA sequencing (RNA-seq) covers the expressed exome with depth proportional to expression. We hypothesized that integrating DNA-WES and RNA-seq would enable superior mutation detection versus DNA-WES alone. We developed a first-of-its-kind method, called UNCeqR, that detects somatic mutations by integrating patient-matched RNA-seq and DNA-WES. In simulation, the integrated DNA and RNA model outperformed the DNA-WES only model. Validation by patient-matched whole genome sequencing demonstrated superior performance of the integrated model over DNA-WES only models, including a published method and published mutation profiles. Genome-wide mutational analysis of breast and lung cancer cohorts (n = 871) revealed remarkable tumor genomics properties. Low purity tumors experienced the largest gains in mutation detection by integrating RNA-seq and DNA-WES. RNA provided greater mutation signal than DNA in expressed mutations. Compared to earlier studies on this cohort, UNCeqR increased mutation rates of driver and therapeutically targeted genes (e.g. PIK3CA, ERBB2 and FGFR2). In summary, integrating RNA-seq with DNA-WES increases mutation detection performance, especially for low purity tumors

Characterizing genomic alterations in cancer by complementary functional associations.

Systematic efforts to sequence the cancer genome have identified large numbers of mutations and copy number alterations in human cancers. However, elucidating the functional consequences of these variants, and their interactions to drive or maintain oncogenic states, remains a challenge in cancer research. We developed REVEALER, a computational method that identifies combinations of mutually exclusive genomic alterations correlated with functional phenotypes, such as the activation or gene dependency of oncogenic pathways or sensitivity to a drug treatment. We used REVEALER to uncover complementary genomic alterations associated with the transcriptional activation of β-catenin and NRF2, MEK-inhibitor sensitivity, and KRAS dependency. REVEALER successfully identified both known and new associations, demonstrating the power of combining functional profiles with extensive characterization of genomic alterations in cancer genomes

Noisy-threshold control of cell death

<p>Abstract</p> <p>Background</p> <p>Cellular responses to death-promoting stimuli typically proceed through a differentiated multistage process, involving a lag phase, extensive death, and potential adaptation. Deregulation of this chain of events is at the root of many diseases. Improper adaptation is particularly important because it allows cell sub-populations to survive even in the continuous presence of death conditions, which results, among others, in the eventual failure of many targeted anticancer therapies.</p> <p>Results</p> <p>Here, I show that these typical responses arise naturally from the interplay of intracellular variability with a threshold-based control mechanism that detects cellular changes in addition to just the cellular state itself. Implementation of this mechanism in a quantitative model for T-cell apoptosis, a prototypical example of programmed cell death, captures with exceptional accuracy experimental observations for different expression levels of the oncogene Bcl-x_Land directly links adaptation with noise in an ATP threshold below which cells die.</p> <p>Conclusions</p> <p>These results indicate that oncogenes like Bcl-x_L, besides regulating absolute death values, can have a novel role as active controllers of cell-cell variability and the extent of adaptation.</p