Over the past decade, comprehensive sequencing efforts have revealed the genomic landscapes of common forms of human cancer. For most cancer types, this landscape consists of a small number of “mountains” (genes altered in a high percentage of tumors) and a much larger number of “hills” (genes altered infrequently). To date, these studies have revealed ~140 genes that, when altered by intragenic mutations, can promote or “drive” tumorigenesis. A typical tumor contains two to eight of these “driver gene” mutations; the remaining mutations are passengers that confer no selective growth advantage. Driver genes can be classified into 12 signaling pathways that regulate three core cellular processes: cell fate, cell survival, and genome maintenance. A better understanding of these pathways is one of the most pressing needs in basic cancer research. Even now, however, our knowledge of cancer genomes is sufficient to guide the development of more effective approaches for reducing cancer morbidity and mortality.

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Cancer Genome Landscapes

Interest in the topic of tumour metabolism has waxed and waned over the past century of cancer research. The early observations of Warburg and his contemporaries established that there are fundamental differences in the central metabolic pathways operating in malignant tissue. However, the initial hypotheses that were based on these observations proved inadequate to explain tumorigenesis, and the oncogene revolution pushed tumour metabolism to the margins of cancer research. In recent years, interest has been renewed as it has become clear that many of the signalling pathways that are affected by genetic mutations and the tumour microenvironment have a profound effect on core metabolism, making this topic once again one of the most intense areas of research in cancer biology.

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Regulation of cancer cell metabolism

KEGG(Kyoto Encyclopedia of Genes and Genomes)〔和文〕 (特集 ゲノム医学の現在と未来--基礎と臨床) -- (データベース)

Mutations in the enzyme cytosolic isocitrate dehydrogenase 1 (IDH1) are a common feature of a major subset of primary human brain cancers. These mutations occur at a single amino acid residue of the IDH1 active site, resulting in loss of the enzyme's ability to catalyse conversion of isocitrate to alpha-ketoglutarate. However, only a single copy of the gene is mutated in tumours, raising the possibility that the mutations do not result in a simple loss of function. Here we show that cancer-associated IDH1 mutations result in a new ability of the enzyme to catalyse the NADPH-dependent reduction of alpha-ketoglutarate to R(-)-2-hydroxyglutarate (2HG). Structural studies demonstrate that when arginine 132 is mutated to histidine, residues in the active site are shifted to produce structural changes consistent with reduced oxidative decarboxylation of isocitrate and acquisition of the ability to convert alpha-ketoglutarate to 2HG. Excess accumulation of 2HG has been shown to lead to an elevated risk of malignant brain tumours in patients with inborn errors of 2HG metabolism. Similarly, in human malignant gliomas harbouring IDH1 mutations, we find markedly elevated levels of 2HG. These data demonstrate that the IDH1 mutations result in production of the onco-metabolite 2HG, and indicate that the excess 2HG which accumulates in vivo contributes to the formation and malignant progression of gliomas.

/pdf/cancer-associated-idh1-mutations-produce-2-hydroxyglutarate-3hnshr7hh1.pdf

Cancer-associated IDH1 mutations produce 2-hydroxyglutarate

Metabolic Reprogramming: A Cancer Hallmark Even Warburg Did Not Anticipate

To reduce FPGA power, a linear programming (LP) based time slack allocation algorithm, EdTLC-LP, has been proposed recently for Vdd-programmable interconnects without using Vdd-level converters for mixed wire lengths. However, it takes a long time to solve the LP problem for time slack allocation. In this paper, we develop EdTLC-NW, a slack allocation algorithm based on min-cost network flow to reduce runtime. Compared to single Vdd FPGA with power-gating, EdTLC-LP and EdTLC-NW reduce interconnect power by 52.71% and 52.52%, respectively. EdTLC-NW achieves as good results as EdTLC-LP but runs 8times faster on average. Furthermore, the speedup increases for larger circuits and EdTLC-NW is 20times faster for the largest circuit

/pdf/an-efficient-chip-level-time-slack-allocation-algorithm-for-31loter8ka.pdf

An efficient chip-level time slack allocation algorithm for Dual-Vdd FPGA power reduction

In this article, we investigate the anti-jamming problem with joint channel and power allocation for unmanned aerial vehicle (UAV) networks. In particular, we focus on avoiding both mutual interference among UAVs and external malicious jamming to maximize the system Quality of Experience (QoE) relevant to the power consumption. To simultaneously capture the competition and coordination among UAVs, we first model the problem as a local interaction Markov game and then prove it as an exact potential game with at least one Nash equilibrium. Next, we propose a collaborative multiagent layered Q learning (MALQL)-based anti-jamming communication algorithm to reduce the high dimensionality of the action space and analyze the asymptotic convergence of the proposed algorithm. Simulation results show the effectiveness of the proposed algorithm, which outperforms the traditional multiagent $Q$ learning algorithm when suffering from different jamming strategies.

Collaborative Multiagent Reinforcement Learning Aided Resource Allocation for UAV Anti-Jamming Communication

This paper is devoted to the adaptive output tracking for a class of multi-input multi-output nonlinear systems with unknown non-symmetric dead-zone. Under the assumption that the signs of leading principal minors of the control gain matrix are known, an adaptive dynamic surface control scheme is proposed. The proposed scheme is able to avoid the explosion of complexity problem in backstepping design and guarantee the L ∞ performance of the tracking error. Moreover, only one parameter needs to be updated online at each design step, which significantly reduces the computational burden. It is proved that all signals of the closed-loop system are semi-globally uniformly bounded. Simulation results are given to illustrate the effectiveness of the proposed scheme.

Adaptive output tracking of MIMO nonlinear systems with unknown non-symmetric dead-zone

This paper aims to extend the newly developed global adaptive regulation scheme to adaptive tracking for a general class of nonlinear systems with both parameter uncertainties and unknown time dela...

Global adaptive tracking for a class of nonlinear time-delay systems

In this paper, a robust output-feedback adaptive control is proposed for linear time-invariant (LTI) singleinput single-output (SISO) plants with unmeasurable input disturbance. Using dynamic surface control (DSC) technique, it is shown that the explosion of complexity problem in backstepping control can be eliminated. Furthermore, the proposed adaptive DSC scheme has the following merits: 1) by introducing an initialization technique, the L∞ performance of system tracking error can be guaranteed even if the plant high-frequency gain is unknown and the input disturbance exists, and 2) the adaptive law is necessary only at the first design step, which significantly reduces the design procedure. It is proved that with the proposed scheme, all the closed-loop signals are semiglobally uniformly ultimately bounded. Simulation results are presented to demonstrate the effectiveness of the proposed scheme.

Yan Lin

Papers

An efficient chip-level time slack allocation algorithm for Dual-Vdd FPGA power reduction

Collaborative Multiagent Reinforcement Learning Aided Resource Allocation for UAV Anti-Jamming Communication

Adaptive output tracking of MIMO nonlinear systems with unknown non-symmetric dead-zone

Global adaptive tracking for a class of nonlinear time-delay systems

A robust output-feedback adaptive dynamic surface control for linear systems with input disturbance