RNA-binding proteins (RBPs) play fundamental roles in cancer; however, we still lack knowledge about to what extent RBPs are dysregulated, as well as about perturbed signaling pathways in cancer. In this study, we integrated analysis of multidimensional data across >10,000 cancer patients and >1,000 cell lines. We identified a top candidate RBP: eukaryotic translation initiation factor 2 subunit beta (EIF2S2). EIF2S2 is highly expressed in tumors and is associated with malignant features as well as patient prognosis. Functional assays performed in cancer cells revealed that EIF2S2 promotes cancer cell proliferation, migration, and invasion in vitro as well as tumor growth and metastasis in vivo. Mechanistic investigations further demonstrated that EIF2S2 promotes tumorigenesis and progression by directly binding to a long non-coding RNA, LINC01600, which physically interacts with the MYC protein and increases its stability. Interestingly, we revealed that the EIF2S2-LINC01600-MYC axis can activate the Wnt/β-catenin pathway by inhibiting the activity of FHIT-related enhancers and FHIT expression. Finally, EIF2S2 knockdown combined with oxaliplatin treatment could be a potential combination therapy in cancer. Our integrated analysis provided detailed knowledge of the function of the EIF2S2-LINC01600-MYC axis, which will facilitate the development of rational combination therapies for cancer.

In this paper, a model of strain-induced nanomagnet is established at room temperature to explore the effect of size error on the reliability of the straintronic memory and spin neurons. The results show that the relationship between input voltages and 180 magnetization switching probability (activation function) of the nanomagnet has the size dependence. The slope of the activation function is only related to the aspect ratio of the nanomagnet, and the thickness error will not affect its slope. The slope of the activation function will decrease as the aspect ratio increase. At the same time, the offset of the activation function increases with the increasing of the energy barrier (increase thickness or decrease aspect ratio) of the nanomagnet. We found that a slight dimensional error will also significantly reduce the reliability of straintronic memory. Increasing the fabrication accuracy or changing the input voltages can solve this problem. We further studied the relationship between the size error and the reliability of spin neurons by using different size spintronic neural network for handwritten digits recognition under the same input voltages. We found that the size error has minor effect on the spin neuron's neurologic computing function. The thickness error of 3nm or the width error of 8nm will not affect the recognition accuracy of spintronic neural network. In other words, straintronic spin neurons are more tolerant to dimensional errors and more reliable than strain memories, and its fabrication accuracy requirements can be lower. These findings can provide important guidance for the design of straintronic spin neuron and memory.

A stairs-type global strain clocking mechanism for nanomagnetic majority logic gate based on shape engineering of nanomagnets was designed in this paper. Reasonable size nanomagnets and proper strain clocking scheme ensure the computing architecture pipelined at room temperature. The optimal global strain clocking scheme was obtained by investigating the impact of magnetic layer thickness and width on clocking period and strain magnitude. Encouragingly, for the global strain clocking, information transmission speed of majority logic gate is increased 1-2 times as against the local strain clocking scheme due to decreasing the number of start-ups during information transmission. While the energy dissipated per clock cycle of the global strain clocking scheme consumes 3-4 times less energy than that of local strain clocking scheme. Moreover, global clocking is used to control a nanomagnetic logic device(NMLD), in which case single device consisted of many nanomagnets can be treated as single nanomagnet. However, magnetization switching is error-prone in the presence of thermal noise at room temperature. Therefore, the proper structure parameters of the device are obtained at room temperature, in which case the error probability of the majority logic gate is 0.5% in theoretical simulation. These results provide essential guidance for the design of energy-efficient multiferroic nanomagnetic logic devices.