Epigenetic Regulation of Cancer-Associated Genes in Ovarian Cancer

The involvement of epigenetic aberrations in the development and progression of tumors is now well established. However, most studies have focused on the epigenetic inactivation of tumor suppressor genes during tumorigenesis and little is known about the epigenetic activation of cancer-associated genes, except for the DNA hypomethylation of some genes. Recently, we reported that the overexpression of cancer-promoting genes in ovarian cancer is associated with the loss of repressive histone modifications. This discovery suggested that epigenetic derepression may contribute to ovarian tumorigenesis by constituting a possible mechanism for the overexpression of oncogenes or cancer-promoting genes in tumors. The emerging importance of epigenetic aberrations in tumor initiation and in the regulation of cancer-initiating cells, suggests that epigenetically regulated genes may be promising therapeutic targets and biomarkers. Given that the current challenges in ovarian cancer include the identification of biomarkers for early cancer detection and the discovery of novel therapeutic targets for patients with recurrent malignancies undergoing chemotherapy, understanding the epigenetic changes that occur in ovarian cancer is crucial. This review looks at epigenetic mechanisms involved in the regulation of cancer-associated genes, including the contribution of epigenetic derepression to the activation of cancer-associated genes in ovarian cancer. In addition, possible epigenetic therapies targeting epigenetically dysregulated genes are discussed. A better understanding of the epigenetic changes in ovarian cancer will contribute to the improvement of patient outcomes

Overexpression of Cancer-Associated Genes via Epigenetic Derepression Mechanisms in Gynecologic Cancer

Like other cancers, most gynecologic cancers are caused by aberrant expression of cancer-related genes. Epigenetics is one of the most important gene expression mechanisms, which contribute to cancer development and progression by regulating cancer-related genes. Since the discovery of differential gene expression patterns in cancer cells when compared with normal cells, extensive efforts have been made to explore the origins of abnormal gene expression in cancer. Epigenetics, the study of inheritable changes in gene expression that do not alter DNA sequence is a key area of this research. DNA methylation and histone modification are well-known epigenetic mechanisms, while microRNAs and alternative splicing have recently been identified as important regulators of epigenetic mechanisms. These mechanisms not only affect specific target gene expression but also regulate the functioning of other epigenetic mechanisms. Moreover, these diverse epigenetic regulations occur simultaneously. Epigenetic regulation of gene expression is extraordinarily complicated and all epigenetic mechanisms to be studied at once to determine the exact gene regulation mechanisms. Traditionally, the contribution of epigenetics to cancer is thought to be mediated through the inactivation of tumor suppressor genes expression. But recently, it is arising that some oncogenes or cancer-promoting genes (CPGs) are overexpressed in diverse type of cancers through epigenetic derepression mechanism, such as DNA and histone demethylation. Epigenetic derepression arises from diverse epigenetic changes, and all of these mechanisms actively interact with each other to increase oncogenes or CPGs expression in cancer cell. Oncogenes or CPGs overexpressed through epigenetic derepression can initiate cancer development, and accumulation of these abnormal epigenetic changes makes cancer more aggressive and treatment resistance. This review discusses epigenetic mechanisms involved in the overexpression of oncogenes or CPGs via epigenetic derepression in gynecologic cancers. Therefore, improved understanding of these epigenetic mechanisms will provide new targets for gynecologic cancer treatment

Two Cases of Lichen Planus Pigmentosus Presenting with a Linear Pattern

We report two cases of lichen planus pigmentosus (LPP) that developed in a unilateral linear pattern. The patients presented with unilateral linear brown macules on the extremities. Skin biopsy showed orthokeratosis, basal hydropic degeneration with scarce lymphohistiocytic infiltrates, and numerous melanophages in both patients. These patients, to the best of our knowledge, are the first cases of LPP presenting with a linear pattern. LPP should be considered in the differential diagnosis of linear hyperpigmented skin lesions

Contextual Linear Bandits under Noisy Features: Towards Bayesian Oracles

We study contextual linear bandit problems under uncertainty on features; they are noisy with missing entries. To address the challenges from the noise, we analyze Bayesian oracles given observed noisy features. Our Bayesian analysis finds that the optimal hypothesis can be far from the underlying realizability function, depending on noise characteristics, which is highly non-intuitive and does not occur for classical noiseless setups. This implies that classical approaches cannot guarantee a non-trivial regret bound. We thus propose an algorithm aiming at the Bayesian oracle from observed information under this model, achieving $\tilde{O}(d\sqrt{T})$ regret bound with respect to feature dimension $d$ and time horizon $T$. We demonstrate the proposed algorithm using synthetic and real-world datasets.Comment: 30 page

Youth Smoking, Cigarette Prices, and Anti-Smoking Sentiment

In this paper, we develop a new direct measure of state anti-smoking sentiment and merge it with micro data on youth smoking in 1992 and 2000. The empirical results from the cross-sectional models show two consistent patterns: after controlling for differences in state anti-smoking sentiment, the price of cigarettes has a weak and statistically insignificant influence on smoking participation; and state anti-smoking sentiment appears to be a potentially important influence on youth smoking participation. The cross-sectional results are corroborated by results from discrete time hazard models of smoking initiation that include state fixed effects. However, there is evidence of price-responsiveness in the conditional cigarette demand by youth and young adult smokers.

A Cost Effective Block Framing Scheme for Underwater Communication

In this paper, the Selective Multiple Acknowledgement (SMA) method, based on Multiple Acknowledgement (MA), is proposed to efficiently reduce the amount of data transmission by redesigning the transmission frame structure and taking into consideration underwater transmission characteristics. The method is suited to integrated underwater system models, as the proposed method can handle the same amount of data in a much more compact frame structure without any appreciable loss of reliability. Herein, the performance of the proposed SMA method was analyzed and compared to those of the conventional Automatic Repeat-reQuest (ARQ), Block Acknowledgement (BA), block response, and MA methods. The efficiency of the underwater sensor network, which forms a large cluster and mostly contains uplink data, is expected to be improved by the proposed method