Non-Coding RNAs in Oral Cancer: Emerging Roles and Clinical Applications.

Oral cancer (OC) is among the most prevalent cancers in the world. Certain geographical areas are disproportionately affected by OC cases due to the regional differences in dietary habits, tobacco and alcohol consumption. However, conventional therapeutic methods do not yield satisfying treatment outcomes. Thus, there is an urgent need to understand the disease process and to develop diagnostic and therapeutic strategies for OC. In this review, we discuss the role of various types of ncRNAs in OC, and their promising clinical implications as prognostic or diagnostic markers and therapeutic targets. MicroRNA (miRNA), long ncRNA (lncRNA), circular RNA (circRNA), PIWI-interacting RNA (piRNA), and small nucleolar RNA (snoRNA) are the major ncRNA types whose involvement in OC are emerging. Dysregulated expression of ncRNAs, particularly miRNAs, lncRNAs, and circRNAs, are linked with the initiation, progression, as well as therapy resistance of OC via modulation in a series of cellular pathways through epigenetic, transcriptional, post-transcriptional, and translational modifications. Differential expressions of miRNAs and lncRNAs in blood, saliva or extracellular vesicles have indicated potential diagnostic and prognostic importance. In this review, we have summarized all the promising aspects of ncRNAs in the management of OC.

Revisiting the Role of CD63 as Pro-Tumorigenic or Anti-Tumorigenic Tetraspanin in Cancers and its Theragnostic Implications.

Cluster of differentiation antigen 63 (CD63) belongs to a superfamily of proteins, usually defined as tetraspanins which are known to transverse the bilayer membranes four times. The expression of CD63 has been shown to get altered in several cancers, where it has been demonstrated to act as both a tumor promoter and tumor suppressor. The present review describes the mechanism of how CD63 promotes tumor formation in certain cancer types while inhibiting in some other specific cancers. Glycosylation, a post-translational process plays a significant role in regulating the expression and function of these membrane proteins. Being a crucial exosomal flag protein, CD63 has been found to get involved in endosomal cargo sorting as well as the production of extracellular vesicles. Increased expression of exosomal CD63 derived from advanced tumors has demonstrated its role in promoting metastasis. CD63 also regulates the characteristic and function of stem cells on which they get expressed. This particular tetraspanin has been discovered to participate in gene fusion to perform distinctive roles in certain specific cancer types like breast cancer and pigmented epithelioid melanocytoma. Furthermore, this review mentions twelve different microRNAs obtained from miRDB that might target CD63. A few theragnostic uses of this membrane protein are also discussed. Thereby, the review indicates that further studies on CD63 might prove it to be an effective therapeutic target in different cancers in the coming future.

Energy-Balancing Unequal Clustering Approach to Reduce the Blind Spot Problem in Wireless Sensor Networks (WSNs).

Wireless Sensor Networks (WSNs) have become a significant part of surveillance techniques. With unequal clustering approaches and multi-hop communication, WSNs can balance energy among the clusters and serve a wide monitoring area. Recent research has shown significant improvements in unequal clustering approaches by forming clusters prior to the selection of cluster heads. These improvements adopt different geometric fractals, such as the Sierpinski triangle, to divide the monitoring area into multiple clusters. However, performance of such approaches can be improved further by cognitive partitioning of the monitoring area instead of adopting random fractals. This paper proposes a novel clustering approach that partitions the monitoring area in a cognitive way for balancing the energy consumption. In addition, the proposed approach adopts a two-layered scrutinization process for the selection of cluster heads that ensures minimum energy consumption from the network. Furthermore, it reduces the blind spot problem that escalates once the nodes start dying. The proposed approach has been tested in terms of number of alive nodes per round, energy consumption of nodes and clusters, and distribution of alive nodes in the network. Results show a significant improvement in balancing the energy consumption among clusters and a reduction in the blind spot problem.