An integrated approach to understand the regulatory role of miR-27 family in breast cancer metastasis.

One of the prime reasons of increasing breast cancer mortality is metastasizing cancer cells. Owing to the side effects of clinically available drugs to treat breast cancer metastasis, it is of utmost importance to understand the underlying biogenesis of breast cancer tumorigenesis. In-silico identification of potential RNAs might help in utilizing the miR-27 family as a therapeutic target in breast cancer. The experimentally verified common interacting mRNAs for miR27 family are retrieved from three publicly available databases- TargetScan, miRDB and miRTarBase. Finally on comparing the common genes with HCMDB and GEPIA data, four breast cancer-associated differentially expressed metastatic mRNAs (GATA3, ENAH, ITGA2 and SEMA4D) are obtained. Corresponding to the miR27 family and associated mRNAs, interacting drugs are retrieved from Sm2mir and CTDbase, respectively. The interaction network-based approach was utilized to obtain the hub RNAs and triad modules by employing the 'Cytohubba' and 'MClique' plugins, respectively in Cytoscape. Further, sample-, subclass- and promoter methylation-based expression analyses reveals GATA3 and ENAH to be the most significant mRNAs in breast cancer metastasis having >10% genetic alteration in both METABRIC Vs TCGA datasets as per their oncoprint analysis via cBioPortal. Additionally, survival analysis in Oncolnc reveals SEMA4D as survival biomarker. Interactions among the miR27 family, their target mRNAs and drugs interacting with miRNAs and mRNAs can be extensively explored in both in-vivo and in-vitro setups to assess their therapeutic potential in the diminution of breast cancer.

Advances in Drug Discovery based on Genomics, Proteomics and Bioinformatics in Malaria.

Malaria is one of the neglected infectious diseases, and drugs are the first line of action taken against the onset of malaria as therapeutics. The drugs can be of either natural or artificial origin. Drug development has multiple impediments grouped under three categories, a. drug discovery and screening, b. the drug's action on the host and the pathogen, and c. clinical trials. Drug development takes coon's age from discovery to the market after FDA approval. At the same time, targeted organisms develop drug resistance quicker than drug approval, raising the requirement for advancement in drug development. The approach to explore drug candidates using the classical methods from natural sources, computation-based docking, mathematical and machine learningbased high throughput in silico models or drug repurposing has been investigated and developed. Also, drug development with information about the interaction between Plasmodium species and its host, humans, may facilitate obtaining an efficient drug cohort for further drug discovery or repurposing expedition. However, drugs may have side effects on the host system. Hence, machine learning and systems-based approaches may provide a holistic view of genomic, proteomic, and transcriptomic data and their interaction with the selected drug candidates. This review comprehensively describes the drug discovery workflows using drug and target screening methodologies, followed by possible ways to check the binding affinity of the drug and targets using various docking software.

The functional significance and cross-talk of non-coding RNAs in triple negative and quadruple negative breast cancer.

One of the leading causes of cancer-related deaths worldwide is breast cancer, among which triple-negative breast cancer (TNBC) is the most malignant and lethal subtype. This cancer accounts for 10-20% of all breast cancer deaths. Proliferation, tumorigenesis, and prognosis of TNBC are affected when the androgen receptor (AR) is not expressed, and it is classified as quadruple negative breast cancer (QNBC). Non-coding RNAs, such as microRNAs (miRNAs), long non-coding RNAs (lncRNAs), and circular RNAs (circRNAs), play a significant role in tumorigenesis by virtue of their oncogenic and tumor-suppressive properties. To regulate tumorigenesis, miRNAs interact with their target mRNAs and modulate their expression, whereas lncRNAs can either act alone or interact with miRNAs or other molecules through various signaling pathways. Conversely, circRNAs regulate tumorigenesis by acting as miRNA sponges predominantly. Recently, non-coding RNAs were studied comprehensively for their roles in tumor proliferation, progression, and metastasis. As a result of existing studies and research progress, non-coding RNAs have been implicated in TNBC, necessitating their use as biomarkers for future diagnostic applications. In this review, the non-coding RNAs are explicitly implicated in the regulation of breast cancer, and their cross-talk between TNBC and QNBC is also discussed.