CAMIRADA: Cancer microRNA association discovery algorithm, a case study on breast cancer

Abstract

In recent studies, non-coding protein RNAs have been identified as mi-croRNA that can be used as biomarkers for early diagnosis and treatment of cancer, that decrease mortality in cancer. A microRNA may target hundreds or thousands of genes and a gene may regulate several microRNAs, so determining which microRNA is associated with which cancer is a big challenge. Many computational methods have been performed to detect micoRNAs association with cancer, but more effort is needed with higher accuracy. Increasing research has shown that relationship between microR-NAs and TFs play a significant role in the diagnosis of cancer. Therefore, we developed a new computational framework (CAMIRADA) to identify cancerrelated microRNAs based on the relationship between microRNAs and disease genes (DG) in the protein network, the functional relationships between microRNAs and Transcription Factors (TF) on the co-expression network, and the relationship between microRNAs and the Differential Expression Gene (DEG) on co-expression network. The CAMIRADA was applied to assess breast cancer data from two HMDD and miR2Disease databases. In this study, the AUC for the 65 microRNAs of the top of the list was 0.95, which was more accurate than the similar methods used to detect microRNAs associated with the cancer artery.

Extracellular Vesicles in Breast Cancer: From Biology and Function to Clinical Diagnosis and Therapeutic Management

“…Combination of two plasma SEVs miRNAs (miR-21 and miR-1246 [ 433 ], miR-21 and miR-221 [ 434 ], miR-21 and miR-155 [ 435 ], and miR-92a, and miR-25-3p [ 436 ]), three miRNAs (miR-16, miR-30b, and miR-93 [ 437 ]; miR-21, miR-105, and miR-222 [ 438 ]; miR-21, miR-155, and miR-365 [ 439 ]; and miR-145, miR-155, and miR-382 [ 440 ]), four miRNAs (miR-21, miR-55, miR-10b, and Let-7a [ 441 ]), up to thirteen miRNAs (miR-21-3p, miR-192-5p, miR-221-3p, miR-451a, miR-574-5p, miR-1273g-3p, miR-152, miR-22-3p, miR-222-3p, miR-30a-5p, miR-30e-5p, miR-324-3p, and miR-382-5p) [ 442 ] have been described. To optimize and find new relevant miRNA combinations, some algorithms have been developed to detect BC specifically ([ 443 ].…”

MicroRNA-139-5p acts as a suppressor gene for depression by targeting nuclear receptor subfamily 3, group C, member 1

“…MiRNAs, which are widely distributed in various tissues and organs, participate in metabolism, hematopoiesis, immune response, development [ 8 , 9 ] and play critical roles in cell death, cancer development and progression, and disease outcomes [ 3 , 10 ]. MiRNAs play significant roles in neuron differentiation, neurotransmitter transmission, neuromorphological occurrence, and synaptic plasticity formation [ 11 , 12 ]. Therefore, in depressive disorders, the value of miRNAs is worth exploring.…”

CmirC: an integrated database of clustered miRNAs co-localized with copy number variations in cancer

“…In recent years, numerous databases such as miRCancer (Xie et al 2013), miRwayDB (Das et al 2018), TACCO (Chou et al 2019), miRactDB (Tan et al 2021), DriverDBv3 (Liu et al 2020, and miR-TV (Pan and Lin 2020) have been released for public access to comprehend cancer drivers. Additionally, well established computational approaches such as miRDriver (Bose and Bozdag 2019), CAMIRADA (Shamsizadeh et al 2019), FCMDAP (Li et al 2019), and 18) is harbored on the X chromosome PMAMCA (Ha et al 2019) can determine the associations between microRNAs and cancers. However, a comprehensive resource for miRNA clusters co-localized with CNV regions and their expression analysis is unavailable.…”