A systematic review of long non-coding RNAs with a potential role in breast cancer

Long non-coding RNAs; potential contributors in cancer chemoresistance through modulating diverse molecular mechanisms and signaling pathways

One of the mainstays of cancer treatment is chemotherapy. Drug resistance, however, continues to be the primary factor behind clinical treatment failure. Gene expression is regulated by long non-coding RNAs (lncRNAs) in several ways, including chromatin remodeling, translation, epigenetic, and transcriptional levels. Cancer hallmarks such as DNA damage, metastasis, immunological evasion, cell stemness, drug resistance, metabolic reprogramming, and angiogenesis are all influenced by LncRNAs. Numerous studies have been conducted on LncRNA-driven mechanisms of resistance to different antineoplastic drugs. Diverse medication kinds elicit diverse resistance mechanisms, and each mechanism may have multiple contributing factors. As a result, several lncRNAs have been identified as new biomarkers and therapeutic targets for identifying and managing cancers. This compels us to thoroughly outline the crucial roles that lncRNAs play in drug resistance. In this regard, this article provides an in-depth analysis of the recently discovered functions of lncRNAs in the pathogenesis and chemoresistance of cancer. As a result, the current research might offer a substantial foundation for future drug resistance-conquering strategies that target lncRNAs in cancer therapies.

Advancements in small interfering RNAs therapy for acute lymphoblastic leukemia: promising results and future perspectives

Acute lymphoblastic leukemia (ALL) is the most common type of cancer among children, presenting significant healthcare challenges for some patients, including drug resistance and the need for targeted therapies. SiRNA-based therapy is one potential solution, but problems can arise in administration and the need for a delivery system to protect siRNA during intravenous injection. Additionally, siRNA encounters instability and degradation in the reticuloendothelial system, off-target effects, and potential immune system stimulation. Despite these limitations, some promising results about siRNA therapy in ALL patients have been published in recent years, showing the potential for more effective and precise treatment, reduced side effects, and personalized approaches. While siRNA-based therapies demonstrate safety and efficacy, addressing the mentioned limitations is crucial for further optimization. Advancements in siRNA-delivery technologies and combination therapies hold promise to improve treatment effectiveness and overcome drug resistance. Ultimately, despite its challenges, siRNA therapy has the potential to revolutionize ALL treatments and improve patient outcomes.

NORAD-Regulated Signaling Pathways in Breast Cancer Progression

Long non-coding RNA activated by DNA damage (NORAD) has recently been associated with pathologic mechanisms underlying cancer progression. Due to NORAD's extended range of interacting partners, there has been contradictory data on its oncogenic or tumor suppressor roles in BC. This review will summarize the function of NORAD in different BC subtypes and how NORAD impacts crucial signaling pathways in this pathology. Through the preferential binding to pumilio (PUM) proteins PUM1 and PUM2, NORAD has been shown to be involved in the control of cell cycle, angiogenesis, mitosis, DNA replication and transcription and protein translation. More recently, NORAD has been associated with PUM-independent roles, accomplished by interacting with other ncRNAs, mRNAs and proteins. The intricate network of NORAD-mediated signaling pathways may provide insights into the potential design of novel unexplored strategies to overcome chemotherapy resistance in BC treatment.

Proposing a hybrid technique of feature fusion and convolutional neural network for melanoma skin cancer detection

Skin cancer is among the most common cancer types worldwide. Automatic identification of skin cancer is complicated because of the poor contrast and apparent resemblance between skin and lesions. The rate of human death can be significantly reduced if melanoma skin cancer could be detected quickly using dermoscopy images. This research uses an anisotropic diffusion filtering method on dermoscopy images to remove multiplicative speckle noise. To do this, the fast-bounding box (FBB) method is applied here to segment the skin cancer region. We also employ 2 feature extractors to represent images. The first one is the Hybrid Feature Extractor (HFE), and second one is the convolutional neural network VGG19-based CNN. The HFE combines 3 feature extraction approaches namely, Histogram-Oriented Gradient (HOG), Local Binary Pattern (LBP), and Speed Up Robust Feature (SURF) into a single fused feature vector. The CNN method is also used to extract additional features from test and training datasets. This 2-feature vector is then fused to design the classification model. The proposed method is then employed on 2 datasets namely, ISIC 2017 and the academic torrents dataset. Our proposed method achieves 99.85%, 91.65%, and 95.70% in terms of accuracy, sensitivity, and specificity, respectively, making it more successful than previously proposed machine learning algorithms.

Regulatory miRNAs, circRNAs and lncRNAs in cell cycle progression of breast cancer

Breast cancer is a complex and heterogeneous disease that poses a significant public health concern worldwide, and it remains a major challenge despite advances in treatment options. One of the main properties of cancer cells is the increased proliferative activity that has lost regulation. Dysregulation of various positive and negative modulators in the cell cycle has been identified as one of the driving factors of breast cancer. In recent years, non-coding RNAs have garnered much attention in the regulation of cell cycle progression, with microRNAs (miRNAs), circular RNAs (circRNAs), and long non-coding RNAs (lncRNAs) being of particular interest. MiRNAs are a class of highly conserved and regulatory small non-coding RNAs that play a crucial role in the modulation of various cellular and biological processes, including cell cycle regulation. CircRNAs are a novel form of non-coding RNAs that are highly stable and capable of modulating gene expression at posttranscriptional and transcriptional levels. LncRNAs have also attracted considerable attention because of their prominent roles in tumor development, including cell cycle progression. Emerging evidence suggests that miRNAs, circRNAs and lncRNAs play important roles in the regulation of cell cycle progression in breast cancer. Herein, we summarized the latest related literatures in breast cancer that emphasize the regulatory roles of miRNAs, circRNAs and lncRNAs in cell cycle progress of breast cancer. Further understanding of the precise roles and mechanisms of non-coding RNAs in breast cancer cell cycle regulation could lead to the development of new diagnostic and therapeutic strategies for breast cancer.

Regulation of T cell differentiation and function by long noncoding RNAs in homeostasis and cancer

Long noncoding RNAs (lncRNAs) increase in genomes of complex organisms and represent the largest group of RNA genes transcribed in mammalian cells. Previously considered only transcriptional noise, lncRNAs comprise a heterogeneous class of transcripts that are emerging as critical regulators of T cell-mediated immunity. Here we summarize the lncRNA expression landscape of different T cell subsets and highlight recent advances in the role of lncRNAs in regulating T cell differentiation, function and exhaustion during homeostasis and cancer. We discuss the different molecular mechanisms of lncRNAs and highlight lncRNAs that can serve as novel targets to modulate T cell function or to improve the response to cancer immunotherapies by modulating the immunosuppressive tumor microenvironment.

Advances in the Diagnosis and Prognosis of Minimal Residual Lesions of Breast Cancer

PURPOSE

To review the latest research of minimal residual disease (MRD) in breast cancer as well as some emerging or potential detection methods for MRD in breast cancer.

METHODS

Springer, Wiley, and PubMed databases were searched for the electronic literature with search terms of breast cancer, minimal residual disease, circulating tumor cells (CTCs), circulating tumor DNA (ctDNA), exosomes, etc. RESULTS: Minimal residual disease refers to the occult micrometastasis or minimal residual lesions detected in patients with tumor after radical treatment. An early and dynamic monitoring of breast cancer MRD can contribute to clinical treatment decision-making, improving the diagnosis accuracy and prognosis of breast cancer patients. The updated knowledge regarding MRD in breast cancer diagnosis and prognosis were summarized, followed by the review of several emerging or potential detection technologies for MRD in breast cancer. With the developed new MRD detection technologies referring to CTCs, ctDNA and exosomes, the role of MRD in breast cancer has been growingly verified, which is expected to serve as a new risk stratification factor and prognostic indicator for breast cancer.

CONCLUSION

This paper systematically reviews the research progress, opportunities and challenges in MRD in breast cancer in recent years.

A Comprehensive Investigation of Genomic Variants in Prostate Cancer Reveals 30 Putative Regulatory Variants

Prostate cancer (PC) is the most frequently diagnosed non-skin cancer in the world. Previous studies have shown that genomic alterations represent the most common mechanism for molecular alterations responsible for the development and progression of PC. This highlights the importance of identifying functional genomic variants for early detection in high-risk PC individuals. Great efforts have been made to identify common protein-coding genetic variations; however, the impact of non-coding variations, including regulatory genetic variants, is not well understood. Identification of these variants and the underlying target genes will be a key step in improving the detection and treatment of PC. To gain an understanding of the functional impact of genetic variants, and in particular, regulatory variants in PC, we developed an integrative pipeline (AGV) that uses whole genome/exome sequences, GWAS SNPs, chromosome conformation capture data, and ChIP-Seq signals to investigate the potential impact of genomic variants on the underlying target genes in PC. We identified 646 putative regulatory variants, of which 30 significantly altered the expression of at least one protein-coding gene. Our analysis of chromatin interactions data (Hi-C) revealed that the 30 putative regulatory variants could affect 131 coding and non-coding genes. Interestingly, our study identified the 131 protein-coding genes that are involved in disease-related pathways, including Reactome and MSigDB, for most of which targeted treatment options are currently available. Notably, our analysis revealed several non-coding RNAs, including RP11-136K7.2 and RAMP2-AS1, as potential enhancer elements of the protein-coding genes CDH12 and EZH1, respectively. Our results provide a comprehensive map of genomic variants in PC and reveal their potential contribution to prostate cancer progression and development.

Prognostic and diagnostic values of non-coding RNAs as biomarkers for breast cancer: An umbrella review and pan-cancer analysis

Background: Breast cancer (BC) is the most common cancer in women. The incidence and morbidity of BC are expected to rise rapidly. The stage at which BC is diagnosed has a significant impact on clinical outcomes. When detected early, an overall 5-year survival rate of up to 90% is possible. Although numerous studies have been conducted to assess the prognostic and diagnostic values of non-coding RNAs (ncRNAs) in breast cancer, their overall potential remains unclear. In this field of study, there are various systematic reviews and meta-analysis studies that report volumes of data. In this study, we tried to collect all these systematic reviews and meta-analysis studies in order to re-analyze their data without any restriction to breast cancer or non-coding RNA type, to make it as comprehensive as possible. Methods: Three databases, namely, PubMed, Scopus, and Web of Science (WoS), were searched to find any relevant meta-analysis studies. After thoroughly searching, the screening of titles, abstracts, and full-text and the quality of all included studies were assessed using the AMSTAR tool. All the required data including hazard ratios (HRs), sensitivity (SENS), and specificity (SPEC) were extracted for further analysis, and all analyses were carried out using Stata. Results: In the prognostic part, our initial search of three databases produced 10,548 articles, of which 58 studies were included in the current study. We assessed the correlation of non-coding RNA (ncRNA) expression with different survival outcomes in breast cancer patients: overall survival (OS) (HR = 1.521), disease-free survival (DFS) (HR = 1.33), recurrence-free survival (RFS) (HR = 1.66), progression-free survival (PFS) (HR = 1.71), metastasis-free survival (MFS) (HR = 0.90), and disease-specific survival (DSS) (HR = 0.37). After eliminating low-quality studies, the results did not change significantly. In the diagnostic part, 22 articles and 30 datasets were retrieved from 8,453 articles. The quality of all studies was determined. The bivariate and random-effects models were used to assess the diagnostic value of ncRNAs. The overall area under the curve (AUC) of ncRNAs in differentiated patients is 0.88 (SENS: 80% and SPEC: 82%). There was no difference in the potential of single and combined ncRNAs in differentiated BC patients. However, the overall potential of microRNAs (miRNAs) is higher than that of long non-coding RNAs (lncRNAs). No evidence of publication bias was found in the current study. Nine miRNAs, four lncRNAs, and five gene targets showed significant OS and RFS between normal and cancer patients based on pan-cancer data analysis, demonstrating their potential prognostic value. Conclusion: The present umbrella review showed that ncRNAs, including lncRNAs and miRNAs, can be used as prognostic and diagnostic biomarkers for breast cancer patients, regardless of the sample sources, ethnicity of patients, and subtype of breast cancer.

Migration/Differentiation-Associated LncRNA SENCR rs12420823*C/T: A Novel Gene Variant Can Predict Survival and Recurrence in Patients with Breast Cancer

Long non-coding RNAs (lncRNAs) have key roles in tumor development and the progress of many cancers, including breast cancer (BC). This study aimed to explore for the first time the association of the migration/differentiation-associated lncRNA SENCR rs12420823C/T variant with BC risk and prognosis. Genotyping was carried out for 203 participants (110 patients and 93 controls) using the TaqMan allelic discrimination technique. The corresponding clinicopathological data, including the recurrence/survival times, were analyzed with the different genotypes. After adjustment by age and risk factors, the T/T genotype carrier patients were more likely to develop BC under homozygote comparison (T/T vs. C/C: OR = 8.33, 95% CI = 2.44-25.0, p = 0.001), dominant (T/T-C/T vs. C/C: OR = 3.70, 95% CI = 1.72-8.33, p = 0.027), and recessive (T/T vs. C/T-C/C: OR = 2.17, 95% CI = 1.08-4.55, p < 0.001) models. Multivariate logistic regression analysis showed that the T/T genotype carriers were more likely to be triple-negative sub-type (OR = 2.66, 95% CI = 1.02-6.95, p = 0.046), at a higher risk of recurrence (OR = 3.57, 95% CI = 1.33-9.59, p = 0.012), and had short survival times (OR = 3.9, 95% CI = 1.52-10.05, p = 0.005). Moreover, Cox regression analysis supported their twofold increased risk of recurrence (HR = 2.14, 95% CI = 1.27-3.59, p = 0.004). Furthermore, the predictive nomogram confirmed the high weight for SENCR rs12420823*T/T and C/T genotypes in predicting recurrence within the first year. The Kaplan-Meier survival curve demonstrated low disease-free survival (T/T: 12.5 ± 1.16 months and C/T: 15.9 ± 0.86 months versus C/C: 22.3 ± 0.61 months, p < 0.001). In conclusion, the LncRNA SENCR rs12420823*C/T may be associated with an increased risk of BC in women and could be a promising genetic variant for predicting recurrence and survival.

A Survey on Machine Learning and Internet of Medical Things-Based Approaches for Handling COVID-19: Meta-Analysis

Early diagnosis, prioritization, screening, clustering, and tracking of patients with COVID-19, and production of drugs and vaccines are some of the applications that have made it necessary to use a new style of technology to involve, manage, and deal with this epidemic. Strategies backed by artificial intelligence (A.I.) and the Internet of Things (IoT) have been undeniably effective to understand how the virus works and prevent it from spreading. Accordingly, the main aim of this survey is to critically review the ML, IoT, and the integration of IoT and ML-based techniques in the applications related to COVID-19, from the diagnosis of the disease to the prediction of its outbreak. According to the main findings, IoT provided a prompt and efficient approach to tracking the disease spread. On the other hand, most of the studies developed by ML-based techniques aimed at the detection and handling of challenges associated with the COVID-19 pandemic. Among different approaches, Convolutional Neural Network (CNN), Support Vector Machine, Genetic CNN, and pre-trained CNN, followed by ResNet have demonstrated the best performances compared to other methods.

Somatic point mutations are enriched in non-coding RNAs with possible regulatory function in breast cancer

Non-coding RNAs (ncRNAs) form a large portion of the mammalian genome. However, their biological functions are poorly characterized in cancers. In this study, using a newly developed tool, SomaGene, we analyze de novo somatic point mutations from the International Cancer Genome Consortium (ICGC) whole-genome sequencing data of 1,855 breast cancer samples. We identify 1030 candidates of ncRNAs that are significantly and explicitly mutated in breast cancer samples. By integrating data from the ENCODE regulatory features and FANTOM5 expression atlas, we show that the candidate ncRNAs significantly enrich active chromatin histone marks (1.9 times), CTCF binding sites (2.45 times), DNase accessibility (1.76 times), HMM predicted enhancers (2.26 times) and eQTL polymorphisms (1.77 times). Importantly, we show that the 1030 ncRNAs contain a much higher level (3.64 times) of breast cancer-associated genome-wide association (GWAS) single nucleotide polymorphisms (SNPs) than genome-wide expectation. Such enrichment has not been seen with GWAS SNPs from other cancers. Using breast cell line related Hi-C data, we then show that 82% of our candidate ncRNAs (1.9 times) significantly interact with the promoter of protein-coding genes, including previously known cancer-associated genes, suggesting the critical role of candidate ncRNA genes in the activation of essential regulators of development and differentiation in breast cancer. We provide an extensive web-based resource (https://www.ihealthe.unsw.edu.au/research) to communicate our results with the research community. Our list of breast cancer-specific ncRNA genes has the potential to provide a better understanding of the underlying genetic causes of breast cancer. Lastly, the tool developed in this study can be used to analyze somatic mutations in all cancers.

The SomaGene tool is developed to identify non-coding RNAs (ncRNAs) mutated in breast cancer but can be used for other cancers. Candidate ncRNAs are shown to be enriched for regulatory features and to contain specific trait loci polymorphisms.

Integrative analysis of mutated genes and mutational processes reveals novel mutational biomarkers in colorectal cancer

BACKGROUND

Colorectal cancer (CRC) is one of the leading causes of cancer-related deaths worldwide. Recent studies have observed causative mutations in susceptible genes related to colorectal cancer in 10 to 15% of the patients. This highlights the importance of identifying mutations for early detection of this cancer for more effective treatments among high risk individuals. Mutation is considered as the key point in cancer research. Many studies have performed cancer subtyping based on the type of frequently mutated genes, or the proportion of mutational processes. However, to the best of our knowledge, combination of these features has never been used together for this task. This highlights the potential to introduce better and more inclusive subtype classification approaches using wider range of related features to enable biomarker discovery and thus inform drug development for CRC.

RESULTS

In this study, we develop a new pipeline based on a novel concept called 'gene-motif', which merges mutated gene information with tri-nucleotide motif of mutated sites, for colorectal cancer subtype identification. We apply our pipeline to the International Cancer Genome Consortium (ICGC) CRC samples and identify, for the first time, 3131 gene-motif combinations that are significantly mutated in 536 ICGC colorectal cancer samples. Using these features, we identify seven CRC subtypes with distinguishable phenotypes and biomarkers, including unique cancer related signaling pathways, in which for most of them targeted treatment options are currently available. Interestingly, we also identify several genes that are mutated in multiple subtypes but with unique sequence contexts.

CONCLUSION

Our results highlight the importance of considering both the mutation type and mutated genes in identification of cancer subtypes and cancer biomarkers. The new CRC subtypes presented in this study demonstrates distinguished phenotypic properties which can be effectively used to develop new treatments. By knowing the genes and phenotypes associated with the subtypes, a personalized treatment plan can be developed that considers the specific phenotypes associated with their genomic lesion.

MIR210HG promotes breast cancer progression by IGF2BP1 mediated m6A modification

BACKGROUND

Breast cancer is the most common cancer in women around the world, and the molecular mechanisms of breast cancer progression and metastasis are still unclear. This study aims to clarify the function and N6,2'-O-dimethyladenosine (m6A) regulation of lncRNA MIR210HG in breast cancer.

RESULTS

High expression of MIR210HG was confirmed in breast cancer. MIR210HG promoted breast cancer progression, which was mediated by its encoded miR-210. MIR210HG was regulated by IGF2BP1 mediated m6A modification. IGF2BP1 was confirmed highly expressed in breast cancer and induced both MIR210HG and miR-210 expression, which contributed to breast cancer progression. In addition, MIR210HG transcript was stabilized by IGF2BP1 and co-factor ELAVL1. IGF2BP1 was a direct target of MYCN via E-box binding motif. MYCN induced IGF2BP1 expression in breast cancer cells. MIR210HG and miR-210 expressions were also increased by MYCN.

CONCLUSIONS

In breast cancer, MIR210HG functions as an oncogenic lncRNA, which is also mediated by its encoded miR-210. In addition, both IGF2BP1 and ELAVL1 enhance the stability of MIR210HG, which contributes to the progression of breast cancer. Interestingly, IGF2BP1 is directly activated by MYCN, which explains the oncogenic role of MYCN. These findings clarify the m6A regulation related molecular mechanism of breast cancer progression. The MYCN/IGF2BP1/MIR210HG axis may serve as an alternative molecular mechanism of breast cancer progression.

Exosomes in triple negative breast cancer: From bench to bedside

Exosomes are lipid bilayer extracellular vesicles with a size of 30-150 nm, which can be released by various types of cells including breast cancer cells. Exosomes are enriched with multiple nucleic acids, lipids, proteins and play critical biological roles by binding to recipient cells and transmitting various biological cargos. Studies have reported that tumor-derived exosomes are involved in cancer initiation and progression, such as promoting cancer invasion and metastasis, accelerating angiogenesis, contributing to epithelial-mesenchymal transition, and enhancing drug resistance in tumors. Recently the dysregulating of exosomes has been found in triple-negative breast cancer (TNBC), relating to the clinicopathological characteristics and prognosis of TNBC patients. Considering the poor prognosis and lack of adequate response to conventional therapy of TNBC, the discovery of certain exosomes as a new target for diagnosis and treatment of TNBC may be a good choice that provides new opportunities for the early diagnosis, clinical treatment of TNBC. Here, we first discuss the innovative prognostic and predictive effects of exosomes on TNBC, as well as the practical clinical problems. Secondly, we focus on the new therapeutic areas represented by exosomes, especially the impact of introducing exosomes in TNBC treatment in the future.