Genomic instability-derived plasma extracellular vesicle-microRNA signature as a minimally invasive predictor of risk and unfavorable prognosis in breast cancer

The Predictive Value of Blood-Derived Exosomal miRNAs as Biomarkers in Breast Cancer: A Systematic Review

Breast cancer (BC) remains a widespread disease worldwide, despite advances in its detection and treatment. microRNAs (miRNAs) play a significant role in cancer, and their presence within exosomes may confer several advantages in terms of tumor initiation, propagation, immune evasion, and drug resistance compared to freely circulating miRNAs in the blood. The objective of this study was to conduct a systematic review to analyze the role of exosomal miRNAs present in serum or plasma as biomarkers in BC. Bibliographic sources were collected from various databases with no starting date limit until March 2023. The search terms used were related to "breast cancer," "microRNAs," and "exosomes." Following the search, inclusion and exclusion criteria were applied, resulting in a total of 46 articles. Data were extracted from the selected studies and summarized to indicate the miRNAs, type of dysregulation, sample source, number of patients and controls, and clinical relevance of the miRNAs. We carried out an enrichment study of the microRNAs that appeared in at least 3 studies, those that were suitable for selection were miR-16, miR-21 and miR-155. Exosomal miRNAs isolated from blood samples of patients diagnosed with BC could be valuable in the clinical setting. They could provide information about early diagnosis, disease progression, recurrence, treatment response, and metastases. It is crucial to reach a consensus on the specific exosomal miRNAs to detect and the most appropriate type of sample for comprehensive utilization of miRNAs as biomarkers for BC.

Extracellular vesicle-mediated drug delivery in breast cancer theranostics

Breast cancer (BC) continues to be a significant global challenge due to drug resistance and severe side effects. The increasing prevalence is alarming, requiring new therapeutic approaches to address these challenges. At this point, Extracellular vesicles (EVs), specifically small endosome-released nanometer-sized EVs (SEVs) or exosomes, have been explored by literature as potential theranostics. Therefore, this review aims to highlight the therapeutic potential of exosomes in BC, focusing on their advantages in drug delivery and their ability to mitigate metastasis. Following the review, we identified exosomes' potential in combination therapies, serving as miRNA carriers and contributing to improved anti-tumor effects. This is evident in clinical trials investigating exosomes in BC, which have shown their ability to boost chemotherapy efficacy by delivering drugs like paclitaxel (PTX) and doxorubicin (DOX). However, the translation of EVs into BC therapy is hindered by various challenges. These challenges include the heterogeneity of EVs, the selection of the appropriate parent cell, the loading procedures, and determining the optimal administration routes. Despite the promising therapeutic potential of EVs, these obstacles must be addressed to realize their benefits in BC treatment.

Liquid biopsy using non-coding RNAs and extracellular vesicles for breast cancer management

This article examines liquid biopsy using non-coding RNAs and extracellular vesicles in detail. Liquid biopsy is emerging as a prominent non-invasive diagnostic tool in the treatment of breast cancer. We will elucidate the roles of these molecules in early detection, monitoring treatment effectiveness, and prognostic assessment of breast cancer. Additionally, the clinical significance of these molecules will be discussed. We aim to delve into the distinct characteristics of these molecules and their possible roles in breast cancer management, with an anticipation of their contribution to future diagnostic and therapeutic advancements.

Extracellular vesicles in cancer: challenges and opportunities for clinical laboratories

Extracellular vesicles (EVs) are nano-sized particles secreted by most cells. They transport different types of biomolecules (nucleic acids, proteins, and lipids) characteristic of their tissue or cellular origin that can mediate long-distance intercellular communication. In the case of cancer, EVs participate in tumor progression by modifying the tumor microenvironment, favoring immune tolerance and metastasis development. Consequently, EVs have great potential in liquid biopsy for cancer diagnosis, prognosis and follow-up. In addition, EVs could have a role in cancer treatment as a targeted drug delivery system. The intense research in the EV field has resulted in hundreds of patents and the creation of biomedical companies. However, methodological issues and heterogeneity in EV composition have hampered the advancement of EV validation trials and the development of EV-based diagnostic and therapeutic products. Consequently, only a few EV biomarkers have moved from research to clinical laboratories, such as the ExoDx Prostate IntelliScore (EPI) test, a CLIA/FDA-approved EV prostate cancer diagnostic test. In addition, the number of large-scale multicenter studies that would clearly define biomarker performance is limited. In this review, we will critically describe the different types of EVs, the methods for their enrichment and characterization, and their biological role in cancer. Then, we will specially focus on the parameters to be considered for the translation of EV biology to the clinic laboratory, the advances already made in the field of EVs related to cancer diagnosis and treatment, and the issues still pending to be solved before EVs could be used as a routine tool in oncology.

Chromosomal Instability-Driven Cancer Progression: Interplay with the Tumour Microenvironment and Therapeutic Strategies

Chromosomal instability (CIN) is a prevalent characteristic of solid tumours and haematological malignancies. CIN results in an increased frequency of chromosome mis-segregation events, thus yielding numerical and structural copy number alterations, a state also known as aneuploidy. CIN is associated with increased chances of tumour recurrence, metastasis, and acquisition of resistance to therapeutic interventions, and this is a dismal prognosis. In this review, we delve into the interplay between CIN and cancer, with a focus on its impact on the tumour microenvironment-a driving force behind metastasis. We discuss the potential therapeutic avenues that have resulted from these insights and underscore their crucial role in shaping innovative strategies for cancer treatment.

The Emerging Roles of Exosomal miRNAs in Breast Cancer Progression and Potential Clinical Applications

Breast cancer remains the leading malignancy in terms of morbidity and mortality today. The tumor microenvironment of breast cancer includes multiple cell types, secreted proteins, and signaling components such as exosomes. Among these, exosomes have a lipid bilayer structure. Exosomes can reflect the biological traits of the parent cell and carry a variety of biologically active components, including proteins, lipids, small molecules, and non-coding RNAs, which include miRNA, lncRNA, and circRNA. MiRNAs are a group of non-coding RNAs of approximately 20-23 nucleotides in length encoded by the genome, triggering silencing and functional repression of target genes. MiRNAs have been shown to play a significant role in the development of cancer owing to their role in the prognosis, pathogenesis, diagnosis, and treatment of cancer. MiRNAs in exosomes can serve as effective mediators of information transfer from parental cells to recipient cells and trigger changes in biological traits such as proliferation, invasion, migration, and drug resistance. These changes can profoundly alter the progression of breast cancer. Therefore, here, we systematically summarize the association of exosomal miRNAs on breast cancer progression, diagnosis, and treatment in the hope of providing novel strategies and directions for subsequent breast cancer treatment.

Identification of T-cell exhaustion-related gene signature for predicting prognosis in glioblastoma multiforme

Glioblastoma multiforme (GBM) is a highly malignant primary brain tumour with a poor prognosis in adults. Identifying biomarkers that can aid in the molecular classification and risk stratification of GBM is critical. Here, we conducted a transcriptional profiling analysis of T-cell immunity in the tumour microenvironment of GBM patients and identified two novel T cell exhaustion (TEX)-related GBM subtypes (termed TEX-C1 and TEX-C2) using the consensus clustering. Our multi-omics analysis revealed distinct immunological, molecular and clinical characteristics for these two subtypes. Specifically, the TEX-C1 subtype had higher infiltration levels of immune cells and expressed higher levels of immune checkpoint molecules than the TEX-C2 subtype. Functional analysis revealed that upregulated genes in the TEX-C1 subtype were significantly enriched in immune response and signal transduction pathways, and upregulated genes in the TEX-C2 subtype were predominantly associated with cell fate and nervous system development pathways. Notably, patients with activated T-cell activity status in the TEX-C1 subgroup demonstrated a significantly worse prognosis than those with severe T cell exhaustion status in the TEX-C2 subgroup. Finally, we proposed a machine-learning-derived novel gene signature comprising 12 TEX-related genes (12TexSig) to indicate tumour subtyping. In the TCGA cohort, the 12TexSig demonstrated the ability to accurately predict the prognosis of GBM patients, and this prognostic value was further confirmed in two independent external cohorts. Taken together, our results suggest that the TEX-derived subtyping and gene signature has the potential to serve as a clinically helpful biomarker for guiding the management of GBM patients, pending further prospective validation.

DNA damage repair profiling of esophageal squamous cell carcinoma uncovers clinically relevant molecular subtypes with distinct prognoses and therapeutic vulnerabilities

BACKGROUND

DNA damage repair (DDR) is a critical process that maintains genomic integrity and plays essential roles at both the cellular and organismic levels. Here, we aimed to characterize the DDR profiling of esophageal squamous cell carcinoma (ESCC), investigate the prognostic value of DDR-related features, and explore their potential for guiding personalized treatment strategies.

METHODS

We analyzed bulk and single-cell transcriptomics data from 377 ESCC cases from our institution and other publicly available cohorts to identify major DDR subtypes. The heterogeneity in cellular and functional properties, tumor microenvironment (TME) characteristics, and prognostic significance of these DDR subtypes were investigated using immunogenomic analysis and in vitro experiments. Additionally, we experimentally validated a combinatorial immunotherapy strategy using syngeneic mouse models of ESCC.

FINDINGS

DDR alteration profiling enabled us to identify two distinct DDR subtypes, DDRactive and DDRsilent, which exhibited independent prognostic values in locoregional ESCC but not in metastatic ESCC. The DDRsilent subtype was characterized by an inflamed but immune-suppressed microenvironment with relatively high immune cell infiltration, abnormal immune checkpoint expression, T-cell exhaustion, and enrichment of cancer-related pathways. Moreover, DDR subtyping indicates that BRCA1 and HFM1 are robust and independent prognostic factors in locoregional ESCC. Finally, we proposed and verified that the concomitant triggering of GITR or blockade of BTLA with PD-1 blockade or cisplatin chemotherapy represents effective combination strategies for high-risk locoregional ESCC tumors.

INTERPRETATION

Our discovery of DDR-based molecular subtypes will enhance our understanding of tumor heterogeneity and have significant clinical implications for the therapeutic and management strategies of locoregional ESCC.

FUNDING

This study was supported by the National Key R&D Program of China (2021YFC2501000, 2022YFC3401003), National Natural Science Foundation of China (82172882), the Beijing Natural Science Foundation (7212085), the CAMS Innovation Fund for Medical Sciences (2021-I2M-1-018, 2021-I2M-1-067), the Fundamental Research Funds for the Central Universities (3332021091), and the Non-profit Central Research Institute Fund of Chinese Academy of Medical Sciences (2019PT310027).

A mutator-derived prognostic eRNA signature provides insight into the pathogenesis of breast cancer

Abundant evidence suggests that enhancer RNA (eRNA) is closely related to tumorigenesis, and the role of eRNA transcription in promoting genomic instability in cancers is gradually unveiled. However, research on the evaluation of the prognostic value and molecular mechanisms of genomic instability associated eRNAs in breast cancer is long overdue. Here, we integratively analyzed eRNA expression and somatic mutation profiles in breast cancer genome. We identified genomic instability associated eRNAs and developed a prognostic signature based on these eRNAs with the area under the curve (AUC) around 0.8 at 9-year survival. We further found the prognostic value of this signature is independent of common clinical factors and is better than TP53 status. Higher expression of genomic instability associated genes in the high-risk group was observed, suggesting that this eRNA signature may serve as an indicator of genomic instability in breast cancer. We found prognostic eRNA co-expressed genes are mainly enriched in Gene set 'Breast Cancer 8P12-P11 Amplicon', Gene set 'Metabolism of lipids' and GO process 'Ubiquitin protein ligase binding'. Furthermore, 11 eRNA-signature regulated genes are identified by assessing promoter-enhancer interaction. Among these genes, F11R, BHLHE40, and NECTIN4 are previously reported oncogenes and EGOT is a tumor suppressor gene, indicating the direct roles of eRNAs in tumorigenesis.

Deciphering the Functional Status of Breast Cancers through the Analysis of Their Extracellular Vesicles

Breast cancer (BC) accounts for the highest incidence of tumor-related mortality among women worldwide, justifying the growing search for molecular tools for the early diagnosis and follow-up of BC patients under treatment. Circulating extracellular vesicles (EVs) are membranous nanocompartments produced by all human cells, including tumor cells. Since minimally invasive methods collect EVs, which represent reservoirs of signals for cell communication, these particles have attracted the interest of many researchers aiming to improve BC screening and treatment. Here, we analyzed the cargoes of BC-derived EVs, both proteins and nucleic acids, which yielded a comprehensive list of potential markers divided into four distinct categories, namely, (i) modulation of aggressiveness and growth; (ii) preparation of the pre-metastatic niche; (iii) epithelial-to-mesenchymal transition; and (iv) drug resistance phenotype, further classified according to their specificity and sensitivity as vesicular BC biomarkers. We discuss the therapeutic potential of and barriers to the clinical implementation of EV-based tests, including the heterogeneity of EVs and the available technologies for analyzing their content, to present a consistent, reproducible, and affordable set of markers for further evaluation.

DKK1-targeting cholesterol-modified siRNA implication in hair growth regulation

Despite advancements in medical research, androgenetic alopecia (AGA) remains a humankind problem that still needs to be overcome. To date, clinical practice lacks an ideal treatment for AGA. The Wnt/β-catenin signaling pathway is evidenced to play a key role in hair regrowth, hence, modulating this signaling pathway for AGA therapy appears to be rational. One of the major inhibitors of the canonical Wnt/β-catenin signaling pathway is dickkopf-related protein 1 (DKK1). In this report, we have selected a small interfering RNA (siRNA) targeting DKK1 in vitro via qPCR and then tested its efficacy in vivo on the depilated dorsal skin of the mice. The changes in hair growth in different groups were observed over time. Moreover, the visual observation of the hair growth and hematoxylin and eosin (HE) staining showed that DKK1-targeting siRNA reveals non-inferior results compared with the mice treated with the Food and Drug Administration (FDA)-approved, commercially available minoxidil (5%) topical solution that was used as a positive control. Both- positive control and DKK1-targeting siRNA groups demonstrated significantly superior results compared with the control group that received negative control siRNA. Consequently, siRNAs targeting DKK1 may promote hair growth regulation in the AGA population via potentially activating the Wnt/β-catenin signaling pathway.

Extracellular vesicles in the treatment and diagnosis of breast cancer: a status update

Breast cancer is one of the leading causes of cancer-related death in women. Currently, the treatment of breast cancer is limited by the lack of effectively targeted therapy and patients often suffer from higher severity, metastasis, and resistance. Extracellular vesicles (EVs) consist of lipid bilayers that encapsulate a complex cargo, including proteins, nucleic acids, and metabolites. These bioactive cargoes have been found to play crucial roles in breast cancer initiation and progression. Moreover, EV cargoes play pivotal roles in converting mammary cells to carcinogenic cells and metastatic foci by extensively inducing proliferation, angiogenesis, pre-metastatic niche formation, migration, and chemoresistance. The present update review mainly discusses EVs cargoes released from breast cancer cells and tumor-derived EVs in the breast cancer microenvironment, focusing on proliferation, metastasis, chemoresistance, and their clinical potential as effective biomarkers.

A novel exosome-derived prognostic signature and risk stratification for breast cancer based on multi-omics and systematic biological heterogeneity

Tumor heterogeneity remains a major challenge for disease subtyping, risk stratification, and accurate clinical management. Exosome-based liquid biopsy can effectively overcome the limitations of tissue biopsy, achieving minimal invasion, multi-point dynamic monitoring, and good prognosis assessment, and has broad clinical prospects. However, there is still lacking comprehensive analysis of tumor-derived exosome (TDE)-based stratification of risk patients and prognostic assessment for breast cancer with systematic dissection of biological heterogeneity. In this study, the robust corroborative analysis for biomarker discovery (RCABD) strategy was used for the identification of exosome molecules, differential expression verification, risk prediction modeling, heterogenous dissection with multi-ome (6101 molecules), our ExoBCD database (306 molecules), and 53 independent studies (481 molecules). Our results showed that a 10-molecule exosome-derived signature (exoSIG) could successfully fulfill breast cancer risk stratification, making it a novel and accurate exosome prognostic indicator (Cox P = 9.9E-04, HR = 3.3, 95% CI 1.6-6.8). Interestingly, HLA-DQB2 and COL17A1, closely related to tumor metastasis, achieved high performance in prognosis prediction (86.35% contribution) and accuracy (Log-rank P = 0.028, AUC = 85.42%). With the combined information of patient age and tumor stage, they formed a bimolecular risk signature (Clinmin-exoSIG) and a convenient nomogram as operable tools for clinical applications. In conclusion, as an extension of ExoBCD, this study conducted systematic analyses to identify prognostic multi-molecular panel and risk signature, stratify patients and dissect biological heterogeneity based on breast cancer exosomes from a multi-omics perspective. Our results provide an important reference for in-depth exploration of the "biological heterogeneity - risk stratification - prognosis prediction".

Genomic instability-related twelve-microRNA signatures for predicting the prognosis of gastric cancer

Gastric cancer (GC) ranks fifth among all malignant tumors globally, especially in East Asia, and has attracted extensive attention and research. MicroRNA (miRNA) modulation during genomic instability (GI) may be associated with the development and metastasis of malignant tumors. We aimed to identify GI-related miRNA signatures for the prediction of GC prognosis. We constructed a GI-related miRNA signature (GIMiSig) scheme based on The Cancer Genome Atlas (TCGA) training set (n = 389), which was later verified based on the TCGA test set (n = 194). GI-related miRNAs were identified by analyzing somatic mutation profiles and miRNA expression. A GI-related miRNA-gene co-expression network was also constructed. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) were analyzed to reveal possible biological pathways associated with GI-related miRNAs. The correlation of the GIMiSig with clinical factors of the TCGA dataset was analyzed. MiRNA mimics and inhibitors were used to evaluate the biological functions of miR-100-5p and miR-145-3p in GC cell lines AGS and MKN-45. This study identified a GI-related 12-miRNA signature for the prediction of GC prognosis. GIMiSig scores, similar to tumor stages, showed significant correlations with overall survival (OS, p < 0.05). GIMiSig showed high accuracy in predicting GC prognosis. MiR-100-5p and miR-145-3p promoted cell growth, invasion, and migration but inhibited apoptosis in GC cells. We report a reliable GI-related 12-miRNA signature for predicting GC prognosis. Furthermore, miR-100-5p and miR-145-3p may promote GC cell growth, invasion, and migration.

Recent advances of small extracellular vesicle biomarkers in breast cancer diagnosis and prognosis

Current clinical tools for breast cancer (BC) diagnosis are insufficient but liquid biopsy of different bodily fluids has recently emerged as a minimally invasive strategy that provides a real-time snapshot of tumour biomarkers for early diagnosis, active surveillance of progression, and post-treatment recurrence. Extracellular vesicles (EVs) are nano-sized membranous structures 50-1000 nm in diameter that are released by cells into biological fluids. EVs contain proteins, nucleic acids, and lipids which play pivotal roles in tumourigenesis and metastasis through cell-to-cell communication. Proteins and miRNAs from small EVs (sEV), which range in size from 50-150 nm, are being investigated as a potential source for novel BC biomarkers using mass spectrometry-based proteomics and next-generation sequencing. This review covers recent developments in sEV isolation and single sEV analysis technologies and summarises the sEV protein and miRNA biomarkers identified for BC diagnosis, prognosis, and chemoresistance. The limitations of current sEV biomarker research are discussed along with future perspective applications.

The Role and Application of Exosomes and Their Cargos in Reproductive Diseases: A Systematic Review

In recent years, the incidence of the reproductive diseases is increasing year-by-year, leading to abortion or fetal arrest, which seriously affects the reproductive health of human beings and the reproductive efficiency of animals. Exosomes are phospholipid bilayer vesicles that are widely distributed in living organisms and released by the cells of various organs and tissues. Exosomes contain proteins, RNA, lipids, and other components and are important carriers of information transfer between cells, which play a variety of physiological and pathological regulatory functions. More and more studies have found that exosomes and their connotations play an important role in the diagnosis, prognosis and treatment of diseases. A systematic review was conducted in this manuscript and then highlights our knowledge about the diagnostic and therapeutic applications of exosomes to reproductive diseases, such as polycystic ovary syndrome (PCOS), endometriosis, premature ovarian failure (POF), preeclampsia, polycystic, endometrial cancer, cervical cancer, ovarian cancer, and prostate gland cancer.

Cancer Biomarkers in Liquid Biopsy for Early Detection of Breast Cancer: A Systematic Review

Background:

Breast cancer (BC) is the most common neoplasm in women worldwide. Liquid biopsy (LB) is a non-invasive diagnostic technique that allows the analysis of biomarkers in different body fluids, particularly in peripheral blood and also in urine, saliva, nipple discharge, volatile respiratory fluids, nasal secretions, breast milk, and tears. The objective was to analyze the available evidence related to the use of biomarkers obtained by LB for the early diagnosis of BC.

Methods:

Articles related to the use of biomarkers for the early diagnosis of BC due to LB, published between 2010 and 2022, from the databases (WoS, EMBASE, PubMed, and SCOPUS) were included. The MInCir diagnostic scale was applied in the articles to determine their methodological quality (MQ). Descriptive statistics were used, as well as determination of weighted averages of each variable, to analyze the extracted data. Sensitivity, specificity, and area under the curve values for specific biomarkers (individual or in panels) are described.

Results:

In this systematic review (SR), 136 articles met the selection criteria, representing 17 709 patients with BC. However, 95.6% were case-control studies. In 96.3% of cases, LB was performed in peripheral blood samples. Most of the articles were based on microRNA (miRNA) analysis. The mean MQ score was 25/45 points. Sensitivity, specificity, and area under the curve values for specific biomarkers (individual or in panels) have been found.

Conclusions:

The determination of biomarkers through LB is a useful mechanism for the diagnosis of BC. The analysis of miRNA in peripheral blood is the most studied methodology. Our results indicate that LB has a high sensitivity and specificity for the diagnosis of BC, especially in early stages.

Identification of microsatellite instability and immune-related prognostic biomarkers in colon adenocarcinoma

Background

Colon adenocarcinoma (COAD) is a prevalent malignancy that causes significant mortality. Microsatellite instability plays a pivotal function in COAD development and immunotherapy resistance. However, the detailed underlying mechanism requires further investigation. Consequently, identifying molecular biomarkers with prognostic significance and revealing the role of MSI in COAD is important for addressing key obstacles in the available treatments.

Methods

CIBERSORT and ESTIMATE analyses were performed to evaluate immune infiltration in COAD samples, followed by correlation analysis for MSI and immune infiltration. Then, differentially expressed genes (DEGs) in MSI and microsatellite stability (MSS) samples were identified and subjected to weighted gene co-expression network analysis (WGCNA). A prognostic model was established with univariate cox regression and LASSO analyses, then evaluated with Kaplan-Meier analysis. The correlation between the prognostic model and immune checkpoint inhibitor (ICI) response was also analyzed.

Results

In total, 701 significant DEGs related to MSI status were identified, and WGCNA revealed two modules associated with the immune score. Then, a seven-gene prognostic model was constructed using LASSO and univariate cox regression analyses to predict survival and ICI response. The high-risk score patients in TCGA and GEO cohorts presented a poor prognosis, as well as a high immune checkpoint expression, so they are more likely to benefit from ICI treatment.

Conclusion

The seven-gene prognostic model constructed could predict the survival of COAD and ICI response and serve as a reference for immunotherapy decisions.

Integrated machine learning methods identify FNDC3B as a potential prognostic biomarker and correlated with immune infiltrates in glioma

Background

Recent discoveries have revealed that fibronectin type III domain containing 3B (FNDC3B) acts as an oncogene in various cancers; however, its role in glioma remains unclear.

Methods

In this study, we comprehensively investigated the expression, prognostic value, and immune significance of FNDC3B in glioma using several databases and a variety of machine learning algorithms. RNA expression data and clinical information of 529 patients from the Cancer Genome Atlas (TCGA) and 1319 patients from Chinese Glioma Genome Atlas (CGGA) databases were downloaded for further investigation. To evaluate whether FNDC3B expression can predict clinical prognosis of glioma, we constructed a clinical nomogram to estimate long-term survival probabilities. The predicted nomogram was validated by CGGA cohorts. Differentially expressed genes (DEGs) were detected by the Wilcoxon test based on the TCGA-LGG dataset and the weighted gene co-expression network analysis (WGCNA) was implemented to identify the significant module associated with the expression level of FNDC3B. Furthermore, we investigated the correlation between FNDC3B with cancer immune infiltrates using TISIDB, ESTIMATE, and CIBERSORTx.

Results

Higher FNDC3B expression displayed a remarkably worse overall survival and the expression level of FNDC3B was an independent prognostic indicator for patients with glioma. Based on TCGA LGG dataset, a co-expression network was established and the hub genes were identified. FNDC3B expression was positively correlated to the tumor-infiltrating lymphocytes and immune infiltration score, and high FNDC3B expression was accompanied by the increased expression of B7-H3, PD-L1, TIM-3, PD-1, and CTLA-4. Moreover, expression of FNDC3B was significantly associated with infiltrating levels of several types of immune cells and most of their gene markers in glioma.

Conclusion

This study demonstrated that FNDC3B may be involved in the occurrence and development of glioma and can be regarded as a promising prognostic and immunotherapeutic biomarker for the treatment of glioma.

Overview of MicroRNAs as Diagnostic and Prognostic Biomarkers for High-Incidence Cancers in 2021

MicroRNAs (miRNAs) are small non-coding RNAs (ncRNAs) about 22 nucleotides in size, which play an important role in gene regulation and are involved in almost all major cellular physiological processes. In recent years, the abnormal expression of miRNAs has been shown to be associated with human diseases including cancer. In the past ten years, the link between miRNAs and various cancers has been extensively studied, and the abnormal expression of miRNAs has been reported in various malignant tumors, such as lung cancer, gastric cancer, colorectal cancer, liver cancer, breast cancer, and prostate cancer. Due to the high malignancy grade of these cancers, it is more necessary to develop the related diagnostic and prognostic methods. According to the study of miRNAs, many potential cancer biomarkers have been proposed for the diagnosis and prognosis of diseases, especially cancer, thus providing a new theoretical basis and perspective for cancer screening. The use of miRNAs as biomarkers for diagnosis or prognosis of cancer has the advantages of being less invasive to patients, with better accuracy and lower price. In view of the important clinical significance of miRNAs in human cancer research, this article reviewed the research status of miRNAs in the above-mentioned cancers in 2021, especially in terms of diagnosis and prognosis, and provided some new perspectives and theoretical basis for the diagnosis and treatment of cancers.

A blood-based miRNA signature for early non-invasive diagnosis of preeclampsia

BACKGROUND

Preeclampsia (PE) is a multisystemic maternal syndrome with substantial maternal and fetal morbidity and mortality. Currently, there is no clinically viable non-invasive biomarker assay for early detection, thus limiting the effective prevention and therapeutic strategies for PE.

METHODS

We conducted a discovery-training-validation three-phase retrospective and prospective study with cross-platform and multicenter cohorts. The initial biomarkers were discovered and verified in tissue specimens by small RNA sequencing and qRT-PCR. A miRNA signature (miR2PE-score) was developed using Firth's bias-reduced logistic regression analysis and subsequently validated in two independent multinational retrospective cohorts and two prospective plasma cohorts.

RESULTS

We initially identified five PE-associated differentially expressed miRNAs from miRNA sequencing data and subsequently validated two miRNAs (miR-196b-5p and miR-584-5p) as robust biomarkers by association analysis with clinical characteristics and qRT-PCR in tissue specimens in the discovery phase. Using Firth's bias-reduced logistic regression analysis, we developed the miR2PE-score for the early detection of PE. The miR2PE-score showed a high diagnostic performance with an area under the receiver operating characteristic curve (AUROC) of 0.920, 0.848, 0.864, and 0.812 in training, internal, and two external validation cross-platform and multicenter cohorts, respectively. Finally, we demonstrated the non-invasive diagnostic performance of the miR2PE-score in two prospective plasma cohorts with AUROC of 0.933 and 0.787. Furthermore, the miR2PE-score revealed superior performance in non-invasive diagnosis compared with previously published miRNA biomarkers.

CONCLUSIONS

We developed and validated a novel and robust blood-based miRNA signature, which may serve as a promising clinically applicable non-invasive tool for the early detection of PE.

A Ferroptosis-Related LncRNA Signature Associated with Prognosis, Tumor Immune Environment, and Genome Instability in Hepatocellular Carcinoma

Background

Ferroptosis is an iron-dependent form of cell death. In this study, we identified ferroptosis-related long noncoding RNAs (FRlncRNAs) to investigate their association with hepatocellular carcinoma (HCC) in prognosis, tumor immune environment, and genome instability.

Methods

Transcriptome profile data of HCC were retrieved from a public database. FRlncRNAs were identified by co-expression analysis. Patients were randomly divided into training and test cohorts. Univariate Cox analysis and Least Absolute Shrinkage and Selection Operator (LASSO) Cox regression were performed to construct a risk model. Patients were divided into high- and low-risk groups based on the risk model. AUC and C index were used to assess the risk model. Survival analysis, immune status, and genome instability were compared between the two groups.

Results

Sixteen FRlncRNAs were identified and used to construct an FRlncRNA signature for the risk model. The Kaplan-Meier analysis revealed that patients in the high-risk group had poorer overall survival than patients in the low-risk group. The area under curve of the risk model was 0.879, 0.809, and 0.757 in the training cohort and 0.635, 0.688, and 0.739 in the test cohort at 1, 2, and 3 years, respectively. The risk model was an independent prognostic predictor and showed excellent prediction of prognosis compared with clinicopathological features. For the differentially expressed ferroptosis-related genes, many enriched metabolic pathways were identified in the functional enrichment analysis. Immune cells such as CD8+ T cells, macrophages M1, natural killer cells, and B cells, which may be associated with antitumor immune responses, differed between the high- and low-risk groups. Genome instability based on the risk model was also explored. A total of 61 genes were differently mutated between the two risk groups, and among them, TP53, HECW2, TRIM66, MCTP2, and KIAA1551 had the most significant mutation frequency differences.

Conclusion

The FRlncRNA signature is closely related with overall survival, tumor immune environment, and genome instability in HCC.

Exosomes: Small Vesicles with Important Roles in the Development, Metastasis and Treatment of Breast Cancer

Breast cancer (BC) has now overtaken lung cancer as the most common cancer, while no biopredictive marker isolated from biological fluids has yet emerged clinically. After traditional chemotherapy, with the huge side effects brought by drugs, patients also suffer from the double affliction of drugs to the body while fighting cancer, and they often quickly develop drug resistance after the drug, leading to a poor prognosis. And the treatment of some breast cancer subtypes, such as triple negative breast cancer (TNBC), is even more difficult. Exosomes (Exos), which are naturally occurring extracellular vesicles (EVs) with nanoscale acellular structures ranging in diameter from 40 to 160 nm, can be isolated from various biological fluids and have been widely studied because they are derived from the cell membrane, have extremely small diameter, and are widely involved in various biological activities of the body. It can be used directly or modified to make derivatives or to make some analogs for the treatment of breast cancer. This review will focus on the involvement of exosomes in breast cancer initiation, progression, invasion as well as metastasis and the therapeutic role of exosomes in breast cancer.

Exosomes in Breast Cancer: Involvement in Tumor Dissemination and Prospects for Liquid Biopsy

In women, breast cancer (BC) is the most commonly diagnosed cancer (24.5%) and the leading cause of cancer death (15.5%). Understanding how this heterogeneous disease develops and the confirm mechanisms behind tumor progression is of utmost importance. Exosomes are long-range message vesicles that mediate communication between cells in physiological conditions but also in pathology, such as breast cancer. In recent years, there has been an exponential rise in the scientific studies reporting the change in morphology and cargo of tumor-derived exosomes. Due to the transfer of biologically active molecules, such as RNA (microRNA, long non-coding RNA, mRNA, etc.) and proteins (transcription factors, enzymes, etc.) into recipient cells, these lipid bilayer 30–150 nm vesicles activate numerous signaling pathways that promote tumor development. In this review, we attempt to shed light on exosomes’ involvement in breast cancer pathogenesis (including epithelial-to-mesenchymal transition (EMT), tumor cell proliferation and motility, metastatic processes, angiogenesis stimulation, and immune system repression). Moreover, the potential use of exosomes as promising diagnostic biomarkers for liquid biopsy of breast cancer is also discussed.

Potential utility of miRNAs for liquid biopsy in breast cancer

Breast cancer (BC) remains the most prevalent malignancy due to its incidence rate, recurrence, and metastasis in women. Conventional strategies of cancer detection– mammography and tissue biopsy lack the capacity to detect the complete cancer genomic landscape. Besides, they often give false- positive or negative results. The presence of this and other disadvantages such as invasiveness, high-cost, and side effects necessitates developing new strategies to overcome the BC burden. Liquid biopsy (LB) has been brought to the fore owing to its early detection, screening, prognosis, simplicity of the technique, and efficient monitoring. Remarkably, microRNAs (miRNAs)– gene expression regulators seem to play a major role as biomarkers detected in the samples of LB. Particularly, miR-21 and miR-155 among other possible candidates seem to serve as favorable biomarkers in the diagnosis and prognosis of BC. Hence, this review will assess the potential utility of miRNAs as biomarkers and will highlight certain promising candidates for the LB approach in the diagnosis and management of BC that may optimize the patient outcome.

Triple negative breast cancer-derived small extracellular vesicles as modulator of biomechanics in target cells

Extracellular vesicle (EV) mediated communication has recently been proposed as one of the pivotal routes in the development of cancer metastasis. EVs are nano-sized vesicles swapped between cells, carrying a biologically active content that can promote tumor-induced immune suppression, metastasis and angiogenesis. Thus, EVs constitute a potential target in cancer therapy. However, their role in triggering the premetastatic niche and in tumor spreading is still unclear. Here, we focused on the EV ability to modulate the biomechanical properties of target cells, known to play a crucial role in metastatic spreading. To this purpose, we isolated and thoroughly characterized triple-negative breast cancer (TNBC)-derived small EVs. We then evaluated variations in the mechanical properties (cell stiffness, cytoskeleton/nuclear/morphology and Yap activity rearrangements) of non-metastatic breast cancer MCF7 cells upon EV treatment. Our results suggest that TNBC-derived small EVs are able to directly modify MCF7 cells by inducing a decrease in cell stiffness, rearrangements in cytoskeleton, focal adhesions and nuclear/cellular morphology, and an increase in Yap downstream gene expression. Testing the biomechanical response of cells after EV addition might represent a new functional assay in metastatic cancer framework that can be exploited for future application both in diagnosis and in therapy.

Spotlight on Exosomal Non-Coding RNAs in Breast Cancer: An In Silico Analysis to Identify Potential lncRNA/circRNA-miRNA-Target Axis

Breast cancer (BC) has recently become the most common cancer type worldwide, with metastatic disease being the main reason for disease mortality. This has brought about strategies for early detection, especially the utilization of minimally invasive biomarkers found in various bodily fluids. Exosomes have been proposed as novel extracellular vesicles, readily detectable in bodily fluids, secreted from BC-cells or BC-tumor microenvironment cells, and capable of conferring cellular signals over long distances via various cargo molecules. This cargo is composed of different biomolecules, among which are the novel non-coding genome products, such as microRNAs (miRNAs), long non-coding RNAs (lncRNAs), and the recently discovered circular RNA (circRNA), all of which were found to be implicated in BC pathology. In this review, the diverse roles of the ncRNA cargo of BC-derived exosomes will be discussed, shedding light on their primarily oncogenic and additionally tumor suppressor roles at different levels of BC tumor progression, and drug sensitivity/resistance, along with presenting their diagnostic, prognostic, and predictive biomarker potential. Finally, benefiting from the miRNA sponging mechanism of action of lncRNAs and circRNAs, we established an experimentally validated breast cancer exosomal non-coding RNAs-regulated target gene axis from already published exosomal ncRNAs in BC. The resulting genes, pathways, gene ontology (GO) terms, and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis could be a starting point to better understand BC and may pave the way for the development of novel diagnostic and prognostic biomarkers and therapeutics.

Multidimensional difference analysis in gastric cancer patients between high and low latitude

Genetic variation has been shown to affect tumor growth and progression, and the temperature at different latitudes may promote the evolution of genetic variation. Geographical data with latitudinal information is of importance to understand the interplay between genetic variants and environmental influence, such as the temperature, in gastric cancer (GC). In this study, we classified the GC samples from The Cancer Genome Atlas database into two groups based on the latitudinal information of patients and found that GC samples with low-latitude had better clinical outcomes. Further analyses revealed significant differences in other clinical factors such as disease stage and grade between high and low latitudes GC samples. Then, we analyzed the genomic and transcriptomic differences between the two groups. Furthermore, we evaluated the activity score of metabolic pathways and infiltrating immune cells in GC samples with different latitudes using the single-sample gene set enrichment analysis algorithm. These results showed that GC samples at low-latitude had lower tumor mutation burden and subclones as well as higher DNA repair activities. Meanwhile, we found that most immune cells were associated with the prognosis of low-latitude GC patients. At last, we constructed and validated an immune-related prognostic model to evaluate the prognosis of GC samples at different latitudes. This study has provided a further understanding of the geographical contribution to GC at the multiomic level and may benefit the individualized treatment of GC patients at different latitudes.

Identification and Validation of a Five-Gene Diagnostic Signature for Preeclampsia

Preeclampsia is the leading cause of morbidity and mortality for mothers and newborns worldwide. Despite extensive efforts made to understand the underlying pathology of preeclampsia, there is still no clinically useful effective tool for the early diagnosis of preeclampsia. In this study, we conducted a retrospectively multicenter discover-validation study to develop and validate a novel biomarker for preeclampsia diagnosis. We identified 38 differentially expressed genes (DEGs) involved in preeclampsia in a case-control study by analyzing expression profiles in the discovery cohort. We developed a 5-mRNA signature (termed PE5-signature) to diagnose preeclampsia from 38 DEGs using recursive feature elimination with a random forest supervised classification algorithm, including ENG, KRT80, CEBPA, RDH13 and WASH9P. The PE5-signature showed high accuracy in discriminating preeclampsia from controls with a receiver operating characteristic area under the curve value (AUC) of 0.971, a sensitivity of 0.842 and a specificity of 0.950. The PE5-signature was then validated in an independent case-control study and achieved a reliable and robust predictive performance with an AUC of 0.929, a sensitivity of 0.696, and a specificity of 0.946. In summary, we have developed and validated a five-mRNA biomarker panel as a risk assessment tool to assist in the detection of preeclampsia. This gene panel has potential clinical value for early preeclampsia diagnosis and may help us better understand the precise mechanisms involved.

Somatic mutation-associated risk index based on lncRNA expression for predicting prognosis in acute myeloid leukemia

Objectives: Genomic instability has several implications for acute myeloid leukemia (AML) prognosis. This article aims to construct a somatic mutation-associated risk index (SMRI) of genomic instability for AML to predict prognosis and explore the potential determinants of AML prognosis.Methods: We obtained differentially expressed lncRNAs from genomic instability subtypes and selected six lncRNAs to construct the SMRI through multivariate Cox regression analysis. The median SMRI classified patients into high and low SMRI groups. Kaplan-Meier survival analysis was used to clarify the prognostic differences of SMRI subtypes. Receiver operating characteristic curve analysis was performed to elucidate the value of SMRI as a prognostic indicator. Gene set variation analysis, tumor mutation burden (TMB) analysis, immune infiltration, and immune checkpoint expression analysis were performed to investigate possible causes for the differences in prognosis of SMRI subtypes.Results: The high SMRI group exhibited a poor prognosis, which was characterized by elevated levels of TMB, mutation counts (TP53, NPM1, DNMT3A, and FLT3-TKD), CD8⁺ T cell infiltration, and immune checkpoint (PD-1, PD-L2, CTLA4, LAG3) expression. The SMRI was still associated with prognosis, even after adjustment for age, sex, cytogenetic risk, DNMT3A status, FLT3 status, and NPM1 status. Gene set variation analysis showed that AML with FLT3-ITD mutation, CEBPA mutation, and LSCs (leukemia stem cells) were enriched in the high SMRI group.Conclusion: Our research suggests that the SMRI derived from genomic instability subtypes is a useful biomarker for predicting prognosis and may be beneficial for improving the clinical outcome of patients with AML.

DNA Damage and Activation of cGAS/STING Pathway Induce Tumor Microenvironment Remodeling

DNA damage occurs throughout tumorigenesis and development. The immunogenicity of DNA makes it an immune stimulatory molecule that initiates strong inflammatory responses. The cGAS/STING pathway has been investigated as a critical receptor in both exogenous and endogenous DNA sensing to activate the innate immune response. Growing lines of evidence have indicated that activation of the cGAS/STING pathway is critical in antitumor immunity. Recent studies have demonstrated the outstanding advancement of this pathway in tumor-combined immunotherapy; accordingly, increased studies focus on exploration of STING pathway agonists and analogues. However, current studies propose the potential use of the cGAS/STING pathway in tumor initiation and metastasis. Here, we review the molecular mechanisms and activation of the cGAS/STING pathway, and the relationship between DNA damage and this pathway, particularly highlighting the remodeling of immune contexture in tumor environment (TME) triggered by cascade inflammatory signals. A detailed understanding of TME reprogramming initiated by this pathway may pave the way for the development of new therapeutic strategies and rational clinical application.

Modification Patterns of DNA Methylation-Related lncRNAs Regulating Genomic Instability for Improving the Clinical Outcomes and Tumour Microenvironment Characterisation of Lower-Grade Gliomas

Background: DNA methylation is an important epigenetic modification that affects genomic instability and regulates gene expression. Long non-coding RNAs (lncRNAs) modulate gene expression by interacting with chromosomal modifications or remodelling factors. It is urgently needed to evaluate the effects of DNA methylation-related lncRNAs (DMlncRNAs) on genome instability and further investigate the mechanism of action of DMlncRNAs in mediating the progression of lower-grade gliomas (LGGs) and their impact on the immune microenvironment.

Methods: LGG transcriptome data, somatic mutation profiles and clinical features analysed in the present study were obtained from the CGGA, GEO and TCGA databases. Univariate, multivariate Cox and Lasso regression analyses were performed to establish a DMlncRNA signature. The KEGG and GO analyses were performed to screen for pathways and biological functions associated with key genes. The ESTIMATE and CIBERSORT algorithms were used to determine the level of immune cells in LGGs and the immune microenvironment fraction. In addition, DMlncRNAs were assessed using survival analysis, ROC curves, correlation analysis, external validation, independent prognostic analysis, clinical stratification analysis and qRT-PCR.

Results: We identified five DMlncRNAs with prognostic value for LGGs and established a prognostic signature using them. The Kaplan–Meier analysis revealed 10-years survival rate of 10.10% [95% confidence interval (CI): 3.27–31.40%] in high-risk patients and 57.28% (95% CI: 43.17–76.00%) in low-risk patients. The hazard ratio (HR) and 95% CI of risk scores were 1.013 and 1.009–1.017 (p &lt; 0.001), respectively, based on the univariate Cox regression analysis and 1.009 and 1.004–1.013 (p &lt; 0.001), respectively, based on the multivariate Cox regression analysis. Therefore, the five-lncRNAs were identified as independent prognostic markers for patients with LGGs. Furthermore, GO and KEGG analyses revealed that these lncRNAs are involved in the prognosis and tumorigenesis of LGGs by regulating cancer pathways and DNA methylation.

Conclusion: The findings of the study provide key information regarding the functions of lncRNAs in DNA methylation and reveal that DNA methylation can regulate tumour progression through modulation of the immune microenvironment and genomic instability. The identified prognostic lncRNAs have high potential for clinical grouping of patients with LGGs to ensure effective treatment and management.

Diagnostic and prognostic value of genomic instability-derived long non-coding RNA signature of endometrial cancer

OBJECTIVE

To investigate whether genomic instability (GI)-derived long non-coding RNAs (lncRNAs) have a prognostic impact on the patients with endometrial cancer.

MATERIAL AND METHODS

Patients with Uterine Corpus Endometrial Carcinoma (UCEC) were selected from The Cancer Genome Atlas (TCGA) database. Systematic bioinformatics analyses were performed, including Pearson correlations, GO and KEGG enrichment analysis, bivariate and multiple logistic regression analysis, and Kaplan-Meier (KM) method.

RESULTS

A total of 552 UCEC samples were included in the study. The differentially expressed lncRNAs (DELs) were identified, including 79 down-regulated lncRNAs and 31 up-regulated lncRNAs. Bivariate logistic regression analysis showed that 19 GI-derived lncRNAs were prognostic factors. By further multivariate logistic regression analysis, AC005256.1 (estimated coefficient = -0.474), AC026336.3 (estimated coefficient = -0.030), AL161618.1 (estimated coefficient = -1.661), and BX322234.1 (estimated coefficient = 1.511) were used to construct a prognostic risk model. In the train set and test set, the risk model was shown to have both a high prognostic and a diagnostic value.

CONCLUSION

We developed a novel GI-derived 4-lncRNA signature for the diagnosis and prognosis of patients with endometrial cancer. These findings offered a novel perspective in the clinical management of endometrial cancer.

Roles of extracellular vesicles associated non-coding RNAs in Diabetes Mellitus

Extracellular vesicles (EVs), especially exosomes (50 to 150 nm), have been shown to play important roles in a wide range of physiological and pathological processes, including metabolic diseases such as Diabetes Mellitus (DM). In the last decade, several studies have demonstrated how EVs are involved in cell-to-cell communication. EVs are enriched in proteins, mRNAs and non-coding RNAs (miRNAs, long non-coding RNAs and circRNAS, among others) which are transferred to recipient cells and may have a profound impact in either their survival or functionality. Several studies have pointed out the contribution of exosomal miRNAs, such as miR-l42-3p and miR-26, in the development of Type 1 and Type 2 DM (T1DM and T2DM), respectively. In addition, some miRNA families such as miR-let7 and miR-29 found in exosomes have been associated with both types of diabetes, suggesting that they share common etiological features. The knowledge about the role of exosomal long non-coding RNAs in this group of diseases is more immature, but the exosomal lncRNA MALAT1 has been found to be elevated in the plasma of individuals with T2DM, while more than 169 lncRNAs were reported to be differentially expressed between healthy donors and people with T1DM. Here, we review the current knowledge about exosomal non-coding RNAs in DM and discuss their potential as novel biomarkers and possible therapeutic targets.

Anti-Cancer Role and Therapeutic Potential of Extracellular Vesicles

Cell-cell communication is an important mechanism in biological processes. Extracellular vesicles (EVs), also referred to as exosomes, microvesicles, and prostasomes, are microvesicles secreted by a variety of cells. EVs are nanometer-scale vesicles composed of a lipid bilayer and contain biological functional molecules, such as microRNAs (miRNAs), mRNAs, and proteins. In this review, "EVs" is used as a comprehensive term for vesicles that are secreted from cells. EV research has been developing over the last four decades. Many studies have suggested that EVs play a crucial role in cell-cell communication. Importantly, EVs contribute to cancer malignancy mechanisms such as carcinogenesis, proliferation, angiogenesis, metastasis, and escape from the immune system. EVs derived from cancer cells and their microenvironments are diverse, change in nature depending on the condition. As EVs are thought to be secreted into body fluids, they have the potential to serve as diagnostic markers for liquid biopsy. In addition, cells can encapsulate functional molecules in EVs. Hence, the characteristics of EVs make them suitable for use in drug delivery systems and novel cancer treatments. In this review, the potential of EVs as anti-cancer therapeutics is discussed.

A Mutation-Related Long Noncoding RNA Signature of Genome Instability Predicts Immune Infiltration and Hepatocellular Carcinoma Prognosis

Background: Long noncoding RNAs (lncRNAs) have been discovered to play a regulatory role in genomic instability (GI), which participates in the carcinogenesis of various cancers, including hepatocellular carcinoma (HCC). We endeavored to establish a GI-derived lncRNA signature (GILncSig) as a potential biomarker and explore its impact on immune infiltration and prognostic significance. Methods: Combining expression and somatic mutation profiles from The Cancer Genome Atlas database, we identified GI-related lncRNAs and conducted functional analyses on co-expressed genes. Based on Cox regression analysis, a GILncSig was established in the training cohort (n = 187), and an independent testing patient cohort (n = 183) was used to validate its predictive ability. Kaplan-Meier method and receiver operating characteristic curves were adopted to evaluate the performance. The correlation between GI and immune infiltration status was investigated based on the CIBERSORT algorithm and single sample gene set enrichment analysis. In addition, a comprehensive nomogram integrating the GILncSig and clinicopathological variables was constructed to efficiently assess HCC patient prognosis in clinical applications. Results: A total of 88 GI-related lncRNAs were screened out and the functional analyses indicated diversified effects on HCC progression. The GILncSig was established using four independent lncRNAs (AC116351.1, ZFPM2-AS1, AC145343.1, and MIR210HG) with significant prognostic value (p < 0.05). Following evaluation with the GILncSig, low-risk patients had significantly better clinical outcomes than high-risk patients in the training cohort (p < 0.001), which was subsequently validated in the independent testing cohort. High-risk group exhibited more immunocyte infiltration including B cells memory, macrophages M0 and neutrophils and higher expression of HLA gene set and immune checkpoint genes. Compared to existing HCC signatures, the GILncSig showed better prognosis predictive performance [area under the curve (AUC) = 0.709]. Furthermore, an integrated nomogram was constructed and validated to efficiently and reliably evaluate HCC patient prognosis (3-years survival AUC = 0.710 and 5-years survival AUC = 0.707). Conclusion: The GILncSig measuring GI and impacting immune infiltration serves as a potential biomarker and independent predictor of HCC patient prognosis. Our results highlight further investigation of GI and HCC molecular mechanisms.

Advances of Exosomal miRNAs in Breast Cancer Progression and Diagnosis

Breast cancer is one of the most commonly diagnosed malignancies and the leading cause of cancer death in women worldwide. Although many factors associated with breast cancer have been identified, the definite etiology of breast cancer is still unclear. In addition, early diagnosis of breast cancer remains challenging. Exosomes are membrane-bound nanovesicles secreted by most types of cells and contain a series of biologically important molecules, such as lipids, proteins, and miRNAs, etc. Emerging evidence shows that exosomes can affect the status of cells by transmitting substances and messages among cells and are involved in various physiological and pathological processes. In breast cancer, exosomes play a significant role in breast tumorigenesis and progression through transfer miRNAs which can be potential biomarkers for early diagnosis of breast cancer. This review discusses the potential utility of exosomal miRNAs in breast cancer progression such as tumorigenesis, metastasis, immune regulation and drug resistance, and further in breast cancer diagnosis.

Genomic Instability-Related LncRNA Signature Predicts the Prognosis and Highlights LINC01614 Is a Tumor Microenvironment-Related Oncogenic lncRNA of Papillary Thyroid Carcinoma

Background

Genomic instability (GI) is among the top ten characteristics of malignancy. Long non-coding RNAs (lncRNAs) are promising cancer biomarkers that are reportedly involved in GI. So far, the clinical value of GI-related lncRNAs (GIlncs) in papillary thyroid cancer (PTC) has not been clarified.

Methods

Integrative analysis of lncRNA expression and somatic mutation profiles was performed to identify GIlncs. Analysis of differentially expressed lncRNAs in the group with high- and low- cumulative number of somatic mutations revealed significant GIlncs in PTC. Univariate and multivariate Cox proportional hazard regression analyses were performed to identify hub-GIlncs.

Results

A computational model based on four lncRNAs (FOXD2-AS1, LINC01614, AC073257.2, and AC005082.1) was identified as a quantitative index using an in-silicon discovery cohort. GILS score was significantly associated with poor prognosis, as validated in the TCGA dataset and further tested in our local RNA-Seq cohort. Moreover, a combination of clinical characteristics and the composite GILS-clinical prognostic nomogram demonstrates satisfactory discrimination and calibration. Furthermore, the GILS score and FOXD2-AS1, LINC01614, AC073257.2, and AC005082.1 were also associated with driver mutations and multiple clinical-pathological variables, respectively. Moreover, RNA-Seq confirmed the expression patterns of FOXD2-AS1, LINC01614, AC073257.2, and AC005082.1 in PTC and normal thyroid tissues. Biological experiments demonstrated that downregulated or overexpressed LINC01614 affect PTC cell proliferation, migration, and invasion in vitro. Activation of the stromal and immune cell infiltration was also observed in the high LINC01614 group in the PTC microenvironment.

Conclusion

In summary, we identified a signature for clinical outcome prediction in PTC comprising four lncRNAs associated with GI. A better understanding of the GI providing an alternative evaluation of the progression risk of PTC. Our study also demonstrated LINC01614 as a novel oncogenic lncRNA and verified its phenotype in PTC.

Genomic instability-associated lncRNA signature predicts prognosis and distinct immune landscape in gastric cancer

Background

Characterized by multiple features, genomic stability-related markers, such as microsatellite instability (MSI), were regulated as an important predictor of chemotherapy and immunity responses in cancer treatment. The aim of our study was to identify a genomic instability-associated long non-coding RNA (lncRNA) signature to help predict the survival and therapy response of gastric cancers (GCs).

Methods

We used RNA sequencing and single nucleotide variant (SNV) data from The Cancer Genome Atlas-stomach adenocarcinoma (TCGA-STAD) datasets to explore genomic instability-associated lncRNAs. Hierarchical cluster analyses of 197 differentially expressed genomic instability-associated lncRNAs were performed to separate GC patients into two groups, namely, the genomically unstable (GU)-like group and the genomically stable (GS)-like group.

Results

Cox regression analysis was conducted to finally identify six lncRNAs (LINC02678, HOXA10-AS, RHOXF1-AS1, AC010789.1, LINC01150, and TGFB2-AS1) with independent prognostic value to establish the genomic instability-associated lncRNA signature (GILncSig). Based on the SNV analysis, GILncSig was correlated with accumulation of gene mutation counts. Further comparisons between different risk score groups were performed to assess chemotherapy drug sensitivity and immune landscape variations.

Conclusions

Our study not only revealed the genomic instability-associated lncRNAs in GCs, but provided a key method and resource for further studies of the role of these lncRNAs play, and introduced a potential new way to identify genomic instability-associated cancer biomarkers.

Developing ZNF Gene Signatures Predicting Radiosensitivity of Patients with Breast Cancer

Adjuvant radiotherapy is one of the main treatment methods for breast cancer, but its clinical benefit depends largely on the characteristics of the patient. This study aimed to explore the relationship between the expression of zinc finger (ZNF) gene family proteins and the radiosensitivity of breast cancer patients. Clinical and gene expression data on a total of 976 breast cancer samples were obtained from The Cancer Genome Atlas (TCGA) database. ZNF gene expression was dichotomized into groups with a higher or lower level than the median level of expression. Univariate and multivariate Cox regression analyses were used to evaluate the relationship between ZNF gene expression levels and radiosensitivity. The Molecular Taxonomy Data of the International Federation of Breast Cancer (METABRIC) database was used for validation. The results revealed that 4 ZNF genes were possible radiosensitivity markers. High expression of ZNF644 and low expression levels of the other 3 genes (ZNF341, ZNF541, and ZNF653) were related to the radiosensitivity of breast cancer. Hierarchical cluster, Cox, and CoxBoost analysis based on these 4 ZNF genes indicated that patients with a favorable 4-gene signature had better overall survival on radiotherapy. Thus, this 4-gene signature may have value for selecting those patients most likely to benefit from radiotherapy. ZNF gene clusters could act as radiosensitivity signatures for breast cancer patients and may be involved in determining the radiosensitivity of cancer.

Genome Instability-Derived Genes Are Novel Prognostic Biomarkers for Triple-Negative Breast Cancer

Background

Triple-negative breast cancer (TNBC) is an aggressive disease. Recent studies have identified genome instability-derived genes for patient outcomes. However, most of the studies mainly focused on only one or a few genome instability-related genes. Prognostic potential and clinical significance of genome instability-associated genes in TNBC have not been well explored.

Methods

In this study, we developed a computational approach to identify TNBC prognostic signature. It consisted of (1) using somatic mutations and copy number variations (CNVs) in TNBC to build a binary matrix and identifying the top and bottom 25% mutated samples, (2) comparing the gene expression between the top and bottom 25% samples to identify genome instability-related genes, and (3) performing univariate Cox proportional hazards regression analysis to identify survival-associated gene signature, and Kaplan–Meier, log-rank test, and multivariate Cox regression analyses to obtain overall survival (OS) information for TNBC outcome prediction.

Results

From the identified 111 genome instability-related genes, we extracted a genome instability-derived gene signature (GIGenSig) of 11 genes. Through survival analysis, we were able to classify TNBC cases into high- and low-risk groups by the signature in the training dataset (log-rank test p = 2.66e−04), validated its prognostic performance in the testing (log-rank test p = 2.45e−02) and Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) (log-rank test p = 2.57e−05) datasets, and further validated the predictive power of the signature in five independent datasets.

Conclusion

The identified novel signature provides a better understanding of genome instability in TNBC and can be applied as prognostic markers for clinical TNBC management.

Circulating exosomal miR-363-5p inhibits lymph node metastasis by downregulating PDGFB and serves as a potential noninvasive biomarker for breast cancer

Sentinel lymph node (LN) biopsy is currently the standard procedure for clinical LN-negative breast cancer (BC) patients but it is prone to false-negative results and complications. Thus, an accurate noninvasive approach for LN staging is urgently needed in clinical practice. Here, circulating exosomal microRNA (miRNA) expression profiles in peripheral blood from BC patients and age-matched healthy women were obtained and analyzed. We identified an exosomal miRNA, miR-363-5p, that was significantly downregulated in exosomes from plasma of BC patients with LN metastasis which exhibited a consistent decreasing trend in tissue samples from multiple independent datasets. Plasma exosomal miR-363-5p achieved high diagnostic performance in distinguishing LN-positive patients from LN-negative patients. The high miR-363-5p expression level was significantly correlated with improved overall survival. Functional assays demonstrated that exosomal miR-363-5p modulates platelet-derived growth factor (PDGF) signaling activity by targeting PDGFB to inhibit cell proliferation and migration. Our study revealed, for the first time, plasma exosomal miR-363-5p plays a tumor suppressor role in BC and has the potential for noninvasive LN staging and prognosis prediction of BC.

Bone mesenchymal stem cell derived exosomes alleviate high phosphorus-induced calcification of vascular smooth muscle cells through the NONHSAT 084969.2/NF-κB axis

Our previous study showed that bone marrow mesenchymal stem cell derived exosomes (BMSC-Exos) suppress high phosphorus (Pi)-induced calcification of vascular smooth muscle cells (VSMCs). However, the mechanism had remained unclear. This study aimed to investigate the mechanism by which BMSC-Exos inhibit vascular calcification (VC). We found that BMSC-Exos reduced high Pi-induced Runx2, osteocalcin and BMP2 expression and inhibited the calcium deposition. Gene expression of human VSMCs stimulated by Pi or Pi plus BMSC-Exos (Pi + Exo) was systematically examined by microarray technology. NONHSAT 084969.2 and transcription factor p65 expression was significantly lower in the Pi + Exo group compared with the Pi group. This finding indicated that NONHSAT 084969.2 and the nuclear factor-κB pathway might play an important role in VC inhibition by BMSC-Exos. By silencing NONHSAT 084969.2 with small interfering RNA, Runx2, BMP2, and osteocalcin expression was decreased significantly. The calcified nodule content and alkaline phosphatase activity were reduced after NONHSAT 084969.2 inhibition and p65, p50, and IκB kinase-α expression was decreased significantly. These results indicated that BMSC-Exos inhibited Pi-induced transdifferentiation and calcification of VSMCs by regulating the NONHSAT 084969.2/nuclear factor-κB axis.

The Functional Characterization of Epigenetically Related lncRNAs Involved in Dysregulated CeRNA-CeRNA Networks Across Eight Cancer Types

Numerous studies have demonstrated that lncRNAs could compete with other RNAs to bind miRNAs, as competing endogenous RNAs (ceRNAs), to regulate each other. On the other hand, ceRNAs were found to be recurrently dysregulated in cancer status. However, limited studies considered the upstream epigenetic regulatory factors that disrupted the normal competing mechanism. In the present study, we constructed the lncRNA-associated dysregulated ceRNA networks across eight cancer types. lncRNAs in the individual dysregulated network and pan-cancer core dysregulated ceRNA subnetwork were found to play more important roles than mRNAs. Integrating lncRNA methylation profiles, we identified 49 epigenetically related (ER) lncRNAs involved in the dysregulated ceRNA networks, including 18 epigenetically activated (EA) lncRNAs, 18 epigenetically silenced (ES) lncRNAs, and 13 rewired ER lncRNAs across eight cancer types. Furthermore, we evaluated the epigenetic regulating patterns of these lncRNAs and screened nine pan-cancer ER lncRNAs (six EA and three ES lncRNAs). The nine lncRNAs were found to regulate the cancer hallmarks by competing with mRNAs. Moreover, we found that integrating the expression and methylation profiles of the nine lncRNAs could predict cancer incidence in eight cancer types robustly and the cancer outcome of several cancer types. These results provide an improved understanding of methylation regulation to ceRNA and offer novel potential molecular therapeutic targets for the diagnosis and prognosis across different cancer types.

Regulatory Network Analysis of Mutated Genes Based on Multi-Omics Data Reveals the Exclusive Features in Tumor Immune Microenvironment Between Left-Sided and Right-Sided Colon Cancer

Left-sided colon cancer (LCC) and right-sided colon cancer (RCC) have distinct characteristics in tumor immune microenvironment (TIME). Although existing studies have shown a strong association between gene mutations and TIME, whether the regulatory mechanisms between gene mutations and TIME are different between RCC and LCC is still unclear. In this study, we showed the fractions of CD8+ T cells were higher while those of regulatory T cells were lower in RCC. Besides, a stronger association between gene mutations and TIME was observed in RCC. Specifically, using multi-omics data, we demonstrated the mutations of most top mutated genes (TMGs) including BRAF, PCLO, MUC16, LRP2, ANK3, KMT2D, RYR2 made great contributions to elevated fraction of immune cells by up-regulating immune-related genes directly or indirectly through miRNA and DNA methylation, whereas the effects of APC, TP53 and KRAS mutations on TIME were reversed in RCC. Remarkably, we found the expression levels of several immune checkpoint molecules such as PD-1 and LAG3 were correlated with corresponding DNA methylation levels, which were associated with the mutations of TMGs in RCC. In contrast, the associations between gene mutations and TIME were less significant in LCC. Besides, survival analyses showed APC mutation had adverse impact on immunotherapy while patients with BRAF mutation were more suitable for immunotherapy in colon cancer. We hope that our results will provide a deeper insight into the sophisticated mechanism underlying the regulation between mutations and TIME, and thus boost the discovery of differential immunotherapeutic strategies for RCC and LCC.

Integrated Analysis of the Transcriptome Profile Reveals the Potential Roles Played by Long Noncoding RNAs in Immunotherapy for Sarcoma

Background

Long-term survival is still low for high-risk patients with soft tissue sarcoma treated with standard management options, including surgery, radiation, and chemotherapy. Immunotherapy is a promising new potential treatment paradigm. However, the application of immune checkpoint inhibitors for the treatment of patients with sarcoma did not yield promising results in a clinical trial. Therefore, there is a considerable need to identify factors that may lead to immune checkpoint inhibitor resistance.

Methods

In this study, we performed a bioinformatic analysis of The Cancer Genome Atlas (TCGA) to detect key long noncoding RNAs (lncRNAs) that were correlated with immune checkpoint inhibitory molecules in sarcoma. The expression levels of these lncRNAs and their correlation with patient prognosis were explored. The upstream long noncoding RNAs were also examined via 450K array data from the TCGA. The potential roles of these lncRNAs were further examined via KEGG and GO analysis using DAVID online software. Finally, the relationship between these lncRNAs and immune cell infiltration in tumors and their effect on immune checkpoint inhibitors were further explored.

Results

We identified lncRNAs correlated with tumor cell immune evasion in sarcoma. The expression of these lncRNAs was upregulated and correlated with worse prognosis in sarcoma and other human cancer types. Moreover, low DNA methylation occupation of these lncRNA loci was detected. Negative correlations between DNA methylation and lncRNA expression were also found in sarcoma and other human cancer types. KEGG and GO analyses indicated that these lncRNAs correlated with immune evasion and negative regulation of the immune response in sarcoma. Finally, high expression of these lncRNAs correlated with more suppressive immune cell infiltration and reduced sensitivity to immune checkpoint inhibitors in sarcoma and other human cancer types.

Conclusion

Our results suggest that long noncoding RNAs confer immune checkpoint inhibitor resistance in human cancer. Further characterization of these lncRNAs may help to elucidate the mechanisms underlying immune checkpoint inhibitor resistance and uncover a novel therapeutic intervention point for immunotherapy.

Characterization of DNA Methylation and Screening of Epigenetic Markers in Polycystic Ovary Syndrome

Polycystic ovary syndrome (PCOS) is a heterogeneous endocrine and metabolic disorder in women, which is characterized by androgen excess, ovulation dysfunction, and polycystic ovary. Although the etiology of PCOS is largely unknown, many studies suggest that aberrant DNA methylation is an important contributing factor for its pathological changes. In this study, we investigated DNA methylation characteristics and their impact on gene expression in granulosa cells obtained from PCOS patients. Transcriptome analysis found that differentially expressed genes were mainly enriched in pathways of insulin resistance, fat cell differentiation, and steroid metabolism in PCOS. Overall DNA methylation level in granulosa cells was reduced in PCOS, and the first introns were found to be the major genomic regions that were hypomethylated in PCOS. Integrated analysis of transcriptome, DNA methylation, and miRNAs in ovarian granulosa cells revealed a DNA methylation and miRNA coregulated network and identified key candidate genes for pathogenesis of PCOS, including BMP4, ETS1, and IRS1. Our study shed more light on epigenetic mechanism of PCOS and provided valuable reference for its diagnosis and treatment.

Development and Interpretation of a Genomic Instability Derived lncRNAs Based Risk Signature as a Predictor of Prognosis for Clear Cell Renal Cell Carcinoma Patients

Background

Clear cell renal cell carcinoma (ccRCC) is a kind of frequently diagnosed cancer, leading to high death rate in patients. Genomic instability (GI) is regarded as playing indispensable roles in tumorigenesis and impacting the prognosis of patients. The aberrant regulation of long non-coding RNAs (lncRNAs) is a main cause of GI. We combined the somatic mutation profiles and expression profiles to identify GI derived lncRNAs (GID-lncRNAs) in ccRCC and developed a GID-lncRNAs based risk signature for prognosis prediction and medication guidance.

Methods

We decided cases with top 25% cumulative number of somatic mutations as genomically unstable (GU) group and last 25% as genomically stable (GS) group, and identified differentially expressed lncRNAs (GID-lncRNAs) between two groups. Then we developed the risk signature with all overall survival related GID-lncRNAs with least absolute shrinkage and selection operator (LASSO) Cox regression. The functions of the GID-lncRNAs were partly interpreted by enrichment analysis. We finally validated the effectiveness of the risk signature in prognosis prediction and medication guidance.

Results

We developed a seven-lncRNAs (LINC00460, AL139351.1, AC156455.1, AL035446.1, LINC02471, AC022509.2, and LINC01606) risk signature and divided all samples into high-risk and low-risk groups. Patients in high-risk group were in more severe clinicopathologic status (higher tumor grade, pathological stage, T stage, and more metastasis) and were deemed to have less survival time and lower survival rate. The efficacy of prognosis prediction was validated by receiver operating characteristic analysis. Enrichment analysis revealed that the lncRNAs in the risk signature mainly participate in regulation of cell cycle, DNA replication, material metabolism, and other vital biological processes in the tumorigenesis of ccRCC. Moreover, the risk signature could help assess the possibility of response to precise treatments.

Conclusion

Our study combined the somatic mutation profiles and the expression profiles of ccRCC for the first time and developed a GID-lncRNAs based risk signature for prognosis predicting and therapeutic scheme deciding. We validated the efficacy of the risk signature and partly interpreted the roles of the seven lncRNAs composing the risk signature in ccRCC. Our study provides novel insights into the roles of genomic instability derived lncRNAs in ccRCC.

Integrative Analysis of DNA Methylation Data and Transcriptome Data Identified a DNA Methylation-Dysregulated Four-LncRNA Signature for Predicting Prognosis in Head and Neck Squamous Cell Carcinoma

Increasing evidence has demonstrated the crosstalk between DNA epigenetic alterations and aberrant expression of long non-coding RNAs (lncRNAs) during carcinogenesis. However, epigenetically dysregulated lncRNAs and their functional and clinical roles in Head and Neck Squamous Cell Carcinoma (HNSCC) are still not explored. In this study, we performed an integrative analysis of DNA methylation data and transcriptome data and identified a DNA methylation-dysregulated four-lncRNA signature (DNAMeFourLncSig) from 596 DNA methylation-dysregulated lncRNAs using a machine-learning-based feature selection method, which classified the patients of the discovery cohort into two risk groups with significantly different survival including overall survival, disease-specific survival, and progression-free survival. Then the DNAMeFourLncSig was implemented to another two HNSCC patient cohorts and showed similar prognostic values in both. Results from multivariable Cox regression analysis revealed that the DNAMeFourLncSig might be an independent prognostic factor. Furthermore, the DNAMeFourLncSig was substantially correlated with the complete response rate of chemotherapy and may predict chemotherapy response. Functional in silico analysis found that DNAMeFourLncSig-related mRNAs were mainly enriched in cell differentiation, tissue development and immune-related pathways. Overall, our study will improve our understanding of underlying transcriptional and epigenetic mechanisms in HNSCC carcinogenesis and provided a new potential biomarker for the prognosis of patients with HNSCC.