Classification of the four main types of lung cancer using a microRNA-based diagnostic assay. J Mol Diagn. 2012;14:510-517. [PMID: 22749746 DOI: 10.1016/j.jmoldx.2012.03.004]

Emerging biomarkers for non-invasive diagnosis and treatment of cancer: a systematic review

Cancer remains a global health challenge, necessitating continuous advancements in diagnostic and treatment strategies. This review focuses on the utility of non-invasive biomarkers in cancer diagnosis and treatment, their role in early detection, disease monitoring, and personalized therapeutic interventions. Through a systematic review of the literature, we identified 45 relevant studies that highlight the potential of these biomarkers across various cancer types, such as breast, prostate, lung, and colorectal cancers. The non-invasive biomarkers discussed include liquid biopsies, epigenetic markers, non-coding RNAs, exosomal cargo, and metabolites. Notably, liquid biopsies, particularly those based on circulating tumour DNA (ctDNA), have emerged as the most promising method for early, non-invasive cancer detection due to their ability to provide comprehensive genetic and epigenetic information from easily accessible blood samples. This review demonstrates how non-invasive biomarkers can facilitate early cancer detection, accurate subtyping, and tailored treatment strategies, thereby improving patient outcomes. It underscores the transformative potential of non-invasive biomarkers in oncology, highlighting their application for enhancing early detection, survival rates, and treatment precision in cancer care.

Systematic review registration

https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42023474749 PROSPERO, identifier CRD42023474749.

An NHS Trust comparison of reporting radiographers and consultant radiologists ability to identify cancer on chest radiographs with confirmation through a Fast track CT thorax referral system

INTRODUCTION

The National Institute for Health and Care Excellence (NICE) recommends that GPs initially refer patients with suspected lung cancer for a chest X-ray (CXR). The Radiology department has a 'fast track system' to identify those patients who may have lung cancer on CXR and are referred for a CT thorax with contrast to help determine a cancer diagnosis. This fast track system was put in place to ensure the NICE guidelines and NHS England's standards on a faster cancer diagnosis are being met. This audit studied the ability of radiologists and reporting radiographers to identify lung cancer on CXRs and the accuracy of the fast-track system.

METHODS

846 cases with lung alerts were analysed and 545 CXRs were audited. The CXRs were split into images reported by radiologists (168) and those reported by reporting radiographers (377). CT thorax results were collected through PACS and Cerner computer systems to identify if the 'fast track' system had yielded a "positive", "negative", or "other findings" result for lung cancer.

RESULTS

32.8% (179) of CXRs flagged for lung cancer were positive, 40.6% (221) were negative, and 26.6% (145) had other findings. Chi square statistical test showed no significant difference (p = 0.14) between the two reporting groups in their ability to identify lung cancer on CXRs. 27% (38) of CXRs flagged by radiologists and 35% (125) by reporting radiographers were positive for lung cancer.

CONCLUSION

This clinical audit indicates, reporting radiographers and radiologists are not statistically significantly different regarding their ability to identify lung cancer on CXRs, when supported by the fast track system. The fast-track system had a 59.4 % accuracy rate, detected by the number of imaging of reports that identified a serious pathology. This concludes that the system is performing well, yet could still be improved.

IMPLICATIONS FOR PRACTICE

This audit provides further evidence for the value of developing and deploying reporting radiographers for projection radiography reporting.

Deciphering the Epigenetic Symphony of Cancer: Insights and Epigenetic Therapies Implications

Epigenetic machinery is a cornerstone in normal cell development, orchestrating tissue-specific gene expression in mammalian cells. Aberrations in this intricate landscape drive substantial changes in gene function, emerging as a linchpin in cancer etiology and progression. While cancer was conventionally perceived as solely a genetic disorder, its contemporary definition encompasses genetic alterations intertwined with disruptive epigenetic abnormalities. This review explores the profound impact of DNA methylation, histone modifications, and noncoding RNAs on fundamental cellular processes. When these pivotal epigenetic mechanisms undergo disruption, they intricately guide the acquisition of the 6 hallmark characteristics of cancer within seemingly normal cells. Leveraging the latest advancements in decoding these epigenetic intricacies holds immense promise, heralding a new era in developing targeted and more efficacious treatment modalities against cancers driven by aberrant epigenetic modifications.

miRNA in head and neck squamous cell carcinomas: promising but still distant future of personalized oncology

Head and neck squamous cell carcinoma is one of the most common and fatal cancers worldwide. Lack of appropriate preventive screening tests, late detection, and high heterogeneity of these tumors are the main reasons for the unsatisfactory effects of therapy and, consequently, unfavorable outcomes for patients. An opportunity to improve the quality of diagnostics and treatment of this group of cancers are microRNAs (miRNAs) - molecules with a great potential both as biomarkers and therapeutic targets. This review aims to present the characteristics of these short non-coding RNAs (ncRNAs) and summarize the current reports on their use in oncology focused on medical strategies tailored to patients' needs.

An outlook of docking analysis and structure-activity relationship of pyrimidine-based analogues as EGFR inhibitors against non-small cell lung cancer (NSCLC)

Almost 80% of lung cancer diagnoses each year correspond to non-small cell lung cancer (NSCLC). The percentage of NSCLC with EGFR overexpression ranges from 40% to 89%, with squamous tumors showing the greatest rates (89%) and adenocarcinomas showing the lowest rates (41%). Therefore, in NSCLC therapy, blocking the EGFR-driven pathway by inhibiting the intracellular tyrosine kinase domain of EGFR has exhibited significant improvement. In this view, several small molecules particularly pyrimidine/fused pyrimidine scaffolds were intended for molecular hybridization to develop EGFR-TK inhibitors. However, the associated limitation such as resistance and genetic mutation along with adverse effects, constrained the long-term treatment and effectiveness of such medication. Therefore, in recent years, pyrimidine derivatives were uncovered as potential EGFR TKIs. The present review summarised the research progress of EGFR TKIs to dazed structure-activity relationship, biological evaluation, and comparative docking studies of pyrimidine compounds. We have added the comparative docking analysis followed by the molecular simulation study against the four different PDBs of EGFR to strengthen the already existing research. Docking analysis unfolded that compound 14 resulted as noticeable with all different PDB and managed to interact with some of the crucial amino acid residues. From a future perspective, researchers must develop a more selective inhibitor, that can selectively target the mutation. Our review will support medicinal chemists in the direction of the development of novel pyrimidine-based EGFR TKIs.Communicated by Ramaswamy H. Sarma.

MicroRNAs as Targets for Cancer Diagnosis: Interests and Limitations

MicroRNAs are small RNAs with ability to attach to the large number of RNA that regulate gene expression on post-transcriptional level via inhibition or degradation of specific mRNAs. MiRNAs in cells are the primary regulators of functions such as cell growth, differentiation, and apoptosis and considerably influence cell function. The expression levels of microRNAs change in human diseases, including cancer. These changes highlight their essential role in cancer pathogenesis. Ubiquitous irregular expression profiles of miRNAs have been detected in various human cancers using genome-wide identification techniques, which are emerging as novel diagnostic and prognostic cancer biomarkers of high specificity and sensitivity. The measurable miRNAs with enhanced stability in blood, tissues, and other body fluids provide a comprehensive source of miRNA-dependent biomarkers for human cancers. The leading role of miRNAs as potential biomarkers in human cancers is discussed in this article. In addition, the interests and difficulties of miRNAs as biomarkers have been explored.

LncRNA NNT-AS1/hsa-miR-485-5p/HSP90 axis in-silico and clinical prospect correlated-to histologic grades-based CRC stratification: A step toward ncRNA Precision

The oncogenic effects of long non-coding RNA (lncRNA) Nicotinamide Nucleotide Transhydrogenase-antisense RNA1 (NNT-AS1) role in colorectal cancer (CRC) hasn't been sufficiently inspected in relation to the Homo sapiens (hsa)-microRNA (miR)- 485-5p/ heat shock protein 90 (HSP90) axis, clinically. qRT-PCR was performed to detect lncRNA NNT-AS1 and hsa-miR-485-5p expression levels in 60 Egyptian patients' sera. HSP90 serum level was quantified using Enzyme-linked immunosorbent assay (ELISA). The relative expression level of the studied non-coding RNAs as well as the HSP90 ELISA concentration were correlated with patients clinicopathological characteristics and correlated to each other. The axis diagnostic utility in comparison with carbohydrate antigen 19-9 (CA19-9) and carcinoembryonic antigen (CEA) tumor markers (TMs) was studied by receiver operating characteristic (ROC) curve analysis. The relative lncRNA NNT-AS1 expression level fold change 56.7 (13.5-112) and HSP90 protein ELISA level 6.68 (5.14-8.77) (ng/mL) were elevated, while, for hsa-miR-485-5p 0.0474 (0.0236-0.135) expression fold change was repressed in CRC Egyptian patients' cohort sera, being compared to 28 apparently healthy control subjects. LncRNA NNT-AS1 specificity is 96.4% and a sensitivity of 91.7%, hsa-miR-485-5p showed 96.4% specificity, 90% sensitivity, and for HSP90 89.3%, 70% specificity and sensitivity, respectively. Those specificities and sensitivities were superior to the classical CRC TMs. A significant negative correlation was found between hsa-miR-485-5p with lncRNA NNT-AS1 (r = -0.933) expression fold change or with HSP90 protein blood level (r = -0.997), but, significant positive correlation was there between lncRNA NNT-AS1 and HSP90 (r = 0.927). LncRNA NNT-AS1/hsa-miR-485-5p/HSP90 axis could be a prospect for CRC development as well as diagnosis. Being correlated and related to CRC histologic grades 1-3, therefore, lncRNA NNT-AS1/hsa-miR-485-5p/HSP90 axis (not individually) expression approved clinically and in silico, could aid treatment precision.

Risk factors and actionable molecular signatures in COVID-19-associated lung adenocarcinoma and lung squamous cell carcinoma patients

The molecular mechanism of COVID-19's pathogenic effect on lung cancer patients is yet unknown. In this study, we used differential gene expression pattern analysis to try to figure out the possible disease mechanism of COVID-19 and its associated risk factors in patients with the two most common types of non-small-cell lung cancer, lung adenocarcinoma and lung squamous cell carcinoma. We also used network-based approaches to identify potential diagnostic and molecular targets for COVID-19-infected lung cancer patients. Our study showed that lung cancer and COVID-19 patients share 36 genes that are expressed differently and in common. Most of these genes are expressed in lung tissues and are mostly involved in the pathogenesis of different respiratory tract diseases. Additionally, we also found that COVID-19 may affect the expression of several cancer-associated genes in lung cancer patients, such as the oncogenes JUN, TNC, and POU2AF1. Moreover, we also reported that COVID-19 may predispose lung cancer patients to other diseases like acute liver failure and respiratory distress syndrome. Also, our findings in concert with published literature suggest that molecular signatures like hsa-mir-93-5p, CCNB2, IRF1, CD163, and different immune cell-based approaches could help both diagnose and treat this group of patients. Overall, the scientific results of this research will aid in the formulation of suitable management strategies as well as the development of diagnostic and therapeutic methods for COVID-19-infected lung cancer patients.

The uprise of RNA biology in neuroendocrine neoplasms: altered splicing and RNA species unveil translational opportunities

Neuroendocrine neoplasms (NENs) comprise a highly heterogeneous group of tumors arising from the diffuse neuroendocrine system. NENs mainly originate in gastrointestinal, pancreatic, and pulmonary tissues, and despite being rare, show rising incidence. The molecular mechanisms underlying NEN development are still poorly understood, although recent studies are unveiling their genomic, epigenomic and transcriptomic landscapes. RNA was originally considered as an intermediary between DNA and protein. Today, compelling evidence underscores the regulatory relevance of RNA processing, while new RNA molecules emerge with key functional roles in core cell processes. Indeed, correct functioning of the interrelated complementary processes comprising RNA biology, its processing, transport, and surveillance, is essential to ensure adequate cell homeostasis, and its misfunction is related to cancer at multiple levels. This review is focused on the dysregulation of RNA biology in NENs. In particular, we survey alterations in the splicing process and available information implicating the main RNA species and processes in NENs pathology, including their role as biomarkers, and their functionality and targetability. Understanding how NENs precisely (mis)behave requires a profound knowledge at every layer of their heterogeneity, to help improve NEN management. RNA biology provides a wide spectrum of previously unexplored processes and molecules that open new avenues for NEN detection, classification and treatment. The current molecular biology era is rapidly evolving to facilitate a detailed comprehension of cancer biology and is enabling the arrival of personalized, predictive and precision medicine to rare tumors like NENs.

A review of sensors for classification and subtype discrimination of cancer: Insights into circulating tumor cells and tumor-derived extracellular vesicles

Liquid biopsy can reflect the state of tumors in vivo non-invasively, thus providing a strong basis for the early diagnosis, individualized treatment monitoring and prognosis of tumors. Circulating tumor cells (CTCs) and tumor-derived extracellular vesicles (tdEVs) contain information-rich components, such as nucleic acids and proteins, and they are essential markers for liquid biopsies. Their capture and analysis are of great importance for the study of disease occurrence and development and, consequently, have been the subject of many reviews. However, both CTCs and tdEVs carry the biological characteristics of their original tissue, and few reviews have focused on their function in the staging and classification of cancer. In this review, we focus on state-of-the-art sensors based on the simultaneous detection of multiple biomarkers within CTCs and tdEVs, with clinical applications centered on cancer classification and subtyping. We also provide a thorough discussion of the current challenges and prospects for novel sensors with the ultimate goal of cancer classification and staging. It is hoped that these most advanced technologies will bring new insights into the clinical practice of cancer screening and diagnosis.

Deep learning ensemble 2D CNN approach towards the detection of lung cancer

In recent times, deep learning has emerged as a great resource to help research in medical sciences. A lot of work has been done with the help of computer science to expose and predict different diseases in human beings. This research uses the Deep Learning algorithm Convolutional Neural Network (CNN) to detect a Lung Nodule, which can be cancerous, from different CT Scan images given to the model. For this work, an Ensemble approach has been developed to address the issue of Lung Nodule Detection. Instead of using only one Deep Learning model, we combined the performance of two or more CNNs so they could perform and predict the outcome with more accuracy. The LUNA 16 Grand challenge dataset has been utilized, which is available online on their website. The dataset consists of a CT scan with annotations that better understand the data and information about each CT scan. Deep Learning works the same way our brain neurons work; therefore, deep learning is based on Artificial Neural Networks. An extensive CT scan dataset is collected to train the deep learning model. CNNs are prepared using the data set to classify cancerous and non-cancerous images. A set of training, validation, and testing datasets is developed, which is used by our Deep Ensemble 2D CNN. Deep Ensemble 2D CNN consists of three different CNNs with different layers, kernels, and pooling techniques. Our Deep Ensemble 2D CNN gave us a great result with 95% combined accuracy, which is higher than the baseline method.

Tissue-Specific microRNA Expression Profiling to Derive Novel Biomarkers for the Diagnosis and Subtyping of Small B-Cell Lymphomas

Accurate diagnosis of the most common histological subtypes of small B-cell lymphomas is challenging due to overlapping morphological features and limitations of ancillary testing, which involves a large number of immunostains and molecular investigations. In addition, a common diagnostic challenge is to distinguish reactive lymphoid hyperplasia that do not require additional stains from such lymphomas that need ancillary investigations. We investigated if tissue-specific microRNA (miRNA) expression may provide potential biomarkers to improve the pathology diagnostic workflow. This study seeks to distinguish reactive lymphoid proliferation (RL) from small B-cell lymphomas, and to further distinguish the four main subtypes of small B-cell lymphomas. Two datasets were included: a discovery cohort (n = 100) to screen for differentially expressed miRNAs and a validation cohort (n = 282) to develop classification models. The models were evaluated for accuracy in subtype prediction. MiRNA gene set enrichment was also performed to identify differentially regulated pathways. 306 miRNAs were detected and quantified, resulting in 90-miRNA classification models from which smaller panels of miRNAs biomarkers with good accuracy were derived. Bioinformatic analysis revealed the upregulation of known and other potentially relevant signaling pathways in such lymphomas. In conclusion, this study suggests that miRNA expression profiling may serve as a promising tool to aid the diagnosis of common lymphoid lesions.

Noncoding RNome as Enabling Biomarkers for Precision Health

Noncoding RNAs (ncRNAs), in the form of structural, catalytic or regulatory RNAs, have emerged to be critical effectors of many biological processes. With the advent of new technologies, we have begun to appreciate how intracellular and circulatory ncRNAs elegantly choreograph the regulation of gene expression and protein function(s) in the cell. Armed with this knowledge, the clinical utility of ncRNAs as biomarkers has been recently tested in a wide range of human diseases. In this review, we examine how critical factors govern the success of interrogating ncRNA biomarker expression in liquid biopsies and tissues to enhance our current clinical management of human diseases, particularly in the context of cancer. We also discuss strategies to overcome key challenges that preclude ncRNAs from becoming standard-of-care clinical biomarkers, including sample pre-analytics standardization, data cross-validation with closer attention to discordant findings, as well as correlation with clinical outcomes. Although harnessing multi-modal information from disease-associated noncoding RNome (ncRNome) in biofluids or in tissues using artificial intelligence or machine learning is at the nascent stage, it will undoubtedly fuel the community adoption of precision population health.

MicroRNAs as Potential Biomarkers in the Differential Diagnosis of Lipomatous Tumors and Their Mimics

Adipocytic tumors are the most common subtype of soft tissue tumors. In current clinical practice, distinguishing benign lipomas from well-differentiated liposarcomas (WDLPS), as well as dedifferentiated liposarcomas (DDLPS) from their morphologic mimics, remains a significant diagnostic challenge. This is especially so when examining small biopsy samples and without the aid of additional ancillary tests. Recognizing the important role that microRNAs (miRNAs) play in tumorigenesis and their potential utility in tumor classification, we analyzed routine clinical tissue samples of benign and malignant lipomatous tumors, as well as other sarcoma mimics, to identify distinguishing miRNA-based signatures that can aid in the differential diagnosis of these entities. We discovered a 6-miRNA signature that separated lipomas from WDLPS with high confidence (AUC of 0.963), as well as a separate 6-miRNA signature that distinguished DDLPS from their more aggressive histologic mimics (AUC of 0.740). Functional enrichment analysis unveiled possible mechanistic involvement of these predictive miRNAs in adipocytic cancer-related biological processes and pathways such as PI3K/AKT/mTOR and MAPK signaling, further supporting the relevance of these miRNAs as biomarkers for adipocytic tumors. Our results demonstrate that miRNA expression profiling may potentially be used as an adjunctive tool for the diagnosis of benign and malignant adipocytic tumors. Further validation studies are warranted.

CT Combined with Multiparameter MRI in Differentiating Pathological Subtypes of Non-Small-Cell Lung Cancer before Surgery

Objective

To investigate the diagnostic value of computed tomography (CT) combined with multiparametric magnetic resonance imaging (mpMRI) for preoperative differentiation of non-small-cell lung cancer (NSCLC).

Methods

CT and MRI imaging data were collected from all patients with squamous lung cancer and adenocarcinoma admitted to our hospital from June 2019 to December 2020 (286 cases). ROC curves were plotted to evaluate the performance of CT, mpMRI, and CT combined with mpMRI to differentiate pathological subtypes of NSCLC. Univariate and multivariate regression were used to be independent predictors of pathological subtypes of NSCLC.

Results

ROC curves showed that CT combined with mpMRI had the largest area under the curve, followed by mpMRI and CT successively. Univariate regression analysis showed that gender, smoking, tumor size, morphology, marginal lobulation, marginal burr, bronchial truncation sign, and vascular convergence sign were factors influencing the pathological subtype of NSCLC. Multivariate regression analysis suggested the fact that gender, tumor size, morphology, marginal lobulation, bronchial truncation, and vascular convergence sign are likely the independent predictors of NSCLC pathological subtypes.

Conclusions

CT combined with mpMRI can effectively distinguish NSCLC pathological subtypes, which is worthy of clinical application.

Unique circulating microRNA profiles in epidemic Kaposi's sarcoma

Background

Human herpesvirus 8 (HHV-8) causes Kaposi's sarcoma (KS). Kaposi sarcoma in HIV/AIDS patients is referred to as epidemic KS and is the most common HIV-related malignancy worldwide. The lack of a diagnostic assay to detect latent and early-stage disease has increased disease morbidity and mortality. Serum miRNAs have previously been used as potential biomarkers of normal physiology and disease. In the current study, we profiled unique serum miRNAs in patients with epidemic KS to generate baseline data to aid in developing a miRNA-based noninvasive biomarker assay for epidemic KS.

Methods

This was a comparative cross-sectional study involving 27 patients with epidemic KS and 27 HIV-positive adults with no prior diagnosis or clinical manifestation of KS. DNA and RNA were isolated from blood and serum collected from study participants. Nested PCR for circulating HHV-8 DNA was performed on the isolated DNA, whereas miRNA library preparation and sequencing for circulating miRNA were performed on the RNA samples. The miRge2 pipeline and EdgeR were used to analyse the sequencing data.

Results

Fifteen out of the 27 epidemic KS-positive subjects (55.6%) tested positive for HHV-8 DNA, whereas only 3 (11.1%) out of the 27 HIV-positive, KS-negative subjects tested positive for HHV-8 DNA. Additionally, we found a unique miRNA expression signature in 49 circulating miRNAs in epidemic KS subjects compared to subjects with no epidemic KS, with 41 miRNAs upregulated and 8 miRNAs downregulated. Subjects with latent KS infection had a differential upregulation of circulating miR-193a compared to HIV-positive, KS-negative subjects for whom circulating HHV-8 DNA was not detected. Further analysis of serum from epidemic KS patients revealed a miRNA signature according to KS tumor status and time since first HIV diagnosis.

Conclusions

This study reveals unique circulating miRNA profiles in the serum of patients with epidemic KS versus HIV-infected subjects with no KS, as well as in subjects with latent KS. Many of the dysregulated miRNAs in epidemic KS patients were previously reported to have crucial roles in KS infection and latency, highlighting their promising roles as potential biomarkers of latent or active KS infection.

SC-Dynamic R-CNN: A Self-Calibrated Dynamic R-CNN Model for Lung Cancer Lesion Detection

Lung cancer has complex biological characteristics and a high degree of malignancy. It has always been the number one “killer” in cancer, threatening human life and health. The diagnosis and early treatment of lung cancer still require improvement and further development. With high morbidity and mortality, there is an urgent need for an accurate diagnosis method. However, the existing computer-aided detection system has a complicated process and low detection accuracy. To solve this problem, this paper proposed a two-stage detection method based on the dynamic region-based convolutional neural network (Dynamic R-CNN). We divide lung cancer into squamous cell carcinoma, adenocarcinoma, and small cell carcinoma. By adding the self-calibrated convolution module into the feature network, we extracted more abundant lung cancer features and proposed a new regression loss function to further improve the detection performance of lung cancer. After experimental verification, the mAP (mean average precision) of the model can reach 88.1% on the lung cancer dataset and it performed particularly well with a high IoU (intersection over union) threshold. This method has a good performance in the detection of lung cancer and can improve the efficiency of doctors' diagnoses. It can avoid false detection and miss detection to a certain extent.

Alfaleh M, H. Abdulaal W, Bakhaidar RB, Alselami MO, Zahrani MAL, Alqarni HM, F. Alghaith A, Alshehri S, Badr-Eldin SM, Aldawsari HM, Al-hejaili OD, Aldhabi BM, Mahdi WA. Wasp venom peptide improves the proapoptotic activity of alendronate sodium in A549 lung cancer cells

BACKGROUND

Lung cancer in men and women is considered the leading cause for cancer-related mortality worldwide. Anti-cancer peptides represent a potential untapped reservoir of effective cancer therapy.

METHODOLOGY

Box-Behnken response surface design was applied for formulating Alendronate sodium (ALS)-mastoparan peptide (MP) nanoconjugates using Design-Expert software. The optimization process aimed at minimizing the size of the prepared ALS-MP nanoconjugates. ALS-MP nanoconjugates' particle size, encapsulation efficiency and the release profile were determined. Cytotoxicity, cell cycle, annexin V staining and caspase 3 analyses on A549 cells were carried out for the optimized formula.

RESULTS

The results revealed that the optimized formula was of 134.91±5.1 nm particle size. The novel ALS-MP demonstrated the lowest IC50 (1.3 ± 0.34 μM) in comparison to ALS-Raw (37.6 ± 1.79 μM). Thus, the results indicated that when optimized ALS-MP nanoconjugate was used, the IC50 of ALS was also reduced by half. Cell cycle analysis demonstrated a significantly higher percentage of cells in the G2-M phase following the treatment with optimized ALS-MP nanoconjugates.

CONCLUSION

The optimized ALS-MP formula had significantly improved the parameters related to the cytotoxic activity towards A549 cells, compared to control, MP and ALS-Raw.

Using bioinformatics approaches to identify survival-related oncomiRs as potential targets of miRNA-based treatments for lung adenocarcinoma

Lung cancer is a major cause of cancer-associated deaths worldwide, and lung adenocarcinoma (LUAD) is the most common lung cancer subtype. Micro RNAs (miRNAs) regulate the pattern of gene expression in multiple cancer types and have been explored as potential drug development targets. To develop an oncomiR-based panel, we identified miRNA candidates that show differential expression patterns and are relevant to the worse 5-year overall survival outcomes in LUAD patient samples. We further evaluated various combinations of miRNA candidates for association with 5-year overall survival and identified a four-miRNA panel: miR-9-5p, miR-1246, miR-31-3p, and miR-3136-5p. The combination of these four miRNAs outperformed any single miRNA for predicting 5-year overall survival (hazard ratio [HR]: 3.47, log-rank p-value = 0.000271). Experiments were performed on lung cancer cell lines and animal models to validate the effects of these miRNAs. The results showed that singly transfected antagomiRs largely inhibited cell growth, migration, and invasion, and the combination of all four antagomiRs considerably reduced cell numbers, which is twice as effective as any single miRNA-targeted transfected. The in vivo studies revealed that antagomiR-mediated knockdown of all four miRNAs significantly reduced tumor growth and metastatic ability of lung cancer cells compared to the negative control group. The success of these in vivo and in vitro experiments suggested that these four identified oncomiRs may have therapeutic potential.

Diagnostic, Predictive, and Prognostic Biomarkers in Non-Small Cell Lung Cancer (NSCLC) Management

Lung cancer is the leading cause of cancer-related deaths worldwide. Despite growing efforts for its early detection by screening populations at risk, the majority of lung cancer patients are still diagnosed in an advanced stage. The management of lung cancer has dramatically improved in the last decade and is no longer based on the "one-fits-all" paradigm or the general histological classification of non-small cell versus small cell lung cancer. Emerging options of targeted therapies and immunotherapies have shifted the management of lung cancer to a more personalized treatment approach, significantly influencing the clinical course and outcome of the disease. Molecular biomarkers have emerged as valuable tools in the prognosis and prediction of therapy response. In this review, we discuss the relevant biomarkers used in the clinical management of lung tumors, from diagnosis to prognosis. We also discuss promising new biomarkers, focusing on non-small cell lung cancer as the most abundant type of lung cancer.

Role of microRNAs in regulating cell proliferation, metastasis and chemoresistance and their applications as cancer biomarkers in small cell lung cancer

Small cell lung cancer (SCLC), a smoking-related highly aggressive neuroendocrine cancer, is characterized by rapid cell proliferation, early metastatic dissemination, and early relapse due to chemoresistance to first-line platinum-doublet chemotherapy. Genomically, SCLC tumors show nearly universal loss of TP53 and RB1 tumor suppressor genes, while gene expression signature classifies them into 4 distinct subgroups based on the expression patterns of lineage transcription factors - ASCL1/ASH1, NEUROD1, YAP-1, and POU2F3. Due to the lack of targetable molecular alterations and clinically useful diagnostic, prognostic and predictive biomarker, there is insignificant progress in the therapeutic management of SCLC patients. Numerous studies have shown a significant involvement of non-coding RNAs in the regulation of cell proliferation, invasion and migration, apoptosis, metastasis, and chemoresistance in various human cancers. In this review, we comprehensively discuss the role of microRNAs (miRNAs) in regulating the aforementioned biological process in SCLC. For this, we searched the scientific literature and selected studies that have evaluated the role of miRNAs in the disease pathogenesis or as a cancer biomarker in SCLC. Our review suggests that several miRNAs are involved in the pathogenesis of SCLC mainly by regulating cell proliferation, metastasis, and chemoresistance. Few studies have also demonstrated the clinical utility of miRNAs in monitoring response to chemotherapy as well as in predicting survival outcomes. However, more in-depth mechanistic studies utilizing in vivo models and multicentric studies with larger patient cohorts are needed before the applications of miRNAs as therapeutic targets or as biomarkers are translated from the laboratory into clinics.

Circulating Biomarkers for Early Stage Non-Small Cell Lung Carcinoma Detection: Supplementation to Low-Dose Computed Tomography

Lung cancer is currently the leading cause of cancer death in both developing and developed countries. Given that lung cancer has poor prognosis in later stages, it is essential to achieve an early diagnosis to maximize patients’ overall survival. Non-small cell lung cancer (NSCLC) is the most common form of primary lung cancer in both smokers and non-smokers. The current standard screening method, low‐dose computed tomography (LDCT), is the only radiological method that demonstrates to have mortality benefits across multiple large randomized clinical trials (RCT). However, these RCTs also found LDCT to have a significant false positive rate that results in unnecessary invasive biopsies being performed. Due to the lack of both sensitive and specific screening methods for the early detection of lung cancer, there is an urgent need for alternative minimally or non-invasive biomarkers that may provide diagnostic, and/or prognostic information. This has led to the identification of circulating biomarkers that can be readily detectable in blood and have been extensively studied as prognosis markers. Circulating microRNA (miRNA) in particular has been investigated for these purposes as an augmentation to LDCT, or as direct diagnosis of lung cancer. There is, however, a lack of consensus across the studies on which miRNAs are the most clinically useful. Besides miRNA, other potential circulating biomarkers include circulating tumor cells (CTCs), circulating tumor DNA (ctDNAs) and non-coding RNAs (ncRNAs). In this review, we provide the current outlook of several of these biomarkers for the early diagnosis of NSCLC.

3D Bioprinted cancer models: Revolutionizing personalized cancer therapy

After cardiovascular disease, cancer is the leading cause of death worldwide with devastating health and economic consequences, particularly in developing countries. Inter-patient variations in anti-cancer drug responses further limit the success of therapeutic interventions. Therefore, personalized medicines approach is key for this patient group involving molecular and genetic screening and appropriate stratification of patients to treatment regimen that they will respond to. However, the knowledge related to adequate risk stratification methods identifying patients who will respond to specific anti-cancer agents is still lacking in many cancer types. Recent advancements in three-dimensional (3D) bioprinting technology, have been extensively used to generate representative bioengineered tumor in vitro models, which recapitulate the human tumor tissues and microenvironment for high-throughput drug screening. Bioprinting process involves the precise deposition of multiple layers of different cell types in combination with biomaterials capable of generating 3D bioengineered tissues based on a computer-aided design. Bioprinted cancer models containing patient-derived cancer and stromal cells together with genetic material, extracellular matrix proteins and growth factors, represent a promising approach for personalized cancer therapy screening. Both natural and synthetic biopolymers have been utilized to support the proliferation of cells and biological material within the personalized tumor models/implants. These models can provide a physiologically pertinent cell-cell and cell-matrix interactions by mimicking the 3D heterogeneity of real tumors. Here, we reviewed the potential applications of 3D bioprinted tumor constructs as personalized in vitro models in anticancer drug screening and in the establishment of precision treatment regimens.

Clinico-Pathological Importance of miR-146a in Lung Cancer

Lung cancer is a well-known malignant tumor of the respiratory tract, which has caused a significant level of damage to human health in the 21st century. Micro-RNAs (miRNAs) are tiny, non-coding RNA stem-loop structures with a length of roughly 20–25 nucleotides that function as powerful modulators of mRNA and protein products of a gene. miRNAs may modulate many biological processes involving growth, differentiation, proliferation, and cell death and play a key role in the pathogenesis of various types of malignancies. Several accumulating pieces of evidence have proven that miRNA, especially miR-146a, are crucial modulators of innate immune response sequences. A novel and exciting cancer research field has involved miRNA for the detection and suppression of cancer. However, the actual mechanism which is adopted by these miRNA is still unclear. miRNAs have been used as a cancer-associated biomarker in several studies, suggesting their altered expression in various cancers compared to the normal cells. The amount of expression of miRNA can also be used to determine the stage of the disease, aiding in early detection. In breast, pancreatic, and hepatocellular carcinoma, and gastric cancer, cancer cell proliferation and metastasis has been suppressed by miR-146a. Changes in miR-146a expression levels have biomarker importance and possess a high potential as a therapeutic target in lung cancer. It retards epithelial-mesenchymal transition and promotes the therapeutic action of anticancer agents in lung cancer. Studies have also suggested that miR-146a affects gene expression through different signaling pathways viz. TNF-α, NF-κB and MEK-1/2, and JNK-1/2. Further research is required for understanding the molecular mechanisms of miR-146a in lung cancer. The potential role of miR-146a as a diagnostic marker of lung cancer must also be analyzed. This review summarizes the tumor-suppressing, anti-inflammatory, and antichemoresistive nature of miR-146a in lung cancer.

Clinical Utility of microRNAs in Exhaled Breath Condensate as Biomarkers for Lung Cancer

This study represents a novel proof of concept of the clinical utility of miRNAs from exhaled breath condensate (EBC) as biomarkers of lung cancer (LC). Genome-wide miRNA profiling and machine learning analysis were performed on EBC from 21 healthy volunteers and 21 LC patients. The levels of 12 miRNAs were significantly altered in EBC from LC patients where a specific signature of miR-4507, miR-6777-5p and miR-451a distinguished these patients with high accuracy. Besides, a distinctive miRNA profile between LC adenocarcinoma and squamous cell carcinoma was observed, where a combined panel of miR-4529-3p, miR-8075 and miR-7704 enabling discrimination between them. EBC levels of miR-6777-5p, 6780a-5p and miR-877-5p predicted clinical outcome at 500 days. Two additional miRNA signatures were also associated with other clinical features such as stage and invasion status. Dysregulated EBC miRNAs showed potential target genes related to LC pathogenesis, including CDKN2B, PTEN, TP53, BCL2, KRAS and EGFR. We conclude that EBC miRNAs might allow the identification, stratification and monitorization of LC, which could lead to the development of precision medicine in this and other respiratory diseases.

Circulating microRNAs: Biomarkers of disease

MicroRNAs are a class of endogenous noncoding single-stranded RNA molecules with approximately 20-24 nucleotides and are associated with a broad range of biological processes. Researchers found that microRNAs are abundant in tissues, and more importantly, there are also trace circulating microRNAs that exist in biological fluids. In recent years, circulating microRNAs had emerged as promising diagnostic and prognostic biomarkers for the noninvasive detection of diseases with high specificity and sensitivity. More importantly, specific microRNA expression signatures reflect not only the existence of early-stage diseases but also the dynamic development of advanced-stage diseases, disease prognosis prediction, and drug resistance. To date, an increasing number of potential miRNA biomarkers have been reported, but their practical application prospects are still unclear. Therefore, microRNAs, as potential diagnostic and prognostic biomarkers in a variety of diseases, need to be updated, as they are of great importance in the diagnosis, prognosis and prediction of therapeutic responses. In this review, we summary our current understanding of microRNAs as potential biomarkers in the major diseases (e.g., cancers and cardio-cerebrovascular diseases), which provide the basis for the design of diagnosis and treatment plan and the improvement of the cure rate.

Current Status and Future Perspectives of Liquid Biopsy in Small Cell Lung Cancer

Approximately 19% of all cancer-related deaths are due to lung cancer, which is the leading cause of mortality worldwide. Small cell lung cancer (SCLC) affects approximately 15% of patients diagnosed with lung cancer. SCLC is characterized by aggressiveness; the majority of SCLC patients present with metastatic disease, and less than 5% of patients are alive at 5 years. The gold standard of SCLC treatment is platinum and etoposide-based chemotherapy; however, its effects are short. In recent years, treatment for SCLC has changed; new drugs have been approved, and new biomarkers are needed for treatment selection. Liquid biopsy is a non-invasive, rapid, repeated and alternative tool to the traditional tumor biopsy that could allow the most personalized medicine into the management of SCLC patients. Circulating tumor cells (CTCs) and cell-free DNA (cfDNA) are the most commonly used liquid biopsy biomarkers. Some studies have reported the prognostic factors of CTCs and cfDNA in SCLC patients, independent of the stage. In this review, we summarize the recent SCLC studies of CTCs, cfDNA and other liquid biopsy biomarkers, and we discuss the future utility of liquid biopsy in the clinical management of SCLC.

Classifying Lung Neuroendocrine Neoplasms through MicroRNA Sequence Data Mining

Lung neuroendocrine neoplasms (NENs) can be challenging to classify due to subtle histologic differences between pathological types. MicroRNAs (miRNAs) are small RNA molecules that are valuable markers in many neoplastic diseases. To evaluate miRNAs as classificatory markers for lung NENs, we generated comprehensive miRNA expression profiles from 14 typical carcinoid (TC), 15 atypical carcinoid (AC), 11 small cell lung carcinoma (SCLC), and 15 large cell neuroendocrine carcinoma (LCNEC) samples, through barcoded small RNA sequencing. Following sequence annotation and data preprocessing, we randomly assigned these profiles to discovery and validation sets. Through high expression analyses, we found that miR-21 and -375 are abundant in all lung NENs, and that miR-21/miR-375 expression ratios are significantly lower in carcinoids (TC and AC) than in neuroendocrine carcinomas (NECs; SCLC and LCNEC). Subsequently, we ranked and selected miRNAs for use in miRNA-based classification, to discriminate carcinoids from NECs. Using miR-18a and -155 expression, our classifier discriminated these groups in discovery and validation sets, with 93% and 100% accuracy. We also identified miR-17, -103, and -127, and miR-301a, -106b, and -25, as candidate markers for discriminating TC from AC, and SCLC from LCNEC, respectively. However, these promising findings require external validation due to sample size.

Kinetic and thermodynamic insights into interaction of erlotinib with epidermal growth factor receptor: Surface plasmon resonance and molecular docking approaches

Epidermal growth factor receptor (EGFR) plays an important role in cell proliferation at non-small cell lung cancer (NSCLC). Therefore, targeted therapy of cancer via this kind of receptor is highly interested. Small molecule drugs such as erlotinib and gefitinib inhibit EGFR tyrosine kinase and thus suppress cell proliferation. At this paper, erlotinib interaction with EGFR on the cell surface was studied via surface plasmon resonance (SPR) and molecular docking methods. Kinetic parameters indicated that erlotinib affinity toward EGFR was increased through increment of temperature. The thermodynamic analysis showed that van der Waals and hydrogen binding forces play a major role in the interaction of erlotinib with EGFR. Docking results showed that Domain II in EGFR has role in the interaction with erlotinib. Besides, the binding energy for this interaction was -10.7 kcal/mol, which is suitable for binding of erlotinib to Domain II in EGFR.

miRNAs in drug response variability: potential utility as biomarkers for personalized medicine

MicroRNAs (miRNAs) are 18-22 nucleotide RNA molecules that modulate the expression of multiple protein-encoding genes at the post-transcriptional level. Almost all physiological conditions are probably modulated by miRNAs, including pharmacological response. Indeed, acting on the regulation of numerous genes involved in the pharmacokinetics and pharmacodynamics of drugs, differences in the levels of circulating miRNAs or genetic variants in the sequences of the miRNA genes can contribute to interindividual variability in drug response, both in terms of toxicity and efficacy. For their stability in body fluids and the easy availability and accurate quantification, miRNAs could be ideal biomarkers of individual response to drugs. This review aims to give an overview on the available studies that have investigated the relationship between miRNAs and response to drugs in different classes of diseases and considered their possible clinical application as therapy response predictive biomarkers. A comprehensive search was conducted from the international web database PubMed. We included papers that investigated the relationship between miRNAs and response to drugs, published before January 2019.

MicroRNAs (miRNAs) and Long Non-Coding RNAs (lncRNAs) as New Tools for Cancer Therapy: First Steps from Bench to Bedside

Non-coding RNAs represent a significant proportion of the human genome. After having been considered as 'junk' for a long time, non-coding RNAs are now well established as playing important roles in maintaining cellular homeostasis and functions. Some non-coding RNAs show cell- and tissue-specific expression patterns and are specifically deregulated under pathological conditions (e.g. cancer). Therefore, non-coding RNAs have been extensively studied as potential biomarkers in the context of different diseases with a focus on microRNAs (miRNAs) and long non-coding RNAs (lncRNAs) for several years. Since their discovery, miRNAs have attracted more attention than lncRNAs in research studies; however, both families of non-coding RNAs have been established to play an important role in gene expression control, either as transcriptional or post-transcriptional regulators. Both miRNAs and lncRNAs can regulate key genes involved in the development of cancer, thus influencing tumour growth, invasion, and metastasis by increasing the activation of oncogenic pathways and limiting the expression of tumour suppressors. Furthermore, miRNAs and lncRNAs are also emerging as important mediators in drug-sensitivity and drug-resistance mechanisms. In the light of these premises, a number of pre-clinical and early clinical studies are exploring the potential of non-coding RNAs as new therapeutics. The aim of this review is to summarise the latest knowledge of the use of miRNAs and lncRNAs as therapeutic tools for cancer treatment.

Differential expression of microRNA in serum fractions and association of Argonaute 1 microRNAs with heart failure

The serum or plasma microRNA (miRNA) molecules have been suggested as diagnostic and prognostic biomarkers, in various pathological conditions. However, these molecules are also found in different serum fractions, such as exosomes and Argonaute (Ago) protein complexes. Ago1 is the predominant Ago protein expressed in heart tissue. The objective of the study was to examine the hypothesis that Ago1‐associated miRNAs may be more relevant to cardiac disease and heart failure compared with the serum. In total, 84 miRNA molecules were screened for their expression in the whole serum, exosomes and Ago1, and Ago2 complexes. Ago1‐bound miR‐222‐3p, miR‐497‐5p and miR‐21‐5p were significantly higher, and let‐7a‐5p was significantly lower in HF patients compared with healthy controls, whereas no such difference was observed for those markers in the serum samples among the groups. A combination of these 4 miRNAs into an Ago1‐HF score provided a ROC curve with an AUC of 1, demonstrating clear discrimination between heart failure patients and healthy individuals. Ago1 fraction might be a better and more specific platform for identifying HF‐related miRNAs compared with the whole serum.

Early detection of the major male cancer types in blood-based liquid biopsies using a DNA methylation panel

BACKGROUND

Lung (LC), prostate (PCa) and colorectal (CRC) cancers are the most incident in males worldwide. Despite recent advances, optimal population-based cancer screening methods remain an unmet need. Due to its early onset, cancer specificity and accessibility in body fluids, aberrant DNA promoter methylation might be a valuable minimally invasive tool for early cancer detection. Herein, we aimed to develop a minimally invasive methylation-based test for simultaneous early detection of LC, PCa and CRC in males, using liquid biopsies.

RESULTS

Circulating cell-free DNA was extracted from 102 LC, 121 PCa and 100 CRC patients and 136 asymptomatic donors' plasma samples. Sodium-bisulfite modification and whole-genome amplification was performed. Promoter methylation levels of APC_me, FOXA1_me, GSTP1_me, HOXD3_me, RARβ2_me, RASSF1A_me, SEPT9_me and SOX17_me were assessed by multiplex quantitative methylation-specific PCR. SEPT9_me and SOX17_me were the only biomarkers shared by all three cancer types, although they detected CRC with limited sensitivity. A "PanCancer" panel (FOXA1_me, RARβ2_me and RASSF1A_me) detected LC and PCa with 64% sensitivity and 70% specificity, complemented with "CancerType" panel (GSTP1_me and SOX17_me) which discriminated between LC and PCa with 93% specificity, but with modest sensitivity. Moreover, a HOXD3_me and RASSF1A_me panel discriminated small cell lung carcinoma from non-small cell lung carcinoma with 75% sensitivity, 88% specificity, 6.5 LR+ and 0.28 LR-. An APC_me and RASSF1A_me panel independently predicted disease-specific mortality in LC patients.

CONCLUSIONS

We concluded that a DNA methylation-based test in liquid biopsies might enable minimally invasive screening of LC and PCa, improving patient compliance and reducing healthcare costs. Moreover, it might assist in LC subtyping and prognostication.

Circulating miRNAs as Biomarker in Cancer

Deregulation of microRNA expression has been shown to play an important role in human malignancies. The identification of circulating-free miRNAs in biofluids a decade ago led to great enthusiasm and motivation to develop non-invasive tests based on the expression of these small non-coding RNAs. Herein, we review the progress within the field of research for identifying circulating miRNA cancer biomarkers and discuss the advantages and challenges associated with this. We also discuss the methodological and analytical variables, which may influence the final miRNA quantification and the importance of standardizing pre-analytical, analytical, and post-analytical processes in order to enable a successful translation of the results from basic research into the clinics.

Subtyping Lung Cancer Using DNA Methylation in Liquid Biopsies

BACKGROUND

Lung cancer (LCa) is the most frequently diagnosed and lethal cancer worldwide. Histopathological subtyping, which has important therapeutic and prognostic implications, requires material collection through invasive procedures, which might be insufficient to enable definitive diagnosis. Aberrant DNA methylation is an early event in carcinogenesis, detectable in circulating cell-free DNA (ccfDNA). Herein, we aimed to assess methylation of selected genes in ccfDNA from LCa patients and determine its accuracy for tumor subtyping.

METHODS

Methylation levels of APC, HOXA9, RARβ2, and RASSF1A were assessed in three independent study groups (study group #1: 152 tissue samples; study group #2: 129 plasma samples; study group #3: 28 benign lesions of lung) using quantitative methylation-specific PCR. Associations between gene promoter methylation levels and LCa subtypes were evaluated using non-parametric tests. Receiver operating characteristic (ROC) curve analysis was performed.

RESULTS

In study group #2, HOXA9 and RASSF1A displayed higher methylation levels in small-cell lung cancer (SCLC) than in non-small-cell lung cancer (NSCLC). HOXA9 displayed high sensitivity (63.8%), whereas RASSF1A disclosed high specificity (96.2%) for SCLC detection in ccfDNA. Furthermore, HOXA9 methylation levels showed to be higher in squamous cell carcinoma in comparison with adenocarcinoma in study group #1.

CONCLUSIONS

Methylation level assessments in ccfDNA may provide a minimally invasive procedure for LCa subtyping, complementing standard diagnostic procedures.

Identification of potential biomarkers for diagnosis of pancreatic and biliary tract cancers by sequencing of serum microRNAs

BACKGROUND

Pancreatic and biliary tract cancer (PC and BTC, respectively) are difficult to diagnose because of their clinical characteristics; however, recent studies suggest that serum microRNAs (miRNAs) might be the key to developing more efficient diagnostic methods for these cancers.

METHODS

We analysed the genome-wide expression of serum miRNAs in PC and BTC patients to identify novel biomarker candidates using high-throughput sequencing and experimentally validated miRNAs on clinical samples.

RESULTS

Statistical and classification analysis of the serum miRNA-expression profiles of 55 patient samples showed distinguishable patterns between cancer patients and healthy controls; however, we were unable to distinguish the two cancers. We found that three of the highest performing miRNAs were capable of distinguishing cancer patients from controls, with an accuracy of 92.7%. Additionally, dysregulation of these three cancer-specific miRNAs was demonstrated in an independent sample group by quantitative reverse transcription polymerase chain reaction.

CONCLUSIONS

These results suggested three candidate serum miRNAs (mir-744-5p, mir-409-3p, and mir-128-3p) as potential biomarkers for PC and BTC diagnosis.

MicroRNA amplification and detection technologies: opportunities and challenges for point of care diagnostics

The volume of point of care (POC) testing continues to grow steadily due to the increased availability of easy-to-use devices, thus making it possible to deliver less costly care closer to the patient site in a shorter time relative to the central laboratory services. A novel class of molecules called microRNAs have recently gained attention in healthcare management for their potential as biomarkers for human diseases. The increasing interest of miRNAs in clinical practice has led to an unmet need for assays that can rapidly and accurately measure miRNAs at the POC. However, the most widely used methods for analyzing miRNAs, including Northern blot-based platforms, in situ hybridization, reverse transcription qPCR, microarray, and next-generation sequencing, are still far from being used as ideal POC diagnostic tools, due to considerable time, expertize required for sample preparation, and in terms of miniaturizations making them suitable platforms for centralized labs. In this review, we highlight various existing and upcoming technologies for miRNA amplification and detection with a particular emphasis on the POC testing industries. The review summarizes different miRNA targets and signals amplification-based assays, from conventional methods to alternative technologies, such as isothermal amplification, paper-based, oligonucleotide-templated reaction, nanobead-based, electrochemical signaling- based, and microfluidic chip-based strategies. Based on critical analysis of these technologies, the possibilities and feasibilities for further development of POC testing for miRNA diagnostics are addressed and discussed.

The Roles of MicroRNA in Lung Cancer

Lung cancer is the most devastating malignancy in the world. Beyond genetic research, epigenomic studies—especially investigations of microRNAs—have grown rapidly in quantity and quality in the past decade. This has enriched our understanding about basic cancer biology and lit up the opportunities for potential therapeutic development. In this review, we summarize the involvement of microRNAs in lung cancer carcinogenesis and behavior, by illustrating the relationship to each cancer hallmark capability, and in addition, we briefly describe the clinical applications of microRNAs in lung cancer diagnosis and prognosis. Finally, we discuss the potential therapeutic use of microRNAs in lung cancer.

Prognostic and Predictive Epigenetic Biomarkers in Oncology

Epigenetic patterns, such as DNA methylation, histone modifications, and non-coding RNAs, can be both driver factors and characteristic features of certain malignancies. Aberrant DNA methylation can lead to silencing of crucial tumor suppressor genes or upregulation of oncogene expression. Histone modifications and chromatin spatial organization, which affect transcription, regulation of gene expression, DNA repair, and replication, have been associated with multiple tumors. Certain microRNAs (miRNAs), mainly those that silence tumor suppressor genes and occur in a greater number of copies, have also been shown to promote oncogenesis. Multiple patterns of these epigenetic factors occur specifically in certain malignancies, which allows their potential use as biomarkers. This review presents examples of tests for each group of epigenetic factors that are currently available or in development for use in early cancer detection, prediction, prognosis, and response to treatment. The availability of blood-based biomarkers is noted, as they allow sampling invasiveness to be reduced and the sampling procedure to be simplified. The article stresses the role of epigenetics as a crucial element of future cancer diagnostics and therapy.

Cell-Free DNA Methylation of Selected Genes Allows for Early Detection of the Major Cancers in Women

Background: Breast (BrC), colorectal (CRC) and lung (LC) cancers are the three most common and deadly cancers in women. Cancer screening entails an increase in early stage disease detection but is hampered by high false-positive rates and overdiagnosis/overtreatment. Aberrant DNA methylation occurs early in cancer and may be detected in circulating cell-free DNA (ccfDNA), constituting a valuable biomarker and enabling non-invasive testing for cancer detection. We aimed to develop a ccfDNA methylation-based test for simultaneous detection of BrC, CRC and LC. Methods: CcfDNA from BrC, CRC and LC patients and asymptomatic controls were extracted from plasma, sodium-bisulfite modified and whole-genome amplified. APC, FOXA1, MGMT, RARβ2, RASSF1A, SCGB3A1, SEPT9, SHOX2 and SOX17 promoter methylation levels were determined by multiplex quantitative methylation-specific PCR. Associations between methylation and standard clinicopathological parameters were assessed. Biomarkers’ diagnostic performance was also evaluated. Results: A “PanCancer” panel (APC, FOXA1, RASSF1A) detected the three major cancers with 72% sensitivity and 74% specificity, whereas a “CancerType” panel (SCGB3A1, SEPT9 and SOX17) indicated the most likely cancer topography, with over 80% specificity, although with limited sensitivity. Conclusions: CcfDNA’s methylation assessment allows for simultaneous screening of BrC, CRC and LC, complementing current modalities, perfecting cancer suspects’ triage, increasing compliance and cost-effectiveness.

Circulating Serum miRNA-205 as a Diagnostic Biomarker for Ototoxicity in Mice Treated with Aminoglycoside Antibiotics

Background: To confirm levels and detection timing of circulating microRNAs (miRNAs) in the serum of a mouse model for diagnosis of ototoxicity, circulating miR-205 in the serum was evaluated to reflect damages in the cochlear microstructure and compared to a kidney injury model. Method: A microarray for miRNAs in the serum was performed to assess the ototoxic effects of kanamycin-furosemide. Changes in the levels for the selected miRNAs (miR-205, miR-183, and miR-103) were compared in the serum and microstructures of the cochlea (stria vascularis, organ of Corti, and modiolus) between the ototoxicity and normal mouse groups. An acute kidney injury (AKI) mouse model was used to assess changes in miR-205 levels in the kidney by ototoxic drugs. Results: In the mouse model for ototoxicity, the serum levels of circulating miR-205 peaked on day 3 and were sustained from days 7–14. Furthermore, miR-205 expression was highly expressed in the organ of Corti at day 5, continued to be expressed in the modiolus at high levels until day 14, and was finally also in the stria vascularis. The serum miR-205 in the AKI mice did not change significantly compared to the normal group. Conclusions Circulating miR-205 from the cochlea, after ototoxic damage, migrates through the blood vessels to organs, which is then finally found in blood. In conditions of hearing impairment with ototoxic medications, detection of circulating miR-205 in the blood can be used to determine the extent of hearing loss. In the future, inner ear damage can be identified by simply performing a blood test before the hearing impairment due to ototoxic drugs.

Epigenetic biomarkers: Current strategies and future challenges for their use in the clinical laboratory

Epigenetic modifications and regulators represent potential molecular elements which control relevant physiological and pathological features, thereby contributing to the natural history of human disease. These epigenetic modulators can be employed as disease biomarkers, since they show several advantages and provide information about gene function, thus explaining differences among patient endophenotypes. In addition, epigenetic biomarkers can incorporate information regarding the effects of the environment and lifestyle on health and disease, and monitor the effect of applied therapies. Technologies used to analyze these epigenetic biomarkers are constantly improving, becoming much easier to use. Laboratory professionals can easily acquire experience and techniques are becoming more affordable. A high number of epigenetic biomarker candidates are being continuously proposed, making now the moment to adopt epigenetics in the clinical laboratory and convert epigenetic marks into reliable biomarkers. In this review, we describe some current promising epigenetic biomarkers and technologies being applied in clinical practice. Furthermore, we will discuss some laboratory strategies and kits to accelerate the adoption of epigenetic biomarkers into clinical routine. The likelihood is that over time, better markers will be identified and will likely be incorporated into future multi-target assays that might help to optimize its application in a clinical laboratory. This will improve cost-effectiveness, and consequently encourage the development of theragnosis and the application of precision medicine.

Molecular strategies in the management of bronchopulmonary and thymic neuroendocrine neoplasms

Thoracic NETs [bronchopulmonary NETs (BPNETs) and thymic NETs (TNET)] share a common anatomic primary location, likely a common cell of origin, the "Kulchitsky cell" and presumably, a common etiopathogenesis. Although they are similarly grouped into well-differentiated [typical carcinoids (TC) and atypical carcinoids (AC)] and poorly differentiated neoplasms and both express somatostatin receptors, they exhibit a wide variation in clinical behavior. TNETs are more aggressive, are frequently metastatic, and have a lower 5-year survival rate (~50% vs. ~80%) than BPNETs. They are typically symptomatic, most often secreting ACTH (40% of tumors) but both tumor groups share secretion of common biomarkers including chromogranin A and 5-HIAA. Consistently effective and accurate circulating biomarkers are, however, currently unavailable. Surgery is the primary therapeutic tool for both BPNET and TNETs but there remains little consensus about later interventions e.g., targeted therapy, or how these can be monitored. Genetic analyses have identified different topographies (e.g., significant alterations in chromatin and epigenetic remodeling in BPNETs versus frequent chromosomal abnormalities in TNETs) but there is an absence of clinically actionable mutations in both tumor groups. Liquid biopsies, tools that can measure neoplastic signatures in peripheral blood, can potentially be leveraged to detect disease early i.e., recurrence, predict tumors that may respond to specific therapies and serve as real-time monitors for treatment responses. Recent studies have identified that mRNA transcript analysis in blood effectively identifies both BPNET and TNETs. The clinical utility of this gene expression assay includes use as a diagnostic, confirmation of completeness of surgical resection and use as a molecular management tool to monitor efficacy of PRRT and other therapeutic strategies.

Downregulation of miR-221-3p and upregulation of its target gene PARP1 are prognostic biomarkers for triple negative breast cancer patients and associated with poor prognosis

The purpose of this study was to identify microRNAs (miRNAs) closely associated with the prognosis of triple-negative breast cancer (TNBC) and their possible targets. This study recruited 125 early-stage TNBC patients, including 40 cases in the experimental group (20 cases with poor prognoses vs. 20 cases with good prognoses) and 85 cases in the validation group (27 cases with poor prognoses vs. 58 cases with good prognoses). In the experimental group, miRNA microarray showed 34 differentially expressed miRNAs in patients with different prognoses. We selected 5 miRNAs for validation. The differential expression of miR-221-3p was further verified in the experimental and validation groups using real-time polymerase chain reaction (PCR). High miR-221-3p expression was associated with better 5-year disease-free survival (DFS) (HR = 0.480; 95% CI, 0.263-0.879; p = 0.017) of TNBC patients. High expression of its target gene PARP1 predicted poorer 5-year DFS (HR = 2.236, 95% CI, 1.209-4.136, p = 0.010). MiR-221-3p down-regulated PARP1 by targeting its 3'-untranslated region. In conclusion, low miR-221-3p expression may contribute to the poor outcome of TNBC patients through regulating PARP1. MiR-221-3p likely plays a role as a PARP1 inhibitor by directly regulating PARP1 expression, thereby affecting the prognoses of TNBC patients.

Genome-wide copy number variation pattern analysis and a classification signature for non-small cell lung cancer

The accurate classification of non-small cell lung carcinoma (NSCLC) into lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC) is essential for both clinical practice and lung cancer research. Although the standard WHO diagnosis of NSCLC on biopsy material is rapid and economic, more than 13% of NSCLC tumors in the USA are not further classified. The purpose of this study was to analyze the genome-wide pattern differences in copy number variations (CNVs) and to develop a CNV signature as an adjunct test for the routine histopathologic classification of NSCLCs. We investigated the genome-wide CNV differences between these two tumor types using three independent patient datasets. Approximately half of the genes examined exhibited significant differences between LUAD and LUSC tumors and the corresponding non-malignant tissues. A new classifier was developed to identify signature genes out of 20 000 genes. Thirty-three genes were identified as a CNV signature of NSCLC. Using only their CNV values, the classification model separated the LUADs from the LUSCs with an accuracy of 0.88 and 0.84, respectively, in the training and validation datasets. The same signature also classified NSCLC tumors from their corresponding non-malignant samples with an accuracy of 0.96 and 0.98, respectively. We also compared the CNV patterns of NSCLC tumors with those of histologically similar tumors arising at other sites, such as the breast, head, and neck, and four additional tumors. Of greater importance, the significant differences between these tumors may offer the possibility of identifying the origin of tumors whose origin is unknown.

Non-coding RNAs: the cancer genome dark matter that matters!

Protein-coding genes comprise only 3% of the human genome, while the genes that are transcribed into RNAs but do not code for proteins occupy majority of the genome. Once considered as biological darker matter, non-coding RNAs are now being recognized as critical regulators in cancer genome. Among the many types of non-coding RNAs, microRNAs approximately 20 nucleotides in length are best characterized and their mechanisms of action are well generalized. microRNA exerts oncogenic or tumor suppressor function by regulation of protein-coding genes via sequence complementarity. The expression of microRNA is aberrantly regulated in all cancer types, and both academia and biotech companies have been keenly pursuing the potential of microRNA as cancer biomarker for early detection, prognosis, and therapeutic response. The key involvement of microRNAs in cancer also prompted interest on exploration of therapeutic values of microRNAs as anticancer drugs and drug targets. MRX34, a liposome-formulated miRNA-34 mimic, developed by Mirna Therapeutics, becomes the first microRNA therapeutic entering clinical trial for the treatment of hepatocellular carcinoma, renal cell carcinoma, and melanoma. In this review, we presented a general overview of microRNAs in cancer biology, the potential of microRNAs as cancer biomarkers and therapeutic targets, and associated challenges.

A prediction model for distinguishing lung squamous cell carcinoma from adenocarcinoma

Accurate classification of squamous cell carcinoma (SCC) from adenocarcinoma (AC) of non–small cell lung cancer (NSCLC) can lead to personalized treatments of lung cancer. We aimed to develop a miRNA-based prediction model for differentiating SCC from AC in surgical resected tissues and bronchoalveolar lavage (BAL) samples. Expression levels of seven histological subtype-associated miRNAs were determined in 128 snap-frozen surgical lung tumor specimens by using reverse transcription-polymerase chain reaction (RT-PCR) to develop an optimal panel of miRNAs for acutely distinguishing SCC from AC. The biomarkers were validated in an independent cohort of 112 FFPE lung tumor tissues, and a cohort of 127 BAL specimens by using droplet digital PCR for differentiating SCC from AC. A prediction model with two miRNAs (miRs-205-5p and 944) was developed that had 0.988 area under the curve (AUC) with 96.55% sensitivity and 96.43% specificity for differentiating SCC from AC in frozen tissues, and 0.997 AUC with 96.43% sensitivity and 96.43% specificity in FFPE specimens. The diagnostic performance of the prediction model was reproducibly validated in BAL specimens for distinguishing SCC from AC with a higher accuracy compared with cytology (95.69 vs. 68.10%; P < 0.05). The prediction model might have a clinical value for accurately discriminating SCC from AC in both surgical lung tumor tissues and liquid cytological specimens.