Multiplex Analysis of CircRNAs from Plasma Extracellular Vesicle-Enriched Samples for the Detection of Early-Stage Non-Small Cell Lung Cancer

Extracellular Vesicles in Lung Cancer: Implementation in Diagnosis and Therapeutic Perspectives

Lung cancer represents the leading cause of cancer-related mortality worldwide, with around 1.8 million deaths in 2020. For this reason, there is an enormous interest in finding early diagnostic tools and novel therapeutic approaches, one of which is extracellular vesicles (EVs). EVs are nanoscale membranous particles that can carry proteins, lipids, and nucleic acids (DNA and RNA), mediating various biological processes, especially in cell-cell communication. As such, they represent an interesting biomarker for diagnostic analysis that can be performed easily by liquid biopsy. Moreover, their growing dataset shows promising results as drug delivery cargo. The aim of our work is to summarize the recent advances in and possible implications of EVs for early diagnosis and innovative therapies for lung cancer.

Circular RNAs: characteristics, functions, mechanisms, and potential applications in thyroid cancer

Thyroid cancer (TC) is one of the most common endocrine malignancies, and its incidence has increased globally. Despite extensive research, the underlying molecular mechanisms of TC remain partially understood, warranting continued exploration of molecular markers for diagnostic and prognostic applications. Circular RNAs (circRNAs) have recently garnered significant attention owing to their distinct roles in cancers. This review article introduced the classification and biological functions of circRNAs and summarized their potential as diagnostic and prognostic markers in TC. Further, the interplay of circRNAs with PI3K/Akt/mTOR, Wnt/β-catenin, MAPK/ERK, Notch, JAK/STAT, and AMPK pathways is elaborated upon. The article culminates with an examination of circRNA's role in drug resistance of TC and highlights the challenges in circRNA research in TC.

Brief Report: circRUNX1 as Potential Biomarker for Cancer Recurrence in EGFR Mutation-Positive Surgically Resected NSCLC

Introduction

As recently evidenced by the ADAURA trial, most patients with stages IB to IIIA of resected EGFR-mutant lung adenocarcinoma benefit from osimertinib as adjuvant therapy. Nevertheless, predictive markers of response and recurrence are still an unmet need for more than 10% of these patients. Some circular RNAs (circRNAs) have been reported to play a role in tumor growth and proliferation. In this project, we studied circRNA expression levels in formalin-fixed, paraffin-embedded lung tumor samples to explore their biomarker potential and develop a machine learning (ML)-based signature that could predict the benefit of adjuvant EGFR tyrosine kinase inhibitors in patients with EGFR-mutant NSCLC.

Methods

Patients with surgically resected EGFR mutant-positive, stages I to IIIB NSCLC were recruited from February 2007 to December 2015. Formalin-fixed, paraffin-embedded tumor samples were retrospectively collected from those patients with a follow-up period of more than or equal to 36 months (N = 76). Clinicopathologic features were annotated. Total RNA was purified and quantified prior nCounter processing with our circRNA custom panel. Data analysis and ML were performed taking into consideration circRNA expression levels and recurrence-free survival (RFS). RFS was defined from the day of surgery to the day when recurrence was detected radiologically or the death owing to any cause.

Results

Of the 76 patients with EGFR mutation-positive NSCLC included in the study, 34 relapsed within 3 years after resection. The median age of the relapsing cohort was 71.5 (range: 49-89) years. Most patients were nonsmokers (n = 21; 61.8%) and of female sex (n = 21; 61.8%). Most cases (n = 17; 50%) presented an exon 21 mutation, whereas 15 and four patients had an exon 19 and exon 18 mutation, respectively. Differential expression analysis revealed that circRUNX1, along with circFUT8 and circAASDH, was up-regulated in relapsing patients (p < 0.05 and >2 fold-change). A ML-based circRNA signature predictive of recurrence in patients with EGFR mutation-positive NSCLC, comprising circRUNX1, was developed. Our final model including selected 6-circRNA signature with random forest algorithm was able to classify relapsing patients with an accuracy of 83% and an area under the receiver operating characteristic curve of 0.91.RFS was significantly shorter not only for the subgroup of patients with high versus low circRUNX1 expression but also for the group classified as recurrent by the ML circRNA signature when compared with those classified as nonrecurrent.

Conclusions

Our findings suggest that circRUNX1 and the presented ML-developed signature could be novel tools to predict the benefit of adjuvant EGFR tyrosine kinase inhibitors with regard to RFS in patients with EGFR-mutant NSCLC. The training and validation phases of our ML signature will be conducted including bigger independent cohorts.

Gene expression signatures in conjunctival fornix aspirates of patients with dry eye disease associated with Meibomian gland dysfunction. A proof-of-concept study

BACKGROUND

Meibomian gland dysfunction (MGD) is one of the most common conditions in ophthalmic practice and the most frequent cause of evaporative dry eye disease (DED). However, the immune mechanisms leading to this pathology are not fully understood and the diagnostic tests available are limited. Here, we used the nCounter technology to analyze immune gene expression in DED-MGD that can be used for developing diagnostic signatures for DED.

METHODS

Conjunctival cell samples were obtained by aspiration from patients with DED-MGD (n = 27) and asymptomatic controls (n = 22). RNA was purified, converted to cDNA, preamplified and analyzed using the Gene Expression Human Immune V2 panel (NanoString), which includes 579 target and 15 housekeeping genes. A machine learning (ML) algorithm was applied to design a signature associated with DED-MGD.

RESULTS

Forty-five immune genes were found upregulated in DED-MGD vs. controls, involved in eight signaling pathways, IFN I/II, MHC class I/II, immunometabolism, B cell receptor, T Cell receptor, and T helper-17 (Th-17) differentiation. Additionally, statistically significant correlations were found between 31 genes and clinical characteristics of the disease such as lid margin or tear osmolarity (Pearson's r < 0.05). ML analysis using a recursive feature elimination (RFE) algorithm selected a 4-gene mRNA signature that discriminated DED-MGD from control samples with an area under the ROC curve (AUC ROC) of 0.86 and an accuracy of 77.5%.

CONCLUSIONS

Multiplexed mRNA analysis of conjunctival cells can be used to analyze immune gene expression patterns in patients with DED-MGD and to generate diagnostic signatures.

Liquid biopsy in detecting early non-small cell lung cancer

Lung cancer screening programs, particularly in the UK, have shown a decrease in lung cancer-related deaths among individuals who underwent low-dose computed tomography (CT) screening. Researchers are now focusing on evaluating cell-free DNA through various methods to determine if pre-diagnostic mutations can be detected years before clinical diagnosis. This could help identify individuals at high risk of developing lung cancer. However, while this approach has successfully identified precursors of follicular lymphoma, the presence of occult lung preneoplasia in non-small-cell lung cancer still requires further investigation. The TRACERx consortium is conducting extensive research to comprehensively assess the detection and progression of non-small cell lung cancers (NSCLC). Liquid biopsy is being used in advanced stages of the disease to monitor disease progression, predict treatment response, and identify targetable driver oncogenic mutations and fusion genes. Intense research is also underway to identify numerous diagnostic gene signatures with high accuracy for early-stage lung cancer. However, a more focused clinical approach is needed, with a mechanistic focus on the key pathways of cancer development. Loss of liver kinase B1 (LKB1) function and deactivation due to 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanol (NNAL), a metabolite of tobacco-specific carcinogens, could potentially be traced and contribute to the development of new biomarkers. This testing could complement machine-learning approaches. The discovery of epidermal growth factor receptor (EGFR) and Kirsten rat sarcoma viral oncogene homolog (KRAS) mutations in healthy lung tissues by TRACERx investigators may also lead to the development of novel diagnostic tools. Tumor protein 53 (TP53) loss should also be considered as a marker that could contribute to malignant transformation. Intercepting aggressive non-small-cell lung cancer is a pressing priority. In this review, we discuss our experience and explore other research on exosomes and plasma circular RNA as potential biomarkers. Circular RNAs, formed through non-sequential back-splicing of pre-mRNA transcripts, play a role in epithelial-mesenchymal transition, with many of them regulated by the RNA-binding protein Quaking. Platelet RNA has shown promise in detecting early and late-stage cancer. The extensive exploration of liquid biopsy aims to provide affordable methods for tracing circulating precursors of non-small-cell lung cancer, highlighting the importance of its mission.

Selective Internal Radiotherapy Alters the Profiles of Systemic Extracellular Vesicles in Hepatocellular Carcinoma

Incidence of hepatocellular carcinoma (HCC) is increasing globally. Radioembolization (RE)/selective internal radiotherapy (SIRT) is a promising treatment for inoperable HCC. RE triggers an immune response, involving extracellular vesicles (EVs) which are crucial for cell communication and tumor development. This study explores EV immune profiles and origins in patients with inoperable HCC before and after SIRT/RE. Blood samples from 50 HCC-patients treated with SIRT/RE were collected before and after therapy to determine cytokines and isolate EVs using size exclusion chromatography. The dynamic range and EV quality required for detecting variations in surface markers were assessed. Thirty-seven EV surface markers were analyzed using flow cytometry and correlated with clinical parameters. Several immunological markers (CD4, CD2, CD40, CD45, CD49e, CD69, CD209-EVs) were present in the circulation of HCC patients. These markers positively correlated with therapy response and survival. Conversely, B cell CD20, endothelial cell CD146, platelet CD49e, and CD41b EV markers negatively correlated with 60-day survival. Elevated levels of IL-6 and IL-8 before therapy correlated negatively with patient survival, coinciding with a positive correlation with CD20-positive EVs. Plasma EVs from HCC patients exhibit immunological, cancer, and coagulation markers, including potential biomarkers (CD4, CD20, CD49e, CD146). These may enhance our understanding of cancer biology and facilitate SIRT therapy monitoring.

Metabolic biomarkers in lung cancer screening and early diagnosis (Review)

Late diagnosis is one of the major contributing factors to the high mortality rate of lung cancer, which is now the leading cause of cancer-associated mortality worldwide. At present, low-dose CT (LDCT) screening in the high-risk population, in which lung cancer incidence is higher than that of the low-risk population is the predominant diagnostic strategy. Although this has efficiently reduced lung cancer mortality in large randomized trials, LDCT screening has high false-positive rates, resulting in excessive subsequent follow-up procedures and radiation exposure. Complementation of LDCT examination with biofluid-based biomarkers has been documented to increase efficacy, and this type of preliminary screening can potentially reduce potential radioactive damage to low-risk populations and the burden of hospital resources. Several molecular signatures based on components of the biofluid metabolome that can possibly discriminate patients with lung cancer from healthy individuals have been proposed over the past two decades. In the present review, advancements in currently available technologies in metabolomics were reviewed, with particular focus on their possible application in lung cancer screening and early detection.

Exosomal circRNAs: Novel biomarkers and therapeutic targets for gastrointestinal tumors

Despite the high prevalence of gastrointestinal tumors, early diagnosis and treatment of these tumors is limited by the lack of effective and specific biomarkers and therapeutic targets. Exosomes carry active molecules to mediate cell-to-cell communication, especially in the tumor microenvironment, and are promising biomarkers and therapeutic targets for cancer. Circular RNAs (circRNAs) are stably enriched in exosomes and show a unique circular structure, high stability, conservation, and tissue specificity. Exosomal circRNAs play important roles in regulating cell proliferation, metastasis, angiogenesis, metabolism, and the immune microenvironment of gastrointestinal tumors and exhibit great potential as tumor biomarkers and anti-tumor targets or tools. This review briefly introduces the characteristics and functions of circRNAs and exosomes, and systematically describes the biological roles and mechanisms of exosomal circRNAs in gastrointestinal tumors. This article also summarizes the detection methodology of exosomal circRNAs and discusses their clinical significance as biomarkers and targets for gastrointestinal tumors.