Salivary miRNA-21 expression as a potential non-invasive diagnostic biomarker in breast cancer

Diagnosis of lung cancer using salivary miRNAs expression and clinical characteristics

OBJECTIVE

Lung cancer (LC), the primary cause for cancer-related death globally is a diverse illness with various characteristics. Saliva is a readily available biofluid and a rich source of miRNA. It can be collected non-invasively as well as transported and stored easily. The process is also reproducible and cost-effective. The aim of this study was to evaluate the salivary expression of microRNAs let-7a-2, miR-221, and miR-20a in saliva and evaluate their efficacy, using multiple logistic regression (MLR) model, in diagnosis of lung cancer.

MATERIALS

Samples of saliva were obtained from 40 lung cancer patients (20 lung adenocarcinoma and 20 lung squamous cell carcinoma) and 20 healthy controls. The levels of let-7a-2, miR-221, and miR-20a expression in saliva were assessed by RT-qPCR. Receiver operating characteristic (ROC) curve was utilized to assess the potential significance of miRNAs in saliva for lung cancer diagnosis with the use of multiple logistic regression (MLR), principal component analysis, and machine learning methods.

RESULTS

Diagnostic odds ratio (DOR) of miR-20a in lung adenocarcinoma diagnosis versus healthy control was higher than miR-221, and DOR of miR-221 was higher than let-7a-2. miR-20a demonstrated a higher DOR for small cell lung carcinoma versus healthy control compared to let-7a-2, which in turn exhibited a higher DOR than miR-221. MLR of miR-221, let-7a-2, miR-20a, and smoking habit using main effects led to accuracy of 0.725 (sensitivity: 0.80, specificity: 0.65) and AUC = 0.795 for differentiation of small-cell lung carcinoma from lung adenocarcinoma. Our results showed that MLR based on salivary miRNAs could diagnose LUAD and SCLC from healthy control using main effects and two-way interactions with the accuracy of 0.90 (sensitivity = 0.95 and specificity = 0.85).

CONCLUSION

A salivary miRNA-based MLR model is a promising diagnostic tool for lung cancer, offering a non-invasive screening option for high-risk asymptomatic individuals.

Expression of Salivary miRNAs, Clinical, and Demographic Features in the Early Detection of Gastric Cancer: A Statistical and Machine Learning Analysis

OBJECTIVE

Gastric cancer ranks as one of the top five deadliest cancers worldwide and is often diagnosed at late stages. Analysis of saliva may provide a non-invasive approach for detection of malignancies in organs associated with the oral cavity. This research aims to analyze salivary microRNA expression together with clinical and demographic features with the aim of diagnosing gastric cancer.

MATERIALS

The study included 19 patients with early-stage gastric cancer and 19 healthy controls. Saliva samples were collected and processed for RNA isolation. Salivary expression of miR-223-3p and miR-21-5p were measured using quantitative reverse-transcription polymerase chain reaction (RT-qPCR). Receiver operating characteristic (ROC) curves were generated to evaluate the accuracy of diagnostic models. Machine learning algorithms, multiple logistic regression, and principal component analysis (PCA) were used to assess the predictive power of miRNAs in conjunction with clinical-demographic features.

RESULTS

Significant upregulation of miR-223-3p and downregulation of miR-21-5p in saliva were observed in patients with gastric cancer. The area under ROC curve (AUC) values for salivary miR-21-5p, salivary miR-223-3p, and their multiple logistic regression were determined to be 0.723, 0.791, and 0.850, respectively. The AUC for multiple logistic regression model was 0.919. The PCA model led to the highest diagnostic odds ratio (DOR) of 134.33 (sensitivity = 0.785, specificity = 1.00, AUC = 903). Application of machine learning methods, and in particular a random forest algorithm, showed high accuracy in diagnosing patients with gastric cancer (sensitivity = 1.00, specificity = 0.857, AUC = 0.93).

CONCLUSION

The application of validated salivary diagnostics in clinical practice could help facilitate earlier diagnosis of gastric cancer and improve medical outcome. Expression of miR-21 and miR-223-3p in saliva together with clinical and demographic features, appears promising in screening for GC.

Attenuated Total Reflection-Fourier Transform Infrared (ATR-FTIR) Spectroscopy Analysis of Saliva as a Diagnostic Specimen for Rapid Classification of Oral Squamous Cell Carcinoma Using Chemometrics Methods

BACKGROUND & AIM

Recent advancements in analytical techniques have highlighted the potential of Attenuated Total Reflection-Fourier Transform Infrared (ATR-FTIR) spectroscopy as a quick, cost-effective, non-invasive, and efficient tool for cancer diagnosis. This study aims to evaluate the effectiveness of ATR-FTIR spectroscopy in combination with supervised machine learning classification models for diagnosing OSCC using saliva samples.

METHODS & MATERIALS

Eighty unstimulated whole saliva samples from OSCC patients and healthy controls were collected. The ATR-FTIR spectroscopy was performed and spectral data were used to classify healthy and OSCC groups. The data were analyzed using machine learning classification methods such as Partial Least Squares-Discriminant Analysis (PLS-DA) and Support Vector Machine Classification (SVM-C). The classification performance of the models was evaluated by computing sensitivity, specificity, precision, and accuracy.

RESULTS

The samples were classified into two classes based on their spectral data. The obtained results demonstrate a high level of accuracy in the prediction sets of the PLS-DA and SVM-C models, with accuracy values of 0.960 and 0.962, respectively. The OSCC group sensitivity values for both PLS-DA and SVM-C models was 1.00, respectively.

CONCLUSION

The study indicates that ATR-FTIR spectroscopy, combined with chemometrics, is a potential method for the non-invasive diagnosis of OSCC using saliva samples. This method achieved high accuracy and the findings of this study suggest that ATR-FTIR spectroscopy could be further developed for clinical applications in OSCC diagnosis.

Identification of common salivary miRNA in oral lichen planus and oral squamous cell carcinoma: systematic review and meta-analysis

BACKGROUND

Oral lichen planus (OLP) is a chronic inflammatory condition that can impact patients' quality of life. While its exact etiology remains unclear, it is associated with an increased risk of malignant transformation. Currently, the diagnosis of OLP relies on clinical examination and histopathological analysis, which can be invasive. Therefore, there is an urgent need for non-invasive and accurate diagnostic biomarkers. This systematic review and meta-analysis aims to investigate the potential of salivary microRNAs as promising candidates for OLP diagnosis. This meta-analysis seeks to identify specific microRNAs that are differentially expressed and could serve as reliable biomarkers for OLP diagnosis.

METHODS

Our strategy involved searching for pertinent keywords in multiple academic databases including Cochrane Library, Embase, LIVIVO, MEDLINE, Ovid, ProQuest, Scopus, Web of Science, Espacenet, and Google Scholar search engine. Upon identification, articles were screened and data extracted from the eligible studies. Split component synthesis method was utilized to assess specificity, sensitivity, likelihood and diagnostic odds ratios. The random-effects meta-analysis approach was used to combine study findings and develop pooled diagnostic performance metrics. Hierarchical summary receiver operating characteristic (ROC) plots were generated to determine area under the curve. Subgroup analyses concerning the type of saliva and control groups were also performed.

RESULTS

Among the fourteen studies included in our systematic review, five were eligible for meta-analysis. Salivary microRNAs showed the pooled sensitivity of 0.80 (95% Confidence Interval (95% CI): 0.68-0.88), specificity of 0.89 (95% CI: 0.82-0.94), diagnostic odds ratio of 28.45 (95% CI: 10.40-77.80), and area under the curve (AUC) of 0.93 for OLP diagnosis. Unstimulated saliva had higher sensitivity and specificity than oral swirl samples as the biomarker medium for OLP diagnosis. Meta-analysis uncovered that miR-27a, miR-137, miR-1290, miR-27b, miR-4484, miR-142, and miR-1246 had the highest diagnostic odds ratio for OLP.

CONCLUSIONS

Our systematic review and meta-analysis demonstrate that salivary microRNAs can serve as valuable biomarkers for the diagnosis of OLP. The findings highlight the exceptional accuracy of salivary microRNAs in differentiating OLP patients from healthy controls and assessing the risk of malignant transformation.

Sample-to-answer salivary miRNA testing: New frontiers in point-of-care diagnostic technologies

MicroRNA (miRNA), crucial non-coding RNAs, have emerged as key biomarkers in molecular diagnostics, prognosis, and personalized medicine due to their significant role in gene expression regulation. Salivary miRNA, in particular, stands out for its non-invasive collection method and ease of accessibility, offering promising avenues for the development of point-of-care diagnostics for a spectrum of diseases, including cancer, neurodegenerative disorders, and infectious diseases. Such development promises rapid and precise diagnosis, enabling timely treatment. Despite significant advancements in salivary miRNA-based testing, challenges persist in the quantification, multiplexing, sensitivity, and specificity, particularly for miRNA at low concentrations in complex biological mixtures. This work delves into these challenges, focusing on the development and application of salivary miRNA tests for point-of-care use. We explore the biogenesis of salivary miRNA and analyze their quantitative expression and their disease relevance in cancer, infection, and neurodegenerative disorders. We also examined recent progress in miRNA extraction, amplification, and multiplexed detection methods. This study offers a comprehensive view of the development of salivary miRNA-based point-of-care testing (POCT). Its successful advancement could revolutionize the early detection, monitoring, and management of various conditions, enhancing healthcare outcomes. This article is categorized under: Diagnostic Tools > Biosensing Diagnostic Tools > Diagnostic Nanodevices.

Role of salivary miRNAs in the diagnosis of gastrointestinal disorders: a mini-review of available evidence

MiRNAs are short, non-coding RNA molecules, which are involved in the regulation of gene expression and which play an important role in various biological processes, including inflammation and cell cycle regulation. The possibility of detecting their extracellular expression, within body fluids, represented the main background for their potential use as non-invasive biomarkers of various diseases. Salivary miRNAs particularly gained interest recently due to the facile collection of stimulated/unstimulated saliva and their stability among healthy subjects. Furthermore, miRNAs seem to represent biomarker candidates of gastrointestinal disorders, with miRNA-based therapeutics showing great potential in those conditions. This review aimed to highlight available evidence on the role of salivary miRNAs in different gastrointestinal conditions. Most salivary-based miRNA studies available in the literature that focused on pathologies of the gastrointestinal tract have so far been conducted on pancreatic cancer patients and delivered reliable results. A few studies also showed the diagnostic utility of salivary miRNAs in conditions such as esophagitis, esophageal cancer, colorectal cancer, or inflammatory bowel disease. Moreover, several authors showed that salivary miRNAs may confidently be used as biomarkers of gastric cancer, but the use of salivary miRNA candidates in gastric inflammation and pre-malignant lesions, essential stages of Correa's cascade, is still put into question. On the other hand, besides miRNAs, other salivary omics have shown biomarker potential in gastro-intestinal conditions. The limited available data suggest that salivary miRNAs may represent reliable biomarker candidates for gastrointestinal conditions. However, their diagnostic potential requires validation through future research, performed on larger cohorts.

Association between colorectal cancer and expression levels of miR-21, miR-17-5P, miR-155 genes and the presence of Fusobacterium nucleatum in biopsy samples obtained from Iranian patients

BACKGROUND

Colorectal cancer (CRC) is considered the second-deadliest and third-most common malignancy worldwide. Studying the carcinogenic mechanism of bacteria or their role in aggravating cancer can be precious. Fusobacterium nucleatum (F. nucleatum) is one of the important bacteria in the occurrence and spread of CRC. In this study, we investigated the expression levels of miR-21, miR-17-5P, miR-155, and the relative frequency of F. nucleatum in biopsy samples from patients with CRC.

METHOD

DNA and RNA samples were extracted using a tissue extraction kit, and then cDNAs were synthesized using a related kit. Based on the sequence of miR-17-5P, miR-21, and miR-155 genes, F. nucleatum specific 16srRNA and bacterial universal16srRNA specific primers were selected, and the expression levels of the target genes were analyzed using the Real-Time PCR method.

RESULTS

The expression level of miR-21, miR-17-5P, and miR-155 genes showed a significant increase in the cancer group. Also, the expression of the mentioned miRNAs was significantly raised in the positive samples for F. nucleatum presence. The relative frequency of F. nucleatum in the cancer group was significantly increased compared to the control group.

CONCLUSION

Due to the changes in the expression of genes involved in causing CRC in the presence of F. nucleatum, it is possible to prompt identification and provide therapeutic solutions to cancer patients by studying their microbial profiles and the expression changes of different selected genes.

Evaluation of Salivary KCNJ3 mRNA Levels in Breast Cancer: A Case–control Study and in silico Analysis

Background:

Breast cancer (BC) is considered the most malignant and central cancer-related death among women worldwide. There is an essential need to discover new methods for developing noninvasive and low-cost diagnoses. The present study examines the expression of KCNJ3 which acts as a biomarker for detecting BC in the saliva of BC patients compared to controls.

Methods:

The mRNA expression level of KCNJ3 has been evaluated. Forty-three unstimulated whole saliva samples from BC patients and forty-three salivary samples from healthy controls were collected. The mRNA level was measured using quantitative real-time polymerase chain reaction (qRT-PCR). Furthermore, the protein-protein interaction network in which KCNJ3 is involved was obtained. In silico analysis was applied to predict the possible molecular mechanisms of KCNJ3 in BC development.

Results:

Differentially expressed KCNJ3 was statistically significant between BC patients and controls (p<0.001). The sensitivity and specificity of KCNJ3 mRNA in BC detection were 76.74% and 94.95%, respectively. Receiver operating characteristic (ROC) curve analysis of KCNJ3 mRNA revealed that Area under the curve (AUC) was 0.923 (95% Confidence Interval (CI): 0.866-0.979). AUCs of ROC curve analysis were 0.743 (95% CI: 0.536-0.951), 0.685 (95% CI: 0.445-0.925), and 0.583(95% CI: 0.343-0.823) for differentiation stage I from stage III, stage I to stage II and finally stage II from stage III, respectively. Furthermore, the GABAergic synapse signaling pathway was suggested as a potential pathway involved in BC development.

Conclusion:

Salivary levels of KCNJ3 could be considered a potential diagnostic biomarker with high sensitivity and specificity for BC detection.

Salivary biomarkers in breast cancer diagnosis: A systematic review and diagnostic meta-analysis

BACKGROUND

Salivary diagnostics and their utility as a nonaggressive approach for breast cancer diagnosis have been extensively studied in recent years. This meta-analysis assesses the diagnostic value of salivary biomarkers in differentiating between patients with breast cancer and controls.

METHODS

We conducted a meta-analysis and systematic review of studies related to salivary diagnostics published in PubMed, EMBASE, Scopus, Ovid, Science Direct, Web of Science (WOS), and Google Scholar. The articles were chosen utilizing inclusion and exclusion criteria, as well as assessing their quality. Specificity and sensitivity, along with negative and positive likelihood ratios (NLR and PLR) and diagnostic odds ratio (DOR), were calculated based on random- or fixed-effects model. Area under the curve (AUC) and summary receiver-operating characteristic (SROC) were plotted and evaluated, and Fagan's Nomogram was evaluated for clinical utility.

RESULTS

Our systematic review and meta-analysis included 14 papers containing 121 study units with 8639 adult subjects (4149 breast cancer patients and 4490 controls without cancer). The pooled specificity and sensitivity were 0.727 (95% CI: 0.713-0.740) and 0.717 (95% CI: 0.703-0.730), respectively. The pooled NLR and PLR were 0.396 (95% CI: 0.364-0.432) and 2.597 (95% CI: 2.389-2.824), respectively. The pooled DOR was 7.837 (95% CI: 6.624-9.277), with the AUC equal to 0.801. The Fagan's nomogram showed post-test probabilities of 28% and 72% for negative and positive outcomes, respectively. We also conducted subgroup analyses to determine specificity, sensitivity, DOR, PLR, and NLR based on the mean age of patients (≤52 or >52 years old), saliva type (stimulated and unstimulated saliva), biomarker measurement method (mass spectrometry [MS] and non-MS measurement methods), sample size (≤55 or >55), biomarker type (proteomics, metabolomics, transcriptomics and proteomics, and reagent-free biophotonic), and nations.

CONCLUSION

Saliva, as a noninvasive biomarker, has the potential to accurately differentiate breast cancer patients from healthy controls.

Metabolic Features of Saliva in Breast Cancer Patients

The aim of the work was to study the metabolic characteristics of saliva in breast cancer and the subsequent assessment of the potential information content of its individual biochemical indicators. The study included 487 patients of the Omsk Clinical Oncology Center with morphologically verified breast cancer and 298 volunteers without breast pathologies. Saliva samples were obtained from all patients before the start of treatment, and the values of 34 biochemical indicators were determined. It has been shown that concentration of total protein, urea, uric acid (UA), the total content of α-amino acids and lipid peroxidation products, and the activity of metabolic and antioxidant enzymes (in particular catalase—CAT) of saliva changed significantly in breast cancer. Biochemical indicators characterizing early breast cancer have been identified, which can be used for timely diagnosis in addition to existing methods. The coefficients UA/Urea and UA·CAT/Urea are proposed, for which the maximum deviation from the norm was observed in the early stages of the disease. It was shown that for ductal breast cancer, changes in the activity of metabolic enzymes of saliva were more pronounced, while, for lobular breast cancer, the indicators of enzymatic and non-enzymatic components of antioxidant protection changed. The results confirmed the potential importance of saliva in the diagnosis of breast cancer.