Circulating microRNAs: Next-generation Cancer Detection

Potential utility of pretreatment serum miRNAs for optimal treatment selection in advanced high-grade serous ovarian cancer

OBJECTIVE

The primary treatment of patients with advanced ovarian cancer is selected from whether primary debulking surgery or neoadjuvant chemotherapy. We investigated whether pretreatment serum microRNA profiles are useful for selecting patients with advanced high-grade serous ovarian cancer who obtain better outcomes from undergoing primary debulking surgery or neoadjuvant chemotherapy.

METHODS

Consecutive patients with clinical stage IIIB-IVB and serum microRNA data were selected. Patients who underwent primary debulking surgery or neoadjuvant chemotherapy were subjected to 1:1 propensity score matching before comparing their progression-free survival using Cox modelling. Progression-free probabilities for the selected microRNA profiles were calculated, and the estimated progression-free survival with the recommended primary treatment was determined and compared with the actual progression-free survival of the patients.

RESULTS

Of the 108 patients with stage IIIB-IVB disease, the data of 24 who underwent primary debulking surgery or neoadjuvant chemotherapy were compared. Eleven and three microRNAs were independent predictors of progression-free survival in patients who underwent primary debulking surgery and neoadjuvant chemotherapy, respectively. Two microRNAs correlated significantly with complete resection of the tumours in primary debulking surgery. No differences were found between the actual and estimated progression-free survival in the primary debulking surgery and neoadjuvant chemotherapy groups (P > 0.05). The recommended and actual primary treatments were identical in 27 (56.3%) of the 48 patients. The median improved survival times between recommended and actual treatment were 11.7 and 32.6 months for patients with actual primary debulking surgery and neoadjuvant chemotherapy, respectively.

CONCLUSIONS

Pretreatment microRNA profiles could be used to select subgroups of patients who benefited more from primary debulking surgery or neoadjuvant chemotherapy and might contribute to selecting the optimal primary treatment modality in advanced high-grade serous ovarian cancer patients.

Frequency shift Raman-based sensing of serum MicroRNA for ultrasensitive cervical cancer diagnosis

Cervical cancer is the most common gynaecological tumor. The development of a sensor for the ultrasensitive detection of cervical cancer is significant in guaranteeing its prognosis. Herein, we proposed a novel surface-enhanced Raman scattering (SERS) analysis platform using a frequency shifts-based sensing model for rapid and ultrasensitive microRNA (miRNA) assay. During the analysis process, miR-21 can be captured by the single-stranded DNA (ssDNA) modified on the platform which is complementary pairing with miR-21. The connection of miR-21 can lead to the variation of the molecular weight and result in the deformation extent of the Raman report molecule 6Thioguanine (6TG); thus, the peak at 1301 cm-1 due to the ring C-N stretches of 6TG shifts to lower frequency. The detection limit (LOD) of the proposed SERS analysis platform is as low as 8.32 aM. Moreover, the platform also has excellent specificity and repeatability, with the relative standard deviation (RSD) value of 6.53 %. Serum samples of cervical cancer patients and healthy subjects were analyzed via the platform and the accuracy of the detection results was verified by qRT-PCR, revealing that SERS results and qRT-PCR results have high homogeneity. Thus, the platform can serve as a potential tool for clinical diagnosis of cervical cancer.

Prospects for liquid biopsy using microRNA and extracellular vesicles in breast cancer

Among the analytes circulating in body fluids, microRNAs, a type of non-coding RNA and known to exist 2655 in primates, have attracted attention as a novel biomarker for cancer screening. MicroRNAs are signaling molecules with important gene expression regulatory functions that can simultaneously control many gene functions and multiple different pathways in living organisms. These microRNAs are transported in extracellular vesicles (EVs), which are lipid bilayers with 50-150 nm in diameter, and are used as communication tools between cells. Furthermore, the EVs that carry these microRNAs circulate in the bloodstream and have other important implications for understanding the pathogenesis and diagnosis of breast cancer. The greatest benefit from cancer screening is the reduction in breast cancer mortality rate through early detection. Other benefits include reduced incidence of breast cancer, improved quality of life, prognosis prediction, contribution to personalized medicine, and relative healthcare cost containment. This paper outlines the latest developments in liquid biopsy for breast cancer, especially focusing on microRNA and EV diagnostics.

Plasma extracellular vesicle microRNAs reflecting the therapeutic effect of the CBP/β-catenin inhibitor PRI-724 in patients with liver cirrhosis

There is an unmet need for antifibrotic therapies to prevent the progression of liver cirrhosis. Previously, we conducted an exploratory trial to assess the safety and antifibrotic efficacy of PRI-724, a selective CBP/β-catenin inhibitor, in patients with liver cirrhosis. PRI-724 was well tolerated and exerted a potential antifibrotic effect. Here, we investigated whether the profiles of circulating microRNAs packaged in extracellular vesicles (EV-miRNAs) are associated with responses to liver fibrosis treatments. Eighteen patients who received PRI-724 for 12 weeks in a phase 1/2a study were classified as responders (n = 10) or non-responders (n = 8) based on changes in liver stiffness. Plasma samples were obtained before and after PRI-724 administration and the levels of EV-miRNAs were analyzed. Three miRNAs (miR-6510-5p, miR-6772-5p, and miR-4261) were identified as predictors of response or non-response to PRI-724, and the levels of three other miRNAs (miR-939-3p, miR-887-3p, and miR-7112-5p) correlated with the efficacy of treatment. Expression of miR-887-3p was detected in hepatocytes and was decreased significantly in liver tissue following PRI-724 treatment. In addition, transfection of a miR-887-3p mimic activated hepatic stellate cells. Thus, decreases in the miR-887-3p level in blood may reflect recovery from liver fibroses in patients with liver cirrhosis treated with PRI-724, although further validation studies are warranted to confirm this.

Connecting the dots in the associations between diet, obesity, cancer, and microRNAs

The prevalence of obesity has reached pandemic levels worldwide, leading to a lower quality of life and higher health costs. Obesity is a major risk factor for noncommunicable diseases, including cancer, although obesity is one of the major preventable causes of cancer. Lifestyle factors, such as dietary quality and patterns, are also closely related to the onset and development of obesity and cancer. However, the mechanisms underlying the complex association between diet, obesity, and cancer remain unclear. In the past few decades, microRNAs (miRNAs), a class of small non-coding RNAs, have been demonstrated to play critical roles in biological processes such as cell differentiation, proliferation, and metabolism, highlighting their importance in disease development and suppression and as therapeutic targets. miRNA expression levels can be modulated by diet and are involved in cancer and obesity-related diseases. Circulating miRNAs can also mediate cell-to-cell communications. These multiple aspects of miRNAs present challenges in understanding and integrating their mechanism of action. Here, we introduce a general consideration of the associations between diet, obesity, and cancer and review the current knowledge of the molecular functions of miRNA in each context. A comprehensive understanding of the interplay between diet, obesity, and cancer could be valuable for the development of effective preventive and therapeutic strategies in future.

Biomarker Discovery in Rare Malignancies: Development of a miRNA Signature for RDEB-cSCC

Machine learning has been proven to be a powerful tool in the identification of diagnostic tumor biomarkers but is often impeded in rare cancers due to small patient numbers. In patients suffering from recessive dystrophic epidermolysis bullosa (RDEB), early-in-life development of particularly aggressive cutaneous squamous-cell carcinomas (cSCCs) represents a major threat and timely detection is crucial to facilitate prompt tumor excision. As miRNAs have been shown to hold great potential as liquid biopsy markers, we characterized miRNA signatures derived from cultured primary cells specific for the potential detection of tumors in RDEB patients. To address the limitation in RDEB-sample accessibility, we analyzed the similarity of RDEB miRNA profiles with other tumor entities derived from the Cancer Genome Atlas (TCGA) repository. Due to the similarity in miRNA expression with RDEB-SCC, we used HN-SCC data to train a tumor prediction model. Three models with varying complexity using 33, 10 and 3 miRNAs were derived from the elastic net logistic regression model. The predictive performance of all three models was determined on an independent HN-SCC test dataset (AUC-ROC: 100%, 83% and 96%), as well as on cell-based RDEB miRNA-Seq data (AUC-ROC: 100%, 100% and 91%). In addition, the ability of the models to predict tumor samples based on RDEB exosomes (AUC-ROC: 100%, 93% and 100%) demonstrated the potential feasibility in a clinical setting. Our results support the feasibility of this approach to identify a diagnostic miRNA signature, by exploiting publicly available data and will lay the base for an improvement of early RDEB-SCC detection.

An enzyme-free turn-on fluorescent strategy for nucleic acid detection based on hybridization chain reaction and transferable silver nanoclusters

A fluorescence biosensor has been developed based on hybridisation chain reaction (HCR) amplification coupled with silver nanoclusters (AgNCs) for nucleic acid detection. The fluorescence was activated via end-to-end transfer of dark AgNCs caged within a DNA template to another DNA sequence that could enhance their red fluorescence emission at 611 nm. Such cluster-transfer approach allows us to introduce fluorogenic AgNCs as external signal transducers, thereby enabling HCR to perform in a predictable manner. The resulted HCR-AgNC biosensor was able to detect target DNA with a detection limit of 3.35 fM, and distinguish the DNA target from single-base mismatch sequences. Moreover, the bright red fluorescence emission was detectable with the naked eye, with concentration of target DNA down to 1 pM. The biosensor also performed well in human serum samples with good recovery. Overall, our cluster-transfer approach provides a good alternative to construct HCR-AgNC assay with less risk of circuit leakage and produce AgNCs in a controllable manner.

Circulating microRNA profiling for prediction of oncological outcomes in prostate cancer patients following radical prostatectomy

BACKGROUND

Although radical prostatectomy is associated with good long-term oncological outcomes, approximately 30% of patients present biochemical recurrence, whereupon salvage treatments are required. Identification of novel molecular biomarkers to predict cancer behavior is clinically important. Here, we developed a novel microRNA (miRNA)-based prognostic model for patients who underwent radical prostatectomy.

METHODS

We retrospectively investigated the clinical records of 295 patients who underwent radical prostatectomy between 2009 and 2017. We randomly assigned these cases into training or validation sets. The prognostic model was constructed using Fisher linear discriminant analysis in the training set, and we evaluated its performance in the validation set.

RESULTS

Overall, 72 patients had biochemical recurrence. A prediction model was constructed using a combination of three miRNAs (miR-3147, miR-4513, and miR-4728-5p) and two pathological factors (pathological T stage and Gleason score). In the validation set, the predictive performance of the model was confirmed to be accurate (area under the receiver operating characteristic curve: 0.80; sensitivity: 0.78; specificity: 0.76). Additionally, Kaplan-Meier analysis revealed that the patients with a low prediction index had significantly longer recurrence-free survival than those with a high index (p < 0.001).

CONCLUSIONS

Circulating miRNA profiles can provide information to predict recurrence after prostatectomy. Our model may be helpful for physicians to decide follow-up strategies for patients.

Machine learning diagnosis by immunoglobulin N-glycan signature for precision diagnosis of urological diseases

Early diagnosis of urological diseases is often difficult due to the lack of specific biomarkers. More powerful and less invasive biomarkers that can be used simultaneously to identify urological diseases could improve patient outcomes. The aim of this study was to evaluate a urological disease‐specific scoring system established with a machine learning (ML) approach using Ig N‐glycan signatures. Immunoglobulin N‐glycan signatures were analyzed by capillary electrophoresis from 1312 serum subjects with hormone‐sensitive prostate cancer (n = 234), castration‐resistant prostate cancer (n = 94), renal cell carcinoma (n = 100), upper urinary tract urothelial cancer (n = 105), bladder cancer (n = 176), germ cell tumors (n = 73), benign prostatic hyperplasia (n = 95), urosepsis (n = 145), and urinary tract infection (n = 21) as well as healthy volunteers (n = 269). Immunoglobulin N‐glycan signature data were used in a supervised‐ML model to establish a scoring system that gave the probability of the presence of a urological disease. Diagnostic performance was evaluated using the area under the receiver operating characteristic curve (AUC). The supervised‐ML urologic disease‐specific scores clearly discriminated the urological diseases (AUC 0.78–1.00) and found a distinct N‐glycan pattern that contributed to detect each disease. Limitations included the retrospective and limited pathological information regarding urological diseases. The supervised‐ML urological disease‐specific scoring system based on Ig N‐glycan signatures showed excellent diagnostic ability for nine urological diseases using a one‐time serum collection and could be a promising approach for the diagnosis of urological diseases.

Serum microRNA as liquid biopsy biomarker for the prediction of oncological outcomes in patients with bladder cancer

OBJECTIVES

Radical cystectomy is the gold-standard treatment for muscle-invasive bladder cancer and aggressive non-muscle-invasive bladder cancer. To enhance clinical decision-making regarding patients with bladder cancer who underwent radical cystectomy, a recurrence prediction biomarker with high accuracy is urgently needed. In this study, we developed a model for the prediction of bladder cancer recurrence after radical cystectomy by combining serum microRNA and a pathological factor.

METHODS

We retrospectively analyzed the clinical records of 81 patients with bladder cancer who underwent radical cystectomy between 2008 and 2016. The dataset was divided into two, and Fisher linear discriminant analysis was used to construct a prognostic model for future recurrence in the training set (n = 41). The performance of the model was evaluated in the validation set (n = 40).

RESULTS

Thirty patients had recurrence after having undergone radical cystectomy. A prognostic model for recurrence was constructed by combining a pathological factor (i.e. positive pathological lymph node status) and three microRNAs (miR-23a-3p, miR-3679-3p, and miR-3195). The model showed a sensitivity of 0.87, a specificity of 0.80, and an area under the receiver operating characteristic curve of 0.88 (0.77-0.98) in the validation set. Furthermore, Kaplan-Meier analysis revealed that patients with a low prediction index have significantly longer overall survival than patients with a high prediction index (P = 0.041).

CONCLUSION

A combination of serum microRNA profiles and lymph node statuses is useful for the prediction of oncological outcomes after radical cystectomy in patients with bladder cancer.

MicroRNAs: understanding their role in gene expression and cancer

MicroRNAs are small RNA molecules that regulate gene expression in cells. These small molecules comprise 17 to 25 nucleotides and are able to recognize target messenger RNAs by sequence complementarity and regulate their protein translation. Different microRNAs are expressed in all human cells. There is over 2,500 microRNAs described in humans that are involved in virtually all biological processes. Given their role as gene expression regulators, these molecules have been widely investigated and are thought to be associated with some specific physiological and pathological conditions, being proposed as biomarkers. It has recently been reported that microRNAs are secreted outside cells and are involved in intercellular communication. MicroRNAs in biological fluids are named circulating and have been detected in all body fluids, although the expression profile is specific for each type. The major advantages of using circulating microRNAs as biological markers are the high stability of those molecules and the wide availability of samples. Also, given the individual nature of microRNA expression changes, these molecules have a high potential for use in personalized medicine. In fact, microRNA expression profile determination may support disease recognition and diagnosis, and can be used to monitor therapeutic responses and establish patient prognosis, assisting in choice of treatment. This review provides a general overview of microRNAs and discusses the importance of those molecules in cancer, for deeper understanding of their role in this disease.

Stable duplex-linked antisense targeting miR-148a inhibits breast cancer cell proliferation

MicroRNAs (miRNAs) regulate cancer cell proliferation by binding directly to the untranslated regions of messenger RNA (mRNA). MicroRNA-148a (miR-148a) is expressed at low levels in breast cancer (BC). However, little attention has been paid to the sequestration of miR-148a. Here, we performed a knockdown of miR-148a using anti-miRNA oligonucleotides (AMOs) and investigated the effect on BC cell proliferation. BC cell proliferation was significantly suppressed by AMO flanked by interstrand cross-linked duplexes (CL-AMO), whereas single-stranded and commercially available AMOs had no effect. The suppression was caused by sequestering specifically miR-148a. Indeed, miR-148b, another member of the miR-148 family, was not affected. Importantly, the downregulation of miR-148a induced a greater and longer-lasting inhibition of BC cell proliferation than the targeting of oncogenic microRNA-21 (miR-21) did. We identified thioredoxin-interacting protein (TXNIP), a tumor suppressor gene, as a target of miR-148a and showed that CL-AMO provoked an increase in TXNIP mRNA expression. This study provide evidence that lowly expressed miRNAs such as miR-148a have an oncogenic function and might be a promising target for cancer treatment.