Breast cancer identification via modeling of peripherally circulating miRNAs

Identification of serum miR-1246 and miR-150-5p as novel diagnostic biomarkers for high-grade serous ovarian cancer

Epithelial ovarian cancer (EOC) is one of the leading cancers in women, with high-grade serous ovarian cancer (HGSOC) being the most common and lethal subtype of this disease. A vast majority of HGSOC are diagnosed at the late stage of the disease when the treatment and total recovery chances are low. Thus, there is an urgent need for novel, more sensitive and specific methods for early and routine HGSOC clinical diagnosis. In this study, we performed miRNA expression profiling using the NanoString miRNA assay in 34 serum samples from patients with HGSOC and 36 healthy women. We identified 13 miRNAs that were differentially expressed (DE). For additional exploration of expression patterns correlated with HGSOC, we performed weighted gene co-expression network analysis (WGCNA). As a result, we showed that the module most correlated with tumour size, nodule and metastasis contained 8 DE miRNAs. The panel including miR-1246 and miR-150-5p was identified as a signature that could discriminate HGSOC patients with AUCs of 0.98 and 1 for the training and test sets, respectively. Furthermore, the above two-miRNA panel had an AUC = 0.946 in the verification cohorts of RT-qPCR data and an AUC = 0.895 using external data from the GEO public database. Thus, the model we developed has the potential to markedly improve the diagnosis of ovarian cancer.

TRAIP serves as a potential prognostic biomarker and correlates with immune infiltrates in lung adenocarcinoma

BACKGROUND

Lung adenocarcinoma (LUAD) is one of the major types of lung cancer with high morbidity and mortality. The TRAF-interacting protein (TRAIP) is a ring-type E3 ubiquitin ligase which has been recently identified to play pivotal roles in various cancers. However, the expression and function of TRAIP in LUAD remain elusive.

METHODS

In this study, we used bioinformatic tools as well as molecular experiments to explore the exact role of TRAIP and the underlying mechanism.

RESULTS

Data mining across the UALCAN, GEPIA and GTEx, GEO and HPA databases revealed that TRAIP was significantly overexpressed in LUAD tissues than that in adjacent normal tissues. Kaplan-Meier curve showed that high TRAIP expression was associated with poor overall survival (OS) and relapse-free survival (RFS). Univariate and multivariate cox regression analysis revealed that TRAIP was an independent risk factor in LUAD. And the TRAIP-based nomogram further supported the prognostic role of TRAIP in LUAD. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis demonstrated that TRAIP-associated genes were mainly involved in DNA replication, cell cycle and other processes. The immune infiltration analysis indicated that TRAIP expression was tightly correlated with the infiltration of diverse immune cell types, including B cell, CD8 + T cell, neutrophil and dendritic cell. Moreover, TRAIP expression was observed to be significantly associated with tumor infiltrating lymphocytes (TILs) and immune checkpoint molecules. In vitro experiments further confirmed knockdown of TRAIP inhibited cell migration and invasion, as well as decreasing chemokine production and inhibiting M2-like macrophage recruitment. Lastly, CMap analysis identified 10 small molecule compounds that may target TRAIP, providing potential therapies for LUAD.

CONCLUSIONS

Collectively, our study found that TRAIP is an oncogenic gene in LUAD, which may be a potential prognostic biomarker and promising therapeutic target for LUAD.

Roles of miR-4442 in Colorectal Cancer: Predicting Early Recurrence and Regulating Epithelial-Mesenchymal Transition

Early recurrence in patients with colorectal cancer (CRC) is associated with a poor prognosis. We aimed to identify circulating microRNAs that are biomarkers of early CRC recurrence and elucidate their functions. We identified miR-4442 as a candidate biomarker by microRNA array analysis comparing preoperative and postoperative plasma levels in patients with CRC, with and without recurrence. The association between preoperative plasma miR-4442 levels, clinicopathological features, and recurrence-free survival was analyzed in 108 patients with CRC after curative surgery. Furthermore, cell-function analyses were performed, and the involvement of miR-4442 in regulating epithelial-mesenchymal transition (EMT) was examined. Preoperatively plasma miR-4442 levels were associated with CRC recurrence and exhibited an incremental increase with earlier recurrence dates. Moreover, miR-4442 demonstrated high sensitivity and specificity as a potential biomarker for early CRC recurrence. The expression of miR-4442 in cancer tissues of patients with metastatic liver cancer from CRC was higher than in normal liver, CRC, and normal colorectal tissues. The overexpression of miR-4442 promoted the proliferative, migratory, and invasive activities of CRC cells, decreased levels of RBMS1 and E-cadherin, and increased levels of N-cadherin and Snail1. Plasma miR-4442 is a clinically useful biomarker for predicting the early recurrence of CRC. Furthermore, miR-4442 regulates EMT in CRC by directly targeting the messenger RNA of RBMS1.

Deep Learning Based Methods for Breast Cancer Diagnosis: A Systematic Review and Future Direction

Breast cancer is one of the precarious conditions that affect women, and a substantive cure has not yet been discovered for it. With the advent of Artificial intelligence (AI), recently, deep learning techniques have been used effectively in breast cancer detection, facilitating early diagnosis and therefore increasing the chances of patients' survival. Compared to classical machine learning techniques, deep learning requires less human intervention for similar feature extraction. This study presents a systematic literature review on the deep learning-based methods for breast cancer detection that can guide practitioners and researchers in understanding the challenges and new trends in the field. Particularly, different deep learning-based methods for breast cancer detection are investigated, focusing on the genomics and histopathological imaging data. The study specifically adopts the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA), which offer a detailed analysis and synthesis of the published articles. Several studies were searched and gathered, and after the eligibility screening and quality evaluation, 98 articles were identified. The results of the review indicated that the Convolutional Neural Network (CNN) is the most accurate and extensively used model for breast cancer detection, and the accuracy metrics are the most popular method used for performance evaluation. Moreover, datasets utilized for breast cancer detection and the evaluation metrics are also studied. Finally, the challenges and future research direction in breast cancer detection based on deep learning models are also investigated to help researchers and practitioners acquire in-depth knowledge of and insight into the area.

MicroRNAs in esophageal squamous cell carcinoma: Application in prognosis, diagnosis, and drug delivery

MicroRNAs (miRNAs) play a vital role in various cell biology processes, including cancer formation. These small non-coding RNAs could function as diagnostic and prognostic markers. They may involve esophageal squamous cell carcinoma (ESCC) and distinctive miRNA expression profiles; they are also known as therapeutic targets in human diseases. Therefore, in this study, the function of miRNAs was reviewed regarding the prognosis and diagnosis of ESCC. The changes in miRNAs before and after cancer therapy and the effects of miRNAs on chemo-susceptibility patterns were also investigated. MiRNA delivery systems in ESCC were also highlighted, providing a perspective on how these systems can improve miRNA efficiency.

Extracellular Vesicle MicroRNA in Malignant Pleural Effusion

Lung and breast cancer are the two most common causes of malignant pleural effusion (MPE). MPE diagnosis plays a crucial role in determining staging and therapeutic interventions in these cancers. However, our understanding of the pathogenesis and progression of MPE at the molecular level is limited. Extracellular Vesicles (EVs) and their contents, including microRNAs (miRNAs), can be isolated from all bodily fluids, including pleural fluid. This study aims to compare EV-miRNA patterns of expression in MPE caused by breast (BA-MPE) and lung (LA-MPE) adenocarcinomas compared to the control group of heart-failure-induced effusions (HF-PE). We conducted an analysis of 24 pleural fluid samples (8 LA-MPE, 8 BA-MPE, and 8 HF-PE). Using NanoString technology, we profiled miRNAs within EVs isolated from 12 cases. Bioinformatic analysis demonstrated differential expression of miR-1246 in the MPE group vs. HF-PE group and miR-150-5p and miR-1246 in the BA-MPE vs. LA-MPE group, respectively. This difference was demonstrated and validated in an independent cohort using real-time PCR (RT-PCR). miRNA-1246 demonstrated 4-fold increased expression (OR: 3.87, 95% CI: 0.43, 35) in the MPE vs. HF-PE group, resulting in an area under the curve of 0.80 (95% CI: 0.60, 0.99). The highest accuracy for differentiating MPE vs. HF-PE was seen with a combination of miRNAs compared to each miRNA alone. Consistent with prior studies, this study demonstrates dysregulation of specific EV-based miRNAs in breast and lung cancer; pleural fluid provides direct access for the analysis of these EV-miRNAs as biomarkers and potential targets and may provide insight into the underlying pathogenesis of tumor progression. These findings should be explored in large prospective studies.

Potential utility of miRNAs for liquid biopsy in breast cancer

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

Isolation and Characterization of Urinary Extracellular Vesicles from Healthy Donors and Patients with Castration-Resistant Prostate Cancer

Prostate cancer (PCa) is the most commonly diagnosed malignancy among men in developed countries. The five-year survival rate for men diagnosed with early-stage PCa is approximately 100%, while it is less than 30% for castration-resistant PCa (CRPC). Currently, the detection of prostate-specific antigens as biomarkers for the prognosis of CRPC is criticized because of its low accuracy, high invasiveness, and high false-positive rate. Therefore, it is important to identify new biomarkers for prediction of CRPC progression. Extracellular vesicles (EVs) derived from tumors have been highlighted as potential markers for cancer diagnosis and prognosis. Specifically, urinary EVs directly reflect changes in the pathophysiological conditions of the urogenital system because it is exposed to prostatic secretions. Thus, detecting biomarkers in urinary EVs provides a promising approach for performing an accurate and non-invasive liquid biopsy for CPRC. In this study, we effectively isolated urinary EVs with low protein impurities using size-exclusion chromatography combined with ultrafiltration. After EV isolation and characterization, we evaluated the miRNAs in urinary EVs from healthy donors and patients with CRPC. The results indicated that miRNAs (miR-21-5p, miR-574-3p, and miR-6880-5p) could be used as potential biomarkers for the prognosis of CRPC. This analysis of urinary EVs contributes to the fast and convenient prognosis of diseases, including CRPC, in the clinical setting.

Current and Developing Liquid Biopsy Techniques for Breast Cancer

Breast cancer is the most commonly diagnosed cancer and leading cause of cancer mortality among woman worldwide. The techniques of diagnosis, prognosis, and therapy monitoring of breast cancer are critical. Current diagnostic techniques are mammography and tissue biopsy; however, they have limitations. With the development of novel techniques, such as personalized medicine and genetic profiling, liquid biopsy is emerging as the less invasive tool for diagnosing and monitoring breast cancer. Liquid biopsy is performed by sampling biofluids and extracting tumor components, such as circulating tumor cells (CTCs), circulating tumor DNA (ctDNA), cell-free mRNA (cfRNA) and microRNA (miRNA), proteins, and extracellular vehicles (EVs). In this review, we summarize and focus on the recent discoveries of tumor components and biomarkers applied in liquid biopsy and novel development of detection techniques, such as surface-enhanced Raman spectroscopy (SERS) and microfluidic devices.

A Review on the Role of miR-1246 in the Pathoetiology of Different Cancers

miR-1246 is a microRNA firstly recognized through application of a high throughput sequencing technique in human embryonic stem cells. Subsequent studies have shown the role of this microRNA in the carcinogenesis. miR-1246 has been found to exert oncogenic roles in colorectal, breast, renal, oral, laryngeal, pancreatic and ovarian cancers as well as melanoma and glioma. In lung, cervical and liver cancers, studies have reported contradictory results regarding the role of miR-1246. miR-1246 has been reported to regulate activity of RAF/MEK/ERK, GSK3β, Wnt/β-catenin, JAK/STAT, PI3K/AKT, THBS2/MMP and NOTCH2 pathways. In addition to affecting cell cycle progression and proliferation, miR-1246 can influence stemness and resistance of cancer cells to therapeutics. In the current review, we describe the summary of in vitro and in vivo studies about the influence of miR-1246 in carcinogenesis in addition to studies that measured expression levels of miR-1246 in clinical samples.

Identifying the Signatures and Rules of Circulating Extracellular MicroRNA for Distinguishing Cancer Subtypes

Cancer is one of the most threatening diseases to humans. It can invade multiple significant organs, including lung, liver, stomach, pancreas, and even brain. The identification of cancer biomarkers is one of the most significant components of cancer studies as the foundation of clinical cancer diagnosis and related drug development. During the large-scale screening for cancer prevention and early diagnosis, obtaining cancer-related tissues is impossible. Thus, the identification of cancer-associated circulating biomarkers from liquid biopsy targeting has been proposed and has become the most important direction for research on clinical cancer diagnosis. Here, we analyzed pan-cancer extracellular microRNA profiles by using multiple machine-learning models. The extracellular microRNA profiles on 11 cancer types and non-cancer were first analyzed by Boruta to extract important microRNAs. Selected microRNAs were then evaluated by the Max-Relevance and Min-Redundancy feature selection method, resulting in a feature list, which were fed into the incremental feature selection method to identify candidate circulating extracellular microRNA for cancer recognition and classification. A series of quantitative classification rules was also established for such cancer classification, thereby providing a solid research foundation for further biomarker exploration and functional analyses of tumorigenesis at the level of circulating extracellular microRNA.

RF-PCA: A New Solution for Rapid Identification of Breast Cancer Categorical Data Based on Attribute Selection and Feature Extraction

Breast cancer is one of the most common cancer diseases in women. The rapid and accurate diagnosis of breast cancer is of great significance for the treatment of cancer. Artificial intelligence and machine learning algorithms are used to identify breast malignant tumors, which can effectively solve the problems of insufficient recognition accuracy and long time-consuming in traditional breast cancer diagnosis methods. To solve these problems, we proposed a method of attribute selection and feature extraction based on random forest (RF) combined with principal component analysis (PCA) for rapid and accurate diagnosis of breast cancer. Firstly, RF was used to reduce 30 attributes of breast cancer categorical data. According to the average importance of attributes and out of bag error, 21 relatively important attribute data were selected for feature extraction based on PCA. The seven features extracted from PCA were used to establish an extreme learning machine (ELM) classification model with different activation functions. By comparing the classification accuracy and training time of these different models, the activation function of the hidden layer was determined as the sigmoid function. When the number of neurons in the hidden layer was 27, the accuracy of the test set was 98.75%, the accuracy of the training set was 99.06%, and the training time was only 0.0022 s. Finally, in order to verify the superiority of this method in breast cancer diagnosis, we compared with the ELM model based on the original breast cancer data and other intelligent classification algorithm models. The algorithm used in this article has a faster recognition time and a higher recognition accuracy than other algorithms. We also used the breast cancer data of breast tissue reactance features to verify the reliability of this method, and ideal results were obtained. The experimental results show that RF-PCA combined with ELM can significantly reduce the time required for the diagnosis of breast cancer, which has the ability of rapid and accurate identification of breast cancer and provides a theoretical basis for the intelligent diagnosis of breast cancer.

Liquid biopsy for breast cancer using extracellular vesicles and cell-free microRNAs as biomarkers

Improvement of breast cancer (BC) patient's outcome is directly related to early detection. However, there is still a lack of reliable biomarkers for diagnosis, prognosis and, treatment follow up in BC, leading researchers to study the potential of liquid biopsy based on circulating microRNAs (c-miRNAs). These c-miRNAs can be cell-free or associated with extracellular vesicles (EVs), and have great advantages such as stability in biofluids, noninvasive accessibility compared to current techniques (core-biopsy and surgery), and expression associated with pathogenic conditions. Recently, a new promising field of EV-derived miRNAs (EV-miRNAs) as cancer biomarkers has emerged, receiving special attention due to their selective vesicle sorting which makes them accurate for disease detection. In this review, we discuss new findings about c-miRNA and their potential as biomarkers for BC diagnosis, prognosis, and therapy. Additionally, we address the impact of limitations associated with the standardization of analysis techniques and methods on the implementation of these biomarkers in the clinical setting.

Analysis of miRNA signatures in CSF identifies upregulation of miR-21 and miR-146a/b in patients with multiple sclerosis and active lesions

BACKGROUND

MicroRNAs (miRNAs) have been reported as deregulated in active brain lesions derived from patients with multiple sclerosis (MS). In there, these post-transcriptional regulators may elicit very important effects but proper identification of miRNA candidates as potential biomarkers and/or therapeutic targets is scarcely available.

OBJECTIVE

The aim of the study was to detect the presence of a set of candidate miRNAs in cell-free cerebrospinal fluid (CSF) and to determine their association with gadolinium-enhancing (Gd+) lesions in order to assess their value as biomarkers of MS activity.

METHODS

Assessment of 28 miRNA candidates in cell-free CSF collected from 46 patients with MS (26 Gd+ and 20 Gd- patients) was performed by TaqMan assays and qPCR. Variations in their relative abundance were analyzed by the Mann-Whitney U test and further evaluated by receiver operating characteristic (ROC) analysis. Signaling pathways and biological functions of miRNAs were analyzed using bioinformatic tools (miRTarBase, Enrichr, REVIGO, and Cytoscape softwares).

RESULTS

Seven out of 28 miRNA candidates were detected in at least 75% of CSF samples. Consistent increase of miR-21 and miR-146a/b was found in Gd+ MS patients. This increase was in parallel to the number of Gd+ lesions and neurofilament light chain (NF-L) levels. Gene Ontology enrichment analysis revealed that the target genes of these miRNAs are involved in biological processes of key relevance such as apoptosis, cell migration and proliferation, and in cytokine-mediated signaling pathways.

CONCLUSION

Levels of miR-21 and miR-146a/b in cell-free CSF may represent valuable biomarkers to identify patients with active MS lesions.

First Attempts of the Use of 195Pt NMR of Phenylbenzothiazole Complexes as Spectroscopic Technique for the Cancer Diagnosis

Platinum complexes have been studied for cancer treatment for several decades. Furthermore, another important platinum characteristic is related to its chemical shifts, in which some studies have shown that the ¹⁹⁵Pt chemical shifts are very sensitive to the environment, coordination sphere, and oxidation state. Based on this relevant feature, Pt complexes can be proposed as potential probes for NMR spectroscopy, as the chemical shifts values will be different in different tissues (healthy and damaged) Therefore, in this paper, the main goal was to investigate the behavior of Pt chemical shifts in the different environments. Calculations were carried out in vacuum, implicit solvent, and inside the active site of P13K enzyme, which is related with breast cancer, using the density functional theory (DFT) method. Moreover, the investigation of platinum complexes with a selective moiety can contribute to early cancer diagnosis. Accordingly, the Pt complexes selected for this study presented a selective moiety, the 2-(4′aminophenyl)benzothiazole derivative. More specifically, two Pt complexes were used herein: One containing chlorine ligands and one containing water in place of chlorine. Some studies have shown that platinum complexes coordinated to chlorine atoms may suffer hydrolyses inside the cell due to the low chloride ion concentration. Thus, the same calculations were performed for both complexes. The results showed that both complexes presented different chemical shift values in the different proposed environments. Therefore, this paper shows that platinum complexes can be a potential probe in biological systems, and they should be studied not only for cancer treatment, but also for diagnosis.

Development and Validation of an Esophageal Squamous Cell Carcinoma Detection Model by Large-Scale MicroRNA Profiling

IMPORTANCE

Patients with late-stage esophageal squamous cell carcinoma (ESCC) have a poor prognosis. Noninvasive screening tests using serum microRNAs (miRNAs) to accurately detect early-stage ESCC are needed to improve mortality.

OBJECTIVE

To establish a model using serum miRNAs to distinguish patients with ESCC from noncancer controls.

DESIGN, SETTING, AND PARTICIPANTS

In this case-control study, serum miRNA expression profiles of patients with ESCC (n = 566) and control patients without cancer (n = 4965) were retrospectively analyzed to establish a diagnostic model, which was tested in a training set and confirmed in a validation set. Patients histologically diagnosed as having ESCC who did not receive prior therapy or have a past or concurrent cancer other than ESCC were enrolled from the National Cancer Center Hospital in Tokyo, Japan. Between October 2010 and November 2015, control samples were collected from the National Cancer Center Biobank, the Biobank of the National Center for Geriatrics and Gerontology, and the general population undergoing routine health examination. Data analysis was performed between August 2015 and October 2018. Serum samples were randomly divided into discovery and validation sets.

MAIN OUTCOMES AND MEASURES

The expression of 2565 miRNAs was assessed in each sample. The discriminant model (named the EC index) was evaluated in the training set using Fisher linear discriminant analysis with a greedy algorithm. Receiver operating characteristic curve analysis evaluated the diagnostic ability of the model in the validation set.

RESULTS

In the training set, 283 patients with esophageal cancer (median age, 67 years [range, 37-90 years]; 83.4% male) were compared with 283 control patients (median age, 54 years [range, 22-100 years]; 43.1% male), and the EC index was constructed using 6 miRNAs (miR-8073, miR-6820-5p, miR-6794-5p, miR-3196, miR-744-5p, and miR-6799-5p). The area under the receiver operating characteristic curve was 1.00, with sensitivity of 1.00 and specificity of 0.98. The validation set included 283 patients (median age, 66 years [range, 42-87 years]; 83.0% male) and 4682 control patients (median age, 68 years [range, 20-98 years]; 44.7% male), and the area under the receiver operating characteristic curve for the EC index was 1.00, with sensitivity of 0.96 and specificity of 0.98.

CONCLUSIONS AND RELEVANCE

What appears to be novel serum miRNA discriminant model was developed for the diagnosis of ESCC. A multicenter prospective study is ongoing to confirm the present observations.

MicroRNA-4719 and microRNA-6756-5p Correlate with Castration-Resistant Prostate Cancer Progression through Interleukin-24 Regulation

Prostate cancer (PCa) is the second leading cause of cancer death in the United States. The five-year survival rate for men diagnosed with localized PCa is nearly 100%, yet for those diagnosed with aggressive PCa, it is less than 30%. The pleiotropic cytokine Interleukin-24 (IL-24) has been shown to specifically kill PCa cells compared to normal cells when overexpressed in both in vitro and in vivo studies. Despite this, the mechanisms regulating IL-24 in PCa are not well understood. Since specific microRNAs (miRNAs) are dysregulated in PCa, we used miRNA target prediction algorithm tools to identify miR-4719 and miR-6556-5p as putative regulators of IL-24. This study elucidates the expression profile and role of miR-4719 and miR-6756-5p as regulators of IL-24 in PCa. qRT-PCR analysis shows miR-4719 and miR-6756-5p overexpression significantly decreases the expression of IL-24 in PCa cells compared to the negative control. Compared to the indolent PCa and normal prostate epithelial cells, miR-4719 and miR-6756-5p are significantly overexpressed in castration-resistant prostate cancer (CRPC) cell lines, indicating that their gain may be an early event in PCa progression. Moreover, miR-4719 and miR-6756-5p are significantly overexpressed in the CRPC cell line of African-American males (E006AA-hT) compared to CRPC cell lines of Caucasian males (PC-3 and DU-145), indicating that miR-4719 and miR-6756-5p may also play a role in racial disparity. Lastly, the inhibition of expression of miR-4719 and miR-6756-5p significantly increases IL-24 expression and inhibits proliferation and migration of CRPC cell lines. Our findings indicate that miR-4719 and miR-6756-5p may regulate CRPC progression through the targeting of IL-24 expression and may be biomarkers that differentiate between indolent and CRPC. Strategies to inhibit miR-4719 and miR-6756-5p expression to increase IL-24 in PCa may have therapeutic efficacy in aggressive PCa.

Early identification of recurrence in ovarian cancer: a comparison between the ovarian cancer metastasis index and CA-125 levels

Ovarian cancer (OC) is the second most common gynecologic malignancy. A clinical observational study was performed to investigate whether indicators that assess the risk of metastasis can identify recurrence earlier in OC patients. By successfully recruiting 41 patients with OC who underwent chemotherapy, we compared cancer antigen-125 (CA-125) and the ovarian cancer metastasis index (OCMI), which was previously developed by us in the clinic for this purpose. Our results showed that patients and their families generally took a sensible attitude toward disease progression and were willing to accept a new way to gain knowledge about the disease. Herein, the new way was the possibility of monitoring recurrence by introducing the OCMI into the clinic. Fifteen patients experienced recurrence during chemotherapy, implying treatment failure. For 53% of these patients, an abnormally high OCMI suggested a strong tendency toward metastasis at least one chemotherapy cycle prior to the pathological examination confirming recurrence. In comparison, the early recognition rate of recurrence using CA-125 levels was merely 13%. Furthermore, we found that the mean values of the OCMI no longer declined after the fourth chemotherapy cycle, implying that excessive chemotherapy brings no benefit to OC patients. In conclusion, our findings provide a novel and feasible approach to monitor the effectiveness of chemotherapy in the treatment of OC by assessing the potential risk of metastasis.

Multi-scale representation of proteomic data exhibits distinct microRNA regulatory modules in non-smoking female patients with lung adenocarcinoma

Adenocarcinoma in female non-smokers is an under-explored subgroup of non-small cell lung cancer (NSCLC), in which the molecular mechanism and genetic risk factors remain unclear. We analyzed the protein profiles of plasma samples of 45 patients in this subgroup and 60 non-cancer subjects using surface-enhanced laser desorption/ionization time-of- flight mass spectrometry. Among 85 peaks of mass spectra, the differential expression analysis identified 15 markers based on False Discovery Rate control and the Discrete Wavelet Transforms further selected a cluster of 6 markers that were consistently observed at multiple scales of mass-charge ratios. This marker cluster, corresponding to 7 unique proteins, was able to distinguish the female non-smokers with adenocarcinoma from non-cancer subjects with a value of accuracy of 87.6%. We also predicted the role of competing endogenous RNAs (ceRNAs) in 3 out of these 7 proteins. Other studies reported that these ceRNAs and their targeting microRNAs, miR-206 and miR-613, were significantly associated with NSCLC. This study paves a crucial path for further investigating the genetic markers and molecular mechanism of this special NSCLC subgroup.