scholarly journals Plasma-derived exosomal miR-15a-5p as a promising diagnostic biomarker for early detection of endometrial carcinoma

2021 ◽  
Vol 20 (1) ◽  
Author(s):  
Lanyun Zhou ◽  
Wei Wang ◽  
Fenfen Wang ◽  
Siqi Yang ◽  
Jiaqi Hu ◽  
...  

AbstractEndometrial cancer (EC) is a major cause of death among gynecologic malignancies. To improve early detection of EC in patients, we carried out a large plasma-derived exosomal microRNA (miRNA) studies for diagnostic biomarker discovery in EC. Small RNA sequencing was performed to identify candidate exosomal miRNAs as diagnostic biomarkers in 56 plasma samples from healthy subjects and EC patients. These miRNA candidates were further validated in 202 independent plasma samples by droplet digital PCR (ddPCR), 32 pairs of endometrial tumors and adjacent normal tissues by quantitative real-time PCR (qRT-PCR), and matched plasma samples of 12 patients before and after surgery by ddPCR. miR-15a-5p, miR-106b-5p, and miR107 were significantly upregulated in exomes isolated from plasma samples of EC patients compared with healthy subjects. Particularly, miR-15a-5p alone yielded an AUC value of 0.813 to distinguish EC patients with stage I from healthy subjects. The integration of miR-15a-5p and serum tumor markers (CEA and CA125) achieved a higher AUC value of 0.899. There was also a close connection between miR-15a-5p and clinical manifestations in EC patients. Its exosomal expression was not only associated with the depth of muscular infiltration and aggressiveness of EC, but also correlated with levels of reproductive hormones such as TTE and DHEAS. Collectively, plasma-derived exosomal miR-15a-5p is a promising and effective diagnostic biomarker for the early detection of endometrial cancer.

2019 ◽  
Vol 20 (23) ◽  
pp. 6082 ◽  
Author(s):  
Stine Thorsen ◽  
Irina Gromova ◽  
Ib Christensen ◽  
Simon Fredriksson ◽  
Claus Andersen ◽  
...  

The burden of colorectal cancer (CRC) is considerable—approximately 1.8 million people are diagnosed each year with CRC and of these about half will succumb to the disease. In the case of CRC, there is strong evidence that an early diagnosis leads to a better prognosis, with metastatic CRC having a 5-year survival that is only slightly greater than 10% compared with up to 90% for stage I CRC. Clearly, biomarkers for the early detection of CRC would have a major clinical impact. We implemented a coherent gel-based proteomics biomarker discovery platform for the identification of clinically useful biomarkers for the early detection of CRC. Potential protein biomarkers were identified by a 2D gel-based analysis of a cohort composed of 128 CRC and site-matched normal tissue biopsies. Potential biomarkers were prioritized and assays to quantitatively measure plasma expression of the candidate biomarkers were developed. Those biomarkers that fulfilled the preset criteria for technical validity were validated in a case-control set of plasma samples, including 70 patients with CRC, adenomas, or non-cancer diseases and healthy individuals in each group. We identified 63 consistently upregulated polypeptides (factor of four-fold or more) in our proteomics analysis. We selected 10 out of these 63 upregulated polypeptides, and established assays to measure the concentration of each one of the ten biomarkers in plasma samples. Biomarker levels were analyzed in plasma samples from healthy individuals, individuals with adenomas, CRC patients, and patients with non-cancer diseases and we identified one protein, tropomyosin 3 (Tpm3) that could discriminate CRC at a significant level (p = 0.0146). Our results suggest that at least one of the identified proteins, Tpm3, could be used as a biomarker in the early detection of CRC, and further studies should provide unequivocal evidence for the real-life clinical validity and usefulness of Tpm3.


2018 ◽  
Vol 88 (3-4) ◽  
pp. 151-157 ◽  
Author(s):  
Scott W. Leonard ◽  
Gerd Bobe ◽  
Maret G. Traber

Abstract. To determine optimal conditions for blood collection during clinical trials, where sample handling logistics might preclude prompt separation of erythrocytes from plasma, healthy subjects (n=8, 6 M/2F) were recruited and non-fasting blood samples were collected into tubes containing different anticoagulants (ethylenediaminetetra-acetic acid (EDTA), Li-heparin or Na-heparin). We hypothesized that heparin, but not EDTA, would effectively protect plasma tocopherols, ascorbic acid, and vitamin E catabolites (α- and γ-CEHC) from oxidative damage. To test this hypothesis, one set of tubes was processed immediately and plasma samples were stored at −80°C, while the other set was stored at 4°C and processed the following morning (~30 hours) and analyzed, or the samples were analyzed after 6 months of storage. Plasma ascorbic acid, as measured using HPLC with electrochemical detection (LC-ECD) decreased by 75% with overnight storage using EDTA as an anticoagulant, but was unchanged when heparin was used. Neither time prior to processing, nor anticoagulant, had any significant effects upon plasma α- or γ-tocopherols or α- or γ-CEHC concentrations. α- and γ-tocopherol concentrations remained unchanged after 6 months of storage at −80°C, when measured using either LC-ECD or LC/mass spectrometry. Thus, refrigeration of whole blood at 4°C overnight does not change plasma α- or γ-tocopherol concentrations or their catabolites. Ascorbic acid is unstable in whole blood when EDTA is used as an anticoagulant, but when whole blood is collected with heparin, it can be stored overnight and subsequently processed.


2019 ◽  
Vol 20 (22) ◽  
pp. 5697 ◽  
Author(s):  
Michelle E. Pewarchuk ◽  
Mateus C. Barros-Filho ◽  
Brenda C. Minatel ◽  
David E. Cohn ◽  
Florian Guisier ◽  
...  

Recent studies have uncovered microRNAs (miRNAs) that have been overlooked in early genomic explorations, which show remarkable tissue- and context-specific expression. Here, we aim to identify and characterize previously unannotated miRNAs expressed in gastric adenocarcinoma (GA). Raw small RNA-sequencing data were analyzed using the miRMaster platform to predict and quantify previously unannotated miRNAs. A discovery cohort of 475 gastric samples (434 GA and 41 adjacent nonmalignant samples), collected by The Cancer Genome Atlas (TCGA), were evaluated. Candidate miRNAs were similarly assessed in an independent cohort of 25 gastric samples. We discovered 170 previously unannotated miRNA candidates expressed in gastric tissues. The expression of these novel miRNAs was highly specific to the gastric samples, 143 of which were significantly deregulated between tumor and nonmalignant contexts (p-adjusted < 0.05; fold change > 1.5). Multivariate survival analyses showed that the combined expression of one previously annotated miRNA and two novel miRNA candidates was significantly predictive of patient outcome. Further, the expression of these three miRNAs was able to stratify patients into three distinct prognostic groups (p = 0.00003). These novel miRNAs were also present in the independent cohort (43 sequences detected in both cohorts). Our findings uncover novel miRNA transcripts in gastric tissues that may have implications in the biology and management of gastric adenocarcinoma.


Breast Cancer ◽  
2021 ◽  
Author(s):  
Xuemin Liu ◽  
Qingyu Chang ◽  
Haiqiang Wang ◽  
Hairong Qian ◽  
Yikun Jiang

Abstract Background MicroRNA-155 (miR-155) may function as a diagnostic biomarker of breast cancer (BC). Nevertheless, the available evidence is controversial. Therefore, we performed this study to summarize the global predicting role of miR-155 for early detection of BC and preliminarily explore the functional roles of miR-155 in BC. Methods We first collected published studies and applied the bivariate meta-analysis model to generate the pooled diagnostic parameters of miR-155 in diagnosing BC such as sensitivity, specificity and area under curve (AUC). Then, we applied function enrichment and protein–protein interactions (PPI) analyses to explore the potential mechanisms of miR-155. Results A total of 21 studies were finally included. The results indicated that miR-155 allowed for the discrimination between BC patients and healthy controls with a sensitivity of 0.87 (95% CI 0.78–0.93), specificity of 0.82 (0.72–0.89), and AUC of 0.91 (0.88–0.93). In addition, the overall sensitivity, specificity and AUC for circulating miR-155 were 0.88 (0.76–0.95), 0.83 (0.72–0.90), and 0.92 (0.89–0.94), respectively. Function enrichment analysis revealed several vital ontologies terms and pathways associated with BC occurrence and development. Furthermore, in the PPI network, ten hub genes and two significant modules were identified to be involved in some important pathways associated with the pathogenesis of BC. Conclusions We demonstrated that miR-155 has great potential to facilitate accurate BC detection and may serve as a promising diagnostic biomarker for BC. However, well-designed cohort studies and biological experiments should be implemented to confirm the diagnostic value of miR-155 before it can be applied to routine clinical procedures.


2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Sanna Iivanainen ◽  
Jussi Ekstrom ◽  
Henri Virtanen ◽  
Vesa V. Kataja ◽  
Jussi P. Koivunen

Abstract Background Immune-checkpoint inhibitors (ICIs) have introduced novel immune-related adverse events (irAEs), arising from various organ systems without strong timely dependency on therapy dosing. Early detection of irAEs could result in improved toxicity profile and quality of life. Symptom data collected by electronic (e) patient-reported outcomes (PRO) could be used as an input for machine learning (ML) based prediction models for the early detection of irAEs. Methods The utilized dataset consisted of two data sources. The first dataset consisted of 820 completed symptom questionnaires from 34 ICI treated advanced cancer patients, including 18 monitored symptoms collected using the Kaiku Health digital platform. The second dataset included prospectively collected irAE data, Common Terminology Criteria for Adverse Events (CTCAE) class, and the severity of 26 irAEs. The ML models were built using extreme gradient boosting algorithms. The first model was trained to detect the presence and the second the onset of irAEs. Results The model trained to predict the presence of irAEs had an excellent performance based on four metrics: accuracy score 0.97, Area Under the Curve (AUC) value 0.99, F1-score 0.94 and Matthew’s correlation coefficient (MCC) 0.92. The prediction of the irAE onset was more difficult with accuracy score 0.96, AUC value 0.93, F1-score 0.66 and MCC 0.64 but the model performance was still at a good level. Conclusion The current study suggests that ML based prediction models, using ePRO data as an input, can predict the presence and onset of irAEs with a high accuracy, indicating that ePRO follow-up with ML algorithms could facilitate the detection of irAEs in ICI-treated cancer patients. The results should be validated with a larger dataset. Trial registration Clinical Trials Register (NCT3928938), registration date the 26th of April, 2019


Cancers ◽  
2021 ◽  
Vol 13 (1) ◽  
pp. 147
Author(s):  
Leticia Díaz-Beltrán ◽  
Carmen González-Olmedo ◽  
Natalia Luque-Caro ◽  
Caridad Díaz ◽  
Ariadna Martín-Blázquez ◽  
...  

Purpose: The aim of this study is to identify differential metabolomic signatures in plasma samples of distinct subtypes of breast cancer patients that could be used in clinical practice as diagnostic biomarkers for these molecular phenotypes and to provide a more individualized and accurate therapeutic procedure. Methods: Untargeted LC-HRMS metabolomics approach in positive and negative electrospray ionization mode was used to analyze plasma samples from LA, LB, HER2+ and TN breast cancer patients and healthy controls in order to determine specific metabolomic profiles through univariate and multivariate statistical data analysis. Results: We tentatively identified altered metabolites displaying concentration variations among the four breast cancer molecular subtypes. We found a biomarker panel of 5 candidates in LA, 7 in LB, 5 in HER2 and 3 in TN that were able to discriminate each breast cancer subtype with a false discovery range corrected p-value < 0.05 and a fold-change cutoff value > 1.3. The model clinical value was evaluated with the AUROC, providing diagnostic capacities above 0.85. Conclusion: Our study identifies metabolic profiling differences in molecular phenotypes of breast cancer. This may represent a key step towards therapy improvement in personalized medicine and prioritization of tailored therapeutic intervention strategies.


2021 ◽  
Vol 19 (1) ◽  
Author(s):  
Weiwei Feng ◽  
Nan Jia ◽  
Haining Jiao ◽  
Jun Chen ◽  
Yan Chen ◽  
...  

Abstract Background Currently, there is no reliable blood-based marker to track tumor recurrence in endometrial cancer (EC) patients. Liquid biopsies, specifically, circulating tumor DNA (ctDNA) analysis emerged as a way to monitor tumor metastasis. The objective of this study was to examine the feasibility of ctDNA in recurrence surveillance and prognostic evaluation of high-risk EC. Methods Tumor tissues from nine high-risk EC patients were collected during primary surgery and tumor DNA was subjected to next generation sequencing to obtain the initial mutation spectrum using a 78 cancer-associated gene panel. Baseline and serial post-operative plasma samples were collected and droplet digital PCR (ddPCR) assays for patient-specific mutations were developed to track the mutations in the ctDNA in serial plasma samples. Log-rank test was used to assess the association between detection of ctDNA before or after surgery and disease-free survival. Results Somatic mutations were identified in all of the cases. The most frequent mutated genes were PTEN, FAT4, ARID1A, TP53, ZFHX3, ATM, and FBXW7. For each patient, personalized ddPCR assays were designed for one-to-three high-frequent mutations. DdPCR analysis and tumor panel sequencing had a high level of agreement in the assessment of the mutant allele fractions in baseline tumor tissue DNA. CtDNA was detected in 67% (6 of 9) of baseline plasma samples, which was not predictive of disease-free survival (DFS). CtDNA was detected in serial post-operative plasma samples (ctDNA tracking) of 44% (4 of 9) of the patients, which predicted tumor relapse. The DFS was a median of 9 months (ctDNA detected) versus median DFS undefined (ctDNA not detected), with a hazard ratio of 17.43 (95% CI, 1.616–188.3). The sensitivity of post-operative ctDNA detection in estimating tumor relapse was 100% and specificity was 83.3%, which was superior to CA125 or HE4. Conclusions Personalized ctDNA detection was effective and stable for high-risk EC. CtDNA tracking in post-operative plasma is valuable for predicting tumor recurrence.


Cancers ◽  
2021 ◽  
Vol 13 (4) ◽  
pp. 718
Author(s):  
Kelechi Njoku ◽  
Amy E. Campbell ◽  
Bethany Geary ◽  
Michelle L. MacKintosh ◽  
Abigail E. Derbyshire ◽  
...  

Endometrial cancer is the most common malignancy of the female genital tract and a major cause of morbidity and mortality in women. Early detection is key to ensuring good outcomes but a lack of minimally invasive screening tools is a significant barrier. Most endometrial cancers are obesity-driven and develop in the context of severe metabolomic dysfunction. Blood-derived metabolites may therefore provide clinically relevant biomarkers for endometrial cancer detection. In this study, we analysed plasma samples of women with body mass index (BMI) ≥ 30 kg/m2 and endometrioid endometrial cancer (cases, n = 67) or histologically normal endometrium (controls, n = 69), using a mass spectrometry-based metabolomics approach. Eighty percent of the samples were randomly selected to serve as a training set and the remaining 20% were used to qualify test performance. Robust predictive models (AUC > 0.9) for endometrial cancer detection based on artificial intelligence algorithms were developed and validated. Phospholipids were of significance as biomarkers of endometrial cancer, with sphingolipids (sphingomyelins) discriminatory in post-menopausal women. An algorithm combining the top ten performing metabolites showed 92.6% prediction accuracy (AUC of 0.95) for endometrial cancer detection. These results suggest that a simple blood test could enable the early detection of endometrial cancer and provide the basis for a minimally invasive screening tool for women with a BMI ≥ 30 kg/m2.


2021 ◽  
pp. 1-13
Author(s):  
Teva Phanaksri ◽  
Yodying Yingchutrakul ◽  
Sittiruk Roytrakul ◽  
Sattrachai Prasopdee ◽  
Anthicha Kunjantarachot ◽  
...  

BACKGROUND: Patients infected with a parasite often develop opisthorchiasis viverrini, which often progresses into cholangiocarcinoma (CCA) due to the asymptomatic nature of the infection. Currently, there are no effective diagnostic methods for opisthorchiasis or cholangiocarcinoma. OBJECTIVE: The aim of this study was to identify the host-responsive protein that can be developed as a diagnostic biomarker of opisthorchiasis and cholangiocarcinoma. METHODS: Plasma samples were collected from non-OVCCA, OV, and CCA subjects, and the proteomes were investigated by LC-MS/MS. Venn diagrams and protein network prediction by STITCH were used to identify the potential biomarkers. The level of candidate protein, the plasma checkpoint protein 1 (Chk1), was measured by indirect enzyme-linked immunosorbent assay (ELISA). RESULTS: Chk1 was present in the center of the protein network analysis in both the OV and CCA groups. In addition, the plasma Chk1 levels were significantly increased in both groups (P< 0.05). The sensitivity of the opisthorchiasis viverrini and cholangiocarcinoma was 59.38% and 65.62%, respectively, while the specificity of both was 85.71%. CONCLUSION: Chk1 was identified by differential plasma proteomes and was increased in O. viverrini-infected and cholangiocarcinoma-derived plasma samples. Higher levels of plasma Chk1 levels may serve as a potential diagnostic biomarker for opisthorchiasis and cholangiocarcinoma.


2005 ◽  
Vol 11 (3) ◽  
pp. 353-360 ◽  
Author(s):  
Roberta Seraglia ◽  
Susanna Vogliardi ◽  
Graziella Allegri ◽  
Stefano Comai ◽  
Mario Lise ◽  
...  

Fourteen blood samples from patients with melanomas and 11 blood samples from healthy subjects were analyzed by matrix-assisted laser desorption/ionization mass spectrometry. The study focussed on species of low molecular weight, in the 800–5000 Da range, present in plasma and sera. While for healthy subjects plasma samples lead to the production of a higher number of ionic species, for melanoma patients a high number of diagnostic ions, present with high frequency and with quite high relative abundance, are present, in particular, in serum samples and, to a lesser extent, also in plasma. Since plasma samples are obtained more easily in comparison to sera, it is possible to suggest that plasma can also be used for these studies.


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