Multi-MicroRNA Analysis Can Improve the Diagnostic Performance of Mammography in Determining Breast Cancer Risk.

The objective of this study was to determine whether multi-microRNA analysis using a combination of four microRNA biomarkers (miR-1246, 202, 21, and 219B) could improve the diagnostic performance of mammography in determining breast cancer risk by age group (under 50 vs. over 50) and distinguish breast cancer from benign breast diseases and other cancers (thyroid, colon, stomach, lung, liver, and cervix cancers). To verify breast cancer classification performance of the four miRNA biomarkers and whether the model providing breast cancer risk score could distinguish between benign breast disease and other cancers, the model was verified using nonlinear support vector machine (SVM) and generalized linear model (GLM) and age and four miRNA qRT-PCR analysis values (dCt) were input to these models. Breast cancer risk scores for each Breast Imaging-Reporting and Data System (BI-RADS) category in multi-microRNA analysis were analyzed to examine the correlation between breast cancer risk scores and mammography categories. We generated two models using two classification algorithms, SVM and GLM, with a combination of four miRNA biomarkers showing high performance and sensitivities of 84.5% and 82.1%, a specificity of 85%, and areas under the curve (AUCs) of 0.967 and 0.965, respectively, which showed consistent performance across all stages of breast cancer and patient ages. The results of this study showed that this multi-microRNA analysis using the four miRNA biomarkers was effective in classifying breast cancer in patients under the age of 50, which is challenging to accurately diagnose. In addition, breast cancer and benign breast diseases can be classified, showing the possibility of helping with diagnosis by mammography. Verification of the performance of the four miRNA biomarkers confirmed that multi-microRNA analysis could be used as a new breast cancer screening aid to improve the accuracy of mammography. However, many factors must be considered for clinical use. Further validation with an appropriate screening population in large clinical trials is required. This trial is registered with (KNUCH 2022-04-036).

Multiple biomarkers are more accurate than a combination of carbohydrate antigen 125 and human epididymis protein 4 for ovarian cancer screening.

OBJECTIVE: The objective of this study was to compare and evaluate the diagnostic value of serum carbohydrate antigen 125 (CA125) and/or human epididymis protein 4 (HE4) and a panel of novel multiple biomarkers in patients with ovarian tumors to identify more accurate and effective markers for screening ovarian cancer. METHODS: Candidate ovarian cancer biomarkers were selected based on a literature search. Dozens of candidate biomarkers were examined using 143 serum samples from patients with ovarian cancer and 157 healthy serum samples as noncancer controls. To select the optimal marker panel for an ovarian cancer classification model, a set of biomarker panels was created with the number of possible combinations of eight biomarkers. Using the set of biomarkers as an input variable, the optimal biomarker panel was selected by examining the performance of the biomarker panel set using the Random Forest algorithm as a non-linear classification method and a 10-fold cross-validation technique. RESULTS: The final selected optimal combination of five biomarkers (CA125, HE4, cancer antigen 15-3, apolipoprotein [Apo] A1, and ApoA2) exhibited a sensitivity of 93.71% and specificity of 93.63% for ovarian cancer detection during validation. CONCLUSION: Combining multiple biomarkers is a valid strategy for ovarian cancer diagnosis and can be used as a minimally invasive screening method for early ovarian cancer. A panel of five optimal biomarkers, including CA125 and HE4, was verified in this study. These can potentially be used as clinical biomarkers for early detection of ovarian cancer.

Diagnostic value of combining tumor and inflammatory biomarkers in detecting common cancers in Korea.

BACKGROUND: The ultimate goal of cancer screening is to diagnose invasive cancers early, while they are still curable. We aimed to validate the diagnostic value of blood-derived protein biomarkers that we developed for six common cancer in Korea. METHODS: We have discovered 12 protein biomarkers that are useful in differentiating cancer patients from healthy controls using two-dimensional gel electrophoresis (2-DE), surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF-MS), and literature review. Cancer patients (stomach, colon, liver, lung, breast, and prostate) and control subjects were collected and tested data sets were used to generate predictive models that identify risk scores for each cancer. The validation study was done in serum samples of an independent patient cohort Receiver operating characteristic (ROC) analyses were conducted to evaluate the diagnostic performance of the biomarkercombinations. RESULTS: The AUCs of the model in the test set were 0.971, 0.960, 0.969, 0.942, 0.834, and 0.985 for stomach, colon, liver, lung, breast, and prostate cancer, respectively. CONCLUSIONS: Combining multiple tumor and systemic inflammatory biomarkers proved to be a valid strategy in the diagnosis of six common cancers in Korea. Further validation of appropriate screening populations through large-scale clinical trials are warranted.

Multiple microRNAs as biomarkers for early breast cancer diagnosis.

MicroRNA (miRNA or miR) is stably present in plasma. It has been reported that miRNA could be used for detecting cancer. Circulating miRNAs are being increasingly recognized as powerful biomarkers in a number of different pathologies, including in breast cancer. The aim of the current study was to establish and validate miRNA sets that are useful for the early diagnosis of breast cancer. Specifically, the current study intended to determine whether miRNA biomarkers were tumor-specific and to statistically verify whether circulating miRNA analysis could be used for breast cancer diagnosis. In the present study, a total of nine candidate miRNA biomarkers were selected by examining reference miRNAs associated with the generation and progression of breast cancer to identify novel miRNAs that could be used to detect early breast cancer. A total of 226 plasma samples from patients with breast cancer were used. In addition, 146 plasma healthy samples were used as non-cancer controls. These samples were divided into training and validation cohorts. The training cohort was used to identify a combination of miRNA that could detect breast cancer. The validation cohort was used to validate this combination of miRNA. Total RNAs were isolated from collected samples. A total of 9 miRNAs were quantified using reverse-transcription quantitative PCR. A total of nine candidate miRNA expression levels were compared between patients with breast cancer and healthy controls. It was indicated that combinations of two or more of the nine miRNAs could detect breast cancer with higher accuracy than the use of a single biomarker. As a representative example, combinations of four miRNAs (miR-1246+miR-206+miR-24+miR-373) of the nine miRNAs had a sensitivity of 98%, a specificity of 96% and an accuracy of 97% for breast cancer detection in the validation cohort. The results of the present study suggest that multiple miRNAs could be used as potential biomarkers for early diagnosis of breast cancer. These biomarkers are expected to overcome limitations of mammography when used as an auxiliary diagnosis of mammography.

Evaluation of the Value of Multiplex MicroRNA Analysis as a Breast Cancer Screening in Korean Women under 50 Years of Age with a High Proportion of Dense Breasts.

This study was conducted to confirm the performance of the microRNA (miRNA) biomarker combination as a new breast cancer screening method in Korean women under the age of 50 with a high percentage of dense breasts. To determine the classification performance of a set of miRNA biomarkers (miR-1246, 202, 21, and 219B) useful for breast cancer screening, we determined whether there was a significant difference between the breast cancer and healthy control groups through box plots and the Mann-Whitney U-test, which was further examined in detail by age group. To verify the classification performance of the 4 miRNA biomarker set, 4 classification methods (logistic regression, random forest, XGBoost, and generalized linear model plus random forest) were applied, and 10-fold cross-validation was used as a validation method to improve performance stability. We confirmed that the best breast cancer detection performance was achievable in patients under 50 years of age when the set of 4 miRNAs were used. Under the age of 50, the 4 miRNA biomarkers showed the highest performance with a sensitivity of 85.29%, specificity of 93.33%, and area under the curve (AUC) of 0.961. Examining the results of 4 miRNA biomarkers was found to be an effective strategy for diagnosing breast cancer in Korean women under 50 years of age with dense breasts, and hence has the potential as a new breast cancer screening tool. Further validation in an appropriate screening population with large-scale clinical trials is required.

Biomarker Panel for the Diagnosis of Pancreatic Ductal Adenocarcinoma.

A single tumor marker has a low diagnostic value in pancreatic cancer. Combinations of multiple biomarkers and unique analysis algorithms can be applied to overcome these limitations. This study sought to develop diagnostic algorithms using multiple biomarker panels and to validate their performance in the diagnosis of pancreatic ductal adenocarcinoma (PDAC). We used blood samples from 180 PDAC patients and 573 healthy controls. Candidate markers consisted of 11 markers that are commonly expressed in various cancers and which have previously demonstrated increased expression in pancreatic cancer. Samples were divided into training and validation sets. Five linear or non-linear classification methods were used to determine the optimal model. Differences were identified in 10 out of the 11 markers tested. We identified 2047 combinations, all of which were applied to 5 separate algorithms. The new biomarker combination consisted of 6 markers (ApoA1, CA125, CA19-9, CEA, ApoA2, and TTR). The area under the curve, specificity, and sensitivity were 0.992, 95%, and 96%, respectively, in the training set. Meanwhile, the measures were 0.993, 96%, and 93% in the validation set. This study demonstrated the utility of multiple biomarker combinations in the early detection of PDAC. A diagnostic panel of 6 biomarkers was developed and validated. These algorithms will assist in the early diagnosis of PDAC.

Controlled edge dependent stacking of WS2-WS2 Homo- and WS2-WSe2 Hetero-structures: A Computational Study.

Transition Metal Dichalcogenides (TMDs) are one of the most studied two-dimensional materials in the last 5-10 years due to their extremely interesting layer dependent properties. Despite the presence of vast research work on TMDs, the complex relation between the electro-chemical and physical properties make them the subject of further research. Our main objective is to provide a better insight into the electronic structure of TMDs. This will help us better understand the stability of the bilayer post growth homo/hetero products based on the various edge-termination, and different stacking of the two layers. In this regard, two Tungsten (W) based non-periodic chalcogenide flakes (sulfides and selenides) were considered. An in-depth analysis of their different edge termination and stacking arrangement was performed via Density Functional Theory method using VASP software. Our finding indicates the preference of chalcogenide (c-) terminated structures over the metal (m-) terminated structures for both homo and heterobilayers, and thus strongly suggests the nonexistence of the m-terminated TMDs bilayer products.

Diagnostic Value of Combining Tumor and Inflammatory Markers in Lung Cancer.

BACKGROUND: Despite major advances in lung cancer treatment, early detection remains the most promising way of improving outcomes. To detect lung cancer in earlier stages, many serum biomarkers have been tested. Unfortunately, no single biomarker can reliably detect lung cancer. We combined a set of 2 tumor markers and 4 inflammatory or metabolic markers and tried to validate the diagnostic performance in lung cancer. METHODS: We collected serum samples from 355 lung cancer patients and 590 control subjects and divided them into training and validation datasets. After measuring serum levels of 6 biomarkers (human epididymis secretory protein 4 [HE4], carcinoembryonic antigen [CEA], regulated on activation, normal T cell expressed and secreted [RANTES], apolipoprotein A2 [ApoA2], transthyretin [TTR], and secretory vascular cell adhesion molecule-1 [sVCAM-1]), we tested various sets of biomarkers for their diagnostic performance in lung cancer. RESULTS: In a training dataset, the area under the curve (AUC) values were 0.821 for HE4, 0.753 for CEA, 0.858 for RANTES, 0.867 for ApoA2, 0.830 for TTR, and 0.552 for sVCAM-1. A model using all 6 biomarkers and age yielded an AUC value of 0.986 and sensitivity of 93.2% (cutoff at specificity 94%). Applying this model to the validation dataset showed similar results. The AUC value of the model was 0.988, with sensitivity of 93.33% and specificity of 92.00% at the same cutoff point used in the validation dataset. Analyses by stages and histologic subtypes all yielded similar results. CONCLUSIONS: Combining multiple tumor and systemic inflammatory markers proved to be a valid strategy in the diagnosis of lung cancer.

Erratum: Diagnostic Value of Combining Tumor and Inflammatory Markers in Lung Cancer.

[This corrects the article on p. 187 in vol. 21, PMID: 27722145.].

The growth scale and kinetics of WS2 monolayers under varying H2 concentration.

The optical and electronic properties of tungsten disulfide monolayers (WS2) have been extensively studied in the last few years, yet growth techniques for WS2 remain behind other transition metal dichalcogenides (TMDCs) such as MoS2. Here we demonstrate chemical vapor deposition (CVD) growth of continuous monolayer WS2 films on mm(2) scales and elucidate effects related to hydrogen (H2) gas concentration during growth. WS2 crystals were grown by reduction and sulfurization of WO3 using H2 gas and sulfur evaporated from solid sulfur powder. Several different growth formations (in-plane shapes) were observed depending on the concentration of H2. Characterization using atomic force microscopy (AFM) and scanning electron microscopy (SEM) revealed etching of the SiO2 substrate at low concentrations of H2 and in the presence of an Ar carrier gas. We attribute this to insufficient reduction of WO3 during growth. High H2 concentrations resulted in etching of the grown WS2 crystals after growth. The two dimensional X-ray diffraction (2D XRD) pattern demonstrates that the monolayer WS2 was grown with the (004) plane normal to the substrate, showing that the WS2 conforms to the growth substrate.

Nanorough gold for enhanced Raman scattering.

Conventional Raman scattering is a workhorse technique for detecting and identifying complex molecular samples. In surface enhanced Raman scattering, a nanorough metallic surface close to the sample enhances the Raman signal enormously. In this work, the surface is on a clear epoxy substrate. The epoxy is cast on a silicon wafer, using 20 nm of gold as a mold release. This single step process already produces useful enhanced Raman signals. However, the Raman signal is further enhanced by (1) depositing additional gold on the epoxy substrate and (2) by using a combination of wet and dry etches to roughen the silicon substrate before casting the epoxy. The advantage of a clear substrate is that the Raman signal may be obtained by passing light through the substrate, with opaque samples simply placed against the surface. Results were obtained with solutions of Rhodamine 6G in deionized water over a range of concentrations from 1 nM to 1 mM. In all cases, the signal to noise ratio was greater than 10:1.

RNA aptamers: a review of recent trends and applications.

RNA aptamers, small oligonucleotides derived by an in-vitro selection process called SELEX (Systematic Evolution of Ligands by EXperimental enrichment), are important candidates for therapeutic and diagnostic applications. RNA aptamers have high affinity and specificity for their target molecules. In this review, we describe methods for generating RNA aptamers (the SELEX technique and modified SELEX processes) and therapeutic applications for diseases such as neovascular age-related macular degeneration (AMD), inflammatory diseases, and obesity. We also analyze the social networks among researchers and organizations (universities, research institutes, firms, etc.) that are active in the pursuit of aptamer-based therapeutic approaches. This study provides relevant information on recent research trends in RNA aptamers.

A novel detection method of non-small cell lung cancer using multiplexed bead-based serum biomarker profiling.

OBJECTIVES: Non-small cell lung cancer (NSCLC) is the leading cause of cancer-related mortality. Development of an early diagnosis method may improve survivals. We aimed to develop a new diagnostic model for NSCLC using serum biomarkers. METHODS: We set up a patient group diagnosed with NSCLC (n = 122) and a healthy control group (n = 225). Thirty serum analytes were selected on the basis of previous studies and a literature search. An antibody-bead array of 30 markers was constructed using the Luminex bead array platform (Luminex Inc, Austin, Tex) and was analyzed. Each marker was ranked by importance using the random forest method and then selected. Using selected markers, multivariate classification algorithms were constructed and were validated by application to independent validation cohort of 21 NSCLC and 28 control subjects. RESULTS: There was no difference in demographics between patients and the control population except for age (64.8 ± 10.0 for patients vs 53.0 ± 7.6 years for the control group). Among the 30 serum proteins, 23 showed a difference between the 2 groups (12 increased and 11 decreased in the patient group). We found the highest accuracy of multivariate classification algorithms when using the 5 highest-ranked biomarkers (A1AT, CYFRA 21-1, IGF-1, RANTES, AFP). When we applied the algorithms on a validation cohort, each method recognized the patients from the controls with high accuracy (89.8% with random forest, 91.8% with support vector machine, 88.2% with linear discriminant analysis, and 90.5% with logistic regression). CONCLUSIONS: We confirmed that a new diagnostic method using 5 serum biomarkers profiling constructed by multivariate classification algorithms could distinguish NSCLC from healthy controls with high accuracy.

The multiplex bead array approach to identifying serum biomarkers associated with breast cancer.

INTRODUCTION: Breast cancer is the most common type of cancer seen in women in western countries. Thus, diagnostic modalities sensitive to early-stage breast cancer are needed. Antibody-based array platforms of a data-driven type, which are expected to facilitate more rapid and sensitive detection of novel biomarkers, have emerged as a direct, rapid means for profiling cancer-specific signatures using small samples. In line with this concept, our group constructed an antibody bead array panel for 35 analytes that were selected during the discovery step. This study was aimed at testing the performance of this 35-plex array panel in profiling signatures specific for primary non-metastatic breast cancer and validating its diagnostic utility in this independent population. METHODS: Thirty-five analytes were selected from more than 50 markers through screening steps using a serum bank consisting of 4,500 samples from various types of cancer. An antibody-bead array of 35 markers was constructed using the Luminex bead array platform. A study population consisting of 98 breast cancer patients and 96 normal subjects was analysed using this panel. Multivariate classification algorithms were used to find discriminating biomarkers and validated with another independent population of 90 breast cancer and 79 healthy controls. RESULTS: Serum concentrations of epidermal growth factor, soluble CD40-ligand and proapolipoprotein A1 were increased in breast cancer patients. High-molecular-weight-kininogen, apolipoprotein A1, soluble vascular cell adhesion molecule-1, plasminogen activator inhibitor-1, vitamin-D binding protein and vitronectin were decreased in the cancer group. Multivariate classification algorithms distinguished breast cancer patients from the normal population with high accuracy (91.8% with random forest, 91.5% with support vector machine, 87.6% with linear discriminant analysis). Combinatorial markers also detected breast cancer at an early stage with greater sensitivity. CONCLUSIONS: The current study demonstrated the usefulness of the antibody-bead array approach in finding signatures specific for primary non-metastatic breast cancer and illustrated the potential for early, high sensitivity detection of breast cancer. Further validation is required before array-based technology is used routinely for early detection of breast cancer.

Effects of research tool patents on biotechnology innovation in a developing country: a case study of South Korea.

BACKGROUND: Concerns have recently been raised about the negative effects of patents on innovation. In this study, the effects of patents on innovations in the Korean biotech SMEs (small and medium-sized entrepreneurs) were examined using survey data and statistical analysis. RESULTS: The survey results of this study provided some evidence that restricted access problems have occurred even though their frequency was not high. Statistical analysis revealed that difficulties in accessing patented research tools were not negatively correlated with the level of innovation performance and attitudes toward the patent system. CONCLUSION: On the basis of the results of this investigation in combination with those of previous studies, we concluded that although restricted access problems have occurred, this has not yet deterred innovation in Korea. However, potential problems do exist, and the effects of restricted access should be constantly scrutinized.

What affects the innovation performance of small and medium-sized enterprises (SMEs) in the biotechnology industry? An empirical study on Korean biotech SMEs.

Research-intensive small and medium-sized enterprises (SMEs) play a crucial role in the advancement of the biotechnology industry. This paper explored the impacts of internal and contextual variables on innovative activity in Korea and compared the results of this analysis with previous studies of other countries. Our analysis of 149 Korean biotech SMEs showed that the ratio of R&D expenditure to sales, the ratio of R&D employees to total employees, CEO characteristics, governmental support and international networking are positively correlated with a firm's innovation performance. The results may help decision makers to better foster SMEs in the Korean biotechnology industry.

Characterization of the 5'-flanking region of the human PTK6 gene.

PTK6 (also known as Brk) is a non-receptor protein tyrosine kinase, whose mRNA was expressed in the limited normal tissues such as colon and small intestine, and in breast carcinomas and breast cancer cell lines. The 813 bp region upstream from the translation initiation codon, which constitutes a functional promoter of the human PTK6 gene, was progressively deleted and fused to the luciferase reporter gene and transient expression of the resultant constructs was measured upon transfection into a breast carcinoma cell line, T-47D. Comparative analysis of luciferase activity revealed two major regions, -93 to -76 and -702 to -655, important for transcriptional regulation. The proximal -93 to -76 region was found to be essential for the function of the minimal promoter. By primer extension and PCR, it was shown that a PTK6 transcript started at the most 5' upstream is located around base -104. Therefore, the proximal -93 to -76 region is thought to function as a downstream cis-acting element. Luciferase analysis showed that the distal -702 to -655 region contained at least two cis-acting elements. Gel mobility shift assays with T-47D nuclear extract including competition analyses with consensus and mutant oligonucleotides and supershift analyses with NF-kappaB and Sp1 antibodies showed that NF-kappaB binds to the sequence from -706 to -688 and Sp1 binds to the sequence from -688 to -669. This study thus provides the first molecular insights into the transcriptional regulation of the human PTK6 gene.