Elevation in Inflammatory Serum Biomarkers Predicts Response to Trastuzumab-Containing Therapy

Approximately half of all HER2/neu-overexpressing breast cancer patients do not respond to trastuzumab-containing therapy. Therefore, there remains an urgent and unmet clinical need for the development of predictive biomarkers for trastuzumab response. Recently, several lines of evidence have demonstrated that the inflammatory tumor microenvironment is a major contributor to therapy resistance in breast cancer. In order to explore the predictive value of inflammation in breast cancer patients, we measured the inflammatory biomarkers serum ferritin and C-reactive protein (CRP) in 66 patients immediately before undergoing trastuzumab-containing therapy and evaluated their progression-free and overall survival. The elevation in pre-treatment serum ferritin (>250 ng/ml) or CRP (>7.25 mg/l) was a significant predictor of reduced progression-free survival and shorter overall survival. When patients were stratified based on their serum ferritin and CRP levels, patients with elevation in both inflammatory biomarkers had a markedly poorer response to trastuzumab-containing therapy. Therefore, the elevation in inflammatory serum biomarkers may reflect a pathological state that decreases the clinical efficacy of this therapy. Anti-inflammatory drugs and life-style changes to decrease inflammation in cancer patients should be explored as possible strategies to sensitize patients to anti-cancer therapeutics.     

Technical Factors Involved in the Measurement of Circulating MicroRNA Biomarkers for the Detection of Colorectal Neoplasia

Background

Circulating miRNAs are emerging as promising blood-based biomarkers for colorectal and other human cancers; however, technical factors that confound the development of these assays remain poorly understood and present a clinical challenge. The aim of this study was to systematically evaluate the effects of factors that may interfere with the accurate measurement of circulating miRNAs for clinical purposes.

Methods

Blood samples from 53 subjects, including routinely drawn serum samples, matched plasma from 30 subjects, and matched serum samples drawn before and after bowel preparation for colonoscopy from 29 subjects were collected. Additionally, 38 serum specimens stored in the clinical laboratory for seven days were used to test the stability of miRNAs. Hemolysis controls with serial dilutions of hemoglobin were prepared. RNA was extracted from serum, plasma or hemolyzed controls with spiked-in cel-miR-39, and levels of miR-21, miR-29a, miR-125b and miR-16 were examined by real-time RT-PCR. Hemolysis was measured by spectrophotometry.

Results

The expression levels of miR-16 and the degree of hemolysis were significantly higher in plasma than in serum (P<0.0001). Measured miR-21, miR-29a, miR-125b and miR-16 expression increased with hemoglobin levels in hemolyzed controls. The degree of hemolysis in serum samples correlated significantly with the levels of miR-21 (P<0.0001), miR-29a (P = 0.0002), miR-125b (P<0.0001) and miR-16 (P<0.0001). All four miRNAs showed significantly lower levels in sera that had been stored at 4°C for seven days (P<0.0001). Levels of miR-21 (P<0.0001), miR-29a (P<0.0001) and miR-16 (P = 0.0003), and the degree of hemolysis (P = 0.0002) were significantly higher in sera drawn after vs. before bowel preparation.

Conclusions

The measured levels of miRNAs in serum and plasma from same patients varied in the presence of hemolysis, and since hemolysis and other factors affected miRNA expression, it is important to consider these confounders while developing miRNA-based diagnostic assays.     

Circulating Biomarkers for Predicting Cardiovascular Disease Risk; a Systematic Review and Comprehensive Overview of Meta-Analyses

Background

Cardiovascular disease is one of the major causes of death worldwide.Assessing the risk for cardiovascular disease is an important aspect in clinical decision making and setting a therapeutic strategy, and the use of serological biomarkers may improve this. Despite an overwhelming number of studies and meta-analyses on biomarkers and cardiovascular disease, there are no comprehensive studies comparing the relevance of each biomarker. We performed a systematic review of meta-analyses on levels of serological biomarkers for atherothrombosis to compare the relevance of the most commonly studied biomarkers.

Methods and Findings

Medline and Embase were screened on search terms that were related to “arterial ischemic events” and “meta-analyses”. The meta-analyses were sorted by patient groups without pre-existing cardiovascular disease, with cardiovascular disease and heterogeneous groups concerning general populations, groups with and without cardiovascular disease, or miscellaneous. These were subsequently sorted by end-point for cardiovascular disease or stroke and summarized in tables. We have identified 85 relevant full text articles, with 214 meta-analyses. Markers for primary cardiovascular events include, from high to low result: C-reactive protein, fibrinogen, cholesterol, apolipoprotein B, the apolipoprotein A/apolipoprotein B ratio, high density lipoprotein, and vitamin D. Markers for secondary cardiovascular events include, from high to low result: cardiac troponins I and T, C-reactive protein, serum creatinine, and cystatin C. For primary stroke, fibrinogen and serum uric acid are strong risk markers. Limitations reside in that there is no acknowledged search strategy for prognostic studies or meta-analyses.

Conclusions

For primary cardiovascular events, markers with strong predictive potential are mainly associated with lipids. For secondary cardiovascular events, markers are more associated with ischemia. Fibrinogen is a strong predictor for primary stroke.     

A Stack-based Ensemble Framework for Detecting Cancer MicroRNA Biomarkers

MicroRNA(miRNA) plays vital roles in biological processes like RNA splicing and regulation of gene expression. Studies have revealed that there might be possible links between oncogenesis and expression pro?les of some miRNAs, due to their differential expression between normal and tumor tissues. However, the automatic classi?cation of miRNAs into different categories by considering the similarity of their expression values has rarely been addressed. This article proposes a solution framework for solving some real-life classi?cation problems related to cancer,miRNA, and mRNA expression datasets. In the ?rst stage, a multiobjective optimization based framework, non-dominated sorting genetic algorithm II, is proposed to automatically determine the appropriate classi?er type, along with its suitable parameter and feature combinations, pertinent for classifying a given dataset. In the second page, a stack-based ensemble technique is employed to get a single combinatorial solution from the set of solutions obtained in the ?rst stage. The performance of the proposed two-stage approach is evaluated on several cancer and RNA expression pro-?le datasets. Compared to several state-of-the-art approaches for classifying different datasets, our method shows supremacy in the accuracy of classi?cation.     

Dampening Enthusiasm for Circulating MicroRNA in Breast Cancer

Genome-wide platforms for high-throughput profiling of circulating miRNA (oligoarray or miR-Seq) offer enormous promise for agnostic discovery of circulating miRNA biomarkers as a pathway for development in breast cancer detection. By harmonizing data from 15 previous reports, we found widespread inconsistencies across prior studies. Whether this arises from differences in study design, such as sample source or profiling platform, is unclear. As a reproducibility experiment, we generated a genome-wide plasma miRNA dataset using the Illumina oligoarray and compared this to a publically available dataset generated using an identical sample size, substrate and profiling platform. Samples from 20 breast cancer patients, 20 mammography-screened controls, as well as 20 breast cancer patients after surgical resection and 10 female lung or colorectal cancer patients were included. After filtering for miRNAs derived from blood cells, and for low abundance miRNAs (non-detectable in over 10% of samples), a set of 522 plasma miRNAs remained, of which 46 were found to be differentially expressed between breast cancer patients and healthy controls (p<0.05), of which only 3 normalized to baseline levels in post-resection cases and were unique to breast cancer vs. lung or colorectal cancer (miR-708*, miR-92b* and miR-568, none previously reported). We were unable to demonstrate reproducibility by various measures between the two datasets. This finding, along with widespread inconsistencies across prior studies, highlight the need for better understanding of factors influencing circulating miRNA levels as prerequisites to progress in this area of translational research.     

Personalized Circulating Tumor DNA Biomarkers Dynamically Predict Treatment Response and Survival In Gynecologic Cancers

Background

High-grade serous ovarian and endometrial cancers are the most lethal female reproductive tract malignancies worldwide. In part, failure to treat these two aggressive cancers successfully centers on the fact that while the majority of patients are diagnosed based on current surveillance strategies as having a complete clinical response to their primary therapy, nearly half will develop disease recurrence within 18 months and the majority will die from disease recurrence within 5 years. Moreover, no currently used biomarkers or imaging studies can predict outcome following initial treatment. Circulating tumor DNA (ctDNA) represents a theoretically powerful biomarker for detecting otherwise occult disease. We therefore explored the use of personalized ctDNA markers as both a surveillance and prognostic biomarker in gynecologic cancers and compared this to current FDA-approved surveillance tools.

Methods and Findings

Tumor and serum samples were collected at time of surgery and then throughout treatment course for 44 patients with gynecologic cancers, representing 22 ovarian cancer cases, 17 uterine cancer cases, one peritoneal, three fallopian tube, and one patient with synchronous fallopian tube and uterine cancer. Patient/tumor-specific mutations were identified using whole-exome and targeted gene sequencing and ctDNA levels quantified using droplet digital PCR. CtDNA was detected in 93.8% of patients for whom probes were designed and levels were highly correlated with CA-125 serum and computed tomography (CT) scanning results. In six patients, ctDNA detected the presence of cancer even when CT scanning was negative and, on average, had a predictive lead time of seven months over CT imaging. Most notably, undetectable levels of ctDNA at six months following initial treatment was associated with markedly improved progression free and overall survival.

Conclusions

Detection of residual disease in gynecologic, and indeed all cancers, represents a diagnostic dilemma and a potential critical inflection point in precision medicine. This study suggests that the use of personalized ctDNA biomarkers in gynecologic cancers can identify the presence of residual tumor while also more dynamically predicting response to treatment relative to currently used serum and imaging studies. Of particular interest, ctDNA was an independent predictor of survival in patients with ovarian and endometrial cancers. Earlier recognition of disease persistence and/or recurrence and the ability to stratify into better and worse outcome groups through ctDNA surveillance may open the window for improved survival and quality and life in these cancers.     

Circulating Tumor DNA as Biomarkers for Cancer Detection

Detection of circulating tumor DNAs (ctDNAs) in cancer patients is an important component of cancer precision medicine ctDNAs. Compared to the traditional physical and biochemical methods, blood-based ctDNA detection offers a non-invasive and easily accessible way for cancer diagnosis, prognostic determination, and guidance for treatment. While studies on this topic are currently underway, clinical translation of ctDNA detection in various types of cancers has been attracting much attention, due to the great potential of ctDNA as blood-based biomarkers for early diagnosis and treatment of cancers. ctDNAs are detected and tracked primarily based on tumor-related genetic and epigenetic alterations. In this article, we reviewed the available studies on ctDNA detection and described the representative methods. We also discussed the current understanding of ctDNAs in cancer patients and their availability as potential biomarkers for clinical purposes. Considering the progress made and challenges involved in accurate detection of specific cell-free nucleic acids, ctDNAs hold promise to serve as biomarkers for cancer patients, and further validation is needed prior to their broad clinical use.     

MicroRNA：从生物标志物到基因治疗

microRNA（miRNA）作为生物标志物和治疗靶点的价值已被公认。简介miRNA及其生物合成与功能,探讨 miRNA与疾病 及癌症的关系,综述miRNA在疾病治疗中及作为生物标志物的应用研究。     

MicroRNA 与胶质瘤的分子病理特征研究进展

MicroRNAs(miRNAs)是一类非编码的内源性小RNA分子,通过调节mRNA的稳定性及蛋白翻译过程控制基因表达,从而发挥促癌或抑癌作用;研究表明,在胶质瘤的发生、进展、侵袭过程中,伴随发生了许多分子病理特征的改变,这一过程中miRNAs发挥着重要作用,本文就此方面研究进展进行综述。     

New Genetic Biomarkers Predicting Azathioprine Blood Concentrations in Combination Therapy with 5-Aminosalicylic Acid

Background and Aims

Azathioprine (AZA) is widely used for the treatment of inflammatory bowel disease (IBD) patients. AZA is catabolized by thiopurine S-methyltransferase (TPMT), which exhibits genetic polymorphisms. It has also been reported that 5-aminosalicylic acid (5-ASA) inhibits TPMT activity, and that increased 6-thioguanine nucleotide (6-TGN, a metabolite of AZA) blood concentrations result in an increased number of ADRs. In this study, single nucleotide polymorphisms (SNPs) related to differential gene expression affecting AZA drug metabolism in combination therapy with 5-ASA were examined.

Methods

To identify genetic biomarkers for the prediction of 6-TGN blood concentration, ExpressGenotyping analysis was used. ExpressGenotyping analysis is able to detect critical pharmacogenetic SNPs by analyzing drug-induced expression allelic imbalance (EAI) of premature RNA in HapMap lymphocytes. We collected blood samples on 38 patients with inflammatory bowel disease treated with AZA and corroboration of the obtained SNPs was attempted in clinical samples.

Results

A large number of SNPs with AZA/5-ASA-induced EAI within the investigated HapMap lymphocytes was identified by ExpressGenotyping analysis. The respective SNPs were analyzed in IBD patients'' blood samples. Among these SNPs, several that have not yet been described to be induced by AZA/5-ASA were found. SNPs within SLC38A9 showed a particular correlation with patients'' 6-TGN blood concentrations.

Conclusions

Based on these results, ExpressGenotyping analysis and genotyping of patients appears to be a useful way to identify inter-individual differences in drug responses and ADRs to AZA/5-ASA. This study provides helpful information on genetic biomarkers for optimized AZA/5-ASA treatment of IBD patients.     

MicroRNA与胶质瘤的分子病理特征研究进展

MicroRNAs（miRNAs）是一类非编码的内源性小RNA分子,通过调节mRNA的稳定性及蛋白翻译过程控制基因表达,从而发挥促癌或抑癌作用;研究表明,在胶质瘤的发生、进展、侵袭过程中,伴随发生了许多分子病理特征的改变,这一过程中miRNAs发挥着重要作用,本文就此方面研究进展进行综述。     

Circulating microRNAs as Specific Biomarkers for Breast Cancer Detection

Background

We previously showed microRNAs (miRNAs) in plasma are potential biomarkers for colorectal cancer detection. Here, we aimed to develop specific blood-based miRNA assay for breast cancer detection.

Methodology/Principal Findings

TaqMan-based miRNA profiling was performed in tumor, adjacent non-tumor, corresponding plasma from breast cancer patients, and plasma from matched healthy controls. All putative markers identified were verified in a training set of breast cancer patients. Selected markers were validated in a case-control cohort of 170 breast cancer patients, 100 controls, and 95 other types of cancers and then blindly validated in an independent set of 70 breast cancer patients and 50 healthy controls. Profiling results showed 8 miRNAs were concordantly up-regulated and 1 miRNA was concordantly down-regulated in both plasma and tumor tissue of breast cancer patients. Of the 8 up-regulated miRNAs, only 3 were significantly elevated (p<0.0001) before surgery and reduced after surgery in the training set. Results from the validation cohort showed that a combination of miR-145 and miR-451 was the best biomarker (p<0.0001) in discriminating breast cancer from healthy controls and all other types of cancers. In the blind validation, these plasma markers yielded Receiver Operating Characteristic (ROC) curve area of 0.931. The positive predictive value was 88% and the negative predictive value was 92%. Altered levels of these miRNAs in plasma have been detected not only in advanced stages but also early stages of tumors. The positive predictive value for ductal carcinoma in situ (DCIS) cases was 96%.

Conclusions

These results suggested that these circulating miRNAs could be a potential specific biomarker for breast cancer screening.     

Serum Interferon-Related MicroRNAs as Biomarkers to Predict the Response to Interferon Therapy in Chronic Hepatitis C Genotype 4

MicroRNAs are messengers during interferon-virus interplay and are involved in antiviral immunity, however, little is known about interferon-related microRNAs regarding their detection in serum and their potential use as non-invasive diagnostic and prognostic biomarkers in chronic hepatitis C (CHC). To elucidate some of the molecular aspects underlying failure of pegylated interferon-α/ribavirin therapy, we investigated pretreatment expression profiles of seven selected interferon-related microRNAs (miR-146a, miR-34a, miR-130a, miR-19a, miR-192, miR-195, and miR-296) by quantitative RT-PCR custom array technology in serum of Egyptian CHC genotype 4 patients and whether their pretreatment levels would predict patient response to the combination therapy. One hundred and six CHC patients and forty matched healthy controls were included. Patients were divided into sustained virological response (SVR) and non-responder (NR) groups. Serum miR-34a, miR-130a, miR-19a, miR-192, miR-195, and miR-296 were upregulated, whereas serum miR-146a was downregulated in CHC compared to controls. Significant correlations were found between expression levels of studied microRNAs and also with clinical data. Pretreatment levels of miR-34a, miR-130a, and miR-195 were significantly higher, whereas miR-192 and miR-296 levels were significantly lower in SVR than NR patients. miR-19a and miR-146a levels were not significantly different between the two groups. miR-34a was superior to differentiate CHC from controls, whereas miR-296 was superior to discriminate SVR from NR patients by receiver operating characteristic analysis. Multivariate logistic analysis revealed miR-34a and miR-195 as independent predictors for SVR and miR-192 as an independent variable for non-response. In conclusion, pretreatment expression profiles of five interferon-related microRNAs are associated with treatment outcome in CHC. Of these, miR-34a, miR-195, and miR-192 could predict treatment response. The profiling results could be used as novel non-invasive diagnostic and prognostic pharmacogenetic biomarkers for treatment personalization in CHC and could help to identify new microRNA-based antivirals.