Adaptation of HL7 FHIR for the Exchange of Patients' Gene Expression Profiles.

High-throughput technologies, especially gene expression analyses can accurately capture the molecular state in patients under different conditions. Thus, their application in clinical routine gains increasing relevance and fosters patient stratification towards individualized treatment decisions. Electronic health records already evolved to capture genomic data within clinical systems and standards like FHIR enable sharing within, and even between institutions. However, FHIR only provides profiles tailored to variations in the molecular sequence, while expression patterns are neglected although being equally important for decision making. Here we provide an exemplary implementation of gene expression profiles of a microarray analysis of patients with acute myeloid leukemia using an adaptation of the FHIR genomics extension. Our results demonstrate how FHIR resources can be facilitated in clinical systems and thereby pave the way for usage for the aggregation and exchange of transcriptomic data in multi-center studies.

Gene-expression profiles of pretreatment biopsies predict complete response of rectal cancer patients to preoperative chemoradiotherapy.

PURPOSE: Preoperative (neoadjuvant) chemoradiotherapy (CRT) and total mesorectal excision is the standard treatment for rectal cancer patients (UICC stage II/III). Up to one-third of patients treated with CRT achieve a pathological complete response (pCR). These patients could be spared from surgery and its associated morbidity and mortality, and assigned to a "watch and wait" strategy. However, reliably identifying pCR based on clinical or imaging parameters remains challenging. EXPERIMENTAL DESIGN: We generated gene-expression profiles of 175 patients with locally advanced rectal cancer enrolled in the CAO/ARO/AIO-94 and -04 trials. One hundred and sixty-one samples were used for building, training and validating a predictor of pCR using a machine learning algorithm. The performance of the classifier was validated in three independent cohorts, comprising 76 patients from (i) the CAO/ARO/AIO-94 and -04 trials (n = 14), (ii) a publicly available dataset (n = 38) and (iii) in 24 prospectively collected samples from the TransValid A trial. RESULTS: A 21-transcript signature yielded the best classification of pCR in 161 patients (Sensitivity: 0.31; AUC: 0.81), when not allowing misclassification of non-complete-responders (False-positive rate = 0). The classifier remained robust when applied to three independent datasets (n = 76). CONCLUSION: The classifier can identify >1/3 of rectal cancer patients with a pCR while never classifying patients with an incomplete response as having pCR. Importantly, we could validate this finding in three independent datasets, including a prospectively collected cohort. Therefore, this classifier could help select rectal cancer patients for a "watch and wait" strategy. TRANSLATIONAL RELEVANCE: Forgoing surgery with its associated side effects could be an option for rectal cancer patients if the prediction of a pathological complete response (pCR) after preoperative chemoradiotherapy would be possible. Based on gene-expression profiles of 161 patients a classifier was developed and validated in three independent datasets (n = 76), identifying over 1/3 of patients with pCR, while never misclassifying a non-complete-responder. Therefore, the classifier can identify patients suited for "watch and wait".

Network-Based Approaches Reveal Potential Therapeutic Targets for Host-Directed Antileishmanial Therapy Driving Drug Repurposing.

Leishmania parasites are the causal agent of leishmaniasis, an endemic disease in more than 90 countries worldwide. Over the years, traditional approaches focused on the parasite when developing treatments against leishmaniasis. Despite numerous attempts, there is not yet a universal treatment, and those available have allowed for the appearance of resistance. Here, we propose and follow a host-directed approach that aims to overcome the current lack of treatment. Our approach identifies potential therapeutic targets in the host cell and proposes known drug interactions aiming to improve the immune response and to block the host machinery necessary for the survival of the parasite. We started analyzing transcription factor regulatory networks of macrophages infected with Leishmania major. Next, based on the regulatory dynamics of the infection and available gene expression profiles, we selected potential therapeutic target proteins. The function of these proteins was then analyzed following a multilayered network scheme in which we combined information on metabolic pathways with known drugs that have a direct connection with the activity carried out by these proteins. Using our approach, we were able to identify five host protein-coding gene products that are potential therapeutic targets for treating leishmaniasis. Moreover, from the 11 drugs known to interact with the function performed by these proteins, 3 have already been tested against this parasite, verifying in this way our novel methodology. More importantly, the remaining eight drugs previously employed to treat other diseases, remain as promising yet-untested antileishmanial therapies. IMPORTANCE This work opens a new path to fight parasites by targeting host molecular functions by repurposing available and approved drugs. We created a novel approach to identify key proteins involved in any biological process by combining gene regulatory networks and expression profiles. Once proteins have been selected, our approach employs a multilayered network methodology that relates proteins to functions to drugs that alter these functions. By applying our novel approach to macrophages during the Leishmania infection process, we both validated our work and found eight drugs already approved for use in humans that to the best of our knowledge were never employed to treat leishmaniasis, rendering our work as a new tool in the box available to the scientific community fighting parasites.

Explaining decisions of graph convolutional neural networks: patient-specific molecular subnetworks responsible for metastasis prediction in breast cancer.

BACKGROUND: Contemporary deep learning approaches show cutting-edge performance in a variety of complex prediction tasks. Nonetheless, the application of deep learning in healthcare remains limited since deep learning methods are often considered as non-interpretable black-box models. However, the machine learning community made recent elaborations on interpretability methods explaining data point-specific decisions of deep learning techniques. We believe that such explanations can assist the need in personalized precision medicine decisions via explaining patient-specific predictions. METHODS: Layer-wise Relevance Propagation (LRP) is a technique to explain decisions of deep learning methods. It is widely used to interpret Convolutional Neural Networks (CNNs) applied on image data. Recently, CNNs started to extend towards non-Euclidean domains like graphs. Molecular networks are commonly represented as graphs detailing interactions between molecules. Gene expression data can be assigned to the vertices of these graphs. In other words, gene expression data can be structured by utilizing molecular network information as prior knowledge. Graph-CNNs can be applied to structured gene expression data, for example, to predict metastatic events in breast cancer. Therefore, there is a need for explanations showing which part of a molecular network is relevant for predicting an event, e.g., distant metastasis in cancer, for each individual patient. RESULTS: We extended the procedure of LRP to make it available for Graph-CNN and tested its applicability on a large breast cancer dataset. We present Graph Layer-wise Relevance Propagation (GLRP) as a new method to explain the decisions made by Graph-CNNs. We demonstrate a sanity check of the developed GLRP on a hand-written digits dataset and then apply the method on gene expression data. We show that GLRP provides patient-specific molecular subnetworks that largely agree with clinical knowledge and identify common as well as novel, and potentially druggable, drivers of tumor progression. CONCLUSIONS: The developed method could be potentially highly useful on interpreting classification results in the context of different omics data and prior knowledge molecular networks on the individual patient level, as for example in precision medicine approaches or a molecular tumor board.

MIScnn: a framework for medical image segmentation with convolutional neural networks and deep learning.

BACKGROUND: The increased availability and usage of modern medical imaging induced a strong need for automatic medical image segmentation. Still, current image segmentation platforms do not provide the required functionalities for plain setup of medical image segmentation pipelines. Already implemented pipelines are commonly standalone software, optimized on a specific public data set. Therefore, this paper introduces the open-source Python library MIScnn. IMPLEMENTATION: The aim of MIScnn is to provide an intuitive API allowing fast building of medical image segmentation pipelines including data I/O, preprocessing, data augmentation, patch-wise analysis, metrics, a library with state-of-the-art deep learning models and model utilization like training, prediction, as well as fully automatic evaluation (e.g. cross-validation). Similarly, high configurability and multiple open interfaces allow full pipeline customization. RESULTS: Running a cross-validation with MIScnn on the Kidney Tumor Segmentation Challenge 2019 data set (multi-class semantic segmentation with 300 CT scans) resulted into a powerful predictor based on the standard 3D U-Net model. CONCLUSIONS: With this experiment, we could show that the MIScnn framework enables researchers to rapidly set up a complete medical image segmentation pipeline by using just a few lines of code. The source code for MIScnn is available in the Git repository: https://github.com/frankkramer-lab/MIScnn .

Riociguat in patients with early diffuse cutaneous systemic sclerosis (RISE-SSc): randomised, double-blind, placebo-controlled multicentre trial.

OBJECTIVES: Riociguat is approved for pulmonary arterial hypertension and has antiproliferative, anti-inflammatory and antifibrotic effects in animal models of tissue fibrosis. We evaluated the efficacy and safety of riociguat in patients with early diffuse cutaneous systemic sclerosis (dcSSc) at high risk of skin fibrosis progression. METHODS: In this randomised, double-blind, placebo-controlled, phase IIb trial, adults with dcSSc of <18 months' duration and a modified Rodnan skin score (mRSS) 10-22 units received riociguat 0.5 mg to 2.5 mg orally three times daily (n=60) or placebo (n=61). The primary endpoint was change in mRSS from baseline to week 52. RESULTS: At week 52, change from baseline in mRSS units was -2.09±5.66 (n=57) with riociguat and -0.77±8.24 (n=52) with placebo (difference of least squares means -2.34 (95% CI -4.99 to 0.30; p=0.08)). In patients with interstitial lung disease, forced vital capacity declined by 2.7% with riociguat and 7.6% with placebo. At week 14, average Raynaud's condition score had improved ≥50% in 19 (41.3%)/46 patients with riociguat and 13 (26.0%)/50 patients with placebo. Safety assessments showed no new signals with riociguat and no treatment-related deaths. CONCLUSIONS: Riociguat did not significantly benefit mRSS versus placebo at the predefined p<0.05. Secondary and exploratory analyses showed potential efficacy signals that should be tested in further trials. Riociguat was well tolerated.

Utilizing Molecular Network Information via Graph Convolutional Neural Networks to Predict Metastatic Event in Breast Cancer.

Gene expression data is commonly available in cancer research and provides a snapshot of the molecular status of a specific tumor tissue. This high-dimensional data can be analyzed for diagnoses, prognoses, and to suggest treatment options. Machine learning based methods are widely used for such analysis. Recently, a set of deep learning techniques was successfully applied in different domains including bioinformatics. One of these prominent techniques are convolutional neural networks (CNN). Currently, CNNs are extending to non-Euclidean domains like graphs. Molecular networks are commonly represented as graphs detailing interactions between molecules. Gene expression data can be assigned to the vertices of these graphs, and the edges can depict interactions, regulations and signal flow. In other words, gene expression data can be structured by utilizing molecular network information as prior knowledge. Here, we applied graph CNN to gene expression data of breast cancer patients to predict the occurrence of metastatic events. To structure the data we utilized a protein-protein interaction network. We show that the graph CNN exploiting the prior knowledge is able to provide classification improvements for the prediction of metastatic events compared to existing methods.

Test-Retest Reliability of Non-Invasive Cardiac Output Measurement during Exercise in Healthy Volunteers in Daily Clinical Routine / Confiabilidade Teste-Reteste de Medição Não-Invasiva de Débito Cardíaco durante Exercício em Voluntários Saudáveis sob Condições Clínicas de Rotina

Abstract Background: Thoracic bioreactance (TB), a noninvasive method for the measurement of cardiac output (CO), shows good test-retest reliability in healthy adults examined under research and resting conditions. Objective: In this study, we evaluate the test-retest reliability of CO and cardiac power (CPO) output assessment during exercise assessed by TB in healthy adults under routine clinical conditions. Methods: 25 test persons performed a symptom-limited graded cycling test in an outpatient office on two different days separated by one week. Cardiorespiratory (power output, VO2peak) and hemodynamic parameters (heart rate, stroke volume, CO, mean arterial pressure, CPO) were measured at rest and continuously under exercise using a spiroergometric system and bioreactance cardiograph (NICOM, Cheetah Medical). Results: After 8 participants were excluded due to measurement errors (outliers), there was no systematic bias in all parameters under all conditions (effect size: 0.2-0.6). We found that all noninvasively measured CO showed acceptable test-retest-reliability (intraclass correlation coefficient: 0.59-0.98; typical error: 0.3-1.8). Moreover, peak CPO showed better reliability (intraclass correlation coefficient: 0.80-0.85; effect size: 0.9-1.1) then the TB CO, thanks only to the superior reliability of MAP (intraclass correlation coefficient: 0.59-0.98; effect size: 0.3-1.8). Conclusion: Our findings preclude the clinical use of TB in healthy subject population when outliers are not identified.

Resumo Fundamento: A biorreatância torácica (BT), um método não invasivo destinado à medição do débito cardíaco (DC), mostra boa confiabilidade teste-reteste em adultos saudáveis examinados em condições de pesquisa e repouso. Objetivo: No presente estudo, avaliamos a confiabilidade teste-reteste da avaliação do DC e trabalho cardíaco (TC) durante exercício, avaliado por BT em adultos saudáveis sob condições clínicas de rotina. Métodos: 25 indivíduos realizaram teste ergométrico gradual sintoma-limitante em ambiente ambulatorial em dois dias diferentes, com intervalo de uma semana. Parâmetros cardiorrespiratórios (trabalho cardíaco, VO2máx) e hemodinâmicos (frequência cardíaca, volume sistólico, DC, pressão arterial média, TC) foram medidos em repouso e continuamente sob exercício utilizando sistema espiroergométrico e cardiógrafo de biorreatância (NICOM, Cheetah Medical). Resultados: Após 8 participantes terem sido excluídos devido a erros de medição (outliers), não houve viés sistemático em nenhum dos parâmetros em todas as condições (tamanho do efeito: 0,2-0,6). Observamos que todos os débitos cardíacos medidos de forma não invasiva apresentaram níveis aceitáveis de confiabilidade teste-reteste (coeficiente de correlação intraclasse: 0,59-0,98; erro típico: 0,3-1,8). Além disso, TC máximo apresentou melhor confiabilidade (coeficiente de correlação intraclasse: 0,80-0,85; tamanho do efeito: 0,9-1,1), seguido do DC pela BT, graças apenas à confiabilidade superior da PAM (coeficiente de correlação intraclasse: 0,59-0,98; tamanho do efeito: 0,3-1,8). Conclusão: Nossos achados impedem o uso clínico da BT em indivíduos saudáveis quando outliers não forem identificados.

The histone methyltransferase DOT1L is required for proper DNA damage response, DNA repair, and modulates chemotherapy responsiveness.

BACKGROUND: Disruptor of telomeric silencing 1-like (DOT1L) is a non-SET domain containing methyltransferase known to catalyze mono-, di-, and tri-methylation of histone 3 on lysine 79 (H3K79me). DOT1L-mediated H3K79me has been implicated in chromatin-associated functions including gene transcription, heterochromatin formation, and DNA repair. Recent studies have uncovered a role for DOT1L in the initiation and progression of leukemia and other solid tumors. The development and availability of small molecule inhibitors of DOT1L may provide new and unique therapeutic options for certain types or subgroups of cancer. METHODS: In this study, we examined the role of DOT1L in DNA double-strand break (DSB) response and repair by depleting DOT1L using siRNA or inhibiting its methyltransferase activity using small molecule inhibitors in colorectal cancer cells. Cells were treated with different agents to induce DNA damage in DOT1L-depleted or -inhibited cells and analyzed for DNA repair efficiency and survival. Further, rectal cancer patient samples were analyzed for H3K79me3 levels in order to determine whether it may serve as a potential marker for personalized therapy. RESULTS: Our results indicate that DOT1L is required for a proper DNA damage response following DNA double-strand breaks by regulating the phosphorylation of the variant histone H2AX (γH2AX) and repair via homologous recombination (HR). Importantly, we show that small molecule inhibitors of DOT1L combined with chemotherapeutic agents that are used to treat colorectal cancers show additive effects. Furthermore, examination of H3K79me3 levels in rectal cancer patients demonstrates that lower levels correlate with a poorer prognosis. CONCLUSIONS: In this study, we conclude that DOT1L plays an important role in an early DNA damage response and repair of DNA double-strand breaks via the HR pathway. Moreover, DOT1L inhibition leads to increased sensitivity to chemotherapeutic agents and PARP inhibition, which further highlights its potential clinical utility. Our results further suggest that H3K79me3 can be useful as a predictive and or prognostic marker for rectal cancer patients.

Left atrial thrombus resolution in non-valvular atrial fibrillation or flutter: biomarker substudy results from a prospective study with rivaroxaban (X-TRA).

BACKGROUND: Non-vitamin K antagonist oral anticoagulants including rivaroxaban are widely used for stroke prevention in patients with atrial fibrillation (AF). We investigated the relationship between plasma biomarkers (indicative of thrombogenesis, fibrinolysis and inflammation) and left atrial thrombus resolution after rivaroxaban treatment. METHODS: This was an ancillary analysis of the X-TRA study, which was a prospective interventional study evaluating the use of rivaroxaban for left atrial/left atrial appendage (LA/LAA) thrombus resolution in AF patients. We assessed various biomarkers of thrombogenesis/fibrinolysis [D-dimer, plasminogen activator inhibitor-1 (PAI-1), prothrombin fragment 1 + 2 (F1,2), thrombin-antithrombin (TAT) complexes, von Willebrand factor (vWF)] and inflammation [high-sensitivity interleukin-6 (hsIL-6), and high-sensitivity C-reactive protein (hsCRP)], measured at baseline and after 6 weeks' of rivaroxaban treatment. RESULTS: There was a significant decrease in the mean levels of hsCRP, D-dimer, vWF, and TAT from baseline to end of treatment with rivaroxaban. Although none of the thrombogenesis/fibrinolysis biomarkers showed a significant relationship with thrombus resolution, high inflammatory biomarkers at baseline were significantly associated with an increased chance of the thrombus being completely resolved (hsIL-6) or reduced/resolved (hsCRP). CONCLUSIONS: Biomarkers of inflammation are significantly associated with LA/LAA thrombus outcomes in AF patients prospectively treated with rivaroxaban.

Endostatin a Potential Biomarker for Heart Failure with Preserved Ejection Fraction / Endostatina é um Potencial Biomarcador para a Insuficiência Cardíaca com Fração de Ejeção Preservada

Abstract Background: Endostatin is a circulating endogenous angiogenesis inhibitor preventing neovascularization. Previous studies demonstrated the prognostic value of Endostatin among patients with heart failure with reduced ejection fraction (HFrEF). However, the role of Endostatin among patients with heart failure with preserved ejection fraction (HFpEF) remains unclear. Objective: This study aimed to investigate the association between serum Endostatin levels, natriuretic peptide levels and the severity of left ventricular diastolic dysfunction and the diagnosis of HFpEF. Methods: Endostatin serum concentrations were measured in 301 patients comprising 77 HFpEF patients, 169 patients with asymptomatic left ventricular diastolic dysfunction (ALVDD), and 55 controls with normal cardiac function. Results: Endostatin serum levels were significantly elevated in patients with HFpEF (median/interquartile range 179.0 [159-220]) and ALVDD (163.8 [145.4-191.3]) compared to controls (149.1 [130.6-176.9]), p < 0.001 and p = 0.004, respectively) and significant correlated with N-terminal pro B-type natriuretic peptide (NT-proBNP). Conclusions: This hypothesis-generating pilot study gives first evidence that Endostatin correlates with the severity of diastolic dysfunction and may become a novel biomarker for HFpEF. We hypothesize a rise in Endostatin levels may reflect inhibition of adaptive angiogenesis and adverse cardiac remodeling.

Resumo Fundamentos: A Endostatina é um inibidor circulante endógeno da angiogênese que previne a neovascularização. Estudos anteriores demonstraram o valor prognóstico da Endostatina em pacientes com insuficiência cardíaca com fracção de ejeção reduzida (ICFEr). No entanto, o papel da Endostatina entre os pacientes com insuficiência cardíaca com fração de ejeção preservada (ICFEp) permanece incerto. Objetivo: Investigar a associação entre os níveis séricos de Endostatina, níveis de peptídeos natriuréticos e a gravidade de disfunção ventricular esquerda e diastólica e o diagnóstico de ICFEp. Métodos: Mediu-se a concentração sérica de Endostatina em 301 pacientes, compreendendo 77 pacientes com ICFEp, 169 pacientes com disfunção ventricular esquerda assintomática diastólica (DVEAD) e 55 controles com a função cardíaca normal. Resultados: Os níveis de Endostatina no soro foram significativamente elevados em pacientes com ICFEp (mediana / intervalo interquartil 179,0 [159-220]) e DVEAD (163,8 [145,4-191,3]) em comparação com os controles (149,1 [130,6-176,9]), p < 0,001 e p = 0,004, respectivamente) e correlação significativa com o terminal do pro-peptídeo natriurético tipo B (NT-proBNP). Conclusões: Este estudo piloto gerador de hipótese fornece a primeira evidência de que a Endostatina se correlaciona com a gravidade da disfunção diastólica e pode tornar-se um novo biomarcador para ICFEp. Nossa hipótese é de que um aumento nos níveis de Endostatina pode refletir inibição da angiogênese adaptativa e remodelação cardíaca adversa.

Endostatin a Potential Biomarker for Heart Failure with Preserved Ejection Fraction.

BACKGROUND: Endostatin is a circulating endogenous angiogenesis inhibitor preventing neovascularization. Previous studies demonstrated the prognostic value of Endostatin among patients with heart failure with reduced ejection fraction (HFrEF). However, the role of Endostatin among patients with heart failure with preserved ejection fraction (HFpEF) remains unclear. OBJECTIVE: This study aimed to investigate the association between serum Endostatin levels, natriuretic peptide levels and the severity of left ventricular diastolic dysfunction and the diagnosis of HFpEF. METHODS: Endostatin serum concentrations were measured in 301 patients comprising 77 HFpEF patients, 169 patients with asymptomatic left ventricular diastolic dysfunction (ALVDD), and 55 controls with normal cardiac function. RESULTS: Endostatin serum levels were significantly elevated in patients with HFpEF (median/interquartile range 179.0 [159-220]) and ALVDD (163.8 [145.4-191.3]) compared to controls (149.1 [130.6-176.9]), p < 0.001 and p = 0.004, respectively) and significant correlated with N-terminal pro B-type natriuretic peptide (NT-proBNP). CONCLUSIONS: This hypothesis-generating pilot study gives first evidence that Endostatin correlates with the severity of diastolic dysfunction and may become a novel biomarker for HFpEF. We hypothesize a rise in Endostatin levels may reflect inhibition of adaptive angiogenesis and adverse cardiac remodeling.

Chemoradiotherapy Resistance in Colorectal Cancer Cells is Mediated by Wnt/ß-catenin Signaling.

Activation of Wnt/ß-catenin signaling plays a central role in the development and progression of colorectal cancer. The Wnt-transcription factor, TCF7L2, is overexpressed in primary rectal cancers that are resistant to chemoradiotherapy and TCF7L2 mediates resistance to chemoradiotherapy. However, it is unclear whether the resistance is mediated by a TCF7L2 inherent mechanism or Wnt/ß-catenin signaling in general. Here, inhibition of ß-catenin by siRNAs or a small-molecule inhibitor (XAV-939) resulted in sensitization of colorectal cancer cells to chemoradiotherapy. To investigate the potential role of Wnt/ß-catenin signaling in controlling therapeutic responsiveness, nontumorigenic RPE-1 cells were stimulated with Wnt-3a, a physiologic ligand of Frizzled receptors, which increased resistance to chemoradiotherapy. This effect could be recapitulated by overexpression of a degradation-resistant mutant of ß-catenin (S33Y), also boosting resistance of RPE-1 cells to chemoradiotherapy, which was, conversely, abrogated by siRNA-mediated silencing of ß-catenin. Consistent with these findings, higher expression levels of active ß-catenin were observed as well as increased TCF/LEF reporter activity in SW1463 cells that evolved radiation resistance due to repeated radiation treatment. Global gene expression profiling identified several altered pathways, including PPAR signaling and other metabolic pathways, associated with cellular response to radiation. In summary, aberrant activation of Wnt/ß-catenin signaling not only regulates the development and progression of colorectal cancer, but also mediates resistance of rectal cancers to chemoradiotherapy.Implications: Targeting Wnt/ß-catenin signaling or one of the downstream pathways represents a promising strategy to increase response to chemoradiotherapy. Mol Cancer Res; 15(11); 1481-90. ©2017 AACR.

Changes of Microrna Levels in Plasma of Patients with Rectal Cancer during Chemoradiotherapy.

Since the response to chemoradiotherapy in patients with locally advanced rectal cancer is heterogeneous, valid biomarkers are needed to monitor tumor response. Circulating microRNAs are promising candidates, however analyses of circulating microRNAs in rectal cancer are still rare. 111 patients with rectal cancer and 46 age-matched normal controls were enrolled. The expression levels of 30 microRNAs were analyzed in 17 pre-treatment patients' plasma samples. Differentially regulated microRNAs were validated in 94 independent patients. For 52 of the 94 patients a paired comparison between pre-treatment and post-treatment samples was performed. miR-17, miR-18b, miR-20a, miR-31, and miR-193a_3p, were significantly downregulated in pre-treatment plasma samples of patients with rectal cancer (p < 0.05). miR-29c, miR-30c, and miR-195 showed a trend of differential regulation. After validation, miR-31 and miR-30c were significantly deregulated by a decrease of expression. In 52 patients expression analyses of the 8 microRNAs in matched pre-treatment and post-treatment samples showed a significant decrease for all microRNAs (p < 0.05) after treatment. Expression levels of miR-31 and miR-30c could serve as valid biomarkers if validated in a prospective study. Plasma microRNA expression levels do not necessarily represent miRNA expression levels in tumor tissue. Also, expression levels of microRNAs change during multimodal therapy.

Molecular and Digital Biomarker Supported Decision Making in Clinical Studies in Cardiovascular Indications.

Although a large number of pharmaceutical therapies are available to treat cardiovascular diseases like heart failure, in many medical conditions treatment is still not optimal and, therefore, the need for innovative, safe and efficacious drugs is still very high in this indication. Biomarkers are an important tool in the preclinical and clinical drug development process; they allow patient selection for clinical studies as well as therapy monitoring during studies. Biomarker concepts in cardiovascular indications differ very much from those in oncology and are very diverse. The present article gives an overview of the pathomechanisms of heart failure and describes the socioeconomic impact of the disease and the biomarker strategies being applied in the development of new heart failure drugs. The focus lies on protein biomarkers that can be measured in the blood and on functional biomarkers that can be derived from implanted and wearable medical devices.

Prognostic Value of MicroRNAs in Preoperative Treated Rectal Cancer.

BACKGROUND: Patients with locally advanced rectal cancer are treated with preoperative chemoradiotherapy followed by surgical resection. Despite similar clinical parameters (uT2-3, uN+) and standard therapy, patients' prognoses differ widely. A possible prediction of prognosis through microRNAs as biomarkers out of treatment-naïve biopsies would allow individualized therapy options. METHODS: Microarray analysis of 45 microdissected preoperative biopsies from patients with rectal cancer was performed to identify potential microRNAs to predict overall survival, disease-free survival, cancer-specific survival, distant-metastasis-free survival, tumor regression grade, or nodal stage. Quantitative real-time polymerase chain reaction (qPCR) was performed on an independent set of 147 rectal cancer patients to validate relevant miRNAs. RESULTS: In the microarray screen, 14 microRNAs were significantly correlated to overall survival. Five microRNAs were included from previous work. Finally, 19 miRNAs were evaluated by qPCR. miR-515-5p, miR-573, miR-579 and miR-802 demonstrated significant correlation with overall survival and cancer-specific survival (p < 0.05). miR-573 was also significantly correlated with the tumor regression grade after preoperative chemoradiotherapy. miR-133b showed a significant correlation with distant-metastasis-free survival. miR-146b expression levels showed a significant correlation with nodal stage. CONCLUSION: Specific microRNAs can be used as biomarkers to predict prognosis of patients with rectal cancer and possibly stratify patients' therapy if validated in a prospective study.

Newly Constructed Network Models of Different WNT Signaling Cascades Applied to Breast Cancer Expression Data.

INTRODUCTION: WNT signaling is a complex process comprising multiple pathways: the canonical ß-catenin-dependent pathway and several alternative non-canonical pathways that act in a ß-catenin-independent manner. Representing these intricate signaling mechanisms through bioinformatic approaches is challenging. Nevertheless, a simplified but reliable bioinformatic WNT pathway model is needed, which can be further utilized to decipher specific WNT activation states within e.g. high-throughput data. RESULTS: In order to build such a model, we collected, parsed, and curated available WNT signaling knowledge from different pathway databases. The data were assembled to construct computationally suitable models of different WNT signaling cascades in the form of directed signaling graphs. This resulted in four networks representing canonical WNT signaling, non-canonical WNT signaling, the inhibition of canonical WNT signaling and the regulation of WNT signaling pathways, respectively. Furthermore, these networks were integrated with microarray and RNA sequencing data to gain deeper insight into the underlying biology of gene expression differences between MCF-7 and MDA-MB-231 breast cancer cell lines, representing weakly and highly invasive breast carcinomas, respectively. Differential genes up-regulated in the MDA-MB-231 compared to the MCF-7 cell line were found to display enrichment in the gene set originating from the non-canonical network. Moreover, we identified and validated differentially regulated modules representing canonical and non-canonical WNT pathway components specific for the aggressive basal-like breast cancer subtype. CONCLUSIONS: In conclusion, we demonstrated that these newly constructed WNT networks reliably reflect distinct WNT signaling processes. Using transcriptomic data, we shaped these networks into comprehensive modules of the genes implicated in the aggressive basal-like breast cancer subtype and demonstrated that non-canonical WNT signaling is important in this context. The topology of these networks can be further refined in the future by integration with complementary data such as protein-protein interactions, in order to gain greater insight into signaling processes.

Preoperative Prediction of Lymph Node Status by Circulating Mir-18b and Mir-20a During Chemoradiotherapy in Patients with Rectal Cancer.

BACKGROUND: In locally advanced rectal cancer, therapeutic success of preoperative chemoradiotherapy (CRT) ranges from resistance to complete regression. For those patients that respond well to CRT, local resection (LR) procedures are currently under investigation to minimize surgical morbidity and to improve functional outcome. To maintain the oncologic benefit appropriate staging procedures are essential. However, current clinical assessment and imaging techniques need further improvement. METHODS: Five miRNAs associated with rectal cancer (miR-17, miR-18b, miR-20a, miR-31, and miR-193-3p) were analyzed in the plasma of rectal cancer patients (n = 42) using qPCR. Expression levels were assessed before, during and after CRT and analyzed in regard to patients' lymph node status obtained after total mesorectal excision and intensive histopathological work-up. RESULTS: Four of the five miRNAs revealed reliable results in the plasma. miR-31 was excluded due to its low expression. MicroRNA-17, 18b, 20a, and 193-3p showed altering expression levels at different time points. Only 43% (miR-17), 43% (miR-18b), 53% (miR-20a), and 60% (miR-193-3p) showed a continuous in- or decrease of miRNA expression. The reduced expression of miR-18b and miR-20a during CRT was found to be significantly associated with postoperative lymph node negativity (p < 0.05). CONCLUSION: MicroRNA expression in patient plasma changes during preoperative CRT. The alteration is not continuous and the meaning requires additional analysis on a larger patient cohort. The co-occurrence of reduced miR-18b and miR-20a expression with lymph node negativity after preoperative CRT could help to stratify the surgical procedure with respect to total mesorectal excision and LR if validated prospectively.

STAT3 inhibition sensitizes colorectal cancer to chemoradiotherapy in vitro and in vivo.

Increased activity of signal transducer and activator of transcription 3 (STAT3) is common in human malignancies, including colorectal cancers (CRCs). We have recently reported that STAT3 gene expression correlates with resistance of CRC cell lines to 5-fluorouracil (5-FU)-based chemoradiotherapy (CT/RT). This is of considerable clinical importance, because a large proportion of rectal cancers are resistant to preoperative multimodal treatment. To test whether STAT3 contributes to CT/RT-resistance, we first confirmed that STAT3 protein expression correlated positively with increasing resistance. While STAT3 was not constitutively active, stimulation with interleukin-6 (IL-6) resulted in remarkably higher expression levels of phosphorylated STAT3 in CT/RT-resistant cell lines. A similar result was observed when we determined IL-6-induced expression levels of phosphorylated STAT3 following irradiation. Next, STAT3 was inhibited in SW480 and SW837 using siRNA, shRNA and the small-molecule inhibitor STATTIC. Successful silencing and inhibition of phosphorylation was confirmed using Western blot analysis and a luciferase reporter assay. RNAi-mediated silencing as well as STATTIC treatment resulted in significantly decreased clonogenic survival following exposure to 3 µM of 5-FU and irradiation in a dose-dependent manner, with dose-modifying factors of 1.3-2.5 at a surviving fraction of 0.37. Finally, STAT3 inhibition led to a profound CT/RT-sensitization in a subcutaneous xenograft model, with a significantly delayed tumor regrowth in STATTIC-treated mice compared with control animals. These results highlight a potential role of STAT3 in mediating treatment resistance and provide first proof of concept that STAT3 represents a promising novel molecular target for sensitizing resistant rectal cancers to CT/RT.

Identification of a microRNA expression signature for chemoradiosensitivity of colorectal cancer cells, involving miRNAs-320a, -224, -132 and let7g.

BACKGROUND AND PURPOSE: Preoperative chemoradiotherapy (CRT) represents the standard treatment for locally advanced rectal cancer. Tumor response and progression vary considerably. MicroRNAs represent master regulators of gene expression, and may therefore contribute to this diversity. MATERIAL AND METHODS: Genome-wide microRNA (miRNA) profiling was performed for 12 colorectal cancer (CRC) cell lines and an individual in vitro signature of chemoradiosensitivity was established. Functional relevance of selected miRNAs was established by transfecting miRNA-mimics into SW480 and SW837 cells. The prognostic value of selected miRNAs was assessed in 128 pretherapeutic patient biopsies. RESULTS: Thirty-six miRNAs were identified to significantly correlate with sensitivity to CRT (Q < 0.05) including miR-320a and other miRNAs involved in the MAPK-, TGF- and Wnt-pathway. Transfection of selected miRNAs (let-7g, miR-132, miR-224, miR-320a) each induced a shift of sensitivity. High expression of let-7 g was associated with a good prognosis in rectal cancer patients (P = 0.03). CONCLUSIONS: This is the first report of a miRNA expression signature for in vitro chemoradiosensitivity of CRC cell lines. Many of the identified miRNAs have not been linked to the response to CRT and may represent potential molecular targets to sensitize resistant cancers. If further validated, let7g expression may serve as predictive biomarker.