Towards a New Science of a Clinical Data Intelligence

In this paper we define Clinical Data Intelligence as the analysis of data generated in the clinical routine with the goal of improving patient care. We define a science of a Clinical Data Intelligence as a data analysis that permits the derivation of scientific, i.e., generalizable and reliable results. We argue that a science of a Clinical Data Intelligence is sensible in the context of a Big Data analysis, i.e., with data from many patients and with complete patient information. We discuss that Clinical Data Intelligence requires the joint efforts of knowledge engineering, information extraction (from textual and other unstructured data), and statistics and statistical machine learning. We describe some of our main results as conjectures and relate them to a recently funded research project involving two major German university hospitals.Comment: NIPS 2013 Workshop: Machine Learning for Clinical Data Analysis and Healthcare, 201

The Reality in the Surveillance of Breast Cancer Survivors—Results of a Patient Survey

Background: International guidelines for the surveillance of breast cancer patients recommend a minimized clinical follow-up including routine history and physical examination and regularly scheduled mammograms. However, the abandonment of scheduled follow-up examinations in breast cancer survivors remains a contradiction to established follow-up guidelines for other solid tumours.Patients and Methods: We report the patients’ view on the basis of a survey performed in two separate geographical areas in Germany. The questionnaires were sent out to 2.658 patients with a history of breast cancer.Results: A total of 801 patients (30.1%) responded to the questionnaire. The results of the survey can be summarized in two major categories: First, necessity for surveillance was affi rmed by a majority (>95%), and 47.8% of the organized patients answered that there was a need for more intensive diagnostic effort during follow-up. The main expectation from an intensified follow-up was the increased feeling of security as expressed by >80% of the women. Second, the present survey indicates that most of the regularly scheduled follow-up visits were expanded using extensive laboratory and imaging procedures exceeding the quantity of examinations recommended in the present follow-up guidelines.Conclusion: Despite the fact that only one third of the patients responded to the questionnaire, the survey indicates that a majority of physicians who treated these patients still do not accept the present follow-up guidelines. To some extent this may be explained by the observation that patients and possibly also their doctors trust that intensified follow-up increases diagnostic security and survival. Since considerable changes in the treatment options of breast cancer have been made during the last decades a new trial of investigations in follow-up is warranted

Pathway-Based Analysis of Genome-Wide Association Data Identified SNPs in HMMR as Biomarker for Chemotherapy-Induced Neutropenia in Breast Cancer Patients

Neutropenia secondary to chemotherapy in breast cancer patients can be life-threatening and there are no biomarkers available to predict the risk of drug-induced neutropenia in those patients. We previously performed a genome-wide association study (GWAS) for neutropenia events in women with breast cancer who were treated with 5-fluorouracil, epirubicin and cyclophosphamide and recruited to the SUCCESS A trial. A genome-wide significant single-nucleotide polymorphism (SNP) signal in the tumor necrosis factor superfamily member 13B (TNFSF13B) gene, encoding the cytokine B-cell activating factor (BAFF), was identified in that GWAS. Taking advantage of these existing GWAS data, in the present study we utilized a pathway-based analysis approach by leveraging knowledge of the pharmacokinetics and pharmacodynamics of drugs and breast cancer pathophysiology to identify additional SNPs/genes associated with the underlying etiology of chemotherapy-induced neutropenia. We identified three SNPs in the hyaluronan mediated motility receptor (HMMR) gene that were significantly associated with neutropenia (p < 1.0E-04). Those three SNPs were trans-expression quantitative trait loci for the expression of TNFSF13B (p < 1.0E-04). The minor allele of these HMMR SNPs was associated with a decreased TNFSF13B mRNA level. Additional functional studies performed with lymphoblastoid cell lines (LCLs) demonstrated that LCLs possessing the minor allele for the HMMR SNPs were more sensitive to drug treatment. Knock-down of TNFSF13B in LCLs and HL-60 promyelocytic cells and treatment of those cells with BAFF modulated the cell sensitivity to chemotherapy treatment. These results demonstrate that HMMR SNP-dependent cytotoxicity of these chemotherapeutic agents might be related to TNFSF13B expression level. In summary, utilizing a pathway-based approach for the analysis of GWAS data, we identified additional SNPs in the HMMR gene that were associated with neutropenia and also were correlated with TNFSF13B expression

Ki67, chemotherapy response, and prognosis in breast cancer patients receiving neoadjuvant treatment

<p>Abstract</p> <p>Background</p> <p>The pathological complete response (pCR) after neoadjuvant chemotherapy is a surrogate marker for a favorable prognosis in breast cancer patients. Factors capable of predicting a pCR, such as the proliferation marker Ki67, may therefore help improve our understanding of the drug response and its effect on the prognosis. This study investigated the predictive and prognostic value of Ki67 in patients with invasive breast cancer receiving neoadjuvant treatment for breast cancer.</p> <p>Methods</p> <p>Ki67 was stained routinely from core biopsies in 552 patients directly after the fixation and embedding process. HER2/neu, estrogen and progesterone receptors, and grading were also assessed before treatment. These data were used to construct univariate and multivariate models for predicting pCR and prognosis. The tumors were also classified by molecular phenotype to identify subgroups in which predicting pCR and prognosis with Ki67 might be feasible.</p> <p>Results</p> <p>Using a cut-off value of > 13% positively stained cancer cells, Ki67 was found to be an independent predictor for pCR (OR 3.5; 95% CI, 1.4, 10.1) and for overall survival (HR 8.1; 95% CI, 3.3 to 20.4) and distant disease-free survival (HR 3.2; 95% CI, 1.8 to 5.9). The mean Ki67 value was 50.6 ± 23.4% in patients with pCR. Patients without a pCR had an average of 26.7 ± 22.9% positively stained cancer cells.</p> <p>Conclusions</p> <p>Ki67 has predictive and prognostic value and is a feasible marker for clinical practice. It independently improved the prediction of treatment response and prognosis in a group of breast cancer patients receiving neoadjuvant treatment. As mean Ki67 values in patients with a pCR were very high, cut-off values in a high range above which the prognosis may be better than in patients with lower Ki67 values may be hypothesized. Larger studies will be needed in order to investigate these findings further.</p

Circulating Micro-RNAs as Potential Blood-Based Markers for Early Stage Breast Cancer Detection

INTRODUCTION: MicroRNAs (miRNAs, miRs) are a class of small, non-coding RNA molecules with relevance as regulators of gene expression thereby affecting crucial processes in cancer development. MiRNAs offer great potential as biomarkers for cancer detection due to their remarkable stability in blood and their characteristic expression in many different diseases. We investigated whether microarray-based miRNA profiling on whole blood could discriminate between early stage breast cancer patients and healthy controls. METHODS: We performed microarray-based miRNA profiling on whole blood of 48 early stage breast cancer patients at diagnosis along with 57 healthy individuals as controls. This was followed by a real-time semi-quantitative Polymerase Chain Reaction (RT-qPCR) validation in a separate cohort of 24 early stage breast cancer patients from a breast cancer screening unit and 24 age matched controls using two differentially expressed miRNAs (miR-202, miR-718). RESULTS: Using the significance level of p<0.05, we found that 59 miRNAs were differentially expressed in whole blood of early stage breast cancer patients compared to healthy controls. 13 significantly up-regulated miRNAs and 46 significantly down-regulated miRNAs in our microarray panel of 1100 miRNAs and miRNA star sequences could be detected. A set of 240 miRNAs that was evaluated by radial basis function kernel support vector machines and 10-fold cross validation yielded a specificity of 78.8%, and a sensitivity of 92.5%, as well as an accuracy of 85.6%. Two miRNAs were validated by RT-qPCR in an independent cohort. The relative fold changes of the RT-qPCR validation were in line with the microarray data for both miRNAs, and statistically significant differences in miRNA-expression were found for miR-202. CONCLUSIONS: MiRNA profiling in whole blood has potential as a novel method for early stage breast cancer detection, but there are still challenges that need to be addressed to establish these new biomarkers in clinical use

Comprehensive genetic assessment of the ESR1 locus identifies a risk region for endometrial cancer

Excessive exposure to estrogen is a well-established risk factor for endometrial cancer (EC), particularly for cancers of endometrioid histology. The physiological function of estrogen is primarily mediated by estrogen receptor alpha, encoded by ESR1. Consequently, several studies have investigated whether variation at the ESR1 locus is associated with risk of EC, with conflicting results. We performed comprehensive fine-mapping analyses of 3633 genotyped and imputed single nucleotide polymorphisms (SNPs) in 6607 EC cases and 37 925 controls. There was evidence of an EC risk signal located at a potential alternative promoter of the ESR1 gene (lead SNP rs79575945, P=1.86x10(-5)), which was stronger for cancers of endometrioid subtype (P=3.76x10(-6)). Bioinformatic analysis suggests that this risk signal is in a functionally important region targeting ESR1, and eQTL analysis found that rs79575945 was associated with expression of SYNE1, a neighbouring gene. In summary, we have identified a single EC risk signal located at ESR1, at study-wide significance. Given SNPs located at this locus have been associated with risk for breast cancer, also a hormonally driven cancer, this study adds weight to the rationale for performing informed candidate fine-scale genetic studies across cancer types

Shared genetics underlying epidemiological association between endometriosis and ovarian cancer

Epidemiological studies have demonstrated associations between endometriosis and certain histotypes of ovarian cancer, including clear cell, low-grade serous and endometrioid carcinomas. We aimed to determine whether the observed associations might be due to shared genetic aetiology. To address this, we used two endometriosis datasets genotyped on common arrays with full-genome coverage (3194 cases and 7060 controls) and a large ovarian cancer dataset genotyped on the customized Illumina Infinium iSelect (iCOGS) arrays (10 065 cases and 21 663 controls). Previous work has suggested that a large number of genetic variants contribute to endometriosis and ovarian cancer (all histotypes combined) susceptibility. Here, using the iCOGS data, we confirmed polygenic architecture for most histotypes of ovarian cancer. This led us to evaluate if the polygenic effects are shared across diseases. We found evidence for shared genetic risks between endometriosis and all histotypes of ovarian cancer, except for the intestinal mucinous type. Clear cell carcinoma showed the strongest genetic correlation with endometriosis (0.51, 95% CI = 0.18-0.84). Endometrioid and low-grade serous carcinomas had similar correlation coefficients (0.48, 95% CI = 0.07-0.89 and 0.40, 95% CI = 0.05-0.75, respectively). High-grade serous carcinoma, which often arises from the fallopian tubes, showed a weaker genetic correlation with endometriosis (0.25, 95% CI = 0.11-0.39), despite the absence of a known epidemiological association. These results suggest that the epidemiological association between endometriosis and ovarian adenocarcinoma may be attributable to shared genetic susceptibility loci