Oleg Blyuss

Serum CA19-9 Is Significantly Upregulated up to 2 Years before Diagnosis with Pancreatic Cancer: Implications for Early Disease Detection

Purpose: Biomarkers for the early detection of pancreatic cancer are urgently needed. The primary objective of this study was to evaluate whether increased levels of serum CA19-9, CA125, CEACAM1, and REG3A are present before clinical presentation of pancreatic cancer and to assess the performance of combined markers for early detection and prognosis. Experimental Design: This nested case–control study within the UKCTOCS included 118 single and 143 serial serum samples from 154 postmenopausal women who were subsequently diagnosed with pancreatic cancer and 304 matched noncancer controls. Samples were split randomly into independent training and test sets. CA19-9, CA125, CEACAM1, and REG3A were measured using ELISA and/or CLIA. Performance of markers to detect cancers at different times before diagnosis and for prognosis was evaluated. Results: At 95% specificity, CA19-9 (>37 U/mL) had a sensitivity of 68% up to 1 year, and 53% up to 2 years before diagnosis. Combining CA19-9 and CA125 improved sensitivity as CA125 was elevated (>30 U/mL) in approximately 20% of CA19-9–negative cases. CEACAM1 and REG3A were late markers adding little in combined models. Average lead times of 20 to 23 months were estimated for test-positive cases. Prediagnostic levels of CA19-9 and CA125 were associated with poor overall survival (HR, 2.69 and 3.15, respectively). Conclusions: CA19-9 and CA125 have encouraging sensitivity for detecting preclinical pancreatic cancer, and both markers can be used as prognostic tools. This work challenges the prevailing view that CA19-9 is upregulated late in the course of pancreatic cancer development. Clin Cancer Res; 21(3); 622–31. ©2014 AACR.

Leptin induces upregulation of sphingosine kinase 1 in oestrogen receptor-negative breast cancer via Src family kinase-mediated, janus kinase 2-independent pathway

IntroductionObesity is a known risk factor for breast cancer. Sphingosine kinase 1 (SK1) is an oncogenic lipid kinase that is overexpressed in breast tumours and linked with poor prognosis, however, its role in obesity-driven breast cancer was never elucidated.MethodsHuman primary and secondary breast cancer tissues were analysed for SK1 and leptin receptor expression using quantitative real-time polymerase chain reaction (qRT-PCR) assay. Leptin-induced signalling was analysed in human oestrogen receptor (ER)-positive and negative breast cancer cells using Western blotting, qRT-PCR and radiolabelling assays.ResultsOur findings show for the first time that human primary breast tumours and associated lymph node metastases exhibit a strong correlation between SK1 and leptin receptor expression (Pearson R = 0.78 and R = 0.77, respectively, P <0.001). Both these genes are elevated in metastases of ER-negative patients and show a significant increase in patients with higher body mass index (BMI). Leptin induces SK1 expression and activation in ER-negative breast cancer cell lines MDAMB-231 and BT-549, but not in ER-positive cell lines. Pharmacological inhibition and gene knockdown showed that leptin-induced SK1 activity and expression are mediated by activation of extracellular signal-regulated kinases 1/2 (ERK1/2) and Src family kinase (SFK) pathways, but not by the major pathways downstream of leptin receptor (LEPR) - janus kinase 2 (JAK2) and signal transducer and activator of transcription 3 (STAT3). Src-homology 2 domain-containing phosphatase 2 (SHP2) appeared to be key to SK1 activation, and may function as an adaptor protein between SFKs and LEPR. Importantly, leptin-induced breast cancer cell proliferation was abrogated by SK1-specific small interfering RNA (siRNA).ConclusionsOverall, our findings demonstrate a novel SFK/ERK1/2-mediated pathway that links leptin signalling and expression of oncogenic enzyme SK1 in breast tumours and suggest the potential significance of this pathway in ER-negative breast cancer.

Testing breast cancer serum biomarkers for early detection and prognosis in pre-diagnosis samples

Background:Breast cancer is a leading cause of morbidity and mortality worldwide. Although mammography screening is available, there is an ongoing interest in improved early detection and prognosis. Herein, we have analysed a combination of serological biomarkers in a case–control cohort of sera taken before diagnosis.Methods:This nested case–control study within the UK Collaborative Trial of Ovarian Cancer Screening (UKCTOCS) used serum samples from 239 women who subsequently developed breast cancer and 239 matched cancer-free controls. Sera were screened by ELISA for 9 candidate markers. Univariate and multivariate analyses were performed to examine associations with clinico-pathological features and between case controls in different time groups before diagnosis.Results:Significant associations with clinico-pathological features related to prognosis were found for several candidates (CA15-3, HSP90A and PAI-1). However, there were no consistent differences between cases and controls for any candidate in the lead up to diagnosis. Whilst combination models outperformed single markers, there was no increase in performance towards diagnosis.Conclusions:This study using unique pre-diagnosis samples shows that CA15-3, HSP90A and PAI-1 have potential as early prognostic markers and warrant further investigation. However, none of the candidates or combinations would be useful for screening.

Identification of potential serum peptide biomarkers of biliary tract cancer using MALDI MS profiling

BackgroundThe aim of this discovery study was the identification of peptide serum biomarkers for detecting biliary tract cancer (BTC) using samples from healthy volunteers and benign cases of biliary disease as control groups. This work was based on the hypothesis that cancer-specific exopeptidases exist and that their activities in serum can generate cancer-predictive peptide fragments from circulating proteins during coagulation.MethodsThis case control study used a semi-automated platform incorporating polypeptide extraction linked to matrix-assisted laser desorption/ionisation time-of-flight mass spectrometry (MALDI-TOF MS) to profile 92 patient serum samples. Predictive models were generated to test a validation serum set from BTC cases and healthy volunteers.ResultsSeveral peptide peaks were found that could significantly differentiate BTC patients from healthy controls and benign biliary disease. A predictive model resulted in a sensitivity of 100% and a specificity of 93.8% in detecting BTC in the validation set, whilst another model gave a sensitivity of 79.5% and a specificity of 83.9% in discriminating BTC from benign biliary disease samples in the training set. Discriminatory peaks were identified by tandem MS as fragments of abundant clotting proteins.ConclusionsSerum MALDI MS peptide signatures can accurately discriminate patients with BTC from healthy volunteers.

Serial Patterns of Ovarian Cancer Biomarkers in a Prediagnosis Longitudinal Dataset

Early detection of ovarian cancer through screening may have impact on mortality from the disease. Approaches based on CA125 cut-off have not been effective. Longitudinal algorithms such as the Risk of Ovarian Cancer Algorithm (ROCA) to interpret CA125 have been shown to have higher sensitivity and specificity than a single cut-off. The aim of this study was to investigate whether other ovarian cancer-related biomarkers, Human Epididymis 4 (HE4), glycodelin, mesothelin, matrix metalloproteinase 7 (MMP7), and cytokeratin 19 fragment (CYFRA 21-1), could improve the performance of CA125 in detecting ovarian cancer earlier. Serum samples (single and serial) predating diagnosis from 47 women taking part in the UK Collaborative Trial of Ovarian Cancer Screening (UKCTOCS) who went on to develop primary invasive ovarian, fallopian tube, or peritoneal cancer (index cancer) (170 samples) and 179 matched controls (893 samples) were included in the study. A multiplex immunobased assay platform (Becton Dickinson) allowing simultaneous measurement of the six serum markers was used. The area under the ROC curve for the panel of three biomarkers (CA125, HE4, and glycodelin) was higher than for CA125 alone for all analysed time groups, indicating that these markers can improve on sensitivity of CA125 alone for ovarian cancer detection.

Effect of Noise in Intelligent Cellular Decision Making

Similar to intelligent multicellular neural networks controlling human brains, even single cells, surprisingly, are able to make intelligent decisions to classify several external stimuli or to associate them. This happens because of the fact that gene regulatory networks can perform as perceptrons, simple intelligent schemes known from studies on Artificial Intelligence. We study the role of genetic noise in intelligent decision making at the genetic level and show that noise can play a constructive role helping cells to make a proper decision. We show this using the example of a simple genetic classifier able to classify two external stimuli.

Sex hormone measurements using mass spectrometry and sensitive extraction radioimmunoassay and risk of estrogen receptor negative and positive breast cancer: Case control study in UK Collaborative Cancer Trial of Ovarian Cancer Screening (UKCTOCS).

INTRODUCTION Associations of endogenous sex hormone levels and all as well as estrogen-receptor (ER)-positive breast cancers are well described. However, studies investigating their association with ER-negative tumours are limited and none use accurate assays such as mass spectrometry. METHODS Within the UK Collaborative Trial of Ovarian Cancer Screening (UKCTOCS), a nested case-control study was undertaken of postmenopausal-women who developed ER-negative (n=92) or ER-positive (n=205) breast cancer after sample donation and 297 (1:1) age-matched controls. Androgens (testosterone and androstenedione) were measured using mass spectrometry and estradiol by extraction radioimmunoassay (RIA). Bioavailable estradiol and testosterone were calculated using the total hormone level and the sex hormone-binding globulin concentration. Subjects were classified according to the quartile range among controls. Logistic regression was used to estimate odds-ratio (OR) and 95% confidence-intervals (CI) of the associations between two factors and breast cancer risk. A separate analysis was done by stratifying the women based on whether they provided their samples less than or more than 2years before diagnosis. RESULTS Estradiol and free estradiol were significantly higher prior to diagnosis of ER-negative breast cancer compared with controls while androgens and SHBG did not show any difference. Estradiol, free estradiol, free testosterone and SHBG were significantly higher before ER-positive breast cancer diagnosis compared with controls. Women had a twofold increased ER-negative breast cancer risk if estradiol and free estradiol were in the top quartile but not androgens (testosterone and androstenedione) or SHBG. These associations remained significant only when samples closer (median 1.1y before) to diagnosis were analyzed rather than farther from diagnosis (median 2.9y before). Women had a 2.34 (95% CI: 1.21-4.61, p=0.001), 2.21 (95% CI: 1.14-4.38, p=0.001), 2 (95% CI: 1.05-3.89, p=0.005) fold increased ER-positive breast cancer risk if estradiol, free estradiol and free testosterone respectively were in the top quartile. These associations remained significant regardless of whether the samples were collected less than or more than 2years prior to diagnosis. CONCLUSION In postmenopausal women increased estrogens but not androgens are associated with ER-negative breast cancer. Previously reported associations of estradiol and free testosterone with ER-positive breast cancer are confirmed. The use of mass spectrometry and sensitive RIA add validity to these findings.

Self-reported transvaginal ultrasound visualization of normal ovaries in postmenopausal women is not reliable: results of expert review of archived images in UKCTOCS

In the UK Collaborative Trial of Ovarian Cancer Screening (UKCTOCS), self‐reported visualization rate (VR) of the ovaries by the sonographer on annual transvaginal sonographic (TVS) examinations was a key quality control (QC) metric. The objective of this study was to assess self‐reported VR using expert review of a random sample of archived images of TVS examinations from UKCTOCS, and then to develop software for measuring VR automatically.

Optimal Placement of Irradiation Sources in the Planning of Radiotherapy: Mathematical Models and Methods of Solving

This paper proposes and analyses a mathematical model for the problem of distribution of a finite number of irradiation sources during radiotherapy in continuous environments to maximize the minimal cumulative effects. A new algorithm based on nondifferentiable optimization techniques has been developed to solve this problem.

Current detection rates and time-to-detection of all identifiable BRCA carriers in the Greater London population.

Background BRCA carrier identification offers opportunities for early diagnoses, targeted treatment and cancer prevention. We evaluate BRCA- carrier detection rates in general and Ashkenazi Jewish (AJ) populations across Greater London and estimate time-to-detection of all identifiable BRCA carriers. Methods BRCA carrier data from 1993 to 2014 were obtained from National Health Service genetic laboratories and compared with modelled predictions of BRCA prevalence from published literature and geographical data from UK Office for National Statistics. Proportion of BRCA carriers identified was estimated. Prediction models were developed to fit BRCA detection rate data. BRCA carrier identification rates were evaluated for an ‘Angelina Jolie effect’. Maps for four Greater London regions were constructed, and their relative BRCA detection rates were compared. Models developed were used to predict future time-to-identify all detectable BRCA carriers in AJ and general populations. Results Until 2014, only 2.6% (3072/111 742 estimated) general population and 10.9% (548/4985 estimated) AJ population BRCA carriers have been identified in 16 696 608 (AJ=190 997) Greater London population. 57% general population and 54% AJ mutations were identified through cascade testing. Current detection rates mirror linear fit rather than parabolic model and will not identify all BRCA carriers. Addition of unselected ovarian/triple-negative breast cancer testing would take >250 years to identify all BRCA carriers. Doubling current detection rates can identify all ‘detectable’ BRCA carriers in the general population by year 2181, while parabolic and triple linear rates can identify ‘detectable’ BRCA carriers by 2084 and 2093, respectively. The linear fit model can identify ‘detectable’ AJ carriers by 2044. We did not find an Angelina Jolie effect on BRCA carrier detection rates. There was a significant difference in BRCA detection rates between geographical regions over time (P<0.001). Conclusions The majority of BRCA carriers have not been identified, missing key opportunities for prevention/earlier diagnosis. Enhanced and new strategies/approaches are needed.