Immunohistochemistry for Thymidine Kinase-1 (TK1): A Potential Tool for the Prognostic Stratification of Breast Cancer Patients.
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SUBMITTER: Fanelli GN
PROVIDER: S-EPMC8623797 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:ObjectivesThymidine kinase 1 (TK1) is one of the salvage enzymes engaged in the synthesis of DNA. Although a pro-carcinogenetic role of TK1 has been reported in various types of cancers, its role in pancreatic ductal adenocarcinoma (PDAC) is still unknown. The study is aimed to elaborate the function of TK1 in PDAC and the potential mechanisms in the following study.Materials and methodsTK1 expression was analysed by immunohistochemistry, real-time PCR and Western blot, and its relationship with clinicopathological characteristics of PDAC patients was further investigated. To verify the function of TK1 and potential mechanism, TK1 siRNA was used to transfect PDAC cells and performed a series of assays in cell and animal models.ResultsThe level of TK1 expression was higher in cancerous tissues compared with matched adjacent tissues. TK1 overexpression was associated with progression of PDAC and poor prognosis. Knockdown of TK1 could suppress cell proliferation via inducing S phase arrest mediated by upregulation of P21. Further mechanism investigation suggested that transcription factor E2F-1 could directly regulate the TK1 and promote tumour proliferation.ConclusionsThe results suggested that TK1 might be involved in the development and progression of PDAC by regulating cell proliferation and show that TK1 may work as a promising therapeutic target in patients with PDAC.
| S-EPMC6528927 | biostudies-literature
Project description:BackgroundEmerging data support the use of thymidine kinase 1 (TK1) activity as a prognostic marker and for monitoring of response in breast cancer (BC). The long-term prognostic value of TK1 kinetics during neoadjuvant chemotherapy is unclear, which this study aimed to elucidate.MethodsMaterial from patients enrolled to the single-arm prospective PROMIX trial of neoadjuvant epirubicin, docetaxel and bevacizumab for early BC was used. Ki67 in baseline biopsies was assessed both centrally and by automated digital imaging analysis. TK1 activity was measured from blood samples obtained at baseline and following two cycles of chemotherapy. The associations of TK1 and its kinetics as well as Ki67 with event-free survival and overall survival (OS) were evaluated using multivariable Cox regression models.ResultsCentral Ki67 counting had excellent correlation with the results of digital image analysis (r = 0.814), but not with the diagnostic samples (r = 0.234), while it was independently prognostic for worse OS [adjusted hazard ratio (HRadj) = 2.72, 95% confidence interval (CI) 1.19-6.21, P = 0.02]. Greater increase in TK1 activity after two cycles of chemotherapy resulted in improved event-free survival (HRadj = 0.50, 95% CI 0.26-0.97, P = 0.04) and OS (HRadj = 0.46, 95% CI 0.95, P = 0.04). There was significant interaction between the prognostic value of TK1 kinetics and Ki67 (pinteraction 0.04).ConclusionSerial measurement of serum TK1 activity during neoadjuvant chemotherapy provides long-term prognostic information in BC patients. The ease of obtaining serial samples for TK1 assessment motivates further evaluation in larger studies.
| S-EPMC7957142 | biostudies-literature
Project description:The rapid development of new therapies in metastatic breast cancer (MBC), entails a need for improved prognostic and monitoring tools. Thymidine kinase 1 (TK1) is involved in DNA synthesis and its activity correlates to outcome in cancer patients. The aim of this study was to evaluate serum TK1 activity (sTK1) levels in MBC patients as a tool for prognostication and treatment monitoring. 142 women with MBC scheduled for 1st line systemic treatment were included in a prospective observational study. sTK1 was measured at baseline (BL) and at 1, 3 and 6 months and correlations to progression-free and overall survival (PFS, OS) evaluated. High sTK1 levels (above median) correlated to worse PFS and OS at BL, also after adjusting for other prognostic factors. sTK1 levels were significantly associated with PFS and OS measured from follow-up time points during therapy. Changes from 3 to 6 months during therapy significantly correlated to PFS and OS, whereas early changes did not. We could demonstrate sTK1 level as an independent prognostic factor in patients with newly diagnosed MBC. Changes in sTK1 levels from 3 to 6 months correlated to PFS and OS. Future studies of sTK1 are warranted to further define its clinical utility.
| S-EPMC7066186 | biostudies-literature
Project description:BackgroundLung, breast, and colorectal malignancies are the leading cause of cancer-related deaths in the world causing over 2.8 million cancer-related deaths yearly. Despite efforts to improve prevention methods, early detection, and treatments, survival rates for advanced stage lung, breast, and colon cancer remain low, indicating a critical need to identify cancer-specific biomarkers for early detection and treatment. Thymidine kinase 1 (TK1) is a nucleotide salvage pathway enzyme involved in cellular proliferation and considered an important tumor proliferation biomarker in the serum. In this study, we further characterized TK1's potential as a tumor biomarker and immunotherapeutic target and clinical relevance.MethodsWe assessed TK1 surface localization by flow cytometry and confocal microscopy in lung (NCI-H460, A549), breast (MDA-MB-231, MCF7), and colorectal (HT-29, SW620) cancer cell lines. We also isolated cell surface proteins from HT-29 cells and performed a western blot confirming the presence of TK1 on cell membrane protein fractions. To evaluate TK1's clinical relevance, we compared TK1 expression levels in normal and malignant tissue through flow cytometry and immunohistochemistry. We also analyzed RNA-Seq data from The Cancer Genome Atlas (TCGA) to assess differential expression of the TK1 gene in lung, breast, and colorectal cancer patients.ResultsWe found significant expression of TK1 on the surface of NCI-H460, A549, MDA-MB-231, MCF7, and HT-29 cell lines and a strong association between TK1's localization with the membrane through confocal microscopy and Western blot. We found negligible TK1 surface expression in normal healthy tissue and significantly higher TK1 expression in malignant tissues. Patient data from TCGA revealed that the TK1 gene expression is upregulated in cancer patients compared to normal healthy patients.ConclusionsOur results show that TK1 localizes on the surface of lung, breast, and colorectal cell lines and is upregulated in malignant tissues and patients compared to healthy tissues and patients. We conclude that TK1 is a potential clinical biomarker for the treatment of lung, breast, and colorectal cancer.
| S-EPMC6131957 | biostudies-literature
Project description:BackgroundCanAssist-Breast is an immunohistochemistry based test that predicts risk of distant recurrence in early-stage hormone receptor positive breast cancer patients within first five years of diagnosis. Immunohistochemistry gradings for 5 biomarkers (CD44, ABCC4, ABCC11, N-Cadherin and pan-Cadherins) and 3 clinical parameters (tumor size, tumor grade and node status) of 298 patient cohort were used to develop a machine learning based statistical algorithm. The algorithm generates a risk score based on which patients are stratified into two groups, low- or high-risk for recurrence. The aim of the current study is to demonstrate the analytical performance with respect to repeatability and reproducibility of CanAssist-Breast.MethodsAll potential sources of variation in CanAssist-Breast testing involving operator, run and observer that could affect the immunohistochemistry performance were tested using appropriate statistical analysis methods for each of the CanAssist-Breast biomarkers using a total 309 samples. The cumulative effect of these variations in the immunohistochemistry gradings on the generation of CanAssist-Breast risk score and risk category were also evaluated. Intra-class Correlation Coefficient, Bland Altman plots and pair-wise agreement were performed to establish concordance on IHC gradings, risk score and risk categorization respectively.ResultsCanAssist-Breast test exhibited high levels of concordance on immunohistochemistry gradings for all biomarkers with Intra-class Correlation Coefficient of ≥0.75 across all reproducibility and repeatability experiments. Bland-Altman plots demonstrated that agreement on risk scores between the comparators was within acceptable limits. We also observed > 90% agreement on risk categorization (low- or high-risk) across all variables tested.ConclusionsThe extensive analytical validation data for the CanAssist-Breast test, evaluating immunohistochemistry performance, risk score generation and risk categorization showed excellent agreement across variables, demonstrating that the test is robust.
| S-EPMC6425559 | biostudies-literature
Project description:Lactate concentration is a robust predictor of mortality but in many low resource settings facilities for its analysis are not available. Anion gap (AG), calculated from clinical chemistry results, is a marker of metabolic acidosis and may be more easily obtained in such settings. In this systematic review and meta-analysis we investigated whether the AG predicts mortality in adult patients admitted to critical care settings.We searched Medline, Embase, Web of Science, Scopus, The Cochrane Library and regional electronic databases from inception until May 2016. Studies conducted in any clinical setting that related AG to in-hospital mortality, in-intensive care unit mortality, 31-day mortality or comparable outcome measures were eligible for inclusion. Methodological quality of included studies was assessed using the Quality in Prognostic Studies tool. Descriptive meta-analysis was performed and the I(2) test was used to quantify heterogeneity. Subgroup analysis was undertaken to identify potential sources of heterogeneity between studies.Nineteen studies reporting findings in 12,497 patients were included. Overall, quality of studies was poor and most studies were rated as being at moderate or high risk of attrition bias and confounding. There was substantial diversity between studies with regards to clinical setting, age and mortality rates of patient cohorts. High statistical heterogeneity was found in the meta-analyses of area under the ROC curve (I(2)?=?99 %) and mean difference (I(2)?=?97 %) for the observed AG. Three studies reported good discriminatory power of the AG to predict mortality and were responsible for a large proportion of statistical heterogeneity. The remaining 16 studies reported poor to moderate ability of the AG to predict mortality. Subgroup analysis suggested that intravenous fluids affect the ability of the AG to predict mortality.Based on the limited quality of available evidence, a single AG measurement cannot be recommended for risk stratification in critically ill patients. The probable influence of intravenous fluids on AG levels renders the AG an impractical tool in clinical practice. Future research should focus on increasing the availability of lactate monitoring in low resource settings.CRD42015015249 . Registered on 4th February 2015.
| S-EPMC5006450 | biostudies-other
Project description:MotivationBreast cancer is the second leading cause of cancer death among women. Tumors, even of the same histopathological subtype, exhibit a high genotypic diversity that impedes therapy stratification and that hence must be accounted for in the treatment decision-making process.ResultsHere, we present ClinOmicsTrailbc, a comprehensive visual analytics tool for breast cancer decision support that provides a holistic assessment of standard-of-care targeted drugs, candidates for drug repositioning and immunotherapeutic approaches. To this end, our tool analyzes and visualizes clinical markers and (epi-)genomics and transcriptomics datasets to identify and evaluate the tumor's main driver mutations, the tumor mutational burden, activity patterns of core cancer-relevant pathways, drug-specific biomarkers, the status of molecular drug targets and pharmacogenomic influences. In order to demonstrate ClinOmicsTrailbc's rich functionality, we present three case studies highlighting various ways in which ClinOmicsTrailbc can support breast cancer precision medicine. ClinOmicsTrailbc is a powerful integrated visual analytics tool for breast cancer research in general and for therapy stratification in particular, assisting oncologists to find the best possible treatment options for their breast cancer patients based on actionable, evidence-based results.Availability and implementationClinOmicsTrailbc can be freely accessed at https://clinomicstrail.bioinf.uni-sb.de.Supplementary informationSupplementary data are available at Bioinformatics online.
| S-EPMC6954665 | biostudies-literature
Project description:BackgroundThe individual risk of recurrence in hormone receptor-positive primary breast cancer patients determines whether adjuvant endocrine therapy should be combined with chemotherapy. Clinicopathological parameters and molecular tests such as EndoPredict(®) (EPclin) can support decision making in patients with estrogen receptor-positive, human epidermal growth factor receptor 2 (HER2)-negative cancer.ObjectiveUsing a life-long Markov state transition model, we determined the health economic impact and incremental cost effectiveness of EPclin-based risk stratification in combination with clinical guidelines [German-S3, National Comprehensive Cancer Center Network (NCCN), and St. Gallen] to decide on chemotherapy use.MethodsInformation on overall and metastasis-free survival came from Austrian Breast & Colorectal Cancer Study Group clinical trials 6/8 (n = 1,619) and published literature. Effectiveness was assessed as quality-adjusted life-years (QALYs). Costs (2010) were assessed from a German third-party payer perspective.ResultsLifetime costs per patient ranged from <euro>28,268 (St.Gallen and EPclin) to <euro>33,756 (NCCN). Due to an imperfect prognostic value and differences in chemotherapy use, strategies achieved between 13.165 QALYs (NCCN) and 13.173 QALYs (EPclin alone) per patient. Using German-S3 as reference, three strategies showed dominant results (St. Gallen and EPclin, German-S3 and EPclin, EPclin alone). Compared to German-S3, the addition of EPclin saved <euro>3,388 and gained 0.002 QALYs per patient. Combining guidelines with EPclin remained preferable in sensitivity analysis.ConclusionOur study suggests that molecular markers can be sensibly combined with clinical guidelines to determine the risk profile of adjuvant breast cancer patients. Compared with the current German best practice (German-S3), combinations of EPclin with the St. Gallen, German-S3 or NCCN guideline and EPclin alone were dominant from the perspective of the German healthcare system.
| S-EPMC4305105 | biostudies-literature
Project description:The prognostic value of current multigene assays for breast cancer is limited to hormone receptor-positive, human epidermal growth factor receptor 2-negative early breast cancer. Despite the prognostic significance of immune response-related genes in breast cancer, immune gene signatures have not been incorporated into most multigene assays. Here, using public gene expression microarray datasets, we classified breast cancer patients into three risk groups according to clinical risk and proliferation risk. We then developed the immune prognostic index based on expression of five immune response-related genes (TRAT1, IL2RB, CTLA4, IGHM and IL21R) and lymph node status to predict the risk of recurrence in the clinical and proliferation high-risk (CPH) group. The 10-year probability of disease-free survival (DFS) or distant metastasis-free survival (DMFS) of patients classified as high risk according to the immune prognostic index was significantly lower than those of patients classified as intermediate or low risk. Multivariate analysis revealed that the index is an independent prognostic factor for DFS or DMFS. Moreover, the C-index revealed that it is superior to clinicopathological variables for predicting prognosis. Its prognostic significance was also validated in independent datasets. The immune prognostic index identified low-risk patients among patients classified as CPH, regardless of the molecular subtype of breast cancer, and may overcome the limitations of current multigene assays.
| S-EPMC7794340 | biostudies-literature
Project description:BackgroundThymidine kinase 1 (TK1) is a pyrimidine salvage pathway enzyme that is up-regulated in malignant tissues and elevated in the serum of cancer patients. While TK1 has been well established as a tumor biomarker, little has been done to explore its potential as a tumor target. Recently, we reported the membrane expression of TK1 on malignant cells, but not on normal cells. This study explores the possible use of monoclonal antibodies for the targeting of membrane associated TK1 in lung, breast, colon and prostate cancer cells.MethodsWe generated and evaluated a panel of monoclonal antibodies against six different epitopes exposed in the tetrameric form of TK1. Antibodies were developed with hybridoma technology and validated with Western blot, siRNA TK1 knockdown, enzyme-linked immunosorbent assay (ELISA) and flow cytometry. The therapeutic potential of the antibodies was evaluated in vitro in antibody-dependent cell-mediated-cytotoxicity (ADCC) experiments.ResultsBinding of the antibodies to TK1 was confirmed by Western blot in purified recombinant protein, cancer serum, and cell lysate. After a TK1 knockdown was performed, a reduction of TK1 expression was observed with five antibodies. Using indirect ELISA, we identified 3B2E11, 9C10, 7H2, 3B4, 8G2 among the most sensitive antibodies (LOD?=?10.73-66.9 pg/ml). Surface expression of TK1 on the membrane of various cancer cell lines was analyzed with flow cytometry. Antibodies 8G2, 3B4, 7HD and 5F7G11 detected TK1 on the membrane of various cancer cell lines, including lung, prostate, colon and breast. No significant binding was detected on normal lymphocytes. Increased cytolysis of lung (~?70%. p?=?0.0001), breast (~?70%, p?=?0.0461) and colon (~?50% p?=?0.0216) cancer cells by effector cells was observed when anti-TK1 antibodies were added during ADCC experiments.ConclusionsThe antibodies developed showed potential to be used to detect and target TK1 on the membrane of various tumor cells. The targeting of TK1 in malignant cells using monoclonal antibodies may be a feasible approach for the elimination of high TK1 expressing tumor cells.
| S-EPMC7160906 | biostudies-literature