Literatura académica sobre el tema "Cancer Biomarker(s)"
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Artículos de revistas sobre el tema "Cancer Biomarker(s)"
Zhang, Changyu, Qiang-Zhe Zhang, Kun Zhang, Lu-Yuan Li, Michael D. Pluth, Long Yi y Zhen Xi. "Dual-biomarker-triggered fluorescence probes for differentiating cancer cells and revealing synergistic antioxidant effects under oxidative stress". Chemical Science 10, n.º 7 (2019): 1945–52. http://dx.doi.org/10.1039/c8sc03781g.
Texto completoRostron, Brian L., Jia Wang, Arash Etemadi, Sapna Thakur, Joanne T. Chang, Deepak Bhandari, Julianne Cook Botelho et al. "Associations between Biomarkers of Exposure and Lung Cancer Risk among Exclusive Cigarette Smokers in the Golestan Cohort Study". International Journal of Environmental Research and Public Health 18, n.º 14 (9 de julio de 2021): 7349. http://dx.doi.org/10.3390/ijerph18147349.
Texto completoKaragkounis, Georgios y Matthew Kalady. "Molecular Biology: Are We Getting Any Closer to Providing Clinically Useful Information?" Clinics in Colon and Rectal Surgery 30, n.º 05 (noviembre de 2017): 415–22. http://dx.doi.org/10.1055/s-0037-1606373.
Texto completoYarden, Ronit y Tamara Springer. "Precision medicine in colorectal cancer: Gaps in patients’ literacy of biomarkers and genetic testing." Journal of Clinical Oncology 38, n.º 4_suppl (1 de febrero de 2020): 55. http://dx.doi.org/10.1200/jco.2020.38.4_suppl.55.
Texto completoLiang, Shujing, Lifang Hu, Zixiang Wu, Zhihao Chen, Shuyu Liu, Xia Xu y Airong Qian. "CDK12: A Potent Target and Biomarker for Human Cancer Therapy". Cells 9, n.º 6 (18 de junio de 2020): 1483. http://dx.doi.org/10.3390/cells9061483.
Texto completoBickel, Hubert, Wolfgang Bogner, Peter Christian Dubsky, Rupert Bartsch, Margaretha Rudas, Thomas Helbich y Katja Pinker-Domenig. "Diffusion-weighted imaging using ADC mapping as an imaging biomarker for breast cancer invasiveness." Journal of Clinical Oncology 31, n.º 15_suppl (20 de mayo de 2013): 11093. http://dx.doi.org/10.1200/jco.2013.31.15_suppl.11093.
Texto completoVallejo Morales, Esteban, Gustavo Suárez Guerrero y Lina M. Hoyos Palacio. "Computational Simulation of Colorectal Cancer Biomarker Particle Mobility in a 3D Model". Molecules 28, n.º 2 (6 de enero de 2023): 589. http://dx.doi.org/10.3390/molecules28020589.
Texto completoBoehm, Brock E., Monica E. York, Gyorgy Petrovics, Indu Kohaar y Gregory T. Chesnut. "Biomarkers of Aggressive Prostate Cancer at Diagnosis". International Journal of Molecular Sciences 24, n.º 3 (22 de enero de 2023): 2185. http://dx.doi.org/10.3390/ijms24032185.
Texto completoAliyu, Mansur, Ali Akbar Saboor-Yaraghi, Shima Nejati y Behrouz Robat-Jazi. "Urinary VPAC1: A potential biomarker in prostate cancer". AIMS Allergy and Immunology 6, n.º 2 (2022): 42–63. http://dx.doi.org/10.3934/allergy.2022006.
Texto completoAcharya, Devansh, Haoran Gao, Rick Dean Jorgensen, Muhammad Hamdan, Hussein Al-Ahmad, Brittani Thomas, Ushasree Chamarthy, Venugopal Gangur y Gordan Srkalovic. "Analysis of immune biomarkers in cancer patients with solid tumors versus healthy subjects". Journal of Immunology 206, n.º 1_Supplement (1 de mayo de 2021): 68.19. http://dx.doi.org/10.4049/jimmunol.206.supp.68.19.
Texto completoTesis sobre el tema "Cancer Biomarker(s)"
Wilkinson, Richard David Alan. "Evaluating Cathepsin S as a target and a biomarker in cancer". Thesis, Queen's University Belfast, 2016. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.709859.
Texto completoJobs, Elisabeth. "Cathepsin S as a Biomarker of Low-grade Inflammation, Insulin Resistance, and Cardiometabolic Disease Risk". Doctoral thesis, Uppsala universitet, Institutionen för folkhälso- och vårdvetenskap, 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-234027.
Texto completoNweke, Ekene Emmanuel. "Discovery of pancreatic cancer biomarker(s) using focused pathway analyses". Thesis, 2017. http://hdl.handle.net/10539/23156.
Texto completoPancreatic cancer (PDAC) is a deadly type of cancer with almost an equal amount of new cases and deaths observed yearly. It accounts for about 7% of cancer related deaths worldwide with less than 5% of PDAC patients living up to 5 years. The lack of specific and sensitive diagnostic tests is strongly responsible for this poor statistic. The discovery of differentially expressed genes and proteins associated with PDAC is crucial to elucidating this condition and may lead to biomarker finding and further understanding of the disease. This in turn may lead to improved diagnostic tests for early diagnosis. The aim of this study was to identify novel potential biomarkers for PDAC. [No abstract provided. Information taken from summary]
MT2017
BRANDI, JESSICA. "IN-DEPTH CHARACTERIZATION OF THE SECRETOME OF PANCREATIC CANCER STEM CELLS BY iTRAQ-BASED SHOTGUN PROTEOMICS AND IDENTIFICATION OF POTENTIAL MARKERS FOR EARLY DIAGNOSIS OF PANCREATIC CANCER". Doctoral thesis, 2015. http://hdl.handle.net/11562/910982.
Texto completoPancreatic ductal adenocarcinoma (PDAC) is the fourth most common cause of cancer-related death in the world. The prognosis for patients affected by this type of cancer is poor, with the 5-year survival rate after diagnosis being less than 5%. One major reason for this high mortality is the lack of effective diagnostic and prognostic markers. Emerging research has demonstrated that PDAC tumours contain a small sub-population of cancer stem cells (CSCs), which are characterized by self-renewal, anchorage independent growth, long term proliferative capacity, and chemotherapy resistance. These observations render imperative the identification of the specific biological features of CSCs, in order to improve PDAC diagnosis and prognosis. The present research PhD project aim was focused on the identification of markers for early diagnosis of PDAC through the analysis of cancer stem cells. In this investigation, CSCs were obtained ,by using a selective medium, from five out of nine PDAC cell lines; after the formation of spheres which represent the first evidence of staminal traits, CSCs have been characterized for the expression profile of different markers by using FACS and Western blot analysis. CSCs showed increased expression of the stem cell markers EpCAM and CD44v6, decreased expression of epithelial marker E-cadherin, and higher resistance to five anti-cancer drugs. Finally, PDAC CSCs injected into nude mice developed a larger subcutaneous tumour mass and showed a higher metastatic activity compared to parental cells. The results obtained demonstrated the ability to isolate CSCs from different PDAC cell lines and that these cells are differentially resistant to various anticancer agents. This variability render them a model of great importance to deeply understand pancreatic adenocarcinoma biology, to discover new biomarker and to screen new therapeutic compounds. Since it is known that cells secrete proteins for cell-cell communication and that the specificity of secreted proteins can direct cells to distinct microenvironment, it has been analyzed the difference in protein secretion between CSCs and parental cells. It has been performed an iTRAQ-based mass spectrometry proteomic analysis of Panc1 and Panc1 CSCs secretomes identifying a total of 112 secreted proteins, of which 43 were found to have higher abundance in the secretome of Panc1 CSCs as compared to parental cells. Ingenuity Pathway Analysis (IPA) analyses of Panc1 CSCs secretome showed a predominance of proteins involved in glycolysis and gluconeogenesis, pentose phosphate pathway, signalling of glioma invasiveness, of myc-mediated apoptosis, and of ERK5, and remodelling of epithelial adherent junctions. To discover novel potential markers for PDAC diagnosis, it has been analysed the presence of the three proteins that were over-secreted from Panc1 CSCs, i.e. ceruloplasmin, galectin-3, and myristoylated alanine-rich C-kinase substrate (MARCKS) in 100 pancreatic cancer patient and 20 control sera. It has been found that ceruloplasmin and MARCKS levels, were significantly higher in PDAC patient sera compare to healthy controls. In particular, ceruloplasmin was more abundant in patients at an early stage of PDAC. Furthermore, the combination of ceruloplasmin and CA19-9, the current standard serum tumour marker for PDAC, showed an improved area under the receiver operating characteristic curve compared to CA19-9 alone and ceruloplasmin levels were higher than controls in more than 50% of patients negative for CA19-9. This finding suggested that ceruloplasmin might prove to be an important complementary biomarker for CA19-9 in PDAC diagnosis. The study of CSCs and the analyses of secreted molecules turned out to be an approach with a strong potential to improve PDAC biology knowledge and to identify new potential early markers.
Sochor, Marek. "Exprese a prognostický význam mikroRNA u pacientek s časným karcinomem prsu". Doctoral thesis, 2018. http://www.nusl.cz/ntk/nusl-391378.
Texto completoWu, Ming-Han y 吳明翰. "Establishment of a prediction model of breast cancer using Apurine/Apyrimidinic sites as biomarkers". Thesis, 2019. http://ndltd.ncl.edu.tw/cgi-bin/gs32/gsweb.cgi/login?o=dnclcdr&s=id=%22107NCHU5087043%22.&searchmode=basic.
Texto completo國立中興大學
環境工程學系所
107
The purpose of this study was to establish a prediction model of breast cancer using the background values of Apurine/Apyrimidinic sites (AP sites) in breast cancer patients and healthy controls in Taiwanese women. This model aims to screen for individuals with high risk of developing breast cancer by two different approaches, including the “mixed” model and “independent” model. The mixed model utilizes the background levels of AP sites derived from the combined pool of breast cancer patients and healthy controls. The mean values of AP sites were calculated and served as indicators of breast cancer risk (high and low risk). Subjects’ characteristics for each group of individuals in terms of age and Body Mass Index (BMI) were compared. Additionally, the predictive values, false positive rates, and false negative rates of the screening model were estimated. The mathematical means and standard deviations of the independent model were estimated separately using AP sites derived from cancer patients and controls and served as indicators of breast cancer risk (high, medium, and low). The corresponding characteristics for each group of individuals were compared as distinguished by age and BMI. Subjects with levels of AP sites greater than mean values of the cancer patients was classified as a high-risk group, whereas those individuals with levels lower than the mean values of healthy controls was classified as a low-risk group and the rest of the subjects were classified as a medium-risk group. Results from our current investigation indicated that predictive value of mixed model (standard deviation) using the biomarker is 61.4% with 11.3% of false positive rates and 64.9% of false negative rates. The predictive value of mixed model using quartile approach is 59.0% with 40% of false positive rates and 42.1% of false negative rates. The predictive values of the independent model are estimated to be 85.4% in high-risk group and 58.7% in low-risk group. In conclusions, the model established in this study may be applied to the field of preventive medicine in breast cancer.
Gomolčáková, Barbora. "Stratifikace rizika progrese onemocnění u pacientek s abnormálním cytologickým nálezem čípku dělohy pomocí molekulárně genetické analýzy vybraných biologických faktorů". Master's thesis, 2015. http://www.nusl.cz/ntk/nusl-335154.
Texto completoJin, Shey-Fay y 金學輝. "Using serum albumin adducts of 17β-estradiol quinone as biomarkers for screening individuals with high risk of developing breast cancer". Thesis, 2019. http://ndltd.ncl.edu.tw/cgi-bin/gs32/gsweb.cgi/login?o=dnclcdr&s=id=%22107NCHU5087033%22.&searchmode=basic.
Texto completo國立中興大學
環境工程學系所
107
Breast cancer is one of the most common cancer types in Taiwanese women. According to the Cancer Registry Annual Report (2016) published by the National Health Service of the Ministry of Health and Welfare, breast cancer is the leading cause of cancer in Taiwanese women. The high incidence rate of breast cancer in Taiwanese women urges the need for better and more suitable screening and diagnostic technologies. The purpose of this study is to establish a screening model for individuals with high risk of developing breast cancer using estrogen (17β-estradiol, E2) quinone-derived albumin (Alb) adducts as biomarkers in Taiwanese women with breast cancer and healthy controls, including E2-3,4-Q-2-S-Alb, E2-2,3-Q-4-S-Alb, and E2-3,4-Q-2-S-Alb+E2-2,3-Q-4-S-Alb. Mixed model utilizes the background levels of protein adducts derived from the combined pool of breast cancer patients and healthy controls. The mean or median values of estrogen quinone-derived albumin adducts were calculated and served as indicators of breast cancer risk (high and low risk). Subjects’ characteristics for each group of individuals in terms of age and BMI were compared. Additionally, the predictive values, false positive values, and false negative values of the screening model were estimated. Results indicated that predictive value of the “mixed model” using the median of E2-3,4-Q-2-S-Alb is 96.2% with 0% of false positive value and 7% of false negative value. The background value of E2-3,4-Q-2-S-Alb at 256.7 (pmole/g) is the critical point. In conclusions, this screening model for individuals with high risk of developing breast cancer can be applied to the field of preventive medicine in breast cancer.
Chang, Ching-Ming y 張景明. "Analysis of clinicopathological features and prognostic factors for metastatic colorectal cancer by using biomarkers as IHC of MMR, PD-L1 and TIL". Thesis, 2019. http://ndltd.ncl.edu.tw/cgi-bin/gs32/gsweb.cgi/login?o=dnclcdr&s=id=%22107NCHU5105043%22.&searchmode=basic.
Texto completo國立中興大學
生命科學院碩士在職專班
107
The incidence rate of colorectal cancer is raising in Taiwan, and it ranks second of the top 10 cancers. The average survival time of metastatic colorectal cancer is beyond 2 years in current treatment modalities including surgery, chemotherapy and targeted therapy. In recent years, immune checkpoint inhibitors bring great progress in improving response rate and prolonging survival time in many cancers, such as melanoma, lung cancer, head & neck cancer and urothelial carcinoma. Until the application of mismatch repair (MMR), immune checkpoint inhibitors are found to significantly improve the treatment outcome in colorectal cancer with deficiency MMR (dMMR). Furthermore, tumor-infiltrating lymphocytes (TIL) has been proven to play a major role in many cancers. Meanwhile, the expression level of progreammed death-ligand 1 (PD-L1) in tumor cells may predict the treatment response of immune checkpoint inhibitors, and this applied to many cancers, esp. for lung cancer. Thus the purpose of our study is to explore the prognostic factors of metastatic colorectal cancer by collecting the basic clinical and pathologic features (include TIL) and performing immunohistochemistry analysis for MMR panel and PD-L1 of tumor specimens. Totally, 93 patients were included in our study, and clinical data were collected. We performed immunohistochemistry stain from tumor specimens for MMR panel (MLH-1、MSH-2、MSH-6、PMS2), PD-L1 expression (both in tumor cell (TC-PDL1) and TIL (TIL-PDL1)) and TIL, and then interpreted. Then variables were analyzed for survival analysis by Cox proportional hazards model. Age older than 60 years-old, lymph node invasion more than 4, grade 3 tumor and TIL- were 4 poor prognostic factors by univariate analysis. However TIL- is the only poor prognostic factor reaching statistically significance in multivariate analysis. Gender, primary tumor site, primary tumor size, status of distant metastasis, K-RAS mutation, MMR, TC-PDL1, TIC-PDL1 and initial chemotherapy were not prognostic factors for overall survival. Although MMR, TC-PDL1 are good at predicting treatment response for immune checkpoint inhibitors in many clinical trials, but they are not prognostic in our metastatic colorectal cancer study. In our study, TIL+ cancer has good prognosis in metastatic colorectal cancer which is less reported in available literatures. The good prognostic role of TIL+ is also found in other cancer types by many studies. We found that most of the dMMR patients are TIL+. However, the dMMR patient number is small, it is either difficult to do correlation analysis between dMMR and TIL or to perform survival analysis using MMR and TIL. We suggest large-scale prospective randomized-controlled trials with more patient numbers and immune checkpoint inhibitors intervention in the future.
Chen, Wei-Tzuo y 陳瑋佐. "Establishment of a prediction model of breast cancer using the ratio of albumin adducts of estrogen-3,4-quinone to estrogen-2,3-quinone as biomarkers". Thesis, 2019. http://ndltd.ncl.edu.tw/cgi-bin/gs32/gsweb.cgi/login?o=dnclcdr&s=id=%22107NCHU5087009%22.&searchmode=basic.
Texto completo國立中興大學
環境工程學系所
107
The purpose of this study is to build an optimal screening model for individuals with high risk of developing breast cancer by using the background levels of 17β-estradiol (E2) quinones, including E2-2,3-Q and E2-3,4-Q, generated albumin adducts in breast cancer patients and healthy controls in Taiwanese women. We used the ratio of E2-3,4-Q-2-S-Alb to E2-2,3-Q-4-S-Alb to develop both mixed model and independent model for screening breast cancer risk. Mixed model utilizes the ratios of protein adducts derived from the combined pool of breast cancer patients and healthy controls. The mean ratio and median ratio of estrogen quinone-derived albumin adducts were calculated and served as indicators of breast cancer risk (high and low risk). Subjects’ characteristics for each group of individuals in terms of age and body mass index were compared. Additionally, the predictive values, false positive values, and false negative values of the screening model were estimated. The mathematical means and standard deviations for the independent model were estimated separately using the ratios of protein adducts derived from cancer patients and controls and served as indicators of breast cancer risk (high, medium, and low). The corresponding characteristics for each group of individuals were compared as distinguished by age and body mass index. The subjects with ratios greater than the mean value of cancer patients were classified as high-risk group, whereas those individuals with ratios lower than the mean value of controls were classified as low-risk group and the rest of the subjects were classified as medium-risk group. Results indicated that the predictive value of the mixed model is greater than 92.5% with 0% of false positive value and less than 14% of false negative value. We also noticed that the mixed model also has high sensitivity (greater than 86.0%) and high specificity (100%). In conclusions, this screening model for individuals with high risk of developing breast cancer may be applied to the field of preventive medicine in breast cancer.
Capítulos de libros sobre el tema "Cancer Biomarker(s)"
S. Chauhan, Deepak, Priyanka Mudaliar, Soumya Basu, Jyotirmoi Aich y Manash K. Paul. "Tumor-Derived Exosome and Immune Modulation". En Extracellular Vesicles - Role in Diseases Pathogenesis and Therapy [Working Title]. IntechOpen, 2022. http://dx.doi.org/10.5772/intechopen.103718.
Texto completoSiddiqui, Surayya, Sridevi I. Puranik, Aimen Akbar y Shridhar C. Ghagane. "Genetic Polymorphism and Prostate Cancer: An Update". En Genetic Polymorphisms - New Insights [Working Title]. IntechOpen, 2021. http://dx.doi.org/10.5772/intechopen.99483.
Texto completoBianchi, Thomas S. "Characterization of Organic Matter". En Biogeochemistry of Estuaries. Oxford University Press, 2006. http://dx.doi.org/10.1093/oso/9780195160826.003.0018.
Texto completoActas de conferencias sobre el tema "Cancer Biomarker(s)"
Sathija, P. K., S. Rajaram, V. K. Arora, B. Gupta y N. Goel. "Evaluation of biomarkers p16ink4a/ki-67 in cervical cytology for diagnosis of cervical intraepithelial neoplasia". En 16th Annual International Conference RGCON. Thieme Medical and Scientific Publishers Private Ltd., 2016. http://dx.doi.org/10.1055/s-0039-1685267.
Texto completoRahbari, M., M. Pecqueux, C. Reissfelder, T. Welsch, J. Weitz, NN Rahbari y C. Kahlert. "Exosomal Glypican-3 is a diagnostic and prognostic biomarker in gastric cancer". En Viszeralmedizin 2017. Georg Thieme Verlag KG, 2017. http://dx.doi.org/10.1055/s-0037-1604757.
Texto completoLambert, Elisa, Elodie Barthout, Remi Manczak, Sofiane Sadaa, Barbara Bessette, Muriel Mathonnet, Fabrice Lalloue, Claire Dalmay y Arnaud Pothier. "UHF-Dielectrophoresis Signatures as a Relevant Discriminant Electromagnetic Biomarker of Colorectal Cancer Stem Cells". En 2022 IEEE/MTT-S International Microwave Symposium - IMS 2022. IEEE, 2022. http://dx.doi.org/10.1109/ims37962.2022.9865336.
Texto completoSarkar, Shubhashish, Vsevolod L. L. Popov, Malany O'Connell, Heather L. Stevenson, Brian S. Lee, Robert A. Obeid y Pomila Singh. "Abstract 729: A novel cancer-stem-cell biomarker, DCLK1-S, traffics to nuclei of colon cancer cells: potential use as a biomarker for assessing colon cancer risk after screening colonoscopy". En Proceedings: AACR Annual Meeting 2017; April 1-5, 2017; Washington, DC. American Association for Cancer Research, 2017. http://dx.doi.org/10.1158/1538-7445.am2017-729.
Texto completoVelasquez-Rodriguez, JG, A. Boladeras-Inglada, A. Garcia-Sumalla, S. Maisterra, M. Galan y JB Gornals. "EUS-Guided Esophageal Fiducial Biomarker Placement For Stereotactic Body Radiation Therapy In A Superficial Cancer". En ESGE Days 2021. Georg Thieme Verlag KG, 2021. http://dx.doi.org/10.1055/s-0041-1724939.
Texto completoKemper, M., W. Hentschel, Graß J-K, BO Stüben, L. Konczalla, T. Rawnaq-Müller, T. Ghadban, JR Izbicki y M. Reeh. "Serum Midkine is a clinical significant biomarker for colorectal cancer and associated with poor survival". En DGVS Digital: BEST OF DGVS. © Georg Thieme Verlag KG, 2020. http://dx.doi.org/10.1055/s-0040-1716289.
Texto completoSicking, A., A. Franken, A. Kraemer, M. Watolla, M. Rivandi, L. Yang, J. Warfsmann et al. "Investigation of EpCAM negative CTCs as a prognostic and predictive biomarker in metastatic breast cancer". En 64. Kongress der Deutschen Gesellschaft für Gynäkologie und Geburtshilfe e. V. Georg Thieme Verlag, 2022. http://dx.doi.org/10.1055/s-0042-1757050.
Texto completoEichkorn, D., F. Voßhagen, R. Zeilinger, A. Hasenburg y M. Bossart. "Biomarker-based early detection of epithelial ovarian cancer based on a 5-protein signature in patients serum". En Kongressabstracts zur Tagung 2020 der Deutschen Gesellschaft für Gynäkologie und Geburtshilfe (DGGG). © 2020. Thieme. All rights reserved., 2020. http://dx.doi.org/10.1055/s-0040-1718132.
Texto completoRamdani, H., HJM Groen, E. Schuurig, L. Heukamp, M. Falk, M. Tiemann y F. Griesinger. "Evaluation of Biomarker for Response to Immune Chekcpoint Inhibitors in Patients with Advanced Non-Small Cell Lung Cancer". En 60. Kongress der Deutschen Gesellschaft für Pneumologie und Beatmungsmedizin e. V. Georg Thieme Verlag KG, 2019. http://dx.doi.org/10.1055/s-0039-1678244.
Texto completoLinxweiler, M., W. Schmid, S. Körner, F. Bochen, S. Wemmert, S. Smola, S. Lohse, M. Wagner y B. Schick. "HPV status as predictive biomarker in head and neck cancer – which method fits the best for outcome prediction?" En Abstract- und Posterband – 91. Jahresversammlung der Deutschen Gesellschaft für HNO-Heilkunde, Kopf- und Hals-Chirurgie e.V., Bonn – Welche Qualität macht den Unterschied. © Georg Thieme Verlag KG, 2020. http://dx.doi.org/10.1055/s-0040-1710976.
Texto completo