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Tumor Markers

Tumor markers are substances, usually proteins, that are produced by cancer cells or by other cells in response to cancer in the body.
They can be detected in the blood, urine, or other bodily fluids and are used to help detect, diagnose, and manage certain types of cancers.
Tumor markers can provide valuable information about the presence, location, and stage of a cancer, as well as help monitor the effectiveness of treatment.
Common tumor markers include PSA for prostate cancer, CA-125 for ovarian cancer, and CEA for colorectal cancer.
While tumor markers are a useful tool, they must be interpreted carefuly in the context of other clinical findings, as their levels can be affected by non-cancerous conditions as well.
Researchers can use PubCompare.ai to optimise their tumor marker research protocols and easily locate the best protocols from literature, pre-prints, and patents using the powerful AI-driven platform, improving their research outcomes with data-driven insights.

Most cited protocols related to «Tumor Markers»

A Pubmed search was performed to identify lung cancer survival associated biomarkers using all combinations of the keywords “lung cancer”, “NSCLC”, “adenocarcinoma”, “squamous cell carcinoma”, “survival”, “gene expression”, “signature” and “meta analysis”. Only studies published in English were included. Eligibility criteria also included the investigation of the biomarker in at least 50 patients - biomarkers described in experimental models only were omitted. For each gene/signature the exact conditions in which it was identified have been retrieved, and these have been used as filtering when selecting the patients for the survival analysis.
To visualize the performance of the various biomarkers in datasets including different number of patients, we have generated funnel plots depicting the hazard ratio (and confidence intervals) on the horizontal axis vs. the sample size on the vertical axis for each dataset. We also added an option to the online interface to simultaneously perform the analysis in each of the individual datasets. Finally, significance was set at p<0.01.
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Publication 2013
Adenocarcinoma Biological Markers Eligibility Determination Epistropheus Gene Expression Genes Lung Lung Cancer Non-Small Cell Lung Carcinoma Patients Squamous Cell Carcinoma Tumor Markers
We obtained the clinical information associated with tumor samples, including the patient’s overall survival time, tumor stage and tumor grade from Synapse TCGA Pan-Cancer data portal (https://www.synapse.org/), with ID syn300013. We also obtained known tumor subtype information from TCGA marker papers (if available). To identify lncRNAs differentially expressed between tumor and matched normal samples, we used the paired student t-test to assess the statistical difference between the two groups. To identify lncRNAs differentially expressed among established tumor subtypes or tumor stages, we used analysis of variance (ANOVA) to assess the statistical difference. Groups with fewer than 5 samples were excluded from the analysis.
Publication 2015
Malignant Neoplasms Neoplasms Neoplasms, Liver Patients RNA, Long Untranslated Student Synapses Tumor Markers
This analysis was based on a population-based cohort of 660 stage II/III colon adenocarcinoma patients, representing 89% of all patients undergoing surgery for stage II/III colon adenocarcinoma in two Healthcare Trusts in Northern Ireland between 2004 and 2008. Patients were sampled and clinical information obtained from the Northern Ireland Cancer Registry. All patients were followed up for occurrence and cause of death via linkage to the Northern Ireland Registrar General’s Office up to 31st December 2013. Ethical approval for these linkages was given by ORECNI (REC: 10/NIR02/53). Over ten years (and a mean of 5 years) of clinical follow-up, 46% of patients had died, of which 38% were from CRC-specific causes. Corresponding tumor slides and blocks were retrieved and collated via the Northern Ireland Biobank which has ethical approval to use de-identified tissue samples from the Belfast Health and Social Care Tissue Pathology archive (REC:11/NI/0013).
This study was conducted in accordance to REporting recommendations for tumour MARKer prognostic studies (REMARK)29 (link). The reporting standards of the current study fulfill these recommendations.
Following slide review, a new section was cut for H&E staining from a single representative tumor block in each case, and the new slides annotated for tissue microarray (TMA) construction. Three representative areas within the tumor center of each block were annotated for targeted coring (by an experienced biomedical scientist and confirmed by expert pathologists, MBL and JAJ). One millimeter diameter tissue cores were extracted from donor blocks and inserted into recipient blocks using a manual tissue arrayer (Estigen, Tartu, Estonia).
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Publication 2017
Colon Adenocarcinomas Malignant Neoplasms Microarray Analysis Neoplasms Operative Surgical Procedures Pathologists Patients Tissue Donors Tissues Tumor Markers

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Publication 2017
Antihypertensive Agents Blood Glucose Body Weight Cardiovascular Diseases Childbirth Complete Blood Count Coronary Angiography Diagnosis Drug Reaction, Adverse Eating Echocardiography Enzymes Ethanol High Blood Pressures Index, Body Mass Japanese Kidney Lipids Liver Function Tests Malignant Neoplasms Operative Surgical Procedures Pharmaceutical Preparations Pharmacotherapy Pressure, Diastolic Radiotherapy Systole Systolic Pressure Therapeutics Tumor Markers Urinalysis Woman
It is important to clearly define any endpoints examined (see Item 7). Events typically considered in tumor marker prognostic studies include death due to any cause, death from cancer, distant recurrence, local recurrence, tumor progression, new primary tumor, or tumor response to treatment. The clinical endpoint is reached when the event occurs. For death, recurrence, progression, and new primary tumor, there is usually interest not only in whether the event occurs (endpoint reached), but also the time elapsed (for example, from the date of surgery or date of randomization in a clinical trial) until it occurs. Time until last evaluation is used for patients without an event (time censored). The clinical outcome is the combination of the attainment or non-attainment of the endpoint and the time elapsed. Such clinical outcomes are referred to as time-to-event outcomes. Commonly examined outcomes in tumor marker prognostic studies are disease-free survival (DFS), distant DFS, and overall survival (OS). Different event types are sometimes combined to define a composite endpoint, for example DFS usually includes any recurrence (local, regional, or distant) and death due to any cause. For composite endpoints, the time-to-event is the time elapsed until the first of any of the events comprising the composite endpoint occurs. As recently shown, a majority of articles failed to provide a complete specification of events included in endpoints [197] (link).
Many clinical endpoints do not have standard definitions, although there have been some recent efforts to standardize definitions for some disease sites. The STandardized definitions for Efficacy End Points (STEEP) system [67] (link) proposed standardized endpoint definitions for adjuvant breast cancer trials to address inconsistencies such as the fact that new primary tumors, non-cancer death, and in situ cancers may or may not be included as events in DFS for breast cancer. Different names may be used interchangeably for one survival time outcome, for example, recurrence-free survival and DFS. Furthermore, there is not always agreement on which endpoint is the most relevant endpoint to consider in a particular disease setting. For example, reliable information about cause of death is sometimes not available, so considering death due to any cause is often preferred. In some situations, for example, in an older patient population with small risk of dying from the cancer, it can be argued that death due to cancer is more relevant because it is expected that many deaths will be unrelated to the cancer and including them in the endpoint could make the estimated prognostic effect of the marker difficult to interpret.
The endpoints to be examined should be decided on the basis of clinical relevance. The results for all endpoints that were examined should be reported regardless of the statistical significance of the findings (see Items 15 to 17 and Box 5). A demonstrated association of a marker with one of these endpoints does not guarantee its association with all of the endpoints. For example, local recurrence may be an indication of insensitivity to local or regional therapy (such as radiation therapy) whereas distant recurrence requires that tumor cells have the ability to metastasize. Different markers may be indicative of these distinct characteristics.
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Publication 2012
Carcinoma in Situ Cells Disease Progression Malignant Neoplasm of Breast Malignant Neoplasms Neoplasm Metastasis Neoplasms Operative Surgical Procedures Patients Pharmaceutical Adjuvants Population at Risk Radiotherapy Recurrence STEEP1 protein, human Therapeutics Tumor Markers

Most recents protocols related to «Tumor Markers»

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Example 8

Serum samples from patients were tested with the FLNA IPMRM, as described above, using the anti-FLNA monoclonal antibodies of the invention. The results were combined with data on age, PSA, and Gleason score and subjected to regression modelling. As shown in FIG. 10, a Prostate Cancer Biomarker Panel consisting of biomarkers FLNA, FLNB, age and PSA improved the classification of prediction of prostate cancer over PSA alone (AUC=0.64, [0.59, 0.69], vs 0.58).

Samples of patient serum were also analyzed for the biomarkers FLNA, keratin 19 (KRT19) and age combined, versus PSA alone. FIG. 11 shows that the biomarkers FLNA, KRT19 and age have improved classification of prediction between patients with benign prostatic hyperplasia versus prostate cancer over PSA alone (AUC=0.70 [0.60, 0.80], vs 0.58).

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Patent 2024
Anti-Antibodies Benign Prostatic Hyperplasia Biological Markers Keratin-19 Monoclonal Antibodies Patients Prostate Prostate Cancer Serum Tumor Markers
This study (clinical-trial ID: NCT05313854-clinicaltrials.gov) was approved by the Ethical Committee of Renji Hospital, Shanghai Jiao Tong University. A total of 78 PDAC from 2014 to 2020 were enrolled in this study. The inclusion criteria were: 1) histologically confirmed PDAC; 2) with complete contrast-enhanced MRI data; 3) with complete TNM staging information and tumor markers data (CA199, CEA and CA125). The exclusion criteria were: 1) malignancy other than PDAC; 2) with missing survival information.
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Publication 2023
Anophthalmia with pulmonary hypoplasia CA-125 Antigen Malignant Neoplasms Tumor Markers
The responses to treatments were evaluated every 2 months or suspected disease
progression. Pelvic examination and plasma tumor markers were routinely
performed each time. Imaging tests including computed tomography (CT), positron
emission tomography-computed tomography (PET-CT), single-photon emission
computed tomography (SPECT), and magnetic resonance imaging (MRI) were used as
appropriate to determine the size of tumors. The Response Evaluation Criteria in
Solid Tumors (RECIST) version 1.1 was used to determine CR, PR, stable disease
(SD), or progressive disease (PD). During the nontreatment period, follow-up was
performed every 3 months until death or the patient was censored. Disease-free
survival (DFS) was defined as the period from the date of surgery to the
diagnosis of first recurrence/metastasis, and OS was defined as the period from
the beginning of treatment after first recurrence/metastasis to the death, with
patients alive at last follow-up censored on that date. PFS was defined as the
period from the treatment beginning after first recurrence/metastasis to the
second recurrence/metastasis or death, with patients censored if alive and with
no evidence of tumor recurrence/metastasis.
Publication 2023
Neoplasm Metastasis Neoplasms Operative Surgical Procedures Patients Pelvic Examination Plasma Recurrence Tomography Tumor Markers X-Ray Computed Tomography
The hematological parameters of 1,688 patients diagnosed with lung cancer and underwent surgical resection from the First Affiliated Hospital of Guangzhou Medical University from February 2010 to July 2018 were retrospectively evaluated. All samples of primary surgery patients who had not undergone anti-tumor therapy were obtained from the last preoperative blood test. Ninety-three patients with abnormally high or low results were excluded. The following results were included for analysis: routine blood tests, biochemical tests, coagulation function tests, arterial blood gas analysis, lipid profile, renal function, electrolyte levels, serum tumor markers, and blood pressure. In addition, the last blood index results of 197 consecutive patients with NSCLC in the Cancer Center of Sun Yat-sen University from December 2015 to May 2016 and 147 patients diagnosed with colorectal cancer in our center at 2015 to 2016 were selected as verification cohorts. The study was conducted in accordance with the Declaration of Helsinki (as revised in 2013). This study was confirmed and approved by the Ethics Committee of the First Affiliated Hospital of Guangzhou Medical University (No. 2015-25). Since the study was a retrospective analysis of the patient database, the requirement for informed consent of each patient was waived.
Publication 2023
Arteries BLOOD Blood Gas Analysis Blood Pressure Colorectal Carcinoma Electrolytes Ethics Committees, Clinical Hematologic Tests Kidney Lipids Lung Cancer Malignant Neoplasms Neoplasms Non-Small Cell Lung Carcinoma Operative Surgical Procedures Patients Serum Tests, Blood Coagulation Therapeutics Tumor Markers
Previous studies have identified the gene markers of tumor-infiltrating immune cells25 (link),26 (link), including CD8+ T cells, monocytes, M1 macrophages, M2 macrophages, B cells, T cells (general), TAMs, follicular helper T (Tfh) cells, T-helper 1 (Th1) cells, T-helper 2 (Th2) cells, T-helper 17 (Th17) cells, Tregs, neutrophils, natural killer (NK) cells, dendritic cells (DCs), and exhausted T cells.
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Publication 2023
B-Lymphocytes CD8-Positive T-Lymphocytes Cells Dendritic Cells Genes Macrophage Monocytes Myeloproliferative Syndrome, Transient Natural Killer Cells Neutrophil T-Lymphocyte Th17 Cells Tumor Markers Type-2 Helper T Cell Type 1 Helper T Cells

Top products related to «Tumor Markers»

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The Cobas e601 is an automated immunochemistry analyzer used for in vitro diagnostic testing. It is designed to perform a wide range of immunoassay tests, including those for hormones, tumor markers, and infectious diseases. The Cobas e601 utilizes electrochemiluminescence technology to provide accurate and reliable results.
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Prism 8 is a data analysis and graphing software developed by GraphPad. It is designed for researchers to visualize, analyze, and present scientific data.
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GraphPad Prism 7 is a data analysis and graphing software. It provides tools for data organization, curve fitting, statistical analysis, and visualization. Prism 7 supports a variety of data types and file formats, enabling users to create high-quality scientific graphs and publications.
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The Bio-Plex 200 system is a multiplex immunoassay platform that allows for the simultaneous detection and quantification of multiple analytes in a single sample. The system utilizes fluorescently-labeled magnetic beads and a dual-laser detection system to perform high-throughput, multiplexed analyses.
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GraphPad Prism 5 is a data analysis and graphing software. It provides tools for data organization, statistical analysis, and visual representation of results.
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SPSS version 22.0 is a statistical software package developed by IBM. It is designed to analyze and manipulate data for research and business purposes. The software provides a range of statistical analysis tools and techniques, including regression analysis, hypothesis testing, and data visualization.
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SPSS version 21 is a statistical software package developed by IBM. It is designed for data analysis and statistical modeling. The software provides tools for data management, data analysis, and the generation of reports and visualizations.
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The Cobas e602 is an automated electrochemiluminescence immunoassay (ECLIA) analyzer produced by Roche. It is designed for the in vitro quantitative determination of analytes in human samples. The Cobas e602 provides high-throughput testing and is suitable for clinical laboratory applications.
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Prism 6 is a data analysis and graphing software developed by GraphPad. It provides tools for curve fitting, statistical analysis, and data visualization.
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SPSS 24.0 is a statistical software package developed by IBM. It provides data management, analysis, and reporting capabilities. The software is designed to handle a wide range of data types and is commonly used for social science research, market research, and business analytics.

More about "Tumor Markers"

Tumor markers are biological substances, typically proteins, that are produced by cancer cells or other cells in response to the presence of cancer.
These markers can be detected in bodily fluids like blood, urine, or other fluids, and are used to aid in the detection, diagnosis, and management of various types of cancers.
Common tumor markers include PSA (prostate-specific antigen) for prostate cancer, CA-125 for ovarian cancer, and CEA (carcinoembryonic antigen) for colorectal cancer.
These markers can provide valuable information about the presence, location, and stage of a cancer, as well as help monitor the effectiveness of treatment.
However, it's important to interpret tumor marker levels carefully, as they can be affected by non-cancerous conditions as well.
Researchers can use platforms like PubCompare.ai to optimize their tumor marker research protocols and easily locate the best protocols from literature, preprints, and patents using the powerful AI-driven platform.
This can help improve research outcomes with data-driven insights.
Analytical instruments like the Cobas e601, Prism 8, GraphPad Prism 7, Bio-Plex 200 system, GraphPad Prism 5, SPSS version 22.0, SPSS version 21, Cobas e602, Prism 6, and SPSS 24.0 can be used to analyze and interpret tumor marker data, providing valuable insights for clinicians and researchers.
By leveraging the power of these tools and the data-driven approach of PubCompare.ai, researchers can enhance their understanding of tumor markers and improve the overall quality and efficacy of their cancer research.