Prognostic Biomarker
Prognostic Biomarker - Related Videos
08:29
Biomarkers in an Animal Model for Revealing Neural, Hematologic, and Behavioral Correlates of PTSD
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Cited by 29 •
2012
We describe a rat model of post traumatic stress disorder (PTSD) that reveals the persistent alterations in neuroendocrine function and the delayed long-term, exaggerated fear response, characteristic of PTSD patients. The animal model and methods described here are useful for correlating biomarkers in brain nuclei, which are mechanistic but cannot be measured in patients, with biomarkers in peripheral white blood cells, which can.
08:28
An Overview of bGDGT Biomarker Analysis for Paleoclimatology
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2023
Source: Laboratory of Jeff Salacup - University of Massachusetts Amherst Throughout this series of videos, natural samples were extracted and purified in search of organic compounds, called biomarkers, that can relate information on climates and environments of the past. One of the samples analyzed was sediment. Sediments accumulate over geologic time in basins, depressions in the Earth into which sediment flows through the action of fluid (water or air), movement, and gravity. Two main types...
07:08
A High Throughput, Multiplexed and Targeted Proteomic CSF Assay to Quantify Neurodegenerative Biomarkers and Apolipoprotein E Isoforms Status
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Cited by 3 •
2016
We describe a high-throughput, multiplex, and targeted proteomic cerebrospinal fluid (CSF) assay developed with potential for clinical translation. The test can quantitate potential markers and risk factors for neurodegeneration, such as the apolipoprotein E variants (E2, E3 and E4), and measure their allelic expression.
07:24
Sonication Extraction of Lipid Biomarkers from Sediment
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2023
Source: Laboratory of Jeff Salacup - University of Massachusetts Amherst The material comprising the living "organic" share of any ecosystem (leaves, fungi, bark, tissue; Figure 1) differs fundamentally from the material of the non-living "inorganic" share (rocks and their constituent minerals, oxygen, water, metals). Organic material contains carbon linked to a series of other carbon and hydrogen molecules (Figure 2), which distinguishes it from inorganic material. Carbon's wide valency range...
08:04
Soxhlet Extraction of Lipid Biomarkers from Sediment
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2023
Source: Laboratory of Jeff Salacup - University of Massachusetts Amherst Every lab needs standards that track the performance, accuracy, and precision of its instruments over time to ensure a measurement made today is the same as a measurement made a year from now (Figure 1). Because standards must test the performance of instruments over a long period of time, large volumes of the standards are often required. Many chemical standards can be purchased from retail scientific companies, like...
FAQs
A prognostic biomarker should be interpreted as an indicator of expected disease course, not as evidence that one treatment will work better than another. Its treatment-independent role allows investigators to compare baseline risk across patient groups and use that risk information in study design without confusing outcome prediction with treatment-response assessment.
The biological signal can arise from gene expression, protein abundance, genetic alterations, or immune-cell activity. These readouts capture different aspects of tumor biology, so they may provide complementary views of disease behavior rather than interchangeable measurements. In cancer research, selecting the signal should match the biological question and the outcome being evaluated.
Analytical validation addresses whether the measurement itself is dependable, while outcome evidence addresses whether that measurement reliably correlates with recurrence, survival, or disease progression. Both are necessary: a biologically interesting signal may have limited value if it cannot be measured consistently or if its association with patient outcomes is not demonstrated.
Investigators may evaluate these markers in tumor tissue, blood, or other patient samples. Molecular methods can measure features such as gene expression, protein abundance, or genetic alterations, while clinical methods connect those measurements with outcomes. Combining the biological measurement with clinical information helps determine whether the signal has meaningful prognostic value.
Prognostic biomarkers can help identify differences in the likelihood of recurrence, survival, or disease progression among patients. Researchers can use that information to stratify participants, account for variation in expected outcomes, and design studies with clearer comparisons between groups. The same risk information may also support individualized monitoring during follow-up.
Because these markers may reflect gene activity, proteins, genetic changes, or immune-cell activity, they can provide clues about mechanisms underlying cancer behavior. Those mechanistic insights may inform therapy development, while clinical associations connect laboratory observations with patient outcomes. Thus, prognostic biomarker research can link disease biology, outcome assessment, and therapeutic investigation.