Tumor Response Evaluation
Tumor Response Evaluation - Related Videos
07:49
Evaluation of Tumor-infiltrating Leukocyte Subsets in a Subcutaneous Tumor Model
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Cited by 15 •
2015
This protocol describes a method for the detailed evaluation of leukocyte subsets within the tumor microenvironment in a mouse tumor model. Chemerin-expressing B16 melanoma cells were implanted subcutaneously into syngeneic mice. Cells from the tumor microenvironment were then stained and analyzed by flow cytometry, allowing for detailed leukocyte subset analyses.
12:42
Paramyxoviruses for Tumor-targeted Immunomodulation: Design and Evaluation Ex Vivo
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Cited by 17 •
2019
This protocol describes a detailed workflow for the generation and ex vivo characterization of oncolytic viruses for expression of immunomodulators, using measles viruses encoding bispecific T cell engagers as an example. Application and adaptation to other vector platforms and transgenes will accelerate the development of novel immunovirotherapeutics for clinical translation.
11:09
Establishing Intracranial Brain Tumor Xenografts With Subsequent Analysis of Tumor Growth and Response to Therapy using Bioluminescence Imaging
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Cited by 104 •
2010
Luciferase-modified human brain tumor xenografts can be established intracranially in athymic mice, with subsequent monitoring of tumor growth and response to therapy using bioluminescence imaging. In combination with survival analysis, bioluminescence monitoring is an essential research tool for pre-clinical testing of therapies being considered for treating brain tumors.
03:00
An Assay to Evaluate Immunodominance in Cytotoxic T Lymphocyte Responses
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2025
The video showcases a flow cytometry-based assay for assaying immunodominance in cytotoxic T lymphocytes or CTL responses. Injected fluorescent target cells exhibit varying fluorescence corresponding to immunogenic epitopes. Post-spleen collection and sorting reveal a reduction in high-intensity fluorescent cells, confirming immunodominance in CTL responses.
01:18
Thermally Responsive Biopolymer-Based Inhibition of Tumor Progression in a Rat Model
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2025
Begin with an anesthetized rat bearing a brain tumor composed of proliferating tumor cells.Expose the rat’s skull and create a hole to reveal the brain region with the tumor.Take a thermally responsive biopolymer fused with a cell-penetrating peptide and an inhibitor of c-myc, an oncogenic protein.Inject the biopolymer into the femoral vein of the hind limb for delivery to the brain.Apply infrared light through the skull hole to heat the tumor site, which induces biopolymer aggregation along...
FAQs
Standardized criteria make assessments more consistent by applying defined comparisons to lesion measurements and documenting whether new lesions appear. RECIST, for example, supports a common classification framework rather than relying only on subjective impressions. This consistency helps clinicians compare findings over time and allows clinical trials to use response categories as reproducible endpoints.
Imaging provides measurable anatomic information, while physical examination, pathology, and selected biomarkers can add different evidence about disease status. Considering these sources together is important when one type of finding does not fully explain the clinical picture. The combined assessment can help distinguish genuine treatment benefit from temporary or treatment-related changes.
New lesions carry particular significance because their appearance can change the interpretation of treatment response even when previously measured lesions have changed. For this reason, follow-up review considers both size measurements and disease distribution. A response category based only on shrinking or enlarging known lesions could miss an important change elsewhere.
Clinicians compare baseline findings with results obtained during or after treatment, using the available imaging, examination, pathology, and selected biomarker information. The comparison focuses on how documented disease features have changed and whether new abnormalities are present. This structured before-and-after review supports classification as responding, stable, or progressing.
Repeated assessments show whether an initially favorable pattern is maintained or replaced by evidence of progression. A change from response or stability toward progression may indicate that treatment is no longer controlling the cancer, while later disease changes can raise concern for recurrence. These patterns provide information for reassessing care and prognosis.
Response findings give clinicians evidence for judging whether therapy is achieving its intended effect. Results showing response or stability may support continuation of the current approach, whereas progression can prompt reconsideration of treatment. Interpretation also accounts for possible temporary or treatment-related changes, reducing the risk of making decisions from an isolated finding alone.
Clinical trials need consistent ways to determine whether an intervention produces benefit. Standardized response categories and comparisons with baseline findings provide endpoints that can be applied across participants and assessment times. This common framework supports evaluation of therapeutic effectiveness and enables investigators to relate tumor changes to broader questions about prognosis and treatment activity.