Clonal Lesion Classification
Clonal Lesion Classification - Related Videos
08:16
Comparative Lesions Analysis Through a Targeted Sequencing Approach
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2019
This article describes a method to identify clonal and subclonal alterations among different specimens from a given patient. Although the experiments described here focus on a specific tumor type, the approach is broadly applicable to other solid tumors.
10:32
Enumeration of Neural Stem Cells Using Clonal Assays
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Cited by 5 •
2016
Neural stem cells (NSCs) refer to cells which can self-renew and differentiate into the three neural lineages. Here, we describe a protocol to determine NSC frequency in a given cell population using neurosphere formation and differentiation under clonal conditions.
12:06
Isolation of CD133+ Liver Stem Cells for Clonal Expansion
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Cited by 22 •
2011
Here we describe the isolation of CD133 expressing liver stem cells and cancer stem cells from whole murine liver, a process that requires tissue digestion, cell enrichment, and flow cytometry isolation. We include methods for advanced single cell isolation and clonal expansion.
09:22
Sectioning Mammary Gland Whole Mounts for Lesion Identification
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Cited by 13 •
2017
We developed a method to successfully remove, process, section, and stain, for histopathological evaluation, mammary tissue that had originally been fixed on slides as whole mounts. This method may promote the collection and evaluation of mammary gland whole mounts in reproductive and developmental test guideline studies.
06:40
Visualization of Chondrocyte Intercalation and Directional Proliferation via Zebrabow Clonal Cell Analysis in the Embryonic Meckel’s Cartilage
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Cited by 10 •
2015
Cell organization of craniofacial bones has long been hypothesized but never directly visualized. Multi-spectral cell labeling and in vivo live imaging allows visualization of dynamic cell behavior in zebrafish lower jaw. Here, we detail the protocol to manipulate Zebrabow transgenic fish and directly observe cell intercalation and morphological changes of chondrocytes in the Meckel’s cartilage.
FAQs
Shared somatic mutations, copy-number changes, or other genomic features provide evidence that cells from different lesion areas descended from the same ancestral cell. The strength of the classification depends on comparing these features across sampled regions rather than interpreting one alteration in isolation. This approach helps separate a common neoplastic lineage from unrelated cellular changes.
Histopathology shows the tissue architecture and cellular abnormalities, whereas molecular profiling identifies genomic similarities or differences among cells. Combining both forms of evidence improves interpretation when abnormal tissue could represent either a neoplastic lesion or a reactive, polyclonal change. Their complementary roles connect visible morphology with the biological relationships inferred from somatic alterations.
Genomic differences between sampled regions can indicate the presence of subclones, which are genetically distinct populations within a broader lesion. These patterns provide evidence of ongoing tumor evolution and help explain intratumoral heterogeneity. Recognizing such variation prevents a lesion from being treated as genetically uniform when separate regions may carry different biological features.
Researchers first evaluate the specimen by histopathology, then compare molecular profiles from relevant sampled regions. They assess whether regions share somatic mutations, copy-number changes, or other genomic features, while also noting meaningful differences. The resulting comparison supports interpretation of common lineage, subclonal structure, or a potentially reactive and polyclonal process.
By distinguishing early abnormalities from lesions associated with progression toward invasive disease, clonal analysis can add biological context to risk assessment. Shared alterations may support a relationship across stages, while regional differences can reveal emerging subclones. This information helps researchers interpret lesion behavior more precisely than morphology or isolated molecular findings alone.
Clonal analysis identifies both shared genomic features and genetically distinct tumor populations. Those findings can support disease monitoring by providing features to track across lesions or regions, while the recognition of distinct populations informs treatment selection aimed at the genetic diversity within a tumor. In cancer research, this links lesion classification with progression and therapeutic decision-making.