Human Tumor Samples
Human Tumor Samples - Related Videos
12:04
Human Neuroendocrine Tumor Cell Lines as a Three-Dimensional Model for the Study of Human Neuroendocrine Tumor Therapy
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Cited by 39 •
2012
We present a simple agarose overlay platform to grow 3D multicellular spheroids using neuroendocrine cancer cell lines. This method provides a very convenient way to examine the effect of therapeutic drugs on the neuroendocrine tumor cells. It could also help us establish human neuroendocrine tumor spheroids for cancer therapy.
11:12
Tissue Engineering of a Human 3D in vitro Tumor Test System
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Cited by 34 •
2013
Methods to create human 3D tumor tissues as test systems are described. These technologies are based on a decellularized Biological Vascularized Scaffold (BioVaSc), primary human cells and a tumor cell line, which can be cultured under static as well as under dynamic conditions in a flow bioreactor.
05:58
Dissociation of Human and Mouse Tumor Tissue Samples for Single-cell RNA Sequencing
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Cited by 4 •
2024
This protocol outlines the procedure for rapidly dissociating human and mouse tumor samples for single-cell RNA sequencing.
07:16
Isolation of Cancer Stem Cells From Human Prostate Cancer Samples
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Cited by 6 •
2014
The isolation of cancer stem cells (CSCs) directly from human tissues is requisite for their biological characterization. This manuscript describes a methodology for the isolation of prostate CSCs from human tissues, while also providing tips on troubleshooting difficult steps.
07:10
Depletion of Mouse Cells from Human Tumor Xenografts Significantly Improves Downstream Analysis of Target Cells
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Cited by 9 •
2016
Human tumor xenografts are vascularized and infiltrated by cells of mouse origin during the growth phase in vivo. To circumvent the bias caused by these contaminating cells during downstream analysis, we developed a method allowing for comprehensive depletion of all mouse cells by magnetic cell sorting.
FAQs
A major value of human tumor samples is that they retain biological variation that can be missed when researchers examine only one tumor feature. Evaluating tumor architecture, genetic variation, cellular diversity, and surrounding tissue together helps connect structural patterns with molecular findings. This integrated perspective can clarify why cancers differ among patients and why treatment responses are not uniform.
Controlled collection, processing, and storage help preserve the specimen characteristics required for later investigation. Maintaining suitable material supports assessment of tumor architecture, genetic variation, cellular diversity, and interactions with surrounding tissue. If these features are not adequately preserved, researchers may have less reliable material for histopathology, genomic studies, molecular profiling, or comparisons between patient samples.
Comparisons across patients or treatment stages can identify patterns associated with tumor progression and therapeutic response. Researchers may examine how architecture, molecular features, cellular composition, or tissue interactions vary over time or between individuals. These comparisons help connect laboratory observations with clinically relevant outcomes and can highlight biological differences that influence disease behavior or treatment effectiveness.
Histopathology focuses on tissue structure and tumor architecture, whereas genomic and molecular profiling examines biological features at the genetic or molecular level. Considering these approaches together can relate visible tissue patterns to underlying molecular variation. That combined information supports biomarker discovery and disease classification, while offering a broader basis for interpreting how tumors develop and respond to therapy.
A basic workflow includes controlled collection from patients, followed by processing and storage under conditions that keep the specimens suitable for analysis. Researchers then apply approaches such as histopathology, genomic analysis, or molecular profiling, depending on the question. Careful handling throughout the workflow helps preserve the information needed to compare samples and interpret biologically meaningful findings.
They are especially useful when researchers need to connect an individual tumor's characteristics with clinically relevant outcomes. Analyses can support disease classification, biomarker discovery, and evaluation of therapeutic responses, while comparisons across patients can expose meaningful biological differences. These findings help advance personalized medicine by linking laboratory evidence from tumors with the development of more effective cancer therapies.