Chemotherapy Resistance
Chemotherapy Resistance - Related Videos
08:41
Modeling Chemotherapy Resistant Leukemia In Vitro
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Cited by 15 •
2016
The current report summarizes a protocol that can be utilized to model the influence of the bone marrow microenvironment niche on leukemic cells with emphasis placed on enrichment of the most chemoresistant subpopulation.
07:42
Nerve Excitability Assessment in Chemotherapy-induced Neurotoxicity
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Cited by 28 •
2012
This abstract describes a novel method to assess the development of neurotoxicity in patients receiving chemotherapy treatment. While conventional assessment methods are limited in their ability to detect early changes in nerve function, nerve excitability techniques provide early identification of patients at risk of severe neurotoxicity and insight into pathophysiology.
08:31
Murine Model of Leukemia Relapse to Induction Chemotherapy for Acute Lymphoblastic Leukemia
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2025
The protocol aims to describe a mouse model for generating relapses of acute lymphoblastic leukemia, based on the dynamics of the response to induction chemotherapy.
09:58
Using RNA-sequencing to Detect Novel Splice Variants Related to Drug Resistance in In Vitro Cancer Models
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Cited by 25 •
2016
Here we describe a protocol aimed at investigating the impact of aberrant splicing on drug resistance in solid tumors and hematological malignancies. To this goal, we analyzed the transcriptomic profiles of parental and resistant in vitro models through RNA-seq and established a qRT-PCR based method to validate candidate genes.
01:22
Resistivity
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2023
When a voltage is applied to a conductor, an electrical field is generated, and charges in the conductor feel the force due to the electrical field. The current density that results depends on the electrical field and the properties of the material. In some materials, including metals at a given temperature, the current density is approximately proportional to the electrical field. In these cases, the current density can be modeled as: where σ is the electrical conductivity and is represented...
FAQs
Increased drug efflux can reduce the amount of an anticancer drug retained by a cancer cell, limiting the treatment’s effect. This mechanism matters because cells may survive even when therapy reaches the tumor. In cancer research, identifying efflux-related changes helps explain incomplete responses and can guide efforts to develop treatment combinations that address more than one resistance mechanism.
These changes interfere with two different points of drug action. Altered targets can make cancer cells less affected by a drug, while enhanced DNA repair can help cells correct treatment-related damage. Examining both mechanisms allows researchers to distinguish how resistance arises and supports the search for biomarkers or drug combinations tailored to the mechanisms present.
Reduced apoptosis, the programmed cell death response, allows damaged or stressed cancer cells to remain alive after treatment. Protective interactions with the tumor microenvironment can add another layer of survival support. Studying these influences broadens resistance research beyond the cancer cell alone and may reveal targets for therapies designed to disrupt cellular protection during chemotherapy.
Researchers investigate resistance mechanisms to identify biomarkers, measurable features that may indicate how a tumor will respond to treatment. Such markers can help predict treatment response and distinguish tumors more likely to benefit from a given approach. Their value lies in connecting cellular changes, such as efflux or altered repair, with treatment choices and more individualized cancer research.
Combination therapy is investigated because resistance may arise through several mechanisms at once, including drug efflux, altered targets, DNA repair, reduced apoptosis, and microenvironmental protection. Pairing approaches can therefore address more than one vulnerability rather than relying on a single drug effect. Cancer research uses this strategy to seek more durable treatment responses and prevent resistance from limiting therapy.
Research findings can influence both treatment development and patient-specific strategy. Mechanistic studies may reveal opportunities for new anticancer drugs, while biomarkers and response predictions can support personalized approaches. The broader goal is to match treatment choices with the biological features driving resistance, supporting more durable treatments and reducing the likelihood that ineffective approaches will continue without adjustment.