Note for Challenges with biomarkers in cancer drug discovery and development
Note: Challenges with biomarkers in cancer drug discovery and development
(doi:10.1080/17460441.2018.1479740)
Precision medicine;
1. require molecular profiles of tumors
2. require molecular profiles of microenvironment
3. individual features
Final aim is to use these data to cure the cancer patient effectively!
However, the authors mentioned that it only partially helps. Also, the patients who have a good response, at the very end, they develop the resistance to the treatment, either targeted molecule or immunotherapy.
Gap;
Need to identify the biomarkers in each step of cancer progression as well as the treatment effectiveness (resistance or sensitivity).
Cancer biomarkers -- tumor characteristic or response of the body in the presence of cancer which can be measured and evaluated (can be directly from the cancer or the response from the host body).
Definition of each biomarkers;
1. diagnostic markers - predisposition and early detection of tumors in healthy patients
2.pronostic biomarkers - evaluation of possible natural cause of the disease
3.predictive biomarkers - prediction of response to specific therapy
4.PK, PD and PG biomarkers -evaluate the interaction between drug and patients
5.surrogate biomarkers - used as the intermediate end point biomarkes to determine early response/resistant to treatment
The authors mentioned that to improve the cancer treatment - the most important biomarker is the predictive biomarker which will tell us whether the treatment is effective.
The most important things for finding a good biomarker is that whether that biomolecule/metabolite is the driver or passenger (effect from the cancer, not the key player).
Tumor heterogeneity within tumor mass is very challenge to identify the precise biomarkers, though we can get a cancer driver at a population level - but it cannot recapitulate at the individual level, due to there are the other key factors involved.
Dianostic test in the old day - relies on one gene. Nowadays, with the price of NGS is reduced, we can get the information of the gene panels which are associated with cancers.
large amount of data could potentially be used for the discovery of novel biological mechanisms underlying cancer progression and drug resistance, ultimately only a small fraction of the sequenced data is useful in the clinic for personalized treatment selection based on our current knowledge and availability of genomically matched therapies.
Key factors to use biomarkers as a tool to design the drug regimen -
1.data on tumor biology
2.preclinical data (drug discovery and development)
3.clinical data (PK and PD) - pharmacogenomics data
All of these informations will help treatment effectively.
Actionable gene -- gain of function
Non actionable gene -- loss of function
But both relate to cancer progression.
process of validation and implementation in the clinic of biomarkers is long and complicated, with several challenges such as tumor heterogeneity, actionability of alterations, and differences in techniques used to measure them, and they should work on developing strategies to overcome these limitations.
challenges of biomarkers in drug discovery and development
may be considered at three different levels:
(1) identifying the right target of the drug as biomarker;
(2) validation of the biomarker test in question, and
(3) development of matched biomarker-driven treatments
validated molecular profiling platforms make their way to routine clinical practice, additional challenges
include the costs of implementing and validating newer tools in diagnostic laboratories.
new challenges in the identification and validation of predictive biomarkers for response to treatments, which will require the collaboration and "sharing of knowledge" between oncologists, immunologists, and molecular biologists to optimize their application in cancer medicine.
(doi:10.1080/17460441.2018.1479740)
Precision medicine;
1. require molecular profiles of tumors
2. require molecular profiles of microenvironment
3. individual features
Final aim is to use these data to cure the cancer patient effectively!
However, the authors mentioned that it only partially helps. Also, the patients who have a good response, at the very end, they develop the resistance to the treatment, either targeted molecule or immunotherapy.
Gap;
Need to identify the biomarkers in each step of cancer progression as well as the treatment effectiveness (resistance or sensitivity).
Cancer biomarkers -- tumor characteristic or response of the body in the presence of cancer which can be measured and evaluated (can be directly from the cancer or the response from the host body).
Definition of each biomarkers;
1. diagnostic markers - predisposition and early detection of tumors in healthy patients
2.pronostic biomarkers - evaluation of possible natural cause of the disease
3.predictive biomarkers - prediction of response to specific therapy
4.PK, PD and PG biomarkers -evaluate the interaction between drug and patients
5.surrogate biomarkers - used as the intermediate end point biomarkes to determine early response/resistant to treatment
The authors mentioned that to improve the cancer treatment - the most important biomarker is the predictive biomarker which will tell us whether the treatment is effective.
The most important things for finding a good biomarker is that whether that biomolecule/metabolite is the driver or passenger (effect from the cancer, not the key player).
Tumor heterogeneity within tumor mass is very challenge to identify the precise biomarkers, though we can get a cancer driver at a population level - but it cannot recapitulate at the individual level, due to there are the other key factors involved.
Dianostic test in the old day - relies on one gene. Nowadays, with the price of NGS is reduced, we can get the information of the gene panels which are associated with cancers.
large amount of data could potentially be used for the discovery of novel biological mechanisms underlying cancer progression and drug resistance, ultimately only a small fraction of the sequenced data is useful in the clinic for personalized treatment selection based on our current knowledge and availability of genomically matched therapies.
Key factors to use biomarkers as a tool to design the drug regimen -
1.data on tumor biology
2.preclinical data (drug discovery and development)
3.clinical data (PK and PD) - pharmacogenomics data
All of these informations will help treatment effectively.
Actionable gene -- gain of function
Non actionable gene -- loss of function
But both relate to cancer progression.
process of validation and implementation in the clinic of biomarkers is long and complicated, with several challenges such as tumor heterogeneity, actionability of alterations, and differences in techniques used to measure them, and they should work on developing strategies to overcome these limitations.
challenges of biomarkers in drug discovery and development
may be considered at three different levels:
(1) identifying the right target of the drug as biomarker;
(2) validation of the biomarker test in question, and
(3) development of matched biomarker-driven treatments
validated molecular profiling platforms make their way to routine clinical practice, additional challenges
include the costs of implementing and validating newer tools in diagnostic laboratories.
new challenges in the identification and validation of predictive biomarkers for response to treatments, which will require the collaboration and "sharing of knowledge" between oncologists, immunologists, and molecular biologists to optimize their application in cancer medicine.
Comments
Post a Comment