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Targeted Cancer Therapies

Targeted Cancer Therapies

The targeted cancer therapies, also known as “molecular targeted therapies,” take advantage of the molecular and genetic differences between the cancer cells and the normal cells. It needs a thorough understanding of the cancer cells to develop drugs that can target specific molecular aspects that drive the growth, progression, and spread of cancer cells without affecting the growth and survival of other normal cells in the body.
There are several types of targeted therapies against...

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Performing Data Mining And Integrative Analysis Of Biomarker in Breast Cancer Using Multiple Publicly Accessible Databases

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Published on: May 17, 2019

Emerging methods and techniques for cancer biomarker discovery.

Tikam Chand Dakal¹, Ramgopal Dhakar², Abhijit Beura³

¹Genome and Computational Biology Lab, Department of Biotechnology, Mohanlal Sukhadia University, Udaipur, Rajasthan 313001, India.

Pathology, Research and Practice

|September 4, 2024

Summary

Cancer biomarkers are crucial for diagnosis and treatment. Advances in transcriptomics, multi-omics, and AI enhance biomarker discovery for personalized cancer care.

Keywords:

Cancer biomarkers Heterogeneity Medicine Multi-omics Next-generation sequencing Precision

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Performing Data Mining And Integrative Analysis Of Biomarker in Breast Cancer Using Multiple Publicly Accessible Databases

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Published on: May 17, 2019

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Area of Science:

Oncology
Biomarker Discovery
Computational Biology

Background:

Cancer research relies on biomarkers for diagnosis, prognosis, and treatment response.
Biomarkers guide personalized medicine and clinical decision-making.

Purpose of the Study:

To provide a comprehensive overview of cancer biomarkers.
To highlight recent breakthroughs in biomarker detection technologies.
To discuss the integration of biomarkers for precision cancer care.

Main Methods:

Review of transcriptomics, computational techniques, and multi-omic technologies (genomics, proteomics, metabolomics).
Analysis of blood-based biomarkers (circulating tumor DNA, exosomes, microRNAs).
Integration of next-generation sequencing, mass spectrometry, AI algorithms, and imaging techniques.

Main Results:

Blood-based biomarkers offer non-invasive monitoring of tumor dynamics and treatment response.
Multi-omic approaches provide comprehensive molecular profiles for biomarker identification.
Advancements in AI and imaging improve biomarker validation and patient outcome prediction.

Conclusions:

The use of multiple biomarkers (genetic, protein, mRNA, microRNA, DNA) will increase for personalized treatment plans.
Collaboration is essential for robust biomarker validation and clinical implementation.
Biomarkers integrated with advanced technologies promise a future of improved personalized cancer care.