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Related Concept Videos

Genomics02:02

Genomics

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Genomics is the science of genomes: it is the study of all the genetic material of an organism. In humans, the genome consists of information carried in 23 pairs of chromosomes in the nucleus, as well as mitochondrial DNA. In genomics, both coding and non-coding DNA is sequenced and analyzed. Genomics allows a better understanding of all living things, their evolution, and their diversity. It has a myriad of uses: for example, to build phylogenetic trees, to improve productivity and...
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Combination Therapies and Personalized Medicine02:50

Combination Therapies and Personalized Medicine

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Combining two or more treatment methods increases the life span of cancer patients while reducing damage to vital organs or tissue from the overuse of a single treatment. Combination therapy also targets different cancer-inducing pathways, thus reducing the chances of developing resistance to treatment.
The combination of the drug acetazolamide and sulforaphane is a good example of combination therapy to treat cancer. The cells in the interior of a large tumor often die due to the hypoxic and...
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Cancer Therapies02:49

Cancer Therapies

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Cancer therapies are various modes of treatment, such as surgery, radiation therapy, and chemotherapy that are administered to cancer patients.
However, cancer treatments can pose several challenges, as therapies used to kill cancer cells are generally also toxic to normal cells. Moreover, cancer cells mutate rapidly and can develop resistance to chemical agents or radiation therapy. Besides, all types of cancer cells may not respond to the same therapy. Some cancer cells respond to one...
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Mouse Models of Cancer Study02:43

Mouse Models of Cancer Study

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Mice have long served as models for studying human biology and pathology because of their phylogenetic and physiological similarity with humans. They are also easy to maintain and breed in the laboratory, and hence, many inbred strains are now available for research. Studies on mice have contributed immeasurably to our understanding of cancer biology.
The development of transgenic, knockout, and knock-in mice has led to an exponential increase in their use as model organisms in research,...
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Adaptive Mechanisms in Cancer Cells02:53

Adaptive Mechanisms in Cancer Cells

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Adaptive Mechanisms in Cancer Cells02:53

Adaptive Mechanisms in Cancer Cells

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Cancer cells accumulate genetic changes at an abnormally rapid rate due to the defects in the DNA repair mechanisms. From an evolutionary perspective, such genetic instability is advantageous for cancer development. Mutant cell lines accumulate a series of beneficial mutations that contribute to their progression into cancer.
Some of the advantages that cancer cells have on normal cells include - enhanced ability to divide without terminally differentiating, induce new blood vessel formation,...
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Author Spotlight: Unveiling Transmembrane Protein Family-Related Markers in Gastric Cancer and Implications for Targeted Therapies
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Multiomics Research Strategies in Cancer: A Growing and Innovative Field.

Zhenhua Du1, Xiaomei Liu1, Zhi Lv2

  • 1Department of Gynaecology and Obstetrics Shengjing Hospital of China Medical University Shenyang China.

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|April 3, 2026
PubMed
Summary
This summary is machine-generated.

Multiomics data analysis offers a comprehensive understanding of cancer's molecular mechanisms and pathogenesis. Integrating multiomics with deep learning and advanced techniques like single-cell and spatial omics aids in discovering cancer biomarkers and advancing precision medicine.

Keywords:
biomarkerscancerdeep learningmultiomicsprecision medicinesingle‐cell omicsspatial omics

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Area of Science:

  • Oncology
  • Genomics
  • Bioinformatics

Background:

  • Cancer is a complex, heterogeneous disease with largely unknown molecular mechanisms.
  • Single-omics approaches offer limited insights into cancer pathogenesis.
  • Multiomics data analysis is crucial for understanding cancer's complexity.

Purpose of the Study:

  • To review cancer disease signatures and multiomics biomarker research.
  • To discuss deep learning strategies for integrating multiomics data.
  • To explore the impact of single-cell and spatial omics on precision medicine.

Main Methods:

  • Review of existing literature on cancer omics and biomarkers.
  • Analysis of multiomics data integration strategies using deep learning.
  • Examination of single-cell and spatial omics applications in cancer research.

Main Results:

  • Multiomics data provide deeper insights into cancer pathogenesis and biomarker discovery.
  • Deep learning facilitates the integration of multiomics data for comprehensive analysis.
  • Single-cell and spatial omics show promise for personalized cancer treatment and early diagnosis.

Conclusions:

  • Comprehensive multiomics analysis, enhanced by deep learning and advanced omics technologies, is vital for advancing cancer research.
  • These integrated approaches are key to identifying novel therapeutic targets and biomarkers.
  • The future of cancer precision medicine relies on leveraging multiomics data for improved diagnostics and therapeutics.