Individualised cancer therapeutics: dream or reality? Therapeutics construction

Area of Science:

• Oncology
• Molecular Biology
• Bioinformatics

Background:

• Cancer cells possess complex hierarchical networks crucial for survival and competitiveness.
• Analyzing molecular data like DNA microarrays and proteomics offers insights into these networks.
• Targeted therapies require understanding individual tumor profiles and molecular derangements.

Purpose of the Study:

• To review technologies for analyzing cancer cell networks and identifying therapeutic targets.
• To discuss methods for selective disruption of molecular targets in cancer cells.
• To explore delivery vehicles for synthesized molecular therapeutics, focusing on RNA interference (RNAi).

Main Methods:

• Integration of DNA microarray and proteomic data into functional expression sets.
• Utilizing RNA interference (RNAi) for gene silencing mechanisms.
• Investigating gene-modified conditionally replicating viruses as delivery vehicles.

Main Results:

• Functional expression sets provide a circuit map of cancer cell networks.
• RNAi offers a mechanism to silence specific genes, including those upregulated in cancer.
• Gene-modified viruses show potential for targeted delivery of RNAi to malignant cells.

Conclusions:

• Understanding cancer cell networks through integrated data analysis is key for personalized therapy.
• RNAi technology holds promise for cancer treatment, but delivery remains a challenge.
• Conditionally replicating viruses are promising candidates for the selective delivery of RNAi therapeutics.