Identifying intracellular signaling modules and exploring pathways associated with breast cancer recurrence

Area of Science:

• Computational Biology
• Systems Biology
• Genomics

Background:

• Understanding intracellular signal transduction pathways is crucial for disease development and drug treatment.
• Aberrant cellular responses are linked to complex pathway modularization.

Purpose of the Study:

• To identify pathway modules associated with breast cancer recurrence and Tamoxifen resistance using a novel computational approach.
• To explore pathway landscapes and reconstruct signaling networks.

Main Methods:

• IMPALA (Inferred Modularization of PAthway LAndscapes) integrates gene expression data and genome-scale knowledge databases.
• Analysis focused on estrogen-receptor (ER) positive breast cancer patient samples treated with Tamoxifen.
• Pathway modules were validated using data from sensitive and resistant breast cancer cell lines.

Main Results:

• IMPALA identified key pathway modules associated with ER signaling, cell cycle, and apoptosis.
• Alternative pathways interconnected through cytoplasmic genes and enriched with ErbB, MAPK, and JAK-STAT signaling components were identified.
• Genes in cell cycle/apoptosis modules up-regulated in patients with short survival were also over-expressed in drug-resistant cell lines.

Conclusions:

• IMPALA effectively identifies pathway modules linked to Tamoxifen resistance and increased breast cancer recurrence risk.
• The identified pathways provide insights into cellular mechanisms underlying treatment resistance.
• IMPALA offers a powerful strategy for reconstructing and exploring pathway landscapes in disease contexts.