Small Cell Lung Cancer

Small-cell lung cancer (SCLC) is an extremely aggressive disease with a poor prognosis. A number of different subtypes exist. Comprehensive clinical, pathological, and molecular data, when appropriately integrated with advanced computational approaches, are transforming the way we characterize and study lung cancer.

Breast Cancer

Our Services include but are not limited to:

Genomic Analysis
K-means Clustering
Gene Regulatory Network Construction
Gene Ontology Enrichment Analysis
BooleaBayes Network Simulations
Drug Sensitivity Analysis
High Throughput Screening

Genetically and molecularly, individual patient tumors and preclinical models of lung cancer are profiled by various high-throughput platforms to characterize the molecular properties and functional liabilities. The resulting multi-omics data sets and their interrogation facilitate both basic research mechanistic studies. We utilize a computational biology approach, based on appropriate re-analyses of datasets followed by reliable data filtering, to analyze integrative and combinatorial deregulated interaction networks in SCLC.

SCLC Targets and Drugs
Apoptotic agents	PIC3CA	Focal adhesion kinases (FAK) inhibitors
eIF4E inhibitors	RET inhibitors	Chemokine receptor 4 (CXCR4) inhibitors
Aurora kinase inhibitors	EZH2 inhibitors	Poly ADP ribose polymerase (PARP) inhibitors
Notch inhibitors	Transcription-targeting drugs	Antiangiogenic agents
FGFR inhibitors	Novel cytotoxic chemotherapeutic agents	Antibody drug and radiotherapeutic conjugates

CD ComputaBio has multiple resources including academic research and preclinical works in the identification of a suitable disease target and its corresponding hit. We are also interested in how the machine learning-based integration of multi-omic datasets can aid in the discovery of new cancer subgroups and biomarkers. Contact us for more service details.