How Functional Precision Medicine Is Paving the Way for Personalized Cancer Therapy
"We'd been told repeatedly that surgery was the only possible treatment," Patty recalls. But after three major surgeries and with new tumors appearing, she was rapidly approaching the limit of what her body could endure.
Patty's story reflects the broader challenges in treating soft tissue sarcomas—rare cancers that account for less than 1% of all adult malignancies yet comprise more than 100 different subtypes. This incredible diversity, combined with their rarity, has made developing effective treatments extraordinarily difficult. For decades, patients have faced limited options, often with dismal outcomes—especially for advanced disease where the five-year survival rate plummets to just 16.7% 7 9 .
Soft tissue sarcomas (STS) represent a category of rare cancers arising from connective tissues like fat, muscle, nerves, and blood vessels. Their biological complexity stems from varying frequencies of chromosomal translocations, oncogenic mutations, and gene amplifications across different subtypes 4 .
For decades, the treatment approach for localized sarcomas has centered on three modalities:
Complete removal of the tumor
Eliminating remaining cancer cells
Particularly anthracyclines like doxorubicin for advanced disease 9
Response rate with doxorubicin
Median overall survival
Response rate with subsequent treatments 4
The problem extends beyond efficacy to toxicity. Chemotherapy often causes significant side effects, including cumulative dose-dependent cardiotoxicity that can limit its use 4 . Additionally, elderly patients—who represent more than 20% of sarcoma cases—often receive less aggressive treatment despite having more adverse prognostic features, further complicating their care 5 .
While traditional approaches treat sarcomas based on their histological subtype or location, functional precision medicine (FPM) takes a different approach: it tests how actual living tumor cells respond to various drugs before ever giving them to the patient.
At the forefront of this revolution is the Quadratic Phenotypic Optimization Platform (QPOP), an innovative functional precision medicine approach that goes beyond single-drug testing to identify optimal combination therapies 1 4 .
Unlike genetic testing that looks for specific mutations, QPOP works with fresh tumor samples obtained through biopsy or surgery. These samples are processed, and the tumor cells are exposed to an array of therapeutic agents—both approved and investigational—in various combinations. The platform then analyzes this complex data to rank all possible drug combinations based on their effectiveness at killing the specific patient's cancer cells 4 .
Median turnaround time from sample collection to report generation 1
Fresh tumor biopsy or resection
Exposure to therapeutic agents
Testing 155 combination permutations
Clinically actionable drug sensitivity profile
Recent research published in npj Precision Oncology has demonstrated QPOP's potential to transform sarcoma treatment. The study analyzed 45 primary soft tissue sarcoma patient samples using QPOP, with compelling results 4 .
The research followed a meticulous process:
The platform successfully generated reports for 88.2% of patient samples (45 of 51), a high success rate considering the challenges of working with primary tumor samples 4 .
Success rate in generating reports from patient samples
Successful samples from total collected
| Patient Group | Number of Treatment Cases | Concordance with QPOP Prediction | Statistical Significance |
|---|---|---|---|
| QPOP-defined Responders | 14 | Significant association with positive clinical response (PR/SD) | Odds Ratio: 13.5; p=0.0063 |
| QPOP-defined Non-Responders | 13 | Significant association with disease progression (PD) | Confidence Interval: 2.07-73.3 |
| Overall Accuracy | 27 | 77.8% Total Predictive Value | AUC-ROC: 0.769 |
The study highlighted a compelling case of a young patient with an aggressive solitary fibrous tumor (SFT) that had metastasized to the brain, bone, and liver. After failing first-line liposomal doxorubicin, a tumor sample from her liver metastasis was tested with QPOP. The platform correctly identified her lack of sensitivity to doxorubicin while pinpointing pazopanib as the most effective single agent.
QPOP identified pazopanib as the most effective drug. Liver lesions responded to pazopanib treatment.
New brain lesions appeared while on pazopanib, indicating developing resistance.
QPOP analysis of brain tumor sample showed >10-fold increase in IC50 to pazopanib and identified eribulin as the new most effective drug 4 .
| Primary Liver Metastasis | Brain Metastasis (After Treatment) | |
|---|---|---|
| Most Effective Drug | Pazopanib | Eribulin |
| Pazopanib Sensitivity | Highly sensitive | >10-fold increase in IC50 (resistant) |
| Doxorubicin Sensitivity | Not sensitive | Not sensitive |
| Clinical Correlation | Liver lesions responded to pazopanib | Brain lesions progressed on pazopanib |
Perhaps the most exciting aspect of QPOP is its ability to identify synergistic drug combinations that might otherwise go unnoticed. In the sarcoma study, the platform revealed AZD5153 (a BET inhibitor) combined with pazopanib (a multi-kinase blocker) as particularly effective across multiple patient samples 4 .
BET inhibitor
Multi-kinase blocker
Superior efficacy across multiple patient samples
Repression of oncogenic MYC and related pathways
Provides both therapeutic potential and insights for future drug development
| Tool/Reagent | Function | Application in STS Research |
|---|---|---|
| Primary Patient Samples | Fresh tumor tissue from biopsies or resections | Provides living tumor cells for ex vivo drug testing |
| Drug Panels | Collection of FDA-approved and investigational agents | Enables screening of multiple therapeutic options |
| QPOP Platform | Algorithmic analysis of combination drug sensitivity | Identifies optimal drug combinations from limited data |
| BET Inhibitors (AZD5153) | Novel epigenetic-targeting agents | Shows promise in combination therapies for STS |
| Multi-kinase Inhibitors (Pazopanib) | Targeted therapy blocking multiple cancer pathways | Standard second-line agent with new potential in combinations |
| Patient-Derived Models | In vitro and in vivo models grown from patient samples | Allows validation of drug sensitivity findings |
Functional precision medicine represents a paradigm shift from the traditional one-size-fits-all approach to a truly personalized strategy. As the research demonstrates, platforms like QPOP offer:
In predicting treatment response compared to conventional methods
Identification of synergistic drug combinations beyond standard options
To evolving cancer resistance patterns
Actionable results within clinically relevant timeframes
"I just wish we'd known about MD Anderson sooner. If I'd come here before that very first surgery, maybe I wouldn't have needed any of the others."
As functional precision medicine continues to evolve, it promises to transform the outlook for sarcoma patients—turning rare cancers from death sentences into manageable conditions through the power of personalization.