Related Experiment Video
Updated: Feb 12, 2026

Automated Multiplex Immunofluorescence Panel for Immuno-oncology Studies on Formalin-fixed Carcinoma Tissue Specimens
Published on: January 21, 2019
Rational design and identification of immuno-oncology drug combinations
Marco A J Iafolla1, Heather Selby2, Kathrin Warner3
1Division of Medical Oncology and Hematology, Princess Margaret Cancer Centre, University Health Network, University of Toronto, 610 University Ave, Toronto, Ontario, M5G 2M9, Canada.
Background:
Clinical trials investigating immuno-oncology (IO) drug combinations are largely based on empiricism or limited non-clinical evaluations. This study identified the current combination IO drug clinical trials and investigated how tumour molecular profiling can help rationalise IO drug combinations.
Methods:
IO targets were identified via PubMed search and expert opinion. IO drugs were compiled by searching the National Cancer Institute Drug Dictionary and pharmaceutical pipelines, August 2016. Combination IO trials were obtained by searching doublet IO drug combinations in www.clinicaltrials.gov from September to November 2016. IO target gene expressions were extracted from The Cancer Genome Atlas (TCGA) data set and compared with normal tissues from the Genotype-Tissue Expression database. Differentially expressed genes for each cancer were determined using the Wilcoxon rank-sum test, and p-values were corrected for multiple testing.
Results:
In total, 178 IO targets were identified; 90 targets have either regulatory approved or investigational therapeutics. In total, 410 combination trials involving ≥2 IO drugs were identified: skin (n = 102) and genitourinary (n = 41) malignancies have the largest number of combination IO trials; 109 trials involved >2 disease sites. Summative patient accrual estimates among all trials are 71,345. Trials combining cytotoxic T lymphocyte antigen 4 (CTLA4) with programmed cell death protein 1 (n = 79) and CTLA4 with programmed cell death ligand 1 (n = 44) are the most common. Gene expression data from TCGA were mined to extract the 178 IO targets in 9089 tumours originating from 19 cancer types. IO target expression-clustered heatmap analysis identified several promising drug combinations.
Conclusion:
Our review highlights the great interest in combination IO clinical trials. Our analysis can enrich IO combination therapy selection.
Insights
This study reviewed immuno-oncology (IO) drug combinations in clinical trials and used tumor molecular profiling to guide rational selection of IO therapies. Analysis of gene expression data revealed promising combination strategies for cancer treatment.
Area of Science:
- Oncology
- Immunology
- Genomics
Background:
- Immuno-oncology (IO) drug combination trials often lack a strong scientific rationale.
- Current selection of IO drug combinations relies heavily on empiricism or limited preclinical data.
Purpose of the Study:
- To identify and analyze current clinical trials investigating combination IO drug therapies.
- To explore the utility of tumor molecular profiling in rationalizing the selection of IO drug combinations.
Main Methods:
- Compiled a list of IO targets and drugs from scientific literature and databases.
- Searched clinicaltrials.gov for combination IO drug trials.
- Analyzed The Cancer Genome Atlas (TCGA) data for IO target gene expression in tumors compared to normal tissues.
- Utilized statistical methods to identify differentially expressed genes and performed heatmap analysis.
Main Results:
- Identified 178 IO targets, with 90 having associated therapeutics.
- Cataloged 410 combination IO trials, predominantly in skin and genitourinary cancers.
- Found that combinations of cytotoxic T lymphocyte antigen 4 (CTLA4) with programmed cell death protein 1 (PD-1) or programmed cell death ligand 1 (PD-L1) are most frequent.
- Gene expression analysis revealed promising IO drug combinations through heatmap analysis.
Conclusions:
- There is significant interest and activity in combination IO clinical trials.
- This study provides a data-driven approach to enhance the selection of IO combination therapies.
More Related Videos
Related Concept Videos
Combined Effects of Drugs: Synergism
Such synergistic combinations...
Rationalizing Substitutions
Rational Expressions
Combined Effects of Drugs: Antagonism
The most common type is receptor antagonism, where one drug acts as an antagonist to block the effects of another drug by...
Structure-Activity Relationships and Drug Design
SAR studies the intricate relationship between a drug's chemical structure and biological activity. It focuses on understanding how modifications to a drug's structure can influence...
Asymptotes in Rational Functions

