Related Experiment Video
Updated: Nov 1, 2025

Development of Compendium for Esophageal Squamous Cell Carcinoma
Published on: April 12, 2024
Criteria-based curation of a therapy-focused compendium to support treatment recommendations in precision oncology
Frank P Lin1,2,3, Subotheni Thavaneswaran4,5,6, John P Grady5,6
1Kinghorn Centre for Clinical Genomics, Garvan Institute of Medical Research, Sydney, NSW, Australia. f.lin@garvan.org.au.
Abstract:
While several resources exist that interpret therapeutic significance of genomic alterations in cancer, many regional real-world issues limit access to drugs. There is a need for a pragmatic, evidence-based, context-adapted tool to guide clinical management based on molecular biomarkers. To this end, we have structured a compendium of approved and experimental therapies with associated biomarkers following a survey of drug regulatory databases, existing knowledge bases, and published literature. Each biomarker-disease-therapy triplet was categorised using a tiering system reflective of key therapeutic considerations: approved and reimbursed therapies with respect to a jurisdiction (Tier 1), evidence of efficacy or approval in another jurisdiction (Tier 2), evidence of antitumour activity (Tier 3), and plausible biological rationale (Tier 4). Two resistance categories were defined: lack of efficacy (Tier R1) or antitumor activity (Tier R2). Based on this framework, we curated a digital resource focused on drugs relevant in the Australian healthcare system (TOPOGRAPH: Therapy Oriented Precision Oncology Guidelines for Recommending Anticancer Pharmaceuticals). As of November 2020, TOPOGRAPH comprised 2810 biomarker-disease-therapy triplets in 989 expert-appraised entries, including 373 therapies, 199 biomarkers, and 106 cancer types. In the 345 therapies catalogued, 84 (24%) and 65 (19%) were designated Tiers 1 and 2, respectively, while 271 (79%) therapies were supported by preclinical studies, early clinical trials, retrospective studies, or case series (Tiers 3 and 4). A companion algorithm was also developed to support rational, context-appropriate treatment selection informed by molecular biomarkers. This framework can be readily adapted to build similar resources in other jurisdictions to support therapeutic decision-making.
Insights
A new digital tool, TOPOGRAPH, helps clinicians select cancer therapies based on molecular biomarkers and regional drug access. It categorizes treatments by evidence level, aiding precision oncology decision-making.
Area of Science:
- Oncology
- Genomics
- Pharmacology
Background:
- Genomic alterations in cancer guide therapy, but regional drug access issues complicate clinical management.
- A need exists for practical, evidence-based tools to adapt biomarker-guided cancer treatment to local contexts.
Purpose of the Study:
- To develop a pragmatic, evidence-based framework and digital resource (TOPOGRAPH) for guiding molecular biomarker-informed cancer therapy selection.
- To categorize biomarker-disease-therapy relationships based on therapeutic considerations and evidence levels.
Main Methods:
- Conducted a survey of drug regulatory databases, knowledge bases, and literature to identify approved and experimental therapies linked to biomarkers.
- Developed a tiering system (Tiers 1-4) to classify therapies based on approval, reimbursement, efficacy evidence, and biological rationale.
- Defined resistance categories (Tiers R1-R2) and curated the TOPOGRAPH digital resource for the Australian healthcare system.
Main Results:
- TOPOGRAPH includes 2810 biomarker-disease-therapy triplets across 989 entries, covering 373 therapies, 199 biomarkers, and 106 cancer types.
- Of 345 cataloged therapies, 24% were Tier 1 (approved/reimbursed) and 19% were Tier 2 (approved elsewhere).
- 79% of therapies were supported by preclinical or early clinical evidence (Tiers 3-4), indicating a significant role for experimental treatments.
Conclusions:
- The TOPOGRAPH framework provides a structured approach to therapeutic decision-making in precision oncology.
- The developed digital resource and companion algorithm support rational, context-appropriate treatment selection based on molecular biomarkers.
- This adaptable framework can be implemented in other jurisdictions to enhance biomarker-guided cancer therapy access and utilization.
More Related Videos
13:24Integration of Wet and Dry Bench Processes Optimizes Targeted Next-generation Sequencing of Low-quality and Low-quantity Tumor Biopsies
Published on: April 11, 2016
08:52Profiling Sensitivity to Targeted Therapies in EGFR-Mutant NSCLC Patient-Derived Organoids
Published on: November 22, 2021
Related Concept Videos
Combination Therapies and Personalized Medicine
The combination of the drug acetazolamide and sulforaphane is a good example of combination therapy to treat cancer. The cells in the interior of a large tumor often die due to the hypoxic and...
Targeted Cancer Therapies
There are several types of targeted therapies against...
Cancer Therapies
However, cancer treatments can pose several challenges, as therapies used to kill cancer cells are generally also toxic to normal cells. Moreover, cancer cells mutate rapidly and can develop resistance to chemical agents or radiation therapy. Besides, all types of cancer cells may not respond to the same therapy. Some cancer cells respond to one...
Tumor Immunotherapy
Treatment Resistant Cancers
Drug Administration and Therapy Phases: Overview
The pharmaceutical phase focuses on leveraging the physicochemical properties of the drug to design and manufacture an effective product. Variants include orally administered tablets or capsules, topical creams or ointments, and parenteral-delivery solutions or emulsions.
The pharmacokinetic phase...