Executive problem framing
Therapy-induced senescence (TIS) is increasingly recognized as a potential contributor to tumor relapse and therapy resistance in solid tumors. Despite its clinical relevance, there is no consensus, validated biomarker panel, or translational framework to detect TIS in patients or to guide senolytic/senomorphic interventions. This project seeks to establish (1) clinically translatable biomarkers that detect TIS, (2) preclinical and patient-derived models to test senescence-targeting strategies, and (3) an adaptive clinical-engagement pathway to evaluate whether removing or modulating TIS improves relapse-free outcomes.
Evidence context (design rational)
- TIS is a biologically plausible mechanism of resistance across chemotherapy, radiotherapy, and some targeted therapies, driven by durable cell-cycle arrest and SASP signaling. Preclinical data support the concept that removing senescent cells or altering SASP can impact tumor dynamics. However, there is no validated, non-invasive biomarker panel for TIS applicable in routine clinical practice, nor a robust clinical framework to deploy senolytic strategies.
- Circulating biomarkers (e.g., SASP factors, extracellular vesicle contents) and tissue single-cell transcriptional signatures offer complementary windows into TIS status. Patient-derived organoid/ xenograft platforms provide a mechanistic readout of whether senescence-targeting agents can enhance cancer control when combined with standard therapy.
Proposed solution and research plan (phases)
Phase 1 – Discovery and biomarker assay development
- Objective: assemble a multi-omic candidate biomarker Panel for TIS using serial blood samples and tumor specimens from patients before, during, and after therapy.
- Activities: literature-guided candidate SASP panels, EV-RNA cargo profiling, and single-cell RNA-seq on available tumor biopsies; develop harmonized assay workflows suitable for CLIA-certified settings.
Phase 2 – Mechanistic validation in patient-derived models - Objective: test whether senolytic/senomorphic regimens can modulate TIS-associated readouts and improve cancer-control metrics in organoid and PDX models derived from consenting patients.
- Activities: treat organoids/PDX with standard therapy +/- senescence-targeting agents; monitor viability, SASP decline, and tumor growth dynamics; identify biomarkers that track response.
Phase 3 – Early-phase, biomarker-driven clinical testing - Objective: design an adaptive, biomarker-integrated trial to evaluate senescence-targeting strategies in a selected solid tumor cohort.
- Activities: implement a trial arm guided by TIS biomarker status, with predefined acceptable safety and early efficacy endpoints; include robust correlative analyses to refine biomarker panels and identify responders.
Phase 4 –implementation science and governance - Objective: define data-sharing, ethics, and governance structures to enable cross-institutional learning, with plans for scalable implementation if signals are favorable.
- Activities: establish IRB templates, consent frameworks for multi-omic analyses, and cost-effectiveness considerations for later adoption.
Methods to ensure rigor and accountability
- Predefine endpoints focused on biomarker validation (sensitivity/specificity for TIS), safety of senescence-targeting agents, and exploratory efficacy signals.
- Use standardized, cross-site assay platforms and QC metrics; implement external quality assessments for biomarker measurements.
- Maintain transparent labeling of knowns vs unknowns and ensure IRB oversight and patient privacy protections.
Governance, ethics, and data management
- Engage patient advocates and multidisciplinary ethics oversight to address consent for serial sampling, organoid derivation, and interventional studies.
- Establish data governance agreements enabling secure, de-identified sharing of biomarker and clinical data across sites.
- Plan for iterative refinement of the biomarker panel as new evidence emerges, with clear criteria for de-implementation if performance is insufficient.
Knowns vs unknowns (summary)
- Knowns: TIS is biologically plausible; multi-omic biomarkers can capture complex senescence signatures; patient-derived models can test senescence-targeting strategies;
- Unknowns: the most predictive biomarker combination for TIS, the safety/effectiveness profile of senolytics in humans, and how to implement such a biomarker-driven approach in diverse clinical settings.
Collaborative path forward
- Convene an international, multi-institution consortium to align on biomarker definitions, assay platforms, and model systems.
- Develop shared protocols for sample collection, data annotation, and analysis pipelines to accelerate learning and enable external validation.
- Pursue joint funding opportunities and iterative updates to trial designs based on accumulating correlative data.
Rationale for impact
If successful, this approach would provide a clinically actionable means to detect TIS early, stratify patients for targeted senescence-interventions, and potentially reduce relapse rates across several solid tumors, representing a distinct, mechanistically grounded pivot from prior screening or microbiome-focused cancer research topics.