Research

Chain Compass Anchor Clock

The Gibb lab explores how molecular and spatial profiling can transform the way we understand and treat urologic cancers. By integrating transcriptomics, digital pathology, and machine learning, we aim to uncover hidden patterns in tumor biology and translate them into clinically actionable tools. Our work focuses on bridging the gap between molecular insight and real-world decision making to help clinicians tailor care to individual patients.

Click on one of the project icons to explore the research taking place at The Gibb Lab!

Risk Stratification of Non-Muscle Invasive Bladder Cancer (NMIBC)

NMIBC makes up about 75% of new bladder cancer diagnoses, most commonly as stage Ta, low-grades (TaLG). While these cases often have excellent outcomes, certain patients — particularly those with recurrent, multifocal, or large tumors — face a significantly higher risk of progression to muscle-invasive bladder cancer (MIBC), which requires more aggressive treatment and carries a poorer prognosis.

We aim to:

  • Validate promising molecular classifiers in large, well-annotated TaLG cohorts
  • Investigate the biology and clinical relevance of high-grade Ta (TaHG) and T1 disease
  • Expand classifier frameworks to support prospective clinical testing and decision-making

Relevant Publications:

Upstaging at the Time of Radical Cystectomy

Accurately staging bladder cancer before surgery remains a major challenge, as many presumed organ-confined cases (HGT1/T2) are later upstaged to pT3+ or N+ at cystectomy. Molecular subtyping shows promise, but current classifiers lack sufficient precision to reliably identify high-risk patients.

This project seeks to:

  • Use transcriptome-based approaches to define the biology of aggressive bladder cancer
  • Develop molecular classifiers that improve risk stratification and guide treatment
  • Explore pathology-based AI models to predict upstaging with greater accuracy

Relevant Publications:

Molecular Evolution Following Neoadjuvant Therapy

Despite neoadjuvant chemotherapy (NAC) followed by radical cystectomy, outcomes in muscle-invasive bladder cancer (MIBC) remain poor, with 5-year overall survival around 55%. Post-treatment molecular profiling has revealed residual subtypes, including a "scar-like" profile similar to p53-like tumors, suggesting fibroblast infiltration or tumor cell remodeling.

Our study will:

  • Validate a transcriptome-based classifier to identify scar-like tumors following systemic therapy
  • Define the cellular composition and spatial organization of these tumors
  • Clarify how scar-like profiles arise and whether they can be therapeutically induced as part of a favorable treatment response

Relevant Publications:

Mitochondria

Biomarker Discovery in Intermediate-Risk Prostate Cancer

Grade Group 2 (GG2) prostate cancer presents a clinical dilemma, as some men are suitable for active surveillance while others harbor aggressive disease not captured by current tools.

We are investigating lncRNAs and digital pathology as biomarkers in GG2, with preliminary data suggesting prognostic subtypes.

We aim to:

  • Define molecular subtypes of GG2 tumors linked to adverse outcomes
  • Develop and validate a transcriptome-based risk classifier
  • Integrate spatial and image-based features to enhance prediction