Standard Pathology Tests Outperform Molecular Subtyping in Bladder Cancer
|
By LabMedica International staff writers Posted on 02 Jan 2020 |

Image: Electron micrograph of a bladder cancer cell: clinical pathology tests outperform molecular subtyping in bladder cancer (Photo courtesy of Jim Stallard).
Evolving diagnostic approaches include compiling databanks on gene expression and mutations present in a cancer type to find patterns of gene expression that are then used to subtype tumors that "pathologically look similar" but are molecularly different.
Studies indicate that molecular subtypes in muscle invasive bladder cancer predict the clinical outcome. The idea is that molecular subtypes are better equipped to indicate which cancer is more or less aggressive and to help steer treatment options like whether chemotherapy before surgery to remove a diseased bladder is better.
A team of scientists led by those at the Medical College of Georgia (Augusta, GA, USA) subtyped institutional cohort of 52 patients, including 39 with muscle invasive bladder cancer, an Oncomine (Thermo Fisher Scientific, Waltham, MA, USA) data set of 151 with muscle invasive bladder cancer and TCGA (The Cancer Genome Atlas) data set of 402 with muscle invasive bladder cancer. Subtyping was done using simplified panels (MCG-1 and MCG-Ext) which included only transcripts common in published studies and were analyzed for predicting metastasis, and cancer specific, overall and recurrence-free survival.
The team reported that MCG-1 was only 31% -36% accurate at predicting important indicators like likelihood of metastasis; disease specific survival, meaning surviving bladder cancer; or overall survival, meaning survival from all causes of death from the time of cancer diagnosis or beginning of treatment until the study's end. They looked again at the 402 patients whose specimens were in the dataset and found that 21 patients' tumors were actually low-grade. Patients with low-grade tumors have higher survivability and a better prognosis than patients with high-grade muscle invasive disease.
When they removed the low-grade cases from the TCGA dataset, MCG-1 accurately predicted essentially nothing, not even overall survival. Then they included some patients with low-grade tumors into their own dataset, which they had looked at originally, and MCG-1 was now able to predict metastasis and disease specific survival. All the existing subtypes are categorized as bad or better based on the cancer prognosis. The presence of the low-grade tumors in the classification of subtypes skewed the data to make it look like subtypes were predicting overall survival when really it was the grade of the cancer itself that was predictive.
Vinata B. Lokeshwar, PhD, a professor and corresponding author of the study, said, “Genetic profiling of a patient's tumor definitely has value in enabling you to discover the drivers of growth and metastasis that help direct that individual's treatment, even as it helps to identify new treatment targets. But using this information to subtype tumors does not appear to add diagnostic or prognostic value for patients.”
The authors concluded that molecular subtypes reflect bladder tumor heterogeneity and are associated with tumor grade. In multiple cohorts and subtyping classifications the clinical parameters outperformed subtypes for predicting the outcome. The study was published on January 1, 2020 in the Journal of Urology.
Related Links:
Medical College of Georgia
Oncomine
Studies indicate that molecular subtypes in muscle invasive bladder cancer predict the clinical outcome. The idea is that molecular subtypes are better equipped to indicate which cancer is more or less aggressive and to help steer treatment options like whether chemotherapy before surgery to remove a diseased bladder is better.
A team of scientists led by those at the Medical College of Georgia (Augusta, GA, USA) subtyped institutional cohort of 52 patients, including 39 with muscle invasive bladder cancer, an Oncomine (Thermo Fisher Scientific, Waltham, MA, USA) data set of 151 with muscle invasive bladder cancer and TCGA (The Cancer Genome Atlas) data set of 402 with muscle invasive bladder cancer. Subtyping was done using simplified panels (MCG-1 and MCG-Ext) which included only transcripts common in published studies and were analyzed for predicting metastasis, and cancer specific, overall and recurrence-free survival.
The team reported that MCG-1 was only 31% -36% accurate at predicting important indicators like likelihood of metastasis; disease specific survival, meaning surviving bladder cancer; or overall survival, meaning survival from all causes of death from the time of cancer diagnosis or beginning of treatment until the study's end. They looked again at the 402 patients whose specimens were in the dataset and found that 21 patients' tumors were actually low-grade. Patients with low-grade tumors have higher survivability and a better prognosis than patients with high-grade muscle invasive disease.
When they removed the low-grade cases from the TCGA dataset, MCG-1 accurately predicted essentially nothing, not even overall survival. Then they included some patients with low-grade tumors into their own dataset, which they had looked at originally, and MCG-1 was now able to predict metastasis and disease specific survival. All the existing subtypes are categorized as bad or better based on the cancer prognosis. The presence of the low-grade tumors in the classification of subtypes skewed the data to make it look like subtypes were predicting overall survival when really it was the grade of the cancer itself that was predictive.
Vinata B. Lokeshwar, PhD, a professor and corresponding author of the study, said, “Genetic profiling of a patient's tumor definitely has value in enabling you to discover the drivers of growth and metastasis that help direct that individual's treatment, even as it helps to identify new treatment targets. But using this information to subtype tumors does not appear to add diagnostic or prognostic value for patients.”
The authors concluded that molecular subtypes reflect bladder tumor heterogeneity and are associated with tumor grade. In multiple cohorts and subtyping classifications the clinical parameters outperformed subtypes for predicting the outcome. The study was published on January 1, 2020 in the Journal of Urology.
Related Links:
Medical College of Georgia
Oncomine
Latest Pathology News
- Multimodal AI Tool Predicts Genetic Alterations to Guide Breast Cancer Treatment
- Interpretable AI Reveals Hidden Cellular Features from Microscopy Images
- Tumor Immune Structure Predicts Response to Immunotherapy in Melanoma
- Plug-and-Play AI Pathology System Classifies Multiple Cancers from Few Slides
- AI-Based Assays Support Risk Stratification in Prostate and Breast Cancer
- AI Pathology Model Predicts Immunotherapy Response in Lung Cancer
- Study Reveals Moleclar Mechanism Driving Aggressive Skin Cancer
- AI Precision Tests Deliver Cancer Risk Insights from Routine H&E Slides
- Collaboration Applies AI Pathology to Predict Response to Antibody-Drug Conjugates
- Biomarker Predicts Immunotherapy Response and Prognosis in Colorectal Cancer
- AI Improves Completeness of Complex Cancer Pathology Reports
- AI Tool Predicts Chemotherapy Response in Small Cell Lung Cancer
- Tumor-Specific Biomarker Predicts Neoadjuvant Immunotherapy Response in Gastric Cancer
- AI Tool Predicts Patient-Specific Chemotherapy Benefit in Breast Cancer
- AI-Based Pathology Model Guides Chemotherapy Decisions in Breast Cancer
- Biopsy-Based Gene Test Predicts Recurrence Risk in Lung Adenocarcinoma
Channels
Clinical Chemistry
view channel
Routine Blood Tests Identify Biomarkers Linked to PTSD
Post-traumatic stress disorder (PTSD) is associated with a range of chronic physical health conditions and affects multiple organ systems. Clinical laboratories routinely measure blood analytes that reflect... Read more
Proteomic Data Underscore Need for Age-Specific Pediatric Reference Ranges
Serum proteins underpin many routine tests used to detect inflammation, hormonal imbalance, cardiovascular disease, and metabolic disorders. Yet pediatric interpretation often relies on adult reference... Read more
Routine Blood Count Ratio Linked to Future Alzheimer’s and Dementia Risk
Alzheimer’s disease and related dementias develop over years, making it difficult to identify at-risk patients before symptoms appear. Clinicians therefore need widely available laboratory markers that... Read more
Label-Free Microfluidic Device Enriches Tumor Cells and Clusters from Pleural Effusions
Diagnosing malignancy from pleural effusion remains challenging because tumor cells are rare and clusters are easily disrupted during processing. Conventional cytology can miss malignant tumor cells and... Read moreHematology
view channel
Blood Test Enables Early Detection of Multiple Myeloma Relapse
Bone marrow biopsies remain central to diagnosing and monitoring multiple myeloma, yet the procedure is painful, invasive, and often repeated over time. Older patients—who represent most new cases—can... Read more
Single Assay Enables Rapid HLA and ABO Genotyping for Transplant Matching
CareDx (Brisbane, CA, USA) has introduced AlloSeq Nano, a nanopore‑based HLA (human leukocyte antigen) and ABO genotyping solution unveiled at the European Federation for Immunogenetics (EFI) Conference 2026.... Read moreImmunology
view channel
Study Highlights Low Sensitivity of Current Lyme Tests in Early Infection
Accurate laboratory diagnosis of early Lyme disease remains challenging because serologic responses may be limited soon after infection. Missed detection at this stage can delay evaluation and management... Read more
Immune Aging Clock Quantifies Immunosenescence and Identifies Therapeutic Target
Immune aging undermines host defense and contributes to multiple age-related diseases, yet its heterogeneity complicates measurement and intervention. Clinical laboratories increasingly seek objective... Read moreMicrobiology
view channel
Rapid Antigen Biosensor Detects Active Tuberculosis in One Hour
Tuberculosis remains a major global health challenge and continues to drive significant morbidity and mortality. The World Health Organization’s 2024 global report cites it as the leading cause of death... Read more
Oral–Gut Microbiome Signatures Identify Early Gastric Cancer
Early detection of gastric cancer could be advanced by scalable screening strategies using minimally invasive sampling. Saliva collection is noninvasive and cost-effective, supporting wider adoption... Read morePathology
view channel
Multimodal AI Tool Predicts Genetic Alterations to Guide Breast Cancer Treatment
PIK3CA mutations are key biomarkers for selecting phosphoinositide 3-kinase (PI3K)–targeted therapies in breast cancer, yet access to molecular testing can be inconsistent and costly. Conventional polymerase... Read more
Interpretable AI Reveals Hidden Cellular Features from Microscopy Images
Microscopy images contain rich clues about cell health, but many disease-relevant morphological differences are too subtle to see and difficult to quantify consistently. Artificial intelligence (AI) has... Read moreTechnology
view channel
Microfluidic Single-Cell Assay Predicts Breast Cancer Risk
Risk stratification for breast cancer remains imprecise, as population-based models and breast density can over- or underestimate individual risk, potentially leading to over- or under-screening.... Read more
AI Tool Predicts Non-Response to Targeted Therapy in Colorectal Cancer
Advanced bowel cancer remains difficult to treat, and many patients receive targeted therapies that do not help them but still cause harm. Clinicians need reliable ways to identify likely responders before... Read moreIndustry
view channel
Collaboration Expands Access to Rapid Metagenomic Diagnostics for Complex Infections
Hospitals are seeing rising rates of complicated and healthcare-associated infections, especially in immunocompromised patients, intensifying the need for rapid, comprehensive pathogen detection.... Read more







