Webinar: Rapid Community NGS in Cancer Care for Faster Turnaround and Better Outcomes

Webinar summary

In this webinar, “Community Based Rapid NGS Offers Considerable Advantages in Clinical Cancer Care”, is presented by Dr. Brandon Sheffield, an anatomic and molecular pathologist at William Osler Health System. The session focuses on point-of-care molecular testing, specifically how rapid next-generation sequencing (NGS) can be implemented in a community hospital setting to improve cancer care delivery. 

Study overview

Dr. Sheffield describes the implementation of rapid, on-site NGS within a community-based hospital network where laboratory services are centralized. Lung cancer is used as the primary example due to its high mortality and the large number of required actionable biomarkers.

Key context includes:

• Most lung cancer patients present at advanced stages and require urgent treatment decisions.
• Biomarker results are essential before initiating therapy.
• Traditional workflows involve sending specimens to external molecular labs, leading to turnaround times of approximately two months.

To address these delays, the team:

• Trained immunohistochemistry (IHC) technologists to perform NGS.
• Implemented a highly automated sequencing platform with a validated 50-gene panel.
• Integrated NGS into the existing histopathology workflow, alongside IHC.
• Enabled pathologists to both order and interpret NGS results within the same clinical workflow.

Key findings

Significant reduction in turnaround time

• Median turnaround time for NGS: 3 days.
• Many cases completed in 2–4 days, with some same-day (0-day) and 1-day results.
• This represents a major improvement from prior turnaround times of ~62 days.

Supports improved clinical outcomes and decision-making

• Faster biomarker results enable earlier initiation of targeted therapies.
• A case example showed a critically ill patient benefiting from rapid detection of a ROS1 fusion, enabling targeted treatment and ICU discharge.
• Another example demonstrated diagnosis and treatment guidance from liquid biopsy within 24 hours.

Integration of diagnosis and biomarkers

• NGS results are reported alongside pathology diagnoses in a single document.
• Patients are effectively diagnosed with biomarker-defined disease (e.g., “EGFR-driven lung cancer”), ensuring clinicians always access both diagnosis and actionable data together.

Enabling high analytical performance

• The NGS assay demonstrated high concordance with reference methods for:
  • Single nucleotide variants
  • Copy number alterations
  • RNA fusions
• Observed mutation frequencies (e.g., EGFR, ALK, KRAS) aligned with expected clinical prevalence, supporting assay validity.

Increased detection of actionable mutations

• In colon cancer, NGS identified actionable mutations in >10% of cases that would have been missed by single-gene testing.

Enhanced collaboration between pathology and oncology

• Direct, real-time communication between technologists and oncologists improved workflow efficiency.
• Oncologists could triage urgent cases and interact directly with lab staff, bypassing traditional delays.

Expanded role of pathologists

• Pathologists became more active members of the care team.
• NGS supported not only biomarker testing but also diagnostic challenges (e.g., tumor classification, distinguishing metastasis vs. new primary).

Reduced need for liquid biopsy

• Availability of rapid tissue-based NGS reduced demand for liquid biopsy, which had previously been used primarily due to speed limitations of traditional workflows.

Economic considerations

• While NGS has material costs, overall system costs may decrease due to:
  • Reduced oncology visits
  • Reduced number of times a pathologist assesses any given case
  • Reduction of:
    • filing/pulling/filing
    • testing older archival materials
    • administrative time procesing orders

Conclusion

Rapid, community-based NGS can be successfully integrated into routine histopathology workflows using automated platforms and targeted training. This approach significantly reduces turnaround times, improves access to actionable biomarker data, and enhances collaboration between laboratory and clinical teams. The model enables pathologists to play a more central role in precision oncology and supports both diagnostic and therapeutic decision-making to help improve patient care in community hospital settings.