

Episode # 3 • 17 Jan 2025
Optimizing Treatment for Advanced HER2-Positive Upper GI Cancers
When a gastroesophageal tumor is positive for HER2, PD-L1, and claudin 18.2, which target should you treat first and how do you decide? On this episode of the BackTable GI Oncology Creator Weekend™, host Dr. Kate Baker interviews Dr. Geoffrey Buckle, a GI medical oncologist at UCSF, and Dr. Ronan Hsieh, a GI oncologist at Swedish Cancer Institute in Seattle, for a breakdown of therapy selection and management in advanced HER2-positive upper GI cancers. They start with a detailed case, covering biomarker workup, how to choose a first-line regimen without head-to-head data, and how to manage nutrition and palliative radiation when a patient presents with dysphagia and weight loss.
Timestamps
00:00 - Introduction
01:41 - Case Presentation and Biomarker Workup
05:07 - First-Line Treatment Selection
11:27 - Oligoprogressive Disease and Local Therapy
16:02 - HER2 Testing and Tumor Heterogeneity
20:19 - ctDNA in Upper GI Cancers
22:27 - HERIZON-GEA-01 and Zanidatamab
27:18 - Triplet Versus Doublet and Diarrhea Management
29:17 - Second-Line Therapy and Rebiopsy
32:33 - Trastuzumab Deruxtecan and Interstitial Lung Disease
36:33 - Later-Line Options and HER2-Low Disease
39:17 - Future Directions and Closing Remarks
Resources
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More about this episode
The conversation expands to interpreting equivocal HER2 results, tumor heterogeneity, and the importance of a second pathology review before committing to a treatment strategy. Dr. Hsieh explains how he approaches the HERIZON-GEA-01 trial data and the need to manage triplet therapy toxicity, especially diarrhea. The group discusses second-line rebiopsy to confirm HER2 status, the role of circulating tumor DNA (ctDNA), counseling and monitoring for interstitial lung disease on antibody-drug conjugates, and what to do for HER2 IHC 2+ FISH-negative tumors. They close with future directions, including trials moving HER2-directed therapies into earlier disease, the challenge of limited therapy lines, and why every line counts in this patient population.
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