Genomic markers of panitumumab resistance including ERBB2/HER2 in a phase II study of KRAS wild-type (wt) metastatic colorectal cancer (mCRC)
Bibliographic record
Abstract
// Garrett S. Barry 1 , Maggie C. Cheang 2 , Hector Li Chang 1 , Hagen F. Kennecke 3 1 Department of Pathology and Laboratory Medicine, Faculty of Medicine, University of British Columbia, Vancouver, BC V6T 2B5, Canada 2 The Institute of Cancer Research, Sutton, London, Surrey SM2 5NG, United Kingdom 3 Medical Oncology, BC Cancer Agency, Vancouver, BC V5Z 4E6, Canada Correspondence to: Hagen F. Kennecke, e-mail: hkennecke@bccancer.bc.ca Keywords: mCRC, nanostring, ERBB2, HER2, EGFR inhibitor resistance Received: October 19, 2015 Accepted: January 29, 2016 Published: March 09, 2016 ABSTRACT A prospective study was conducted to identify biomarkers associated with resistance to panitumumab monotherapy in patients with metastatic colorectal cancer (mCRC). Patients with previously treated, codon 12/13 KRAS wt, mCRC were prospectively administered panitumumab 6 mg/kg IV q2weeks. Of 34 panitumumab-treated patients, 11 (32%) had progressive disease at 8 weeks and were classified as non-responders. A Nanostring nCounter-based assay identified a 5-gene expression signature ( ERBB2 , MLPH, IRX3 , MYRF , and KLK6 ) associated with panitumumab resistance ( P = 0.001). Immunohistochemistry and in situ hybridization determined that the HER2 ( ERBB2 ) protein was overexpressed in 4/11 non-responding and 0/21 responding cases ( P = 0.035). Two non-responding tumors had ERBB2 gene amplification only, and one demonstrated both ERBB2 amplification and mutation. A non-codon 12/13 KRAS mutation occurred in one panitumumab-resistant patient and was mutually exclusive with ERBB2 /HER2 abnormalities. This study identifies a 5-gene signature associated with non-response to single agent panitumumab, including a subgroup of non-responders with evidence of aberrant ERBB2/HER2 signaling. KRAS wt tumors resistant to EGFRi may be identified by gene signature analysis, and the HER2 pathway plays an important role in resistance to therapy.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".