Molecular characterization of <i>ERBB2</i>-amplified colorectal cancer identifies potential mechanisms of resistance to targeted therapies: a report of two instructive cases
Bibliographic record
Abstract
ERBB2 amplification has been identified in ∼5% of KRAS wild-type colorectal cancers (CRCs). A recent clinical trial showed response to HER2-directed therapy in a subset of ERBB2-amplified metastatic CRCs resistant to chemotherapy and EGFR-directed therapy. With the aim of better understanding mechanisms of resistance to HER2-directed and EGFR-directed therapies, we report the complete molecular characterization of two cases of ERBB2-amplified CRC. PCR-free whole-genome sequencing was used to identify mutations, copy-number alterations, structural variations, and losses of heterozygosity. ERBB2 copy number was also measured by fluorescence in situ hybridization. Single-stranded mRNA sequencing was used for gene expression profiling. Immunohistochemistry and protein mass spectrometry were used to quantify HER2 protein expression. The cases showed ERBB2 copy number of 86 and 92, respectively. Both cases were immunohistochemically positive for HER2 according to CRC-specific scoring criteria. Fluorescence in situ hybridization and protein mass spectrometry corroborated significantly elevated ERBB2 copy number and abundance of HER2 protein. Both cases were microsatellite stable and without mutation of RAS pathway genes. Additional findings included altered expression of PTEN, MET, and MUC1 and mutation of PIK3CA. The potential effects of the molecular alterations on sensitivity to EGFR and HER2-directed therapies were discussed. Identification of ERBB2 amplification in CRC is necessary to select patients who may respond to HER2-directed therapy. An improved understanding of the molecular characteristics of ERBB2-amplified CRCs and their potential mechanisms of resistance will be useful for future research into targeted therapies and may eventually inform therapeutic decision-making.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".