Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 624

The DOI matches its Crossref record; 9 of the 9 references it cites were found in a registry or an index.

Molecular Predictors of Response to Epidermal Growth Factor Receptor Antagonists in Non–Small-Cell Lung Cancer

Sequist, Lecia V., Bell, Daphne W., Lynch, Thomas J., Haber, Daniel A.·2007·Journal of Clinical Oncology

Abstract

In the last 5 years the epidermal growth factor receptor (EGFR) has emerged as one of the most important targets for drug development in oncology. Monoclonal antibodies targeting the external domain of EGFR have been shown to have clinical benefit in colorectal and head and neck cancer when combined with chemotherapy and/or radiation. Small molecules that inhibit the tyrosine kinase (TK) domain of EGFR have become critical new weapons in the treatment of non–small-cell lung cancer (NSCLC). The discovery that mutations in the TK domain are associated with dramatic and sustained responses to EGFR TK inhibitors (TKIs) has allowed the design of trials to test these agents as potential first-line therapies and has provided a fascinating window into the future of genotype-directed targeted therapy. Recent advances in understanding the biologic basis of acquired resistance to these agents have great potential to improve the clinical effectiveness of this class of drugs. This review summarizes the biology of EGFR in NSCLC, the clinical and molecular predictors of benefit from treatment with EGFR TKIs, the use of patient-specific molecular profiling, and future directions of clinical and basic scientific research.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1200/jco.2006.07.3585

Cites

9 of 9 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Show all 9 references

Cited by

See all 624

Metadata

Authors
Sequist, L. V., Bell, D. W., Lynch, T. J., & Haber, D. A.
Venue
Journal of Clinical Oncology
Published
2007-02-10
Volume
25
Issue
5
Pages
587-595
ISSN
  • 0732-183X (ISSN-L)
  • 1527-7755
OpenAlex
W2005216767
Cited by
624
References
9
FWCI
57.55
Type
journal article
Language
en
Open access
closed

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: Molecular Predictors of Response to Epidermal Growth Factor Receptor Antagonists in Non–Small-Cell Lung Cancer. https://app.cochat.ai/papers/10.1200/jco.2006.07.3585
The paper
Sequist, L. V., Bell, D. W., Lynch, T. J., & Haber, D. A. (2007). Molecular Predictors of Response to Epidermal Growth Factor Receptor Antagonists in Non–Small-Cell Lung Cancer. Journal of Clinical Oncology. https://doi.org/10.1200/jco.2006.07.3585

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.