Cited by 430Lung Cancer Treatments and MutationsCancer Genomics and DiagnosticsLung Cancer Diagnosis and Treatment

Multi-institutional oncogenic driver mutation analysis in lung adenocarcinoma: the lung cancer mutation consortium experience

Open access
Sholl, Lynette M., Aisner, Dara L., Varella-Garcia, Marileila, Berry, Lynne D., Dias-Santagata, Dora, Wistuba, Ignacio I., Chen, Heidi, Fujimoto, Junya +9 more·2015·Journal of Thoracic Oncology

Abstract

Introduction Molecular genetic analyses of lung adenocarcinoma have recently become standard of care for treatment selection. The Lung Cancer Mutation Consortium was formed to enable collaborative multi-institutional analyses of 10 potential oncogenic driver mutations. Technical aspects of testing and clinicopathologic correlations are presented.Methods Mutation testing in at least one of the eight genes (epidermal growth factor receptor [EGFR], KRAS, ERBB2, AKT1, BRAF, MEK1, NRAS, and PIK3CA) using SNaPshot, mass spectrometry, Sanger sequencing+/- peptide nucleic acid and/or sizing assays, along with anaplastic lymphoma kinase (ALK) and/or MET fluorescence in situ hybridization, were performed in six labs on 1007 patients from 14 institutions.Results In all, 1007 specimens had mutation analysis performed, and 733 specimens had all 10 genes analyzed. Mutation identification rates did not vary by analytic method. Biopsy and cytology specimens were inadequate for testing in 26% and 35% of cases compared with 5% of surgical specimens. Among the 1007 cases with mutation analysis performed, EGFR, KRAS, ALK, and ERBB2 alterations were detected in 22%, 25%, 8.5%, and 2.4% of cases, respectively. EGFR mutations were highly associated with female sex, Asian race, and never-smoking status; and less strongly associated with stage IV disease, presence of bone metastases, and absence of adrenal metastases. ALK rearrangements were strongly associated with never-smoking status and more weakly associated with presence of liver metastases. ERBB2 mutations were strongly associated with Asian race and never-smoking status. Two mutations were seen in 2.7% of samples, all but one of which involved one or more of PIK3CA, ALK, or MET.Conclusion Multi-institutional molecular analysis across multiple platforms, sample types, and institutions can yield consistent results and novel clinicopathological observations.

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 · 10.1097/jto.0000000000000516

Cites

41 of 41 references verified0 citation errors · 0 not checkable

Statistics

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

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Self-check

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

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

Cites

Flagged first, then by citations

Cited by

Sorted by citations

Authors
Sholl, L. M., Aisner, D. L., Varella-Garcia, M., Berry, L. D., Dias-Santagata, D., Wistuba, I. I., Chen, H., Fujimoto, J., Kugler, K., Franklin, W. A., Iafrate, A. J., Ladanyi, M., Kris, M. G., Johnson, B. E., Bunn, P. A., Minna, J. D., & Kwiatkowski, D. J.
Affiliations
  • Brigham and Women's Hospital (US)
  • University of Colorado Anschutz (US)
  • Vanderbilt University (US)
  • Harvard University (US)
  • The University of Texas MD Anderson Cancer Center (US)
  • Memorial Sloan Kettering Cancer Center (US)
  • University of Colorado Cancer Center (US)
  • The University of Texas Southwestern Medical Center (US)
Corresponding author
Kwiatkowski, David J.
Venue
Journal of Thoracic Oncology
Publisher
Elsevier BV
Published
2015-05
Volume
10
Issue
5
Pages
768-777
ISSN
1556-0864 (ISSN-L)
OpenAlex
W2009775937
Cited by
430
References
41
Citations by year
2026: 13 · 2025: 24 · 2024: 37 · 2023: 52 · 2022: 43 · 2021: 51 · 2020: 40 · 2019: 31 · 2018: 42 · 2017: 37 · 2016: 44 · 2015: 16
FWCI
36.39
Type
journal article
Language
en
Open access
Locations
  • Journal of Thoracic Oncology (publishedVersion)
  • PubMed (publishedVersion)
  • Europe PMC (PubMed Central) (acceptedVersion)
  • PubMed Central (acceptedVersion)
  • Digital Access to Scholarship at Harvard (DASH) (Harvard University) (submittedVersion, cc-by)
Funders
National Cancer Institute (RC2CA148394, P50CA090578, P50CA070907, P50CA058187, P30CA008748, P01CA120964, P30CA016672, P30CA046934)
Topics
  • Health Sciences › Medicine › Pulmonary and Respiratory Medicine › Lung Cancer Treatments and Mutations
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Cancer Research › Cancer Genomics and Diagnostics
  • Health Sciences › Medicine › Pulmonary and Respiratory Medicine › Lung Cancer Diagnosis and Treatment
Keywords
lung adenocarcinoma, driver mutations, EGFR mutation, KRAS mutation, ALK rearrangement, ERBB2 mutations, PIK3CA mutation, MET amplification, clinicopathological correlation
MeSH terms
Anaplastic Lymphoma Kinase, Adenocarcinoma, Adrenal Gland Neoplasms, Bone Neoplasms, Cooperative Behavior, DNA Mutational Analysis, Female, Humans, Liver Neoplasms, Lung Neoplasms, Male, Mutation, Neoplasm Staging, Genes, ras, Sex Factors, Smoking, Gene Rearrangement, Genes, erbB-2, Genes, erbB-1, Proto-Oncogene Proteins c-met, Phosphatidylinositol 3-Kinases, Receptor Protein-Tyrosine Kinases, Racial Groups, MAP Kinase Kinase 1, Proto-Oncogene Proteins B-raf, Proto-Oncogene Proteins c-akt, Class I Phosphatidylinositol 3-Kinases

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