Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 198

The DOI matches its Crossref record.

Optimal Immunohistochemical Markers For Distinguishing Lung Adenocarcinomas From Squamous Cell Carcinomas in Small Tumor Samples

Terry, Jefferson, Leung, Samuel, Laskin, Janessa, Leslie, Kevin O., Gown, Allen M., Ionescu, Diana N.·2010·American Journal of Surgical Pathology

Abstract

The histologic subtype of non-small cell lung carcinoma is important in selecting appropriate chemotherapy for patients with advanced disease. As many of these patients are not operative candidates, they are treated medically after biopsy for diagnosis. Inherent limitations of small biopsy samples can make distinguishing poorly differentiated lung adenocarcinoma (ADC) from squamous cell carcinoma (SCC) difficult. The value of histochemical and immunohistochemical markers to help separate poorly differentiated ADC from SCC in resection specimens is well established; however, the optimal use of markers in small tissue samples has only recently been examined and the correlation of marker expression in small tissue samples with histologic subtype determined on resection specimens has not been well documented. We address this issue by examining the expression of 9 markers (p63, TTF1, CK5/6, CK7, 34βE12, Napsin A, mucicarmine, NTRK1, and NTRK2) on 200 cases of ADC and 225 cases of SCC in tissue microarray format to mimic small tissue specimens. The single best marker to separate ADC from SCC is p63 (for SCC: sensitivity 84%, specificity 85%). Logistic regression analysis identifies p63, TTF1, CK5/6, CK7, Napsin A, and mucicarmine as the optimal panel to separate ADC from SCC. Reduction of the panel to p63, TTF1, CK5/6, and CK7 is marginally less effective but may be the best compromise when tissue is limited. We present an algorithm for the stepwise application of p63, TTF1, CK5/6, CK7, Napsin A, and mucicarmine in situations in which separation of ADC from SCC in small specimens cannot be accomplished by morphology alone.

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 · 10.1097/pas.0b013e3181f7dae3

Cites

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

Cited by

See all 198

Metadata

Authors
Terry, J., Leung, S., Laskin, J., Leslie, K. O., Gown, A. M., & Ionescu, D. N.
Venue
American Journal of Surgical Pathology
Published
2010-12
Volume
34
Issue
12
Pages
1805-1811
ISSN
0147-5185 (ISSN-L)
OpenAlex
W1973414121
Cited by
198
References
0
FWCI
20.17
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: Optimal Immunohistochemical Markers For Distinguishing Lung Adenocarcinomas From Squamous Cell Carcinomas in Small Tumor Samples. https://app.cochat.ai/papers/10.1097/pas.0b013e3181f7dae3
The paper
Terry, J., Leung, S., Laskin, J., Leslie, K. O., Gown, A. M., & Ionescu, D. N. (2010). Optimal Immunohistochemical Markers For Distinguishing Lung Adenocarcinomas From Squamous Cell Carcinomas in Small Tumor Samples. American Journal of Surgical Pathology. https://doi.org/10.1097/pas.0b013e3181f7dae3

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.