[Algorithms for the diagnosis of lung tumors].
The pathologist must preserve as much material as possible for therapeutic testing when diagnosing lung cancer.
APA
Forest F (2026). [Algorithms for the diagnosis of lung tumors].. Annales de pathologie. https://doi.org/10.1016/j.annpat.2026.03.004
MLA
Forest F. "[Algorithms for the diagnosis of lung tumors].." Annales de pathologie, 2026.
PMID
41925435
Abstract
The pathologist must preserve as much material as possible for therapeutic testing when diagnosing lung cancer. The diagnosis of squamous cell carcinoma and adenocarcinoma may be possible morphologically but the morphology itself can be misleading. Thus, for the diagnosis of non-small cell carcinoma, anti-p40 and anti-TTF-1 immunohistochemistries are the cornerstone of tumor classification. Neuroendocrine marker testing is not recommended in the absence of neuroendocrine morphology. Regarding small cell carcinomas, in addition to the "classic" immunohistochemical markers, the anti-POU2F3 antibody can be useful if these markers are negative. For large cell neuroendocrine carcinomas, the anti-Rb antibody can be helpful in determining patient treatment, in conjunction with KRAS, STK11, and KEAP1mutation testing. Finally, clones of these antibodies can show different results in terms of sensitivity and specificity, which are discussed in this work.