Automated chromogenic multiplexed immunohistochemistry assay for diagnosis and predictive biomarker testing in non-small cell lung cancer.

OBJECTIVES

The current challenge in the management of non-small cell lung cancer (NSCLC) in pathology laboratories is to combine immunohistochemistry (IHC) and molecular approaches on increasingly smaller biopsies and the need to reserve a fair amount of tumor material for molecular analyses with increasingly larger panels. The latest lung cancer classification, especially in the setting of poorly differentiated tumors, requires an IHC workup to allow for accurate diagnosis and also to preserve as much tissue as possible for molecular testing. Thus, it is recommended to reduce use of the term NSCLC not otherwise specified as much as possible and classify tumors according to their specific histologic subtype. This implies limiting the number of tissue slides despite the existence of specific and sensitive biomarkers (ALK, ROS1, BRAF V600E, PD-L1) and the obligation to distinguish lung adenocarcinoma (TTF-1 positive) from squamous cell carcinoma (p40 positive).

MATERIALS AND METHODS

Samples from 18 patients with NSCLC, previously characterized for histologic and genomic/immune features, were included. Two multiplexed IHC assays were developed, for diagnosis and immunophenotyping including TTF1, p40, PD-L1, and pan-Keratin antibodies, and for molecular profiling panel including ALK, ROS1 and BRAF V600E antibodies.

RESULTS

We developed two sensitive multiplexed IHC assays to comprehensively characterize major NSCLC histotypes and FDA-cleared predictive biomarkers, without antigenicity loss, steric interference or increased cross-reactivity. The assays rely on standard antigen retrieval and automated staining protocols, limiting the need for validation strategies.

CONCLUSION

Our multiplexed IHC approach provides a unique sample-sparing tool to characterize limited tissue samples in lung oncology and making it an alternative method in the clinical setting for therapeutic decision making of advanced NSCLC, provided that validation in a larger population is performed.