Work

Elastase reduces background autofluorescence in ALK fluorescence in situ hybridization assays for lung cancers

Year: 2025

Type: article

Abstract: Anaplastic lymphoma kinase (ALK) inhibitors have been effective in treating non-small cell lung cancers (NSCLC) with ALK translocation. However, high background autofluorescence in lung tissues interferes with fluorescence in situ hybridization (FISH) assays, masking molecular probe signals and hindering data interpretation. To reduce autofluorescence, NSCLC tissue sections were treated with various proteases, including collagenase types I, II, IV, and elastase, to determine the most effective enzyme. We then conducted ALK break-apart FISH assays on 120 NSCLC samples comparing standard and novel pretreatment protocols. Elastase was identified as the most effective enzyme for reducing autofluorescence while preserving nuclear integrity. The elastase-based pretreatment enabled clear FISH signal detection in all cases, reducing the retest rate from 86.7% to 0%. Furthermore, two additional ALK translocated cases were detected with elastase pretreatment, which were indeterminable with pepsin treatment alone. This novel elastase pretreatment protocol addresses autofluorescence interference in lung tissues and can significantly improve the reliability of FISH assays for targeted therapy decisions. • Autofluorescence in lung tissue interferes with ALK fluorescence in situ hybridization (FISH) detection, leading to indeterminate results and retesting. • This study presents an elastase-based pretreatment protocol that significantly reduces autofluorescence while preserving nuclear morphology in NSCLC samples. • Optimizing elastase concentration improved FISH assay clarity, reducing the retest rate from 86.7% to 0%. • Two additional cases of ALK translocation were detected using elastase, which were previously indeterminate with standard pepsin pretreatment. • This novel protocol offers a practical solution to improve the diagnostic accuracy of ALK FISH assays, potentially enhancing targeted therapy decisions in clinical practice.

Source: Biomedical Journal

DOI: 10.1016/j.bj.2025.100840

Authors: Sheng-Chi Hsu, Tsai-Hsien Hung, Hsiao-Chun Wu, Kwai-Fong Ng, Tse-Ching Chen

Institutions: Chang Gung University, Chang Gung Memorial Hospital, Taoyuan Chang Gung Memorial Hospital, Linkou Chang Gung Memorial Hospital

Language: English

Topic: Lung Cancer Treatments and Mutations

Subfield: Pulmonary and Respiratory Medicine

Field: Medicine

Domain: Health Sciences

SDG: Good health and well-being

Open Access status: gold

Estimated APC paid: $2,700