Tissue Microarray Analysis Reveals Heterogeneous Expression of Talin-1 and Lactate Dehydrogenase A in Non-Small Cell Lung Cancer: Implications for Biomarker Reliability

Background Tumour heterogeneity significantly impacts biomarker reliability in non-small cell lung cancer (NSCLC), complicating the validation of diagnostic proteins such as lactate dehydrogenase A (LDHA) and Talin-1. This study investigated their expression heterogeneity in tissue microarrays (TMAs) from 40 non-metastatic NSCLC cases (24 squamous cell carcinomas, 16 adenocarcinomas) and 10 normal controls, using standardised immunohistochemistry (IHC). Methods Formalin-fixed, paraffin-embedded (FFPE) TMAs were stained with anti-LDHA and anti-Talin-1 antibodies. Expression was scored (0–3) for intensity and analysed against tumour grade/stage. Results Normal tissues showed minimal reactivity (scores 0–1), while tumours exhibited marked heterogeneity. In adenocarcinomas, 20/32 cores (62.5%) showed moderate LDHA expression (score 2–3), predominantly in stage IIB/IIIA tumours. Talin-1 expression varied widely, with 14/32 (43.6%) adenocarcinoma cores scoring 2–3, with almost same IIIA/IIB stage ratio. Squamous cell carcinomas displayed greater inconsistency, with LDHA scores 2–3 in 34/48 cores (70.8%), and Talin-1 scored 2–3 in 12/48 (25%), the majority were in stage IIB/IIIA but no grade/stage correlation. Such findings demonstrate substantial intra- and inter-tumour heterogeneity for both biomarkers, independent of conventional clinicopathological parameters. This variability explains their inconsistent performance in prior studies and underscores the need for multiplexed biomarker panels to overcome heterogeneity-driven limitations. Conclusion Our findings reveal significant heterogeneity in LDHA and Talin-1 expression across NSCLC subtypes, independent of tumor grade/stage. This underscores the need for standardized IHC protocols and spatial profiling in biomarker development. The variability observed supports using multiplexed panels rather than single-marker approaches for reliable clinical applications.