Technical replicates and multiple sequencing approaches reveal weak and inconsistent microbiome signals in lung tumour and blood samples from patients with lung cancer

Abstract Background Unique bacterial profiles have been described in tumours, blood, and other low biomass samples. However, recent controversy has highlighted the challenges of utilising these microbiomes for cancer diagnosis and treatment. This work aims to characterise current challenges with low biomass samples and identify potential solutions for identifying robust bacterial biomarkers using lung cancer samples. Methods Samples from multiple body sites (lung cancer tumour, adjacent lung tissue, blood, and saliva) were collected from patients undergoing curative surgery for non-small cell lung cancer (NSCLC). DNA extracted from samples underwent a variety of molecular techniques, including full-length amplicon sequencing, nested amplicon sequencing, metagenomic sequencing (MGS), and digital PCR (dPCR). Microbiome profiles were analyzed by sample type, in duplicate, and in relation to controls. Results Full-length 16S gene sequencing failed to generate usable data for nearly all lung tumour, adjacent tissue, and blood samples. While nested short-read 16S sequencing successfully generated sequence data these samples contained very few taxa, exhibited substantial variability across replicates, and were compositionally indistinguishable from negative controls. In contrast, saliva and positive control samples showed high diversity and strong reproducibility. Absolute quantification by dPCR confirmed extremely low bacterial biomass in lung tumour, adjacent tissue, and blood samples, comparable to negative controls. Lastly, metagenomic sequencing of lung tumour, adjacent tissue, and blood samples detected very few taxa with minimal overlap with 16S data, whereas saliva and positive controls showed significant overlap of detected genera. Conclusions Current microbiome methodologies present challenges with samples of low microbial biomass, making it difficult to detect bacterial signals that are distinct or above levels found in collection and processing environments. Of concern is the lack of precision and reproducibility with samples of low microbial biomass. Technical replicates, alternative sequencing strategies, and absolute quantification of bacterial DNA should be used to confirm the reliability of microbiome sequencing data from low biomass samples. This study provides important insights into site-specific microbiomes from lung cancer patients and the challenges encountered when assessing the tumour microbiome.