PURPOSE The human microbiome is increasingly recognized as a key modifier of carcinogenesis, immune regulation, and treatment response. In lung cancer, characterization of both respiratory and gut microbiomes offers opportunities to identify biomarkers and therapeutic targets. However, methodologic variability limits reproducibility and clinical translation. The objective was to systematically evaluate current microbiome testing methodologies in lung cancer, focusing on sequencing-based profiling and short-chain fatty acid (SCFA) analysis. METHODS A systematic search of PubMed, Scopus, and Web of Science identified human lung cancer studies (2014-2023) employing 16S rRNA gene sequencing, shotgun metagenomics, metatranscriptomics, or SCFA quantification. Eligible studies were assessed per PRISMA guidelines for design, analytic workflow, and key findings. RESULTS Eighty-seven studies met inclusion criteria. Most (86%) used 16S rRNA sequencing, primarily on bronchoalveolar lavage, bronchial brushings, or stool. Shotgun metagenomics (9%) provided higher taxonomic and functional resolution, while SCFA analysis (14%), mainly via gas chromatography-mass spectrometry or liquid chromatography-mass spectrometry, explored gut-lung interactions. Substantial heterogeneity was noted in DNA extraction, targeted 16S regions, sequencing platforms, and bioinformatic pipelines, complicating cross-study comparison. Across studies, lung cancer samples showed reduced alpha diversity and enrichment of taxa such as Streptococcus and Veillonella . SCFA studies suggested higher fecal butyrate and propionate levels were associated with favorable immunotherapy responses. CONCLUSION Methodologic inconsistency across microbiome testing platforms remains a major barrier to validation of microbial biomarkers in lung cancer. Standardized protocols for sampling, sequencing, and SCFA quantification are essential for reproducibility. Incorporating harmonized microbiome assays into immuno-oncology trials could improve biomarker reliability, refine patient stratification, and advance precision cancer care.
Kapoor et al. (Sun,) studied this question.