Introduction: Microbes have, to date, been aetiologically linked ~16% of all cancers. However, major gaps remain in understanding the role of microbes and microbiomes in many cancers, including lung cancer (LC). We aimed to identify LC-associated microbial biomarkers in the Australian context that could offer novel approaches to diagnosis, treatment and potentially even prevention of LC. Method: We prospectively recruited adults with suspected LC undergoing bronchoscopy at the Sunshine Coast University Hospital, Queensland. LC site samples included: bronchoalveolar lavage (BAL); transbronchial lung biopsies (TBLBx); transbronchial nodal/tumour aspirates (TBNA); and BAL from contralateral lung and/or oral washes to act as controls. Microbial-enriched metagenomics was utilised to identify microbes associated with LC versus control samples. Results: To date, 29 participants with LC (13 adenocarcinoma; 8 squamous cell carcinoma; 3 small cell; and 4 non-small cell not otherwise specified), have provided 89 samples (29 LC-site BALs; 10 TBLB×; 8 TBNA; 29 contralateral lung BALs; and 13 oral washes). In the samples sequenced thus far (n = 31), Stenotrophomonas maltophilia (43×; 1-way ANOVA p = 3E-12) and Comamonas testosteroni (267×; p = 2.4E-11) were significantly more abundant in LC versus controls (n = 56). When comparing LC site (n = 17) versus contralateral (n = 12) BAL microbiomes, Klebsiella oxytoca, C. testosteroni, and S. maltophilia were 34×, 1.8× and 1.6× in LC, respectively; however, none demonstrated significance due to insufficient participant numbers. Notably, both our Australian and a prior American dataset identified K. oxytoca over-representation in LC specimens, suggesting a possible role of this gut commensal in LC. Contribution to research: Our findings provide the first insights into the microbes associated with LC in an Australian cohort, adding to the growing body of evidence of the ‘LC microbiome’. We are the first to examine the microbiome in small-cell LC. Further work is needed to uncover microbial differences between LC subtypes, and to determine cause versus correlation.