Study of the Microenvironment of the Lung Flora in Female Lung Adenocarcinoma Patients: From Benign Lesions to Invasive Lung Adenocarcinoma

Study of the Microenvironment of the Lung Flora in Female Lung Adenocarcinoma Patients: From Benign Lesions to Invasive Lung Adenocarcinoma | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Study of the Microenvironment of the Lung Flora in Female Lung Adenocarcinoma Patients: From Benign Lesions to Invasive Lung Adenocarcinoma Cheng-Cheng Du, Da-Qian Sun, Yu-Xian Chen, Jing-Shuo Li, Hong Meng, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5232486/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 13 Feb, 2025 Read the published version in BMC Cancer → Version 1 posted 4 You are reading this latest preprint version Abstract Background: The number of female lung adenocarcinoma patients is increasing annually, but these patients are difficult to diagnose in the early stage without obvious clinical symptoms, leading to late-stage diagnoses and poor outcomes. Recent studies have shown that the lung microbiota is closely related to the occurrence and development of lung cancer, especially the characteristic changes in the lung microbiota of lung cancer patients, which opens a new research direction for the diagnosis and treatment of lung cancer. This study aimed to analyze the characteristics of the lung flora in different stages of female lung adenocarcinoma. Methods: 16S rRNA sequencing technology was used to analyze the alpha diversity, beta diversity, composition, and function of the pulmonary flora in female patients with benign lesions (n=7), adenocarcinoma in situ (n = 16), microinvasive adenocarcinoma (n = 31), and invasive adenocarcinoma (n = 25). Results: Progression to invasive lung adenocarcinoma is correlated with reduced alpha diversity in the lung flora. Compared with the other stages, only the invasive adenocarcinoma stage had significant differences in the beta diversity of the lung flora. At the phylum and genus levels, the abundance of major flora species decreased significantly as the disease progressed to the invasive adenocarcinoma stage, whereas the abundance of Bacillus spp. increased significantly. The abundance of phenotypes with mobile elements, biofilm-forming ability, oxidative stress tolerance, parthenogenetic anaerobic properties, and pathogenicity was significantly greater in invasive adenocarcinomas. The abundance of metabolic pathways was significantly lower in invasive adenocarcinomas. Conclusions: Invasive adenocarcinoma has a unique flora structure characterized by decreased flora diversity and abundance and an increase in specific flora (e.g., Bacillus). In terms of bacterial function, adaptability and pathogenicity increased, and metabolic pathway activity decreased. Female lung adenocarcinoma lung flora flora diversity 16S rRNA sequencing Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 1. Introduction The Global Cancer Data for 2022 released by the International Agency for Research on Cancer (IARC) of the World Health Organization show that lung cancer is the most common form of cancer worldwide, with high incidence and mortality [1]. The incidence of female patients has been increasing, which may be related to environmental exposure, occupation, and pollution, such as increased outdoor ambient air pollution and household use of solid fuels [2–5]. Lung adenocarcinoma is the most common type of lung cancer in women. Since most lung cancers are often diagnosed at advanced stages, their treatment outcomes and prognosis are usually poor, with five-year survival rates even lower than 20% [6]. Therefore, it is crucial to find more precise and individualized diagnostic and therapeutic measures. With the advancement of microbial testing technology, an increasing number of studies have revealed the close relationships between microbial communities and human health and disease [7, 8], especially the potential role of microorganisms in the development of cancer, which has received widespread attention [9]. Current studies suggest that there is a correlation between the lung flora and the intestinal flora (gut‒lung axis) [10, 11]. Most current flora studies focus on the intestinal flora, and few studies on the lung flora are directly related to the occurrence, development and treatment of lung cancer. In this study, 16S RNA sequencing was performed on postoperative samples to explore the diversity, composition and functional characteristics of the lung flora in female patients with different stages of lung cancer. The aim of this study was to reveal the role of the lung flora in the development of lung cancer and to identify potential biomarkers for the diagnosis and treatment of this disease. The results revealed that the lung flora is closely related to the development of lung cancer and that invasive lung adenocarcinoma has a unique floral structure. 2. Methods This study was approved by the Ethics Committee of Qilu Hospital (KYLL-2022(ZM)-1121) in accordance with the ethical guidelines of the Declaration of Helsinki, and all patients signed informed consent forms. The study enrolled seventy-nine adult females who underwent lobectomy or partial resection at our institution from October 2021 to October 2022. The inclusion criteria were as follows: (1) adult female; (2) primary lesion; (3) definite pathological diagnosis; (4) no known major risk factors for lung cancer; (5) no history of major chronic or infectious diseases; (6) no antibiotics 2 weeks prior to surgery; and (7) no prior antitumor therapy. The detailed process is shown in Figure 1. 2.1. Sample collection Samples were collected from lung tissue under sterile conditions. A normal lung tissue sample of approximately 1 cubic centimeter at least 3–5 cm from the edge of the tumor was collected. The samples were washed in PBS buffer to remove blood samples, impurities, and nonessential tissues. The treated samples were quickly transferred to 1.8 ml sterile freezer tubes, quickly frozen with liquid nitrogen, and sealed. 2.2. DNA extraction and sequencing Genomic DNA was extracted and verified for purity and integrity. The V3-V4 region of the 16S rRNA gene was amplified and sequenced via Illumina technology to yield high-quality data. 2.3. Data processing The sequencing data were subjected to quality control and clustering, operational taxonomic unit (OTU) clustering, and chimera removal. Species annotations were made against the SILVA database, and functional predictions were made via Integrated Microbial Genomes (IMG), Kyoto Encyclopedia of Genos and Genomes (KEGG), and Pathosystems Resource Integration Cancer (PATRIC). BugBase software and PICRUSt2 software were used to further analyze the phenotypic classification and metabolic pathways. 2.4. Statistical analysis Statistical analysis was performed via SPSS 21.0 software (IBM SPSS software, Armonk, New York). The Wilcoxon rank sum test was used to compare the alpha diversity index, beta diversity index, flora species abundance and functional abundance. p<0.05 was considered statistically significant. 3. Results 3.1. Patient characteristics A total of 79 lung tissue samples were collected in this study, which were categorized as follows: seven cases of benign diseased lung tissue (BD-L), including four cases of atypical adenomatoid hyperplasia, two cases of chronic inflammation and one case of sclerosing alveolar cell tumor. The remaining patients were diagnosed with the following types of lung tissue tumors: 16 patients with adenocarcinoma-in situ lung tissue (AIS-L), 31 patients with microinvasive adenocarcinoma-in-the-lung (MIA-L), and 25 patients with invasive adenocarcinoma-in-the-lung (IAC-L). The demographics, clinical characteristics, and pathologic types of the 79 female patients are summarized in Table 1. The median age of the population was 58 years. Forty-three patients were over 60 years old. Table 1. Characteristics of a cohort of 79 patients. Variable Total (n) Percentage (%) Age years, median (IQR) 58(29-76) ≥58 43 54.43% <58 36 45.57% Histology benign lesions 7 8.86% adenocarcinoma in situ 16 20.25% microinvasive adenocarcinoma 31 39.24% invasive adenocarcinoma 25 31.65% Location superior lobe of right lung 22 27.85% middle lobe of right lung 7 8.86% inferior lobe of right lung 17 21.52% superior lobe of left lung 24 30.38% inferior lobe of left lung 9 11.39% Stage at diagnosis (invasive adenocarcinoma) IA1 4 16.00% IA2 12 48.00% IA3 2 8.00% IB 1 4.00% IIA 4 16.00% IIB 1 4.00% IIIA 1 4.00% History of radiotherapy No 3.2. Sequence analysis results Through a strict quality control process, we screened 10,071,206 high-quality reads from 10,086,956 reads generated via preliminary sequencing. After further assembly and quality screening, we obtained 9,915,124 clean tags, which provided a solid data foundation for subsequent bioinformatics analysis. In the cluster analysis stage, we identified and excluded 1,513,843 chimeric tags and ultimately obtained 8,401,281 high-quality valid tags, accounting for 83.29% of the original reads. This high percentage validates the high-quality standard of our data and ensures the reliability of the study results. According to the abundance information of the OTUs, the overall characteristics of each grouped OTU were statistically summarized, as shown in Table 2. On the basis of the abundance information of the OTUs, we performed an exhaustive statistical summary and taxonomic identification of the microbial communities in our samples, including 9 phyla, 22 orders, 37 orders, 69 families, 101 genera, and 117 species, which provided a new perspective on the structure of the structure of lung microbial communities. Table 2. Statistical table of Tags data of lung tissues at different stages of development. Groups Total Tags Taxon Tags BD-L 778098 724891 AIS-L 1787994 1654026 MIA-L 3403861 3123250 IAC-L 2431328 1988212 Avg 106345 94814 Total Tags: the number of effective tags; Taxon Tags: the number of tags with species annotations; Singleton Tags: OUT with tags totaling 1 in all samples-filtered OUT; OTUs: the final number of OUTs obtained. 3.2.1. Alpha diversity analysis As a key indicator of the diversity of the sample flora, the value of the alpha diversity index directly reflects the richness and homogeneity of the flora. Specifically, the Chao1 and ACE indices were the key indicators for assessing the richness of the sample flora, whereas the Shannon and Simpson indices further synthesized the richness of the species and the uniformity of their distributions. Through the above four indicators, the microbial diversity of the samples in each group was detected, as shown in Table 3. Table 3. Alpha diversity index of lung tissue at different developmental stages. Alpha diversity index Chao1 index ACE index BD-L 343.49±37.75 354.14±32.28 AIS-L 333.24±44.92 339.44±44.49 MIA-L 324.58±45.51 332.19±43.96 IAC-L 225.22±42.30 231.68±39.00 Alpha diversity index Chao1 index ACE index The results revealed that the Chao1 and ACE indices gradually decreased during the gradual progression from benign lesions to invasive adenocarcinomas, whereas the Shannon and Simpson indices did not significantly change in the early stages of the lesions but significantly decreased in the invasive adenocarcinoma stage (Figure 2). According to the above results, the alpha diversity indices did not show significant intergroup differences in the progression from benign lesions to the stage of minimally invasive adenocarcinoma. However, when the disease progressed to the invasive adenocarcinoma stage, the significant decrease in the alpha diversity index (p < 0.001) suggested that patients with invasive adenocarcinoma may have experienced a significant reduction in the diversity of the lung flora. 3.2.2. Beta diversity analysis In this study, principal coordinate analysis (PCoA), the UniFrac distance index and the unweighted distance index were used to comprehensively evaluate the differences in bacterial community structure among lung samples at different disease stages. The UniFrac distance indices, which consider phylogenetic relationships and microbial population abundance, provide a quantitative comparison of microbial community features. The results of the PCoA analyses, as shown in Figure 3, illustrated sample variations from benign lesions to invasive adenocarcinomas. The samples from the benign, in situ, and minimally invasive stages presented considerable structural similarity, as indicated by their clustered distributions in the PCoA plots. In contrast, the flora structure characteristics of invasive adenocarcinoma samples were significantly different from those of the other lesion types on PCoA maps. The statistical significance of the differences in colony structure between the different lesion types was further confirmed by the Adonis test. In the unweighted UniFrac distance analysis, statistically significant differences in colony structure were observed only between adenocarcinoma in situ and minimally invasive adenocarcinoma (p = 0.026) and between minimally invasive adenocarcinoma and invasive adenocarcinoma (p = 0.001), whereas in the weighted UniFrac distance analysis, significant differences were observed only between minimally invasive adenocarcinoma and invasive adenocarcinoma (p = 0.001). The statistical results in Table 4 show that the microflora structure of invasive adenocarcinoma significantly changed, whereas the microflora structure of the other groups did not significantly differ. Table 4. A comparative analysis of the beta diversity of lung tissues at different developmental stages. Unifrac distance Diffs Df SumsOfSqs MeanSqs F R2 P Unweighted BD-L vs AIS-L 1 0.0806 0.0806 0.9565 0.0436 0.437 AIS-L vs MIA-L 1 0.1656 0.1656 1.9627 0.0418 0.026 MIA-L vs IAC-L 1 0.8562 0.8562 9.1184 0.1445 0.001 Weighted BD-L vs AIS-L 1 0 0 1.1798 0.0532 0.302 AIS-L vs MLA-L 1 0.0001 0.0001 2.1244 0.0451 0.075 MIA-L vs IAC-L 1 0.0004 0.0004 13.6337 0.2016 0.001 Taken together, these findings suggest that the lung flora structure of invasive adenocarcinoma is significantly different from that of other lesion types, whereas the differences in the flora structure among benign lesions, adenocarcinoma in situ, and microinvasive adenocarcinoma are not significant. 3.2.3. Species composition analysis This study utilized a species distribution stacked map to analyze the composition of the lung tissue flora, as depicted in Figure 4. We compared and analyzed the bacterial composition of lung adenocarcinoma at the phylum and genus levels. At the phylum level, the results revealed that the abundances of Proteobacteria, Firmicutes, and Bacteroidetes did not change significantly across the different stages of lung adenocarcinoma development (p>0.05). In addition, the species abundance of Actinobacteria remained relatively consistent in the early stages but decreased significantly in the aggressive adenocarcinoma stage (p0.05). In contrast, the genera Delftia (p<0.001), Agrobacterium (p<0.001), Caulobacter (p<0.001), Brevundimonas (p<0.01), Ralstonia (p<0.01) and Afipia (p<0.05) decreased significantly in the invasive adenocarcinoma stage but not in the early stage. Notably, the abundance of Bacillus spp. increased in invasive adenocarcinoma patients (p<0.05). Overall, the composition of the lung flora was similar between the groups, with the main difference being in species abundance. These distinctions became more pronounced as the disease transitioned to invasive adenocarcinoma, as detailed in Figure 5. 3.2.4. Functional analysis In this study, BugBase software was used to analyze the microbial phenotypic characteristics of different stages of lung adenocarcinoma, as shown in Figure 6(a). The analysis revealed that at the invasive adenocarcinoma stage, the number of microorganisms with mobile element-containing, biofilm-forming, facultatively anaerobic, oxidative stress-tolerant, and pathogenic characteristics significantly increased in invasive adenocarcinomas compared with early-stage lung adenocarcinomas. In contrast, the phenotypic abundance of the aerobic and anaerobic phenotypes was greatly reduced. In addition, PICRUSt2 software was used in this study to predict the functions of metabolic pathways in different stages of lung adenocarcinoma, as shown in Figure 6(b). The analysis revealed that with the progression of lung adenocarcinoma, the abundance of metabolic pathways generally decreased, especially in the stage of invasive adenocarcinoma. 4. Discussion In this study, we found that the pulmonary flora of invasive lung adenocarcinoma patients has significant characteristics in terms of species abundance, diversity, floral function, and metabolic pathways. Alpha diversity analyses revealed that the Chao1 and ACE indices declined as the lesions progressed from benign to invasive adenocarcinomas. This trend suggests that the abundance of the lung flora gradually decreases as lung adenocarcinoma progresses. Furthermore, the Shannon and Simpson indices remained stable in early lung adenocarcinoma but significantly declined during the invasive stage, which may be indicative of the negative impact of disease progression on the diversity of the bacterial flora. We hypothesized that reduced flora diversity may be associated with an increased risk of developing cancer. This hypothesis is supported by epidemiologic studies: repeated use of antibiotics increases the risk of lung cancer, suggesting that abnormal lung microflora may play a role in the development of lung cancer [12, 13]. Additionally, the lung microbiome is implicated in cancer progression, potentially by modulating metabolic pathways, dampening immune responses, and promoting inflammation [14]. Specifically, bacterial activation of inflammatory pathways releases proinflammatory cytokines that promote the proliferation of airway epithelial cells. In a long-term chronic inflammatory environment, this proliferation may promote aberrant cell transformation, increasing the potential risk of tumorigenesis [15–17]. These findings not only provide new insights into the relationship between the lung flora and lung cancer, but also provide new ideas and strategies for future diagnosis and treatment. Beta diversity analysis showed no statistically significant differences in microbial community structure between benign lesions, lung adenocarcinoma in situ and microinvasive lung adenocarcinoma. However, as the disease progresses to the invasive adenocarcinoma stage, beta diversity analysis clearly revealed significant changes in the structure of the lung microbiota, suggesting that the lung microbiota of patients with invasive adenocarcinoma has unique structural characteristics compared with other stages. These findings suggest that in the early stages of lung adenocarcinoma development, the lung flora may remain somewhat stable structurally. However, as the disease progresses further, especially in the stage of invasive adenocarcinoma, the structure of the lung flora undergoes significant changes, which may lead to an imbalance in the microbial community, and studies have pointed out that an imbalance in the microbial community in the organ is directly or indirectly linked to carcinogenesis processes [18, 19]. An imbalance in the microbial community affects an individual's susceptibility, which may lead to aberrant cell proliferation or tumor formation, including the modulation of the host's immune and inflammatory responses and the production of potentially oncogenic metabolites [16]. Species composition analysis revealed that, at the phylum level, major flora such as Proteobacteria, Firmicutes, and Bacteroidetes changed little during lung cancer development, with only the abundance of actinomycetes decreasing in patients with invasive adenocarcinoma. However, at the genus level, not all genera changed in the early stage of lung adenocarcinoma development (from benign lesions to minimally invasive adenocarcinomas). The abundance of some genera was significantly reduced only during the development of invasive adenocarcinomas, and only the abundance of Bacillus was significantly increased in invasive adenocarcinomas, which may be related to the antitumor response of the organism [20, 21]. Different subgroups of the genus Bacillus and their metabolites show great potential for application in lung cancer therapy and may become new therapeutic targets in the future. To inhibit the growth, development and metastasis of cancer cells, organisms may promote the colonization and proliferation of beneficial flora while suppressing potentially harmful flora, thereby dynamically adjusting the composition and distribution of the lung microbiota. For example, Yu et al. [22] sequenced the bacterial flora in lung tissue samples from 165 lung cancer patients and reported that the composition of the lung flora was different from that of other parts of the body (e.g., the oral and nasal cavities), with a predominantly Aspergillus phylum, which was consistent with the results of the present study. At different stages of lung cancer progression, the lungs present characteristic dominant genera that may be involved in the process of lung cancer development or progression. These floras not only are important for the study of oncogenic or procarcinogenic mechanisms of the lung flora but can also be used as new biomarkers or biological targets for the diagnosis and treatment of lung cancer. Functional composition alterations, especially the increase in bacterial phenotypes with mobile elements, biofilm-forming capabilities, and oxidative stress tolerance in invasive adenocarcinoma, suggest an adaptive microbial response to the cancer microenvironment. These characteristics are closely related to the adaptation and survival of bacteria in the lung cancer microenvironment: the presence of mobile elements may accelerate the adaptability of bacteria in the tumor microenvironment, allowing bacteria to improve their survival in the changing environment [23]. The formation of biofilms provides an effective protective mechanism for bacteria, allowing them to withstand a variety of adverse conditions, including antibiotic treatment [24]. The oxidative stress tolerance of bacteria allows them to survive in the lung cancer microenvironment, which is full of oxidative stress [25]. In addition, the increased abundance of bacteria with pathogenic phenotypes in invasive adenocarcinomas may indicate an increased pathogenic potential of the lung flora during disease progression. Moreover, we detected a decrease in the abundance of aerobic and anaerobic flora and an increase in the abundance of facultative anaerobic flora in invasive adenocarcinomas. Facultative anaerobic bacteria may be better adapted to changes in metabolic and oxidative stress in the lung cancer environment. At the pathway level, we observed an overall decrease in pathway abundance with lung adenocarcinoma progression. This decline may be associated with a decrease in the diversity of the lung flora, suggesting that tumor progression may negatively affect the metabolic function of the lung microbiome. This study revealed an association between the diversity of the lung flora and lung cancer, but due to time factors, the sample size was limited and may have affected the statistical significance of the findings. Future studies should increase the sample size and use better analytical techniques to overcome these problems. A comprehensive examination of the lung microbiome has the potential to increase the efficacy of diagnosing and treating lung adenocarcinoma in women. By analyzing changes in microbial community composition, we can identify microbial species or metabolites associated with the development and progression of lung adenocarcinoma. These indicators of microbial changes are expected to serve as markers for early diagnosis, which will facilitate the efficient screening of high-risk women and early intervention. These research advances not only provide new insights into the link between lung microbiology and lung adenocarcinoma, but also contribute to the development of new diagnostic strategies and therapeutic approaches. 5. Conclusion Invasive adenocarcinoma has a unique flora structure characterized by decreased flora diversity and abundance and an increase in specific flora (e.g., Bacillus). In terms of bacterial function, adaptability and pathogenicity increased and metabolic pathway activity decreased. These changes are closely associated with the pathological progression of lung adenocarcinoma and may serve as potential biomarkers for diagnosis and treatment. This study provides potential targets for the development of microbiota-based diagnostic tools that can contribute to the development of personalized therapeutic strategies to improve treatment efficacy and patient quality of life. Declarations Ethics approval and consent to participate: This study was approved by the Institutional Animal Care and Use Committee (KYLL-2022(ZM)-1121), and all experiments were performed according to animal care guidelines. Consent for publication: Written informed consent for publication has been obtained. Availability of data and materials: All data generated or analysed during this study are included in this published article [and its supplementary information files]. Competing interests: The authors declare that they have no competing interests Funding: Natural Science Foundation of Shandong Province (grant number ZR2023QH328) and Shanghai Aitrox Technology Corporation Limited, Shanghai, PR China (Contract No. 6010124020) Authors' contributions ： Conceptualization, Chengcheng Du; Data curation, Jingshuo Li; Formal analysis, Yuxian Chen; Funding acquisition, Fanlei Kong; Investigation, Yuxian Chen; Methodology, Daqian Sun; Project administration, Chunhai Li and Fanlei Kong; Resources, Jingshuo Li; Software, Daqian Sun; Supervision, Hong Meng; Validation, Daqian Sun; Visualization, Chengcheng Du; Writing – original draft, Chengcheng Du; Writing – review & editing, Hong Meng. Acknowledgements ： We would like to thank Dr. Hui Tian, Dr. Guo-Tao Yang, and Dr. Xi-Bo Li from Department of Chest surgery, Qilu Hospital, for their contributions to the technical support of thoracic surgery; Dr. Shu-Xin Yan from the Department of Pathology, Qilu Hospital, for their help in pathological specimen making; and Dr. Hai-Peng Jia, Dr. Tian-Xiao Yao, and Dr. Bo Liu from the Department of Minimally Invasive Tumor Intervention, Qilu Hospital, for his help in proofreading. References Bray F, Laversanne M, Sung H, et al. Global cancer statistics 2022: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin . 2024;74(3):229-263. Fidler-Benaoudia MM, Torre LA, Bray F, Ferlay J, Jemal A. Lung cancer incidence in young women vs. young men: A systematic analysis in 40 countries. Int J Cancer . 2020;147(3):811-819. Jemal A, Miller KD, Ma J, et al. Higher Lung Cancer Incidence in Young Women Than Young Men in the United States. 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Int Immunopharmacol . 2023;120:110322. Yu G, Gail MH, Consonni D, et al. Characterizing human lung tissue microbiota and its relationship to epidemiological and clinical features. Genome Biol . 2016;17(1):163. Durrant MG, Li MM, Siranosian BA, Montgomery SB, Bhatt AS. A Bioinformatic Analysis of Integrative Mobile Genetic Elements Highlights Their Role in Bacterial Adaptation. Cell Host Microbe . 2020;27(1):140-153.e9. Paula AJ, Hwang G, Koo H. Dynamics of bacterial population growth in biofilms resemble spatial and structural aspects of urbanization. Nat Commun . 2020;11(1):1354. Zhu M, Dai X. Maintenance of translational elongation rate underlies the survival of Escherichia coli during oxidative stress. Nucleic Acids Res . 2019;47(14):7592-7604. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 13 Feb, 2025 Read the published version in BMC Cancer → Version 1 posted Editorial decision: Revision requested 14 Oct, 2024 Editor assigned by journal 09 Oct, 2024 Submission checks completed at journal 09 Oct, 2024 First submitted to journal 09 Oct, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-5232486","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":365606481,"identity":"d38828e7-9a57-4fd3-aa09-e58efc8ae5ed","order_by":0,"name":"Cheng-Cheng Du","email":"","orcid":"","institution":"Qilu Hospital of Shandong University","correspondingAuthor":false,"prefix":"","firstName":"Cheng-Cheng","middleName":"","lastName":"Du","suffix":""},{"id":365606483,"identity":"4b5e5c4b-4c4a-47ba-b4a8-a370b52e777f","order_by":1,"name":"Da-Qian Sun","email":"","orcid":"","institution":"Qilu Hospital of Shandong University","correspondingAuthor":false,"prefix":"","firstName":"Da-Qian","middleName":"","lastName":"Sun","suffix":""},{"id":365606485,"identity":"174c6672-89fd-49b1-bb17-d428fdbca359","order_by":2,"name":"Yu-Xian Chen","email":"","orcid":"","institution":"Qilu Hospital of Shandong University","correspondingAuthor":false,"prefix":"","firstName":"Yu-Xian","middleName":"","lastName":"Chen","suffix":""},{"id":365606488,"identity":"3bbd20dc-a3d3-43a7-8193-102e7ac8c40c","order_by":3,"name":"Jing-Shuo Li","email":"","orcid":"","institution":"Qilu Hospital of Shandong University","correspondingAuthor":false,"prefix":"","firstName":"Jing-Shuo","middleName":"","lastName":"Li","suffix":""},{"id":365606490,"identity":"37667bf1-ae31-448a-ae8f-7236195c994a","order_by":4,"name":"Hong Meng","email":"","orcid":"","institution":"Qilu Hospital of Shandong University","correspondingAuthor":false,"prefix":"","firstName":"Hong","middleName":"","lastName":"Meng","suffix":""},{"id":365606492,"identity":"8960e57a-a38c-456d-8862-57baadd879be","order_by":5,"name":"Chun-Hai Li","email":"","orcid":"","institution":"Qilu Hospital of Shandong University","correspondingAuthor":false,"prefix":"","firstName":"Chun-Hai","middleName":"","lastName":"Li","suffix":""},{"id":365606493,"identity":"0a346367-6521-4a0a-be7e-fc3e59c5a151","order_by":6,"name":"Fan-Lei Kong","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA7UlEQVRIiWNgGAWjYBACCRBRwcAgw8DMfMCAeC1nGBh4GJjZEkjVwsBDnA4Gyfbewy8O1Nzh4Wfn+VD4M8cmj5+B+eGjG3i0SPOcS7M4cOwZj2Qz7wZj3m1pxZINbMbGOXi0yEnkmBl/YDvMY3AYqIVx2+HEDQd42KQJaTE48O8wj/1hngeGP4Fa9hPSIi2RY/zgYBvQFmYeBgNekC0MBLRI9pwxYzjYd5hH4jCbAcgviTMOE/CLxPEe4w8Hvh2W4+8//AzoMJvE/vbmh4/xaQECNgkYAxIxzPiVg5V8gDEeEFY8CkbBKBgFIxEAAGKVS3lEW0l6AAAAAElFTkSuQmCC","orcid":"","institution":"Qilu Hospital of Shandong University","correspondingAuthor":true,"prefix":"","firstName":"Fan-Lei","middleName":"","lastName":"Kong","suffix":""}],"badges":[],"createdAt":"2024-10-09 12:23:11","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5232486/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5232486/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s12885-024-13385-1","type":"published","date":"2025-02-13T15:57:36+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":71539149,"identity":"4c076786-bb7d-4ea0-b34b-49e1d143b6c6","added_by":"auto","created_at":"2024-12-16 14:24:46","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":585311,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFlow chart of this study.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"Figure.1.tiff.jpg","url":"https://assets-eu.researchsquare.com/files/rs-5232486/v1/e05e52e8956880d0c259cc9c.jpg"},{"id":71539954,"identity":"5615073b-0300-4b09-b29f-0f84d565ef21","added_by":"auto","created_at":"2024-12-16 14:32:46","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":478361,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eComparison of Alpha diversity.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe horizontal coordinate indicates the lung tissue samples at different stages, and the vertical coordinate indicates the α diversity index size. ***: p \u0026lt; 0.001, ns: no statistically significant difference. (a)-(d): Chao1 index, ACE index, Shannon index and Simpson index showed that the alpha diversity index decreased significantly only when the lesions developed to the invasive adenocarcinoma stage, and there was no significant difference in the alpha index at other stages.\u003c/p\u003e","description":"","filename":"Figure.2.tiff.jpg","url":"https://assets-eu.researchsquare.com/files/rs-5232486/v1/9b2bdc60701266ef8b5992d3.jpg"},{"id":71539145,"identity":"6cdfde95-3dfe-45d8-a1fd-3175a909dea0","added_by":"auto","created_at":"2024-12-16 14:24:46","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":304058,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eComparison of Beta diversity.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(a). Unweighted Unifrac PCoA Scatterplot. (b). Weighted Unifrac PCoA Scatterplot. Each point in the figure represents a sample, and different colored points represent different sample groups. The closer the distance between the points, the more similar the structure of the flora between the two samples. PCoA assesses the degree to which each axis explains the overall differences in colony structure in terms of percentages (numbers in parentheses in the axes' headings). As shown in figure, benign lesions, in situ adenocarcinomas and microinvasive adenocarcinomas showed obvious aggregation, while invasive adenocarcinomas were independent of other lesions, whether weighted or unweighted.\u003c/p\u003e","description":"","filename":"Figure.3.tiff.jpg","url":"https://assets-eu.researchsquare.com/files/rs-5232486/v1/811e0c659cdb64c8caeb7302.jpg"},{"id":71539154,"identity":"0d088a58-a749-4742-9cc8-5b742724575f","added_by":"auto","created_at":"2024-12-16 14:24:46","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":575093,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSpecies composition of flora.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(a). Phylum horizontal species distribution stack map. The main species were Proteobacteria, Firmicutes, and Bacteroidetes, Actinobacteria in order of abundance. (b). Genus horizontal species distribution stack map. The top ten species were: Stenotrophomonas, Pseudomonas, Acinetobacter, Delftia, Brevundimonas, Bacillus, Ralstonia, Bergeyella, Pedobacter, Agrobacterium.\u003c/p\u003e","description":"","filename":"Figure.4.tif.jpg","url":"https://assets-eu.researchsquare.com/files/rs-5232486/v1/3206e91de8e4cdac300753d3.jpg"},{"id":71539953,"identity":"26ab4fb1-347f-4369-bd96-3cdbd580c74b","added_by":"auto","created_at":"2024-12-16 14:32:46","extension":"jpg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":588699,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eComparison of flora species abundance.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSpecies on the horizontal axis and species abundance on the vertical axis. *: p \u0026lt; 0.05, **: p \u0026lt; 0.01, ***: p \u0026lt; 0.001, ns: There was no statistical significance. (a). At the phylum level, only actinomycetes showed a significant reduction in species abundance in invasive adenocarcinomas(p＜0.001). (b)-(d). At the genus level, species abundences of Delftia(p＜0.001), Agrobacterium(p＜0.001), Caulobacter(p＜0.001), Brevundimonas(p＜0.01), Ralstonia(p＜0.01) and Afipia(p＜0.05) all decreased significantly in the development of invasive lung adenocarcinoma, while only the abundences of Bacillus(p＜0.05) increased significantly in invasive lung adenocarcinoma.\u003c/p\u003e","description":"","filename":"Figure.5.tif.jpg","url":"https://assets-eu.researchsquare.com/files/rs-5232486/v1/6f371a35714a507948357d41.jpg"},{"id":71539955,"identity":"db032501-6934-4632-9fe5-77194e69bdb1","added_by":"auto","created_at":"2024-12-16 14:32:46","extension":"jpg","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":404403,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eLung tissue function analysis.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(a). Heatmap of phenotypic abundance. The phenotypic information of species was classified into Aerobic, Anaerobic, Mobile Element Containing, Facultatively anaerobic, Biofilm Forming, Gram Positive, Gram Negative, Pathogenic, Oxidative Stress Tolerant. Among them, the phenotype of the species with mobile elements, Biofilm Forming, Facultatively anaerobic, Oxidative Stress Tolerant and pathogenicity were significantly increased. (b). Heatmap of metabolic pathway abundance. With the progression of the disease, the overall metabolic pathway abundance showed a gradually decreasing trend, especially in invasive lung adenocarcinoma.\u003c/p\u003e","description":"","filename":"Figure.6.tif.jpg","url":"https://assets-eu.researchsquare.com/files/rs-5232486/v1/fa2886aa9b4bec992c7b8154.jpg"},{"id":76487504,"identity":"1bbf314d-8342-40b9-866b-c8a10a8d8157","added_by":"auto","created_at":"2025-02-17 16:08:19","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3707390,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5232486/v1/0a94915a-fc2f-48d4-9f4d-8f3aff4b2d71.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Study of the Microenvironment of the Lung Flora in Female Lung Adenocarcinoma Patients: From Benign Lesions to Invasive Lung Adenocarcinoma","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eThe Global Cancer Data for 2022 released by the International Agency for Research on Cancer (IARC) of the World Health Organization show that lung cancer is the most common form of cancer worldwide, with high incidence and mortality [1]. The incidence of female patients has been increasing, which may be related to environmental exposure, occupation, and pollution, such as increased outdoor ambient air pollution and household use of solid fuels [2\u0026ndash;5].\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eLung adenocarcinoma is the most common type of lung cancer in women. Since most lung cancers are often diagnosed at advanced stages, their treatment outcomes and prognosis are usually poor, with five-year survival rates even lower than 20% [6]. Therefore, it is crucial to find more precise and individualized diagnostic and therapeutic measures. With the advancement of microbial testing technology, an increasing number of studies have revealed the close relationships between microbial communities and human health and disease [7, 8], especially the potential role of microorganisms in the development of cancer, which has received widespread attention [9]. Current studies suggest that there is a correlation between the lung flora and the intestinal flora (gut‒lung axis) [10, 11]. Most current flora studies focus on the intestinal flora, and few studies on the lung flora are directly related to the occurrence, development and treatment of lung cancer.\u003c/p\u003e\n\u003cp\u003eIn this study, 16S RNA sequencing was performed on postoperative samples to explore the diversity, composition and functional characteristics of the lung flora in female patients with different stages of lung cancer. The aim of this study was to reveal the role of the lung flora in the development of lung cancer and to identify potential biomarkers for the diagnosis and treatment of this disease. The results revealed that the lung flora is closely related to the development of lung cancer and that invasive lung adenocarcinoma has a unique floral structure.\u003c/p\u003e"},{"header":"2.\tMethods ","content":"\u003cp\u003eThis study was approved by the Ethics Committee of Qilu Hospital (KYLL-2022(ZM)-1121) in accordance with the ethical guidelines of the Declaration of Helsinki, and all patients signed informed consent forms. The study enrolled seventy-nine adult females who underwent lobectomy or partial resection at our institution from October 2021 to October 2022. The inclusion criteria were as follows: (1) adult female; (2) primary lesion; (3) definite pathological diagnosis; (4) no known major risk factors for lung cancer; (5) no history of major chronic or infectious diseases; (6) no antibiotics 2 weeks prior to surgery; and (7) no prior antitumor therapy. The detailed process is shown in Figure 1.\u003c/p\u003e\n\u003cp\u003e2.1.\u0026nbsp; \u0026nbsp;\u0026nbsp;Sample collection\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eSamples were collected from lung tissue under sterile conditions. A normal lung tissue sample of approximately 1 cubic centimeter at least 3\u0026ndash;5 cm from the edge of the tumor was collected. The samples were washed in PBS buffer to remove blood samples, impurities, and nonessential tissues. The treated samples were quickly transferred to 1.8 ml sterile freezer tubes, quickly frozen with liquid nitrogen, and sealed.\u003c/p\u003e\n\u003cp\u003e2.2.\u0026nbsp; \u0026nbsp;\u0026nbsp;DNA extraction and sequencing\u003c/p\u003e\n\u003cp\u003eGenomic DNA was extracted and verified for purity and integrity. The V3-V4 region of the 16S rRNA gene was amplified and sequenced via Illumina technology to yield high-quality data.\u003c/p\u003e\n\u003cp\u003e2.3.\u0026nbsp; \u0026nbsp;\u0026nbsp;Data processing\u003c/p\u003e\n\u003cp\u003eThe sequencing data were subjected to quality control and clustering, operational taxonomic unit (OTU) clustering, and chimera removal. Species annotations were made against the SILVA database, and functional predictions were made via Integrated Microbial Genomes (IMG), Kyoto Encyclopedia of Genos and Genomes (KEGG), and Pathosystems Resource Integration Cancer (PATRIC). BugBase software and PICRUSt2 software were used to further analyze the phenotypic classification and metabolic pathways.\u003c/p\u003e\n\u003cp\u003e2.4.\u0026nbsp; \u0026nbsp;\u0026nbsp;Statistical analysis\u003c/p\u003e\n\u003cp\u003eStatistical analysis was performed via SPSS 21.0 software (IBM SPSS software, Armonk, New York). The Wilcoxon rank sum test was used to compare the alpha diversity index, beta diversity index, flora species abundance and functional abundance. p\u0026lt;0.05 was considered statistically significant.\u003c/p\u003e"},{"header":"3.\tResults ","content":"\u003cp\u003e3.1. \u0026nbsp; \u0026nbsp;Patient characteristics\u003c/p\u003e\n\u003cp\u003eA total of 79 lung tissue samples were collected in this study, which were categorized as follows: seven cases of benign diseased lung tissue (BD-L), including four cases of atypical adenomatoid hyperplasia, two cases of chronic inflammation and one case of sclerosing alveolar cell tumor. The remaining patients were diagnosed with the following types of lung tissue tumors: 16 patients with adenocarcinoma-in situ lung tissue (AIS-L), 31 patients with microinvasive adenocarcinoma-in-the-lung (MIA-L), and 25 patients with invasive adenocarcinoma-in-the-lung (IAC-L). The demographics, clinical characteristics, and pathologic types of the 79 female patients are summarized in Table 1. The median age of the population was 58 years. Forty-three patients were over 60 years old.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 1. \u0026nbsp; Characteristics of a cohort of 79 patients.\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"524\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 175px;\"\u003e\n \u003cp\u003eVariable\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 175px;\"\u003e\n \u003cp\u003eTotal (n)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 175px;\"\u003e\n \u003cp\u003ePercentage (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 175px;\"\u003e\n \u003cp\u003eAge years, median (IQR) 58(29-76)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 175px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 175px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 175px;\"\u003e\n \u003cp\u003e\u0026ge;58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 175px;\"\u003e\n \u003cp\u003e43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 175px;\"\u003e\n \u003cp\u003e54.43%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 175px;\"\u003e\n \u003cp\u003e\u0026lt;58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 175px;\"\u003e\n \u003cp\u003e36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 175px;\"\u003e\n \u003cp\u003e45.57%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 175px;\"\u003e\n \u003cp\u003eHistology\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 175px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 175px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 175px;\"\u003e\n \u003cp\u003ebenign lesions\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 175px;\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 175px;\"\u003e\n \u003cp\u003e8.86%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 175px;\"\u003e\n \u003cp\u003eadenocarcinoma in situ\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 175px;\"\u003e\n \u003cp\u003e16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 175px;\"\u003e\n \u003cp\u003e20.25%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 175px;\"\u003e\n \u003cp\u003emicroinvasive adenocarcinoma\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 175px;\"\u003e\n \u003cp\u003e31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 175px;\"\u003e\n \u003cp\u003e39.24%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 175px;\"\u003e\n \u003cp\u003einvasive adenocarcinoma\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 175px;\"\u003e\n \u003cp\u003e25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 175px;\"\u003e\n \u003cp\u003e31.65%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 175px;\"\u003e\n \u003cp\u003eLocation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 175px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 175px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 175px;\"\u003e\n \u003cp\u003esuperior lobe of right lung\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 175px;\"\u003e\n \u003cp\u003e22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 175px;\"\u003e\n \u003cp\u003e27.85%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 175px;\"\u003e\n \u003cp\u003emiddle lobe of right lung\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 175px;\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 175px;\"\u003e\n \u003cp\u003e8.86%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 175px;\"\u003e\n \u003cp\u003einferior lobe of right lung\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 175px;\"\u003e\n \u003cp\u003e17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 175px;\"\u003e\n \u003cp\u003e21.52%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 175px;\"\u003e\n \u003cp\u003esuperior lobe of left lung\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 175px;\"\u003e\n \u003cp\u003e24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 175px;\"\u003e\n \u003cp\u003e30.38%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 175px;\"\u003e\n \u003cp\u003einferior lobe of left lung\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 175px;\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 175px;\"\u003e\n \u003cp\u003e11.39%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" style=\"width: 349px;\"\u003e\n \u003cp\u003eStage at diagnosis (invasive adenocarcinoma)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 175px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 175px;\"\u003e\n \u003cp\u003eIA1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 175px;\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 175px;\"\u003e\n \u003cp\u003e16.00%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 175px;\"\u003e\n \u003cp\u003eIA2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 175px;\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 175px;\"\u003e\n \u003cp\u003e48.00%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 175px;\"\u003e\n \u003cp\u003eIA3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 175px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 175px;\"\u003e\n \u003cp\u003e8.00%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 175px;\"\u003e\n \u003cp\u003eIB\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 175px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 175px;\"\u003e\n \u003cp\u003e4.00%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 175px;\"\u003e\n \u003cp\u003eIIA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 175px;\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 175px;\"\u003e\n \u003cp\u003e16.00%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 175px;\"\u003e\n \u003cp\u003eIIB\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 175px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 175px;\"\u003e\n \u003cp\u003e4.00%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 175px;\"\u003e\n \u003cp\u003eIIIA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 175px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 175px;\"\u003e\n \u003cp\u003e4.00%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 175px;\"\u003e\n \u003cp\u003eHistory of radiotherapy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 175px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 175px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 175px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 175px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 175px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e3.2. \u0026nbsp; \u0026nbsp;Sequence analysis results\u003c/p\u003e\n\u003cp\u003eThrough a strict quality control process, we screened 10,071,206 high-quality reads from 10,086,956 reads generated via preliminary sequencing. After further assembly and quality screening, we obtained 9,915,124 clean tags, which provided a solid data foundation for subsequent bioinformatics analysis. In the cluster analysis stage, we identified and excluded 1,513,843 chimeric tags and ultimately obtained 8,401,281 high-quality valid tags, accounting for 83.29% of the original reads. This high percentage validates the high-quality standard of our data and ensures the reliability of the study results. According to the abundance information of the OTUs, the overall characteristics of each grouped OTU were statistically summarized, as shown in Table 2. On the basis of the abundance information of the OTUs, we performed an exhaustive statistical summary and taxonomic identification of the microbial communities in our samples, including 9 phyla, 22 orders, 37 orders, 69 families, 101 genera, and 117 species, which provided a new perspective on the structure of the structure of lung microbial communities.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2. \u0026nbsp; Statistical table of Tags data of lung tissues at different stages of development.\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" align=\"\" width=\"524\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 175px;\"\u003e\n \u003cp\u003eGroups\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 175px;\"\u003e\n \u003cp\u003eTotal Tags\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 175px;\"\u003e\n \u003cp\u003eTaxon Tags\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 175px;\"\u003e\n \u003cp\u003eBD-L\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 175px;\"\u003e\n \u003cp\u003e778098\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 175px;\"\u003e\n \u003cp\u003e724891\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 175px;\"\u003e\n \u003cp\u003eAIS-L\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 175px;\"\u003e\n \u003cp\u003e1787994\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 175px;\"\u003e\n \u003cp\u003e1654026\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 175px;\"\u003e\n \u003cp\u003eMIA-L\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 175px;\"\u003e\n \u003cp\u003e3403861\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 175px;\"\u003e\n \u003cp\u003e3123250\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 175px;\"\u003e\n \u003cp\u003eIAC-L\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 175px;\"\u003e\n \u003cp\u003e2431328\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 175px;\"\u003e\n \u003cp\u003e1988212\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 175px;\"\u003e\n \u003cp\u003eAvg\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 175px;\"\u003e\n \u003cp\u003e106345\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 175px;\"\u003e\n \u003cp\u003e94814\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eTotal Tags: the number of effective tags; Taxon Tags: the number of tags with species annotations; Singleton Tags: OUT with tags totaling 1 in all samples-filtered OUT; OTUs: the final number of OUTs obtained.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e3.2.1. \u0026nbsp; Alpha diversity analysis\u003c/p\u003e\n\u003cp\u003eAs a key indicator of the diversity of the sample flora, the value of the alpha diversity index directly reflects the richness and homogeneity of the flora. Specifically, the Chao1 and ACE indices were the key indicators for assessing the richness of the sample flora, whereas the Shannon and Simpson indices further synthesized the richness of the species and the uniformity of their distributions. Through the above four indicators, the microbial diversity of the samples in each group was detected, as shown in Table 3.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3.\u003c/strong\u003e\u0026nbsp; \u003cstrong\u003eAlpha diversity index of lung tissue at different developmental stages.\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" align=\"\" width=\"524\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 175px;\"\u003e\n \u003cp\u003eAlpha diversity index\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 175px;\"\u003e\n \u003cp\u003eChao1 index\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 175px;\"\u003e\n \u003cp\u003eACE index\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 175px;\"\u003e\n \u003cp\u003eBD-L\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 175px;\"\u003e\n \u003cp\u003e343.49\u0026plusmn;37.75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 175px;\"\u003e\n \u003cp\u003e354.14\u0026plusmn;32.28\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 175px;\"\u003e\n \u003cp\u003eAIS-L\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 175px;\"\u003e\n \u003cp\u003e333.24\u0026plusmn;44.92\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 175px;\"\u003e\n \u003cp\u003e339.44\u0026plusmn;44.49\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 175px;\"\u003e\n \u003cp\u003eMIA-L\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 175px;\"\u003e\n \u003cp\u003e324.58\u0026plusmn;45.51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 175px;\"\u003e\n \u003cp\u003e332.19\u0026plusmn;43.96\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 175px;\"\u003e\n \u003cp\u003eIAC-L\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 175px;\"\u003e\n \u003cp\u003e225.22\u0026plusmn;42.30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 175px;\"\u003e\n \u003cp\u003e231.68\u0026plusmn;39.00\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 175px;\"\u003e\n \u003cp\u003eAlpha diversity index\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 175px;\"\u003e\n \u003cp\u003eChao1 index\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 175px;\"\u003e\n \u003cp\u003eACE index\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eThe results revealed that the Chao1 and ACE indices gradually decreased during the gradual progression from benign lesions to invasive adenocarcinomas, whereas the Shannon and Simpson indices did not significantly change in the early stages of the lesions but significantly decreased in the invasive adenocarcinoma stage (Figure 2). According to the above results, the alpha diversity indices did not show significant intergroup differences in the progression from benign lesions to the stage of minimally invasive adenocarcinoma. However, when the disease progressed to the invasive adenocarcinoma stage, the significant decrease in the alpha diversity index (p \u0026lt; 0.001) suggested that patients with invasive adenocarcinoma may have experienced a significant reduction in the diversity of the lung flora.\u003c/p\u003e\u003cp\u003e3.2.2. \u0026nbsp; Beta diversity analysis\u003c/p\u003e\n\u003cp\u003eIn this study, principal coordinate analysis (PCoA), the UniFrac distance index and the unweighted distance index were used to comprehensively evaluate the differences in bacterial community structure among lung samples at different disease stages. The UniFrac distance indices, which consider phylogenetic relationships and microbial population abundance, provide a quantitative comparison of microbial community features.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe results of the PCoA analyses, as shown in Figure 3, illustrated sample variations from benign lesions to invasive adenocarcinomas. The samples from the benign, in situ, and minimally invasive stages presented considerable structural similarity, as indicated by their clustered distributions in the PCoA plots. In contrast, the flora structure characteristics of invasive adenocarcinoma samples were significantly different from those of the other lesion types on PCoA maps.\u003c/p\u003e\n\u003cp\u003eThe statistical significance of the differences in colony structure between the different lesion types was further confirmed by the Adonis test. In the unweighted UniFrac distance analysis, statistically significant differences in colony structure were observed only between adenocarcinoma in situ and minimally invasive adenocarcinoma (p = 0.026) and between minimally invasive adenocarcinoma and invasive adenocarcinoma (p = 0.001), whereas in the weighted UniFrac distance analysis, significant differences were observed only between minimally invasive adenocarcinoma and invasive adenocarcinoma (p = 0.001). The statistical results in Table 4 show that the microflora structure of invasive adenocarcinoma significantly changed, whereas the microflora structure of the other groups did not significantly differ.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 4. \u0026nbsp;A comparative analysis of the beta diversity of lung tissues at different developmental stages.\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"671\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003eUnifrac distance\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003eDiffs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003eDf\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003eSumsOfSqs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003eMeanSqs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003eF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003eR2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003eP\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" style=\"width: 104px;\"\u003e\n \u003cp\u003eUnweighted\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003eBD-L vs AIS-L\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e0.0806\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e0.0806\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e0.9565\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e0.0436\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e0.437\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003eAIS-L vs MIA-L\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e0.1656\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e0.1656\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e1.9627\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e0.0418\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e0.026\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003eMIA-L vs IAC-L\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e0.8562\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e0.8562\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e9.1184\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e0.1445\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" style=\"width: 104px;\"\u003e\n \u003cp\u003eWeighted\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003eBD-L vs AIS-L\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e1.1798\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e0.0532\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e0.302\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003eAIS-L vs MLA-L\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e0.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e0.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e2.1244\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e0.0451\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e0.075\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003eMIA-L vs IAC-L\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e0.0004\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e0.0004\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e13.6337\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e0.2016\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eTaken together, these findings suggest that the lung flora structure of invasive adenocarcinoma is significantly different from that of other lesion types, whereas the differences in the flora structure among benign lesions, adenocarcinoma in situ, and microinvasive adenocarcinoma are not significant.\u003c/p\u003e\n\u003cp\u003e3.2.3. \u0026nbsp; Species composition analysis\u003c/p\u003e\n\u003cp\u003eThis study utilized a species distribution stacked map to analyze the composition of the lung tissue flora, as depicted in Figure 4. We compared and analyzed the bacterial composition of lung adenocarcinoma at the phylum and genus levels. At the phylum level, the results revealed that the abundances of Proteobacteria, Firmicutes, and Bacteroidetes did not change significantly across the different stages of lung adenocarcinoma development (p\u0026gt;0.05). In addition, the species abundance of Actinobacteria remained relatively consistent in the early stages but decreased significantly in the aggressive adenocarcinoma stage (p\u0026lt;0.001). At the genus level, the abundances of the genera Stenotrophomonas, Pseudomonas, Acinetobacter, Bergeyella, and Pedobacter remained stable throughout the development of lung adenocarcinoma (p\u0026gt;0.05). In contrast, the genera Delftia (p\u0026lt;0.001), Agrobacterium (p\u0026lt;0.001), Caulobacter (p\u0026lt;0.001), Brevundimonas (p\u0026lt;0.01), Ralstonia (p\u0026lt;0.01) and Afipia (p\u0026lt;0.05) decreased significantly in the invasive adenocarcinoma stage but not in the early stage. Notably, the abundance of Bacillus spp. increased in invasive adenocarcinoma patients (p\u0026lt;0.05). Overall, the composition of the lung flora was similar between the groups, with the main difference being in species abundance. These distinctions became more pronounced as the disease transitioned to invasive adenocarcinoma, as detailed in Figure 5.\u003c/p\u003e\n\u003cp\u003e3.2.4.\u0026nbsp; \u0026nbsp;Functional analysis\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIn this study, BugBase software was used to analyze the microbial phenotypic characteristics of different stages of lung adenocarcinoma, as shown in Figure 6(a). The analysis revealed that at the invasive adenocarcinoma stage, the number of microorganisms with mobile element-containing, biofilm-forming, facultatively anaerobic, oxidative stress-tolerant, and pathogenic characteristics significantly increased in invasive adenocarcinomas compared with early-stage lung adenocarcinomas. In contrast, the phenotypic abundance of the aerobic and anaerobic phenotypes was greatly reduced. In addition, PICRUSt2 software was used in this study to predict the functions of metabolic pathways in different stages of lung adenocarcinoma, as shown in Figure 6(b). The analysis revealed that with the progression of lung adenocarcinoma, the abundance of metabolic pathways generally decreased, especially in the stage of invasive adenocarcinoma.\u003c/p\u003e"},{"header":"4.\tDiscussion","content":"\u003cp\u003eIn this study, we found that the pulmonary flora of invasive lung adenocarcinoma patients has significant characteristics in terms of species abundance, diversity, floral function, and metabolic pathways.\u003c/p\u003e\n\u003cp\u003eAlpha diversity analyses revealed that the Chao1 and ACE indices declined as the lesions progressed from benign to invasive adenocarcinomas. This trend suggests that the abundance of the lung flora gradually decreases as lung adenocarcinoma progresses. Furthermore, the Shannon and Simpson indices remained stable in early lung adenocarcinoma but significantly declined during the invasive stage, which may be indicative of the negative impact of disease progression on the diversity of the bacterial flora. We hypothesized that reduced flora diversity may be associated with an increased risk of developing cancer. This hypothesis is supported by epidemiologic studies: repeated use of antibiotics increases the risk of lung cancer, suggesting that abnormal lung microflora may play a role in the development of lung cancer [12, 13]. Additionally, the lung microbiome is implicated in cancer progression, potentially by modulating metabolic pathways, dampening immune responses, and promoting inflammation [14]. Specifically, bacterial activation of inflammatory pathways releases proinflammatory cytokines that promote the proliferation of airway epithelial cells. In a long-term chronic inflammatory environment, this proliferation may promote aberrant cell transformation, increasing the potential risk of tumorigenesis [15\u0026ndash;17]. These findings not only provide new insights into the relationship between the lung flora and lung cancer, but also provide new ideas and strategies for future diagnosis and treatment.\u003c/p\u003e\n\u003cp\u003eBeta diversity analysis showed no statistically significant differences in microbial community structure between benign lesions, lung adenocarcinoma in situ and microinvasive lung adenocarcinoma. However, as the disease progresses to the invasive adenocarcinoma stage, beta diversity analysis clearly revealed significant changes in the structure of the lung microbiota, suggesting that the lung microbiota of patients with invasive adenocarcinoma has unique structural characteristics compared with other stages. These findings suggest that in the early stages of lung adenocarcinoma development, the lung flora may remain somewhat stable structurally. However, as the disease progresses further, especially in the stage of invasive adenocarcinoma, the structure of the lung flora undergoes significant changes, which may lead to an imbalance in the microbial community, and studies have pointed out that an imbalance in the microbial community in the organ is directly or indirectly linked to carcinogenesis processes [18, 19]. An imbalance in the microbial community affects an individual\u0026apos;s susceptibility, which may lead to aberrant cell proliferation or tumor formation, including the modulation of the host\u0026apos;s immune and inflammatory responses and the production of potentially oncogenic metabolites [16].\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eSpecies composition analysis revealed that, at the phylum level, major flora such as Proteobacteria, Firmicutes, and Bacteroidetes changed little during lung cancer development, with only the abundance of actinomycetes decreasing in patients with invasive adenocarcinoma. However, at the genus level, not all genera changed in the early stage of lung adenocarcinoma development (from benign lesions to minimally invasive adenocarcinomas). The abundance of some genera was significantly reduced only during the development of invasive adenocarcinomas, and only the abundance of Bacillus was significantly increased in invasive adenocarcinomas, which may be related to the antitumor response of the organism [20, 21]. Different subgroups of the genus Bacillus and their metabolites show great potential for application in lung cancer therapy and may become new therapeutic targets in the future. To inhibit the growth, development and metastasis of cancer cells, organisms may promote the colonization and proliferation of beneficial flora while suppressing potentially harmful flora, thereby dynamically adjusting the composition and distribution of the lung microbiota. For example, Yu et al. [22] sequenced the bacterial flora in lung tissue samples from 165 lung cancer patients and reported that the composition of the lung flora was different from that of other parts of the body (e.g., the oral and nasal cavities), with a predominantly Aspergillus phylum, which was consistent with the results of the present study. At different stages of lung cancer progression, the lungs present characteristic dominant genera that may be involved in the process of lung cancer development or progression. These floras not only are important for the study of oncogenic or procarcinogenic mechanisms of the lung flora but can also be used as new biomarkers or biological targets for the diagnosis and treatment of lung cancer.\u003c/p\u003e\n\u003cp\u003eFunctional composition alterations,\u0026nbsp;especially the increase in bacterial phenotypes with mobile elements, biofilm-forming capabilities, and oxidative stress tolerance in invasive adenocarcinoma, suggest an adaptive microbial response to the cancer microenvironment. These characteristics are closely related to the adaptation and survival of bacteria in the lung cancer microenvironment: the presence of mobile elements may accelerate the adaptability of bacteria in the tumor microenvironment, allowing bacteria to improve their survival in the changing environment [23]. The formation of biofilms provides an effective protective mechanism for bacteria, allowing them to withstand a variety of adverse conditions, including antibiotic treatment [24]. The oxidative stress tolerance of bacteria allows them to survive in the lung cancer microenvironment, which is full of oxidative stress [25]. In addition, the increased abundance of bacteria with pathogenic phenotypes in invasive adenocarcinomas may indicate an increased pathogenic potential of the lung flora during disease progression. Moreover, we detected a decrease in the abundance of aerobic and anaerobic flora and an increase in the abundance of facultative anaerobic flora in invasive adenocarcinomas. Facultative anaerobic bacteria may be better adapted to changes in metabolic and oxidative stress in the lung cancer environment.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAt the pathway level, we observed an overall decrease in pathway abundance with lung adenocarcinoma progression. This decline may be associated with a decrease in the diversity of the lung flora, suggesting that tumor progression may negatively affect the metabolic function of the lung microbiome.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThis study revealed an association between the diversity of the lung flora and lung cancer, but due to time factors, the sample size was limited and may have affected the statistical significance of the findings. Future studies should increase the sample size and use better analytical techniques to overcome these problems.\u003c/p\u003e\n\u003cp\u003eA comprehensive examination of the lung microbiome has the potential to increase the efficacy of diagnosing and treating lung adenocarcinoma in women. By analyzing changes in microbial community composition, we can identify microbial species or metabolites associated with the development and progression of lung adenocarcinoma. These indicators of microbial changes are expected to serve as markers for early diagnosis, which will facilitate the efficient screening of high-risk women and early intervention. These research advances not only provide new insights into the link between lung microbiology and lung adenocarcinoma, but also contribute to the development of new diagnostic strategies and therapeutic approaches.\u003c/p\u003e"},{"header":"5.\tConclusion ","content":"\u003cp\u003eInvasive adenocarcinoma has a unique flora structure characterized by decreased flora diversity and abundance and an increase in specific flora (e.g., Bacillus). In terms of bacterial function, adaptability and pathogenicity increased and metabolic pathway activity decreased. These changes are closely associated with the pathological progression of lung adenocarcinoma and may serve as potential biomarkers for diagnosis and treatment. This study provides potential targets for the development of microbiota-based diagnostic tools that can contribute to the development of personalized therapeutic strategies to improve treatment efficacy and patient quality of life.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003e\u003cem\u003eEthics approval and consent to participate:\u0026nbsp;\u003c/em\u003e\u003c/strong\u003eThis study was approved by the Institutional Animal Care and Use Committee (KYLL-2022(ZM)-1121), and all experiments were performed according to animal care guidelines.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eConsent for publication:\u0026nbsp;\u003c/em\u003e\u003c/strong\u003eWritten informed consent for publication has been obtained.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eAvailability of data and materials:\u0026nbsp;\u003c/em\u003e\u003c/strong\u003eAll data generated or analysed during this study are included in this published article [and its supplementary information files].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eCompeting interests:\u003c/em\u003e\u003c/strong\u003e The authors declare that they have no competing interests\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eFunding:\u003c/em\u003e\u003c/strong\u003e Natural Science Foundation of Shandong Province (grant number ZR2023QH328) and Shanghai Aitrox Technology Corporation Limited, Shanghai, PR China (Contract No. 6010124020)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eAuthors\u0026apos; contributions\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e\u003cem\u003e：\u003c/em\u003e\u003c/strong\u003eConceptualization, Chengcheng Du; Data curation, Jingshuo Li; Formal analysis, Yuxian Chen; Funding acquisition, Fanlei Kong; Investigation, Yuxian Chen; Methodology, Daqian Sun; Project administration, Chunhai Li and Fanlei Kong; Resources, Jingshuo Li; Software, Daqian Sun; Supervision, Hong Meng; Validation, Daqian Sun; Visualization, Chengcheng Du; Writing\u0026nbsp;\u0026ndash;\u0026nbsp;original draft, Chengcheng Du; Writing\u0026nbsp;\u0026ndash;\u0026nbsp;review \u0026amp; editing, Hong Meng.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eAcknowledgements\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e\u003cem\u003e：\u003c/em\u003e\u003c/strong\u003eWe would like to thank Dr. Hui Tian, Dr. Guo-Tao Yang, and Dr. Xi-Bo Li from Department of Chest surgery, Qilu Hospital, for their contributions to the technical support of thoracic surgery; Dr. Shu-Xin Yan from the Department of Pathology, Qilu Hospital, for their help in pathological specimen making; and Dr. Hai-Peng Jia, Dr. Tian-Xiao Yao, and Dr. Bo Liu from the Department of Minimally Invasive Tumor Intervention, Qilu Hospital, for his help in proofreading.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eBray F, Laversanne M, Sung H, et al. 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Recombinant Phaseolus vulgaris phytohemagglutinin L-form expressed in the Bacillus brevis exerts in vitro and in vivo anti-tumor activity through potentiation of apoptosis and immunomodulation. \u003cem\u003eInt Immunopharmacol\u003c/em\u003e. 2023;120:110322.\u003c/li\u003e\n\u003cli\u003eYu G, Gail MH, Consonni D, et al. Characterizing human lung tissue microbiota and its relationship to epidemiological and clinical features. \u003cem\u003eGenome Biol\u003c/em\u003e. 2016;17(1):163.\u003c/li\u003e\n\u003cli\u003eDurrant MG, Li MM, Siranosian BA, Montgomery SB, Bhatt AS. A Bioinformatic Analysis of Integrative Mobile Genetic Elements Highlights Their Role in Bacterial Adaptation. \u003cem\u003eCell Host Microbe\u003c/em\u003e. 2020;27(1):140-153.e9.\u003c/li\u003e\n\u003cli\u003ePaula AJ, Hwang G, Koo H. Dynamics of bacterial population growth in biofilms resemble spatial and structural aspects of urbanization. \u003cem\u003eNat Commun\u003c/em\u003e. 2020;11(1):1354.\u003c/li\u003e\n\u003cli\u003eZhu M, Dai X. Maintenance of translational elongation rate underlies the survival of Escherichia coli during oxidative stress. \u003cem\u003eNucleic Acids Res\u003c/em\u003e. 2019;47(14):7592-7604.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-cancer","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bcan","sideBox":"Learn more about [BMC Cancer](http://bmccancer.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bcan/default.aspx","title":"BMC Cancer","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Female, lung adenocarcinoma, lung flora, flora diversity, 16S rRNA sequencing","lastPublishedDoi":"10.21203/rs.3.rs-5232486/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5232486/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground: \u003c/strong\u003eThe number of female lung adenocarcinoma patients is increasing annually, but these patients are difficult to diagnose in the early stage without obvious clinical symptoms, leading to late-stage diagnoses and poor outcomes. Recent studies have shown that the lung microbiota is closely related to the occurrence and development of lung cancer, especially the characteristic changes in the lung microbiota of lung cancer patients, which opens a new research direction for the diagnosis and treatment of lung cancer. This study aimed to analyze the characteristics of the lung flora in different stages of female lung adenocarcinoma.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods:\u003c/strong\u003e 16S rRNA sequencing technology was used to analyze the alpha diversity, beta diversity, composition, and function of the pulmonary flora in female patients with benign lesions (n=7), adenocarcinoma in situ (n = 16), microinvasive adenocarcinoma (n = 31), and invasive adenocarcinoma (n = 25).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults: \u003c/strong\u003eProgression to invasive lung adenocarcinoma is correlated with reduced alpha diversity in the lung flora. Compared with the other stages, only the invasive adenocarcinoma stage had significant differences in the beta diversity of the lung flora. At the phylum and genus levels, the abundance of major flora species decreased significantly as the disease progressed to the invasive adenocarcinoma stage, whereas the abundance of Bacillus spp. increased significantly. The abundance of phenotypes with mobile elements, biofilm-forming ability, oxidative stress tolerance, parthenogenetic anaerobic properties, and pathogenicity was significantly greater in invasive adenocarcinomas. The abundance of metabolic pathways was significantly lower in invasive adenocarcinomas.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions: \u003c/strong\u003eInvasive adenocarcinoma has a unique flora structure characterized by decreased flora diversity and abundance and an increase in specific flora (e.g., Bacillus). In terms of bacterial function, adaptability and pathogenicity increased, and metabolic pathway activity decreased.\u003c/p\u003e","manuscriptTitle":"Study of the Microenvironment of the Lung Flora in Female Lung Adenocarcinoma Patients: From Benign Lesions to Invasive Lung Adenocarcinoma","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-12-16 14:24:41","doi":"10.21203/rs.3.rs-5232486/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-10-14T06:00:36+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-10-10T02:11:04+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-10-10T02:10:24+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Cancer","date":"2024-10-09T12:07:14+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-cancer","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bcan","sideBox":"Learn more about [BMC Cancer](http://bmccancer.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bcan/default.aspx","title":"BMC Cancer","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"15c8d714-dcdc-49ed-8f85-a9754864f28b","owner":[],"postedDate":"December 16th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-02-17T16:02:15+00:00","versionOfRecord":{"articleIdentity":"rs-5232486","link":"https://doi.org/10.1186/s12885-024-13385-1","journal":{"identity":"bmc-cancer","isVorOnly":false,"title":"BMC Cancer"},"publishedOn":"2025-02-13 15:57:36","publishedOnDateReadable":"February 13th, 2025"},"versionCreatedAt":"2024-12-16 14:24:41","video":"","vorDoi":"10.1186/s12885-024-13385-1","vorDoiUrl":"https://doi.org/10.1186/s12885-024-13385-1","workflowStages":[]},"version":"v1","identity":"rs-5232486","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5232486","identity":"rs-5232486","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}