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Microbiome-derived cobalamin and succinyl-CoA as biomarkers for improved screening of anal cancer

An Author Correction to this article was published on 16 August 2023

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Abstract

Human papillomavirus can cause preinvasive, high-grade squamous intraepithelial lesions (HSILs) as precursors to cancer in the anogenital area, and the microbiome is suggested to be a contributing factor. Men who have sex with men (MSM) living with human immunodeficiency virus (HIV) have a high risk of anal cancer, but current screening strategies for HSIL detection lack specificity. Here, we investigated the anal microbiome to improve HSIL screening. We enrolled participants living with HIV, divided into a discovery (n = 167) and validation cohort (n = 46), and who were predominantly (93.9%) cisgender MSM undergoing HSIL screening with high-resolution anoscopy and anal biopsies. We identified no microbiome composition signatures associated with HSILs, but elevated levels of microbiome-encoded proteins producing succinyl coenzyme A and cobalamin were significantly associated with HSILs in both cohorts. Measurement of these candidate biomarkers alone in anal cytobrushes outperformed anal cytology as a diagnostic indicator for HSILs, increasing the sensitivity from 91.2% to 96.6%, the specificity from 34.1% to 81.8%, and reclassifying 82% of false-positive results as true negatives. We propose that these two microbiome-derived biomarkers may improve the current strategy of anal cancer screening.

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Fig. 1: Distribution of most abundant taxonomic groups among patients.
Fig. 2: Differences in microbial protein abundances among patient groups.
Fig. 3: Identification of two HSIL-associated metabolites produced by the anal microbiome through proteomic analysis.
Fig. 4: Succinyl CoA and cobalamin concentrations in anal samples are increased in patients with HSIL.
Fig. 5: Comparative diagnostic performance of succinyl CoA and cobalamin versus anal cytology for detecting anal HSIL.

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Data availability

The data used for these analyses are available as supporting material at https://github.com/sajanraju/SCRAtCH-Codes. All of the sequences are publicly available in the European Nucleotide Archive database under accession number PRJEB58898. The mass spectrometry proteomics data have been deposited with the ProteomeXchange Consortium via the PRIDE partner repository70 with the dataset identifier PXD037268.

Code availability

The code used for these analyses is available as supporting material at https://github.com/sajanraju/SCRAtCH-Codes.

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References

  1. Clifford, G. M. et al. A meta-analysis of anal cancer incidence by risk group: toward a unified anal cancer risk scale. Int. J. Cancer 148, 38–47 (2021).

    Article  CAS  PubMed  Google Scholar 

  2. Koroukian, S. M. et al. Excess cancer prevalence in men with HIV: a nationwide analysis of Medicaid data. Cancer 128, 1987–1995 (2022).

    Article  PubMed  Google Scholar 

  3. Palefsky, J. M. et al. Treatment of anal high-grade squamous intraepithelial lesions to prevent anal cancer. N. Engl. J. Med. 386, 2273–2282 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  4. Clarke, M. A. & Wentzensen, N. Strategies for screening and early detection of anal cancers: a narrative and systematic review and meta-analysis of cytology, HPV testing, and other biomarkers. Cancer Cytopathol. 126, 447–460 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  5. Dias Gonçalves Lima, F. et al. The accuracy of anal swab-based tests to detect high-grade anal intraepithelial neoplasia in HIV-infected patients: a systematic review and meta-analysis. Open Forum Infect. Dis. 6, ofz191 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  6. Serrano-Villar, S., Zhou, Y., Rodgers, A. J. & Moreno, S. Different impact of raltegravir versus efavirenz on CD4/CD8 ratio recovery in HIV-infected patients. J. Antimicrob. Chemother. 72, 235–239 (2017).

    Article  CAS  PubMed  Google Scholar 

  7. Nowak, R. G. et al. High-risk human papillomavirus persistence and anal microbiota among Nigerian men who have sex with men living with or at risk for HIV. JCO Glob. Oncol. 6, 26–27 (2020).

    Article  Google Scholar 

  8. Ron, R. et al. Exploiting the microbiota for the diagnosis of anal precancerous lesions in men who have sex with men. J. Infect. Dis. 224, 1247–1256 (2021).

    Article  CAS  PubMed  Google Scholar 

  9. Ilhan, Z. E. et al. Deciphering the complex interplay between microbiota, HPV, inflammation and cancer through cervicovaginal metabolic profiling. EBioMedicine 44, 675–690 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  10. Qingqing, B. et al. Cervicovaginal microbiota dysbiosis correlates with HPV persistent infection. Microb. Pathog. 152, 104617 (2021).

    Article  PubMed  Google Scholar 

  11. Serrano-Villar, S. et al. HIV, HPV, and microbiota: partners in crime? AIDS 31, 591–594 (2017).

    Article  PubMed  Google Scholar 

  12. Dalal, N. et al. Gut microbiota-derived metabolites in CRC progression and causation. J. Cancer Res. Clin. Oncol. 147, 3141–3155 (2021).

    Article  CAS  PubMed  Google Scholar 

  13. Fu, A. et al. Tumor-resident intracellular microbiota promotes metastatic colonization in breast cancer. Cell 185, 1356–1372 (2022).

    Article  CAS  PubMed  Google Scholar 

  14. Norenhag, J. et al. The vaginal microbiota, human papillomavirus and cervical dysplasia: a systematic review and network meta-analysis. BJOG 127, 171–180 (2020).

    Article  CAS  PubMed  Google Scholar 

  15. Xin, X. et al. Comprehensive analysis of lncRNA-mRNA co-expression networks in HPV-driven cervical cancer reveals the pivotal function of LINC00511-PGK1 in tumorigenesis. Comput. Biol. Med. 159, 106943 (2023).

    Article  CAS  PubMed  Google Scholar 

  16. Yang, T. et al. Enolase 1 regulates stem cell-like properties in gastric cancer cells by stimulating glycolysis. Cell Death Dis. 11, 870 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. Nammi, D., Srimath-Tirumala-Peddinti, R. C. & Neelapu, N. R. Identification of drug targets in Helicobacter pylori by in silico analysis: possible therapeutic implications for gastric cancer. Curr. Cancer Drug Targets 16, 79–98 (2016).

    Article  CAS  PubMed  Google Scholar 

  18. Eschrich, S. et al. Molecular staging for survival prediction of colorectal cancer patients. J. Clin. Oncol. 23, 3526–3535 (2005).

    Article  CAS  PubMed  Google Scholar 

  19. Wang, D., Moothart, D. R., Lowy, D. R. & Qian, X. The expression of glyceraldehyde-3-phosphate dehydrogenase associated cell cycle (GACC) genes correlates with cancer stage and poor survival in patients with solid tumors. PLoS One 8, e61262 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Elkhalfi, B., Senhaji, N., Benomar, H. & Soukri, A. Study of glyceraldehyde-3-phosphate dehydrogenase expression in the tumor process of: breast, cervix and prostate cancers. Adv. Biol. Chem. 2, 335–340 (2012).

    Article  CAS  Google Scholar 

  21. Wentzensen, N. et al. Performance of p16/Ki-67 immunostaining to detect cervical cancer precursors in a colposcopy referral population. Clin. Cancer Res. 18, 4154–4162 (2012).

    Article  PubMed  PubMed Central  Google Scholar 

  22. Tong, W. W. Y. et al. Progression to and spontaneous regression of high-grade anal squamous intraepithelial lesions in HIV-infected and uninfected men. AIDS 27, 2233–2243 (2013).

    Article  PubMed  Google Scholar 

  23. Francis, M. R. et al. Porin threading drives receptor disengagement and establishes active colicin transport through Escherichia coli OmpF. EMBO J. 40, e108610 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. Lee, S. J. et al. A potential protein adjuvant derived from Mycobacterium tuberculosis Rv0652 enhances dendritic cells-based tumor immunotherapy. PLoS One 9, e104351 (2014).

    Article  PubMed  PubMed Central  Google Scholar 

  25. Shang, F.-M. & Liu, H.-L. Fusobacterium nucleatum and colorectal cancer: a review. World J. Gastrointest. Oncol. 10, 71–81 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  26. Elnaggar, J. H. et al. HPV-related anal cancer is associated with changes in the anorectal microbiome during cancer development. Front. Immunol. 14, 1051431 (2023).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. Fahmy, C. A. et al. Bifidobacterium longum suppresses murine colorectal cancer through the modulation of oncomiRs and tumor suppressor miRNAs. Nutr. Cancer 71, 688–700 (2019).

    Article  CAS  PubMed  Google Scholar 

  28. Audirac-Chalifour, A. et al. Cervical microbiome and cytokine profile at various stages of cervical cancer: a pilot study. PLoS One 11, e0153274 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  29. Lee, C. H. et al. Anal human papillomavirus infection among HIV-infected men in Korea. PLoS One 11, e0161460 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  30. Nowak, R. G. et al. Rectal microbiota among HIV-uninfected, untreated HIV, and treated HIV-infected in Nigeria. AIDS 31, 857–862 (2017).

    Article  PubMed  Google Scholar 

  31. Arizmendi-Izazaga, A. et al. Metabolic reprogramming in cancer: role of HPV 16 variants. Pathogens 10, 347 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  32. He, Y. et al. PGK1-mediated cancer progression and drug resistance. Am. J. Cancer Res. 9, 2280–2302 (2019).

    CAS  PubMed  PubMed Central  Google Scholar 

  33. Song, Y. et al. Alpha-enolase as a potential cancer prognostic marker promotes cell growth, migration, and invasion in glioma. Mol. Cancer 13, 65 (2014).

    Article  PubMed  PubMed Central  Google Scholar 

  34. Chang, Y.-C. et al. Metabolic protein phosphoglycerate kinase 1 confers lung cancer migration by directly binding HIV Tat specific factor 1. Cell Death Discov. 7, 135 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  35. Jeffery, C. J. Intracellular/surface moonlighting proteins that aid in the attachment of gut microbiota to the host. AIMS Microbiol. 5, 77–86 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  36. Didiasova, M., Schaefer, L. & Wygrecka, M. When place matters: shuttling of enolase-1 across cellular compartments. Front. Cell Dev. Biol. 7, 61 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  37. Wygrecka, M. et al. Enolase-1 promotes plasminogen-mediated recruitment of monocytes to the acutely inflamed lung. Blood 113, 5588–5598 (2009).

    Article  CAS  PubMed  Google Scholar 

  38. Capello, M. et al. Targeting the Warburg effect in cancer cells through ENO1 knockdown rescues oxidative phosphorylation and induces growth arrest. Oncotarget 7, 5598–5612 (2016).

    Article  PubMed  Google Scholar 

  39. Chhatwal, G. S. Anchorless adhesins and invasins of Gram-positive bacteria: a new class of virulence factors. Trends Microbiol. 10, 205–208 (2002).

    Article  CAS  PubMed  Google Scholar 

  40. Cracan, V. & Banerjee, R. Novel B(12)-dependent acyl-CoA mutases and their biotechnological potential. Biochemistry 51, 6039–6046 (2012).

    Article  CAS  PubMed  Google Scholar 

  41. Sivanand, S. & Vander Heiden, M. G. Emerging roles for branched-chain amino acid metabolism in cancer. Cancer Cell 37, 147–156 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  42. Gomes, A. P. et al. Age-induced accumulation of methylmalonic acid promotes tumour progression. Nature 585, 283–287 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  43. Wang, K. et al. Branched-chain amino acid aminotransferase 2 regulates ferroptotic cell death in cancer cells. Cell Death Differ. 28, 1222–1236 (2021).

    Article  CAS  PubMed  Google Scholar 

  44. Grulich, A. E., van Leeuwen, M. T., Falster, M. O. & Vajdic, C. M. Incidence of cancers in people with HIV/AIDS compared with immunosuppressed transplant recipients: a meta-analysis. Lancet 370, 59–67 (2007).

    Article  PubMed  Google Scholar 

  45. Zhang, Y. et al. Activation of PGK1 under hypoxic conditions promotes glycolysis and increases stem cell-like properties and the epithelial-mesenchymal transition in oral squamous cell carcinoma cells via the AKT signalling pathway. Int. J. Oncol. 57, 743–755 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  46. Tian, Z. et al. Prognostic value of neuron-specific enolase for small cell lung cancer: a systematic review and meta-analysis. World J. Surg. Oncol. 18, 116 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  47. Lv, Y. et al. Nucleotide de novo synthesis increases breast cancer stemness and metastasis via cGMP-PKG-MAPK signaling pathway. PLoS Biol. 18, e3000872 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  48. Gong, L. et al. Propranolol selectively inhibits cervical cancer cell growth by suppressing the cGMP/PKG pathway. Biomed. Pharmacother. 111, 1243–1248 (2019).

    Article  CAS  PubMed  Google Scholar 

  49. Wang, J. et al. High-risk HPV16 E6 activates the cGMP/PKG pathway through glycosyltransferase ST6GAL1 in cervical cancer cells. Front. Oncol. 11, 716246 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  50. Albracht, S. P. J., Meijer, A. J. & Rydström, J. Mammalian NADH:ubiquinone oxidoreductase (Complex I) and nicotinamide nucleotide transhydrogenase (Nnt) together regulate the mitochondrial production of H2O2: implications for their role in disease, especially cancer. J. Bioenerg. Biomembr. 43, 541–564 (2011).

    Article  CAS  PubMed  Google Scholar 

  51. Chang, H. J. et al. Identification of mitochondrial FoF1-ATP synthase involved in liver metastasis of colorectal cancer. Cancer Sci. 98, 1184–1191 (2007).

    Article  CAS  PubMed  Google Scholar 

  52. Li, Q. et al. The combined expressions of B7H4 and ACOT4 in cancer-associated fibroblasts are related to poor prognosis in patients with gastric carcinoma. Int. J. Clin. Exp. Pathol. 12, 2672–2681 (2019).

    CAS  PubMed  PubMed Central  Google Scholar 

  53. Peterson, C. T., Rodionov, D. A., Peterson, S. N. & Osterman, A. L. B vitamins and their role in immune regulation and cancer. Nutrients 12, 3380 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  54. Lamaudière, M. T. F., Arasaradnam, R., Weedall, G. D. & Morozov, I. Y. The colorectal cancer microbiota alter their transcriptome to adapt to the acidity, reactive oxygen species, and metabolite availability of gut microenvironments. mSphere 8, e0062722 (2023).

    Article  PubMed  Google Scholar 

  55. Darragh, T. M. et al. The Lower Anogenital Squamous Terminology Standardization project for HPV-associated lesions: background and consensus recommendations from the College of American Pathologists and the American Society for Colposcopy and Cervical Pathology. Int. J. Gynecol. Pathol. 32, 76–115 (2013).

    Article  PubMed  Google Scholar 

  56. Hillman, R. J. et al. 2016 IANS international guidelines for practice standards in the detection of anal cancer precursors. J. Low. Genit. Tract Dis. 20, 283–291 (2016).

    Article  PubMed  Google Scholar 

  57. Li, J. et al. An integrated catalog of reference genes in the human gut microbiome. Nat. Biotechnol. 32, 834–841 (2014).

    Article  CAS  PubMed  Google Scholar 

  58. Bolyen, E. et al. Reproducible, interactive, scalable and extensible microbiome data science using QIIME 2. Nat. Biotechnol. 37, 852–857 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  59. Callahan, B. J. et al. DADA2: high-resolution sample inference from Illumina amplicon data. Nat. Methods 13, 581–583 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  60. Katoh, K., Misawa, K., Kuma, K. & Miyata, T. MAFFT: a novel method for rapid multiple sequence alignment based on fast Fourier transform. Nucleic Acids Res. 30, 3059–3066 (2002).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  61. Love, M. I., Huber, W. & Anders, S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol. 15, 550 (2014).

    Article  PubMed  PubMed Central  Google Scholar 

  62. Quast, C. et al. The SILVA ribosomal RNA gene database project: improved data processing and web-based tools. Nucleic Acids Res. 41, D590–D596 (2012).

    Article  PubMed  PubMed Central  Google Scholar 

  63. Välikangas, T., Suomi, T. & Elo, L. L. A systematic evaluation of normalization methods in quantitative label-free proteomics. Brief. Bioinform. 19, 1–11 (2018).

    PubMed  Google Scholar 

  64. Lazar, C., Gatto, L., Ferro, M., Bruley, C. & Burger, T. Accounting for the multiple natures of missing values in label-free quantitative proteomics data sets to compare imputation strategies. J. Proteome Res. 15, 1116–1125 (2016).

    Article  CAS  PubMed  Google Scholar 

  65. Kammers, K., Cole, R. N., Tiengwe, C. & Ruczinski, I. Detecting significant changes in protein abundance. EuPA Open Proteom. 7, 11–19 (2015).

    Article  CAS  PubMed  Google Scholar 

  66. Harris, P. A. et al. The REDCap consortium: building an international community of software platform partners. J. Biomed. Inform. 95, 103208 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  67. Leening, M. J. G., Vedder, M. M., Witteman, J. C. M., Pencina, M. J. & Steyerberg, E. W. Net reclassification improvement: computation, interpretation, and controversies: a literature review and clinician’s guide. Ann. Intern. Med. 160, 122–131 (2014).

    Article  PubMed  Google Scholar 

  68. Wynants, L. et al. A simulation study of sample size demonstrated the importance of the number of events per variable to develop prediction models in clustered data. J. Clin. Epidemiol. 68, 1406–1414 (2015).

    Article  CAS  PubMed  Google Scholar 

  69. Serrano-Villar, S. et al. Screening for precancerous anal lesions with P16/Ki67 immunostaining in HIV-infected MSM. PLoS One 12, e0188851 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  70. Perez-Riverol, Y. et al. The PRIDE database resources in 2022: a hub for mass spectrometry-based proteomics evidence. Nucleic Acids Res. 50, D543–D552 (2022).

    Article  CAS  PubMed  Google Scholar 

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Acknowledgements

This work was supported by the ERANET TRANSCAN-2 program, JTC 2016 (SCRAtCH project, grant agreement no. 643638), funded by Instituto de Salud Carlos III (project AC17/00019), AECC (grant TRNSC17002SER), Lombardy Foundation for Biomedical Research, Italy (SCRAtCH project, grant agreement no. 643638); Federal Ministry of Education and Research, Germany (SCRAtCH project, grant agreement no. 643638); and the Research Council of Norway and Norwegian Cancer Society, Norway (SCRAtCH project, grant agreement no. 643638). The work was also supported by grants PI18/00154, ICI20/00058 and PI21/00141, funded by Instituto de Salud Carlos III and cofounded by the European Union, and grants PID2020-112758RB-I00 and PDC2021-121534-I00 funded by the Ministerio de Ciencia e Innovación, Agencia Estatal de Investigación (AEI) (https://doi.org/10.13039/501100011033) and the European Union (‘NextGenerationEU’). The authors thank all of the study participants and their families and the staff involved in this study for their commitment to clinical research.

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S.S.-V. conceptualized the study; S.S.-V., C.T., A.C.-U., E.S., S.M. and J.A.P.M. carried out recruitment and clinical follow-up; J.S.S., E.M., A.B., J.S. and M.F. handled the clinical specimens; L.F.-L. and M.F. carried out sample processing and metabolite analysis; M.F. supervised the 16S sequencing analysis; A.K., J.S.S. and J.S. carried out the proteomic analyses; E.M. performed the bacterial culture experiments; R.C. supervised the bacterial culture experiments; S.C.R., J.S.S. and R.B. performed the bioinformatic analysis; S.S.-V., M.T., J.R.H., and M.F. supervised the 16S RNA gene bioinformatic analysis; S.S.-V. carried out the statistical analysis; A.M. supervised the statistical analysis; S.S.-V. wrote the first version of the manuscript. All of the authors reviewed and approved the final manuscript.

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Correspondence to Sergio Serrano-Villar.

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Competing interests

S.S-V. and M.F. have filed a pending patent (Ref. EP22383112.4) as inventors related to the use of succinyl-CoA and cobalamin for HSIL detection. All other authors have no competing interests.

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Nature Medicine thanks Adam Burgener and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Primary Handling Editor: Alison Farrell, in collaboration with the Nature Medicine team.

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Serrano-Villar, S., Tincati, C., Raju, S.C. et al. Microbiome-derived cobalamin and succinyl-CoA as biomarkers for improved screening of anal cancer. Nat Med 29, 1738–1749 (2023). https://doi.org/10.1038/s41591-023-02407-3

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