Anti-PD-1 immunotherapy has a large impact on cancer treatment but the rate of positive treatment outcomes is 40-45% and depends on many factors. One of the factors affecting the outcome of immunotherapy is the gut microbiota composition. This effect has been demonstrated both in model objects and in clinical patients groups. However, in order to identify clear causal relationships between microbiota and anti-PD1 immunotherapy response, it is necessary to expand the number of patients and experimental samples. This work presents an analysis of metagenomic data obtained using whole-genome sequencing of stool samples from melanoma patients (n=45) with different responses to anti-PD1 therapy. The analysis of the differential representation of microbial species has shown a difference in the composition of the microbiota between the experimental groups. Results of this study indicate existence of a strong link between the composition of the gut microbiota and the outcome of anti-PD1 therapy. Expansion of similar research may help develop additional predictive tools for the outcome of anti-PD1 cancer immunotherapy, as well as increase its effectiveness.
Download PDF:
Keywords: gut microbiota, melanoma, whole genome metagenomic sequencing, microbial communities
Citation:
Fedorov D.E., Olekhnovich E.I., Pavlenko A.V., Klimina K.M., Pokataev I.A., Manolov A.I., Konanov D.N., Veselovsky V.A., Ilina E.N. (2020) Intestinal microbiome as a predictor of the anti-PD-1 therapy success: metagenomic data analysis. Biomeditsinskaya Khimiya, 66(6), 502-507.
Fedorov D.E. et al. Intestinal microbiome as a predictor of the anti-PD-1 therapy success: metagenomic data analysis // Biomeditsinskaya Khimiya. - 2020. - V. 66. -N 6. - P. 502-507.
Fedorov D.E. et al., "Intestinal microbiome as a predictor of the anti-PD-1 therapy success: metagenomic data analysis." Biomeditsinskaya Khimiya 66.6 (2020): 502-507.
Fedorov, D. E., Olekhnovich, E. I., Pavlenko, A. V., Klimina, K. M., Pokataev, I. A., Manolov, A. I., Konanov, D. N., Veselovsky, V. A., Ilina, E. N. (2020). Intestinal microbiome as a predictor of the anti-PD-1 therapy success: metagenomic data analysis. Biomeditsinskaya Khimiya, 66(6), 502-507.
Kaprin A.D., Starinskiy V.V., Petrova G.V. (2019) National Medical Research Radiological Centre of the Ministry of Health of the Russian Federation, Moscow. 250 p. Scholar google search
Melanoma kozhi i slizistyh obolochek (2020). Klinicheskie rekomendacii Ministerstva Zdravoohraneniya Rossii (http://cr.rosminzdrav.ru/#!/schema/766). Scholar google search
Wolchok J.D., Chiarion-Sileni V., Gonzalez R., Rutkowski P., Grob J.J., Cowey C.L., Lao C.D., Wagstaff J., Schadendorf D., Ferrucci P.F., Smylie M., Dummer R., Hill A., Hogg D., Haanen J., Carlino M.S., Bechter O., Maio M., Marquez-Rodas I., Guidoboni M., McArthur G., Lebbé C., Ascierto P.A., Long G.V., Cebon J., Sosman J., Postow M.A., Callahan M.K., Walker D., Rollin L., Bhore R., Hodi S., Larkin J. (2017) N. Engl. J. Med., 377(14), 1345-1356. CrossRef Scholar google search
Caroline R., Ribas A., Schachter J., Arance A., Grob J.J., Mortier L., Daud A., Carlino M.S., McNeil C.M., Lotem M., Larkin J.M.G., Lorigan P., Neyns B., Blank C.U., Petrella T.M., Hamid O., Su S.C., Krepler C., Long G.V. (2019) Lancet Oncology, 20(9), 1239-1251. CrossRef Scholar google search
Lloyd-Price J., Arze C., Ananthakrishnan A.N., Schirmer M., Avila-Pacheco J., Poon T.W., Andrews E., Ajami N.J., Bonham K.S., Brislawn C.J., Casero D., Courtney H., Gonzalez A., Graeber T.G., Hall A.B., Lake K., Landers C.J., Mallick H., Plichta D.R., Prasad M., Rahnavard G., Sauk J., Shungin D., Vázquez-Baeza Y., WhiteIII R.A., IBDMDB Investigators, Braun J., Denson L.A., Jansson J.K., Knight R., Kugathasan S., McGovern D.P.B., Petrosino J.F., Stappenbeck T.S., Winter H.S., Clish C.B., Franzosa E.A., Vlamakis H., Xavier R.J., Huttenhower C. (2019) Nature, 569(7758), 655-662. CrossRef Scholar google search
Mazidi M., Rezaie P., Kengne A.P., Mobarhan M.G., Ferns G.A. (2016) Diabetes & Metabolic Syndrome: Clinical Research & Reviews, 10(2), S150-S157. CrossRef Scholar google search
Wirbel J., Pyl P.T., Kartal E., Zych K., Kashani A., Milanese A., Fleck J.S., Voigt A.Y., Palleja A., Ponnudurai R., Sunagawa S., Coelho L.P., Schrotz-King P., Vogtmann E., Habermann N., Niméus E., Thomas A.M., Manghi P., Gandini S., Serrano D., Mizutani S., Shiroma H., Shiba S., Shibata T., Yachida S., Yamada T., Waldron L., Naccarati A., Segata N., Sinha R., Ulrich C.M., Brenner H., Arumugam M., Bork P., Zeller G. (2019). Nature Medicine, 25(4), 679-689. CrossRef Scholar google search
Hamid O., Robert C., Daud A., Hodi F.S., Hwu W.J., Kefford R., Wolchok J.D., Hersey P., Joseph R.W., Weber J.S., Dronca R., Gangadhar T.C. (2013) N. Engl. J. Med., 369(2), 134-144. CrossRef Scholar google search
Matson V., Fessler J., Bao R., Chongsuwat T., Zha Y., Alegre M.L., Luke J.J., Gajewski T.F. (2018) Science, 359(6371), 104-108. CrossRef Scholar google search
Gopalakrishnan V., Spencer C.N., Nezi L., Reuben A., Andrews M.C., Karpinets T.V., Prieto P.A., Vicente D., Hoffman K., Wei S.C., Cogdill A.P., Zhao L., Hudgens C.W., Hutchinson D.S., Manzo T., Petaccia de Macedo M., Cotechini T., Kumar T., Chen W.S., Reddy S.M., Sloane S.R., Galloway-Pena J., Jiang H., Chen P.L., Shpall E.J., Rezvani K., Alousi A.M., Chemaly R.F., Shelburne S., Vence L.M., Okhuysen C., Jensen V.B., Swennes A.G., McAllister F., Marcelo Riquelme Sanchez E., Zhang Y., Le Chatelier E., Zitvogel L., Pons N., Austin-Breneman J.L., Haydu L.E., Burton E.M., Gardner J.M., Sirmans E., Hu J., Lazar A.J., Tsujikawa T., Diab A., Tawbi H., Glitza I.C., Hwu W.J., Patel S.P., Woodman S.E., Amaria R.N., Davies M.A., Gershenwald J.E., Hwu P., Lee J.E., Zhang J., Coussens L.M., Cooper Z.A., Futreal P.A., Daniel C.R., Ajami N.J., Petrosino J.F., Tetzlaff M.T., Sharma P., Allison J.P., Jenq R.R., Wargo J.A. (2018) Science, 359(6371), 97-103. CrossRef Scholar google search
Routy B., Gopalakrishnan V., Daillère R., Zitvogel L., Wargo J.A., Kroemer G. (2018) Nat. Rev. Clin. Oncol., 15(6), 382-396. CrossRef Scholar google search
Truong D.T., Franzosa E.A., Tickle T.L., Scholz M., Weingart G., Pasolli E., Tett A., Huttenhower C., Segata N. (2015) Nature Methods, 12(10), 902-903. CrossRef Scholar google search
Segata N., Izard J., Waldron L., Gevers D., Miropolsky L., Garrett W.S., Huttenhower C. (2011) Genome Biology, 12(6), 1-18. CrossRef Scholar google search
Pedregosa F., Varoquaux G., Gramfort A., Michel V., Thirion B., Grisel O., Vanderplas J. (2011) J. Machine Learning Res., 12, 2825-2830. Scholar google search
Daillère R., Vétizou M., Waldschmitt N., Yamazaki T., Isnard C., Poirier-Colame V., Duong C.P.M., Flament C., Lepage P., Roberti M.P., Routy B., Jacquelot N., Apetoh L., Becharef S., Rusakiewicz S., Langella P., Sokol H., Kroemer G., Enot D., Roux A., Eggermont A., Tartour E., Johannes L., Woerther P.L., Chachaty E., Soria J.C., Golden E., Formenti S., Plebanski M., Madondo M., Rosenstiel P., Raoult D., Cattoir V., Boneca G.I., Chamaillard M., Zitvogel L. (2016) Immunity, 45(4), 931-943. CrossRef Scholar google search
Zheng Y., Wang T., Tu X., Huang Y., Zhang H., Tan D., Li P., Qin N., Fang W. (2019) J. Immunother. Cancer, 7(1), 193. CrossRef Scholar google search
Spencer C.N., Gopalakrishnan V., McQuade J., Andrews M.C., Helmink B., Wadud Khan M.A., Sirmans E., Haydu L., Cogdill A., Burton E., Amaria R., Patel S., Glitza I., Davies M., Posada E., Hwu W.J., Diab A., Nelson K., Tawbi H., Wong M., Jenq R.R., Cohen L., Daniel-MacDougall C., Wargo J.A. (2019) Cancer Res., 79(13) 2838-2838. Scholar google search
ClinicalTrials.gov. National Library of Medicine (US). (2000, Feb 29 - ). Identifier NCT03269565, (2017) https://clinicaltrials.gov/ct2/show/NCT03269565. Scholar google search
