Intestinal microbiome as a predictor of the anti-PD-1 therapy success: metagenomic data analysis

Fedorov D.E.1 , Olekhnovich E.I.1, Pavlenko A.V.1, Klimina K.M.1, Pokataev I.A.2, Manolov A.I.1, Konanov D.N.1, Veselovsky V.A.1, Ilina E.N.1

1. Federal Research and Clinical Center of Physical-Chemical Medicine, Moscow, Russia
2. Oncology Clinical Hospital No. 1, Moscow, Russia
Section: Clinical and Diagnostic Research
DOI: 10.18097/PBMC20206606502      PubMed Id: 33372909
Year: 2020  Volume: 66  Issue: 6  Pages: 502-507
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

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.
 2020 (vol 66)
 2019 (vol 65)
 2018 (vol 64)
 2017 (vol 63)
 2016 (vol 62)
 2015 (vol 61)
 2014 (vol 60)
 2013 (vol 59)
 2012 (vol 58)
 2011 (vol 57)
 2010 (vol 56)
 2009 (vol 55)
 2008 (vol 54)
 2007 (vol 53)
 2006 (vol 52)
 2005 (vol 51)
 2004 (vol 50)
 2003 (vol 49)