Murine fecal microbiota transfer models selectively colonize human microbes and reveal transcriptional programs associated with response to neoadjuvant checkpoint inhibitors
Abstract Human gut microbial species found to associate with clinical responses to immune checkpoint inhibitors (ICIs) are often tested in mice using fecal microbiota transfer (FMT), wherein tumor responses in recipient mice may recapitulate human responses to ICI treatment. However, many FMT studies have reported only limited methodological description, details of murine cohorts, and statistical methods. To investigate the reproducibility and robustness of gut microbial species that impact ICI responses, we performed human to germ-free mouse FMT using fecal samples from patients with non-small cell lung cancer who had a pathological response or nonresponse after neoadjuvant ICI treatment. R-FMT mice yielded greater anti-tumor responses in combination with anti-PD-L1 treatment compared to NR-FMT, although the magnitude varied depending on mouse cell line, sex, and individual experiment. Detailed investigation of post-FMT mouse microbiota using 16S rRNA amplicon sequencing, with models to classify and correct for biological variables, revealed a shared presence of the most highly abundant taxa between the human inocula and mice, though low abundance human taxa colonized mice more variably after FMT. Multiple Clostridium species also correlated with tumor outcome in individual anti-PD-L1-treated R-FMT mice. RNAseq analysis revealed differential expression of T and NK cell-related pathways in responding tumors, irrespective of FMT source, with enrichment of these cell types confirmed by immunohistochemistry. This study identifies several human gut microbial species that may play a role in clinical responses to ICIs and suggests attention to biological variables is needed to improve reproducibility and limit variability across experimental murine cohorts..
Medienart: |
E-Artikel |
---|
Erscheinungsjahr: |
2022 |
---|---|
Erschienen: |
2022 |
Enthalten in: |
Zur Gesamtaufnahme - volume:71 |
---|---|
Enthalten in: |
Cancer immunology immunotherapy - 71(2022), 10 vom: 26. Feb., Seite 2405-2420 |
Sprache: |
Englisch |
---|
Beteiligte Personen: |
Shaikh, Fyza Y. [VerfasserIn] |
---|
Links: |
Volltext [lizenzpflichtig] |
---|
BKL: | |
---|---|
Themen: |
Biological variables |
RVK: |
---|
Anmerkungen: |
© The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2022 |
---|
doi: |
10.1007/s00262-022-03169-6 |
---|
funding: |
|
---|---|
Förderinstitution / Projekttitel: |
|
PPN (Katalog-ID): |
OLC2131952813 |
---|
LEADER | 01000naa a22002652 4500 | ||
---|---|---|---|
001 | OLC2131952813 | ||
003 | DE-627 | ||
005 | 20230506063146.0 | ||
007 | cr uuu---uuuuu | ||
008 | 230506s2022 xx |||||o 00| ||eng c | ||
024 | 7 | |a 10.1007/s00262-022-03169-6 |2 doi | |
035 | |a (DE-627)OLC2131952813 | ||
035 | |a (DE-He213)s00262-022-03169-6-e | ||
040 | |a DE-627 |b ger |c DE-627 |e rakwb | ||
041 | |a eng | ||
082 | 0 | 4 | |a 610 |q VZ |
082 | 0 | 4 | |a 610 |q VZ |
084 | |a ELIB24 |q VZ |2 rvk | ||
084 | |a 44.81$jOnkologie |2 bkl | ||
084 | |a 44.45$jImmunologie |2 bkl | ||
100 | 1 | |a Shaikh, Fyza Y. |e verfasserin |4 aut | |
245 | 1 | 0 | |a Murine fecal microbiota transfer models selectively colonize human microbes and reveal transcriptional programs associated with response to neoadjuvant checkpoint inhibitors |
264 | 1 | |c 2022 | |
336 | |a Text |b txt |2 rdacontent | ||
337 | |a Computermedien |b c |2 rdamedia | ||
338 | |a Online-Ressource |b cr |2 rdacarrier | ||
500 | |a © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2022 | ||
520 | |a Abstract Human gut microbial species found to associate with clinical responses to immune checkpoint inhibitors (ICIs) are often tested in mice using fecal microbiota transfer (FMT), wherein tumor responses in recipient mice may recapitulate human responses to ICI treatment. However, many FMT studies have reported only limited methodological description, details of murine cohorts, and statistical methods. To investigate the reproducibility and robustness of gut microbial species that impact ICI responses, we performed human to germ-free mouse FMT using fecal samples from patients with non-small cell lung cancer who had a pathological response or nonresponse after neoadjuvant ICI treatment. R-FMT mice yielded greater anti-tumor responses in combination with anti-PD-L1 treatment compared to NR-FMT, although the magnitude varied depending on mouse cell line, sex, and individual experiment. Detailed investigation of post-FMT mouse microbiota using 16S rRNA amplicon sequencing, with models to classify and correct for biological variables, revealed a shared presence of the most highly abundant taxa between the human inocula and mice, though low abundance human taxa colonized mice more variably after FMT. Multiple Clostridium species also correlated with tumor outcome in individual anti-PD-L1-treated R-FMT mice. RNAseq analysis revealed differential expression of T and NK cell-related pathways in responding tumors, irrespective of FMT source, with enrichment of these cell types confirmed by immunohistochemistry. This study identifies several human gut microbial species that may play a role in clinical responses to ICIs and suggests attention to biological variables is needed to improve reproducibility and limit variability across experimental murine cohorts. | ||
650 | 4 | |a Gut microbiome | |
650 | 4 | |a Immune checkpoint inhibitors | |
650 | 4 | |a Neoadjuvant | |
650 | 4 | |a Lung cancer | |
650 | 4 | |a Fecal microbiota transfer | |
650 | 4 | |a Biological variables | |
700 | 1 | |a Gills, Joell J. |4 aut | |
700 | 1 | |a Mohammad, Fuad |4 aut | |
700 | 1 | |a White, James R. |4 aut | |
700 | 1 | |a Stevens, Courtney M. |4 aut | |
700 | 1 | |a Ding, Hua |4 aut | |
700 | 1 | |a Fu, Juan |4 aut | |
700 | 1 | |a Tam, Ada |4 aut | |
700 | 1 | |a Blosser, Richard L. |4 aut | |
700 | 1 | |a Domingue, Jada C. |4 aut | |
700 | 1 | |a Larman, Tatianna C. |4 aut | |
700 | 1 | |a Chaft, Jamie E. |4 aut | |
700 | 1 | |a Spicer, Jonathan D. |4 aut | |
700 | 1 | |a Reuss, Joshua E. |4 aut | |
700 | 1 | |a Naidoo, Jarushka |4 aut | |
700 | 1 | |a Forde, Patrick M. |4 aut | |
700 | 1 | |a Ganguly, Sudipto |4 aut | |
700 | 1 | |a Housseau, Franck |4 aut | |
700 | 1 | |a Pardoll, Drew M. |4 aut | |
700 | 1 | |a Sears, Cynthia L. |0 (orcid)0000-0003-4059-1661 |4 aut | |
773 | 0 | 8 | |i Enthalten in |t Cancer immunology immunotherapy |d Springer Berlin Heidelberg, 1976 |g 71(2022), 10 vom: 26. Feb., Seite 2405-2420 |h Online-Ressource |w (DE-627)253390443 |w (DE-600)1458489-X |w (DE-576)072283475 |x 1432-0851 |7 nnns |
773 | 1 | 8 | |g volume:71 |g year:2022 |g number:10 |g day:26 |g month:02 |g pages:2405-2420 |
856 | 4 | 0 | |u https://dx.doi.org/10.1007/s00262-022-03169-6 |z lizenzpflichtig |3 Volltext |
912 | |a GBV_USEFLAG_A | ||
912 | |a SYSFLAG_A | ||
912 | |a GBV_OLC | ||
912 | |a GBV_ILN_11 | ||
912 | |a GBV_ILN_20 | ||
912 | |a GBV_ILN_22 | ||
912 | |a GBV_ILN_23 | ||
912 | |a GBV_ILN_24 | ||
912 | |a GBV_ILN_31 | ||
912 | |a GBV_ILN_32 | ||
912 | |a GBV_ILN_39 | ||
912 | |a GBV_ILN_40 | ||
912 | |a GBV_ILN_60 | ||
912 | |a GBV_ILN_62 | ||
912 | |a GBV_ILN_63 | ||
912 | |a GBV_ILN_69 | ||
912 | |a GBV_ILN_70 | ||
912 | |a GBV_ILN_73 | ||
912 | |a GBV_ILN_74 | ||
912 | |a GBV_ILN_90 | ||
912 | |a GBV_ILN_95 | ||
912 | |a GBV_ILN_100 | ||
912 | |a GBV_ILN_101 | ||
912 | |a GBV_ILN_105 | ||
912 | |a GBV_ILN_110 | ||
912 | |a GBV_ILN_120 | ||
912 | |a GBV_ILN_138 | ||
912 | |a GBV_ILN_150 | ||
912 | |a GBV_ILN_151 | ||
912 | |a GBV_ILN_152 | ||
912 | |a GBV_ILN_161 | ||
912 | |a GBV_ILN_170 | ||
912 | |a GBV_ILN_171 | ||
912 | |a GBV_ILN_187 | ||
912 | |a GBV_ILN_213 | ||
912 | |a GBV_ILN_224 | ||
912 | |a GBV_ILN_230 | ||
912 | |a GBV_ILN_250 | ||
912 | |a GBV_ILN_267 | ||
912 | |a GBV_ILN_281 | ||
912 | |a GBV_ILN_285 | ||
912 | |a GBV_ILN_293 | ||
912 | |a GBV_ILN_370 | ||
912 | |a GBV_ILN_602 | ||
912 | |a GBV_ILN_636 | ||
912 | |a GBV_ILN_702 | ||
912 | |a GBV_ILN_711 | ||
912 | |a GBV_ILN_2001 | ||
912 | |a GBV_ILN_2003 | ||
912 | |a GBV_ILN_2004 | ||
912 | |a GBV_ILN_2005 | ||
912 | |a GBV_ILN_2006 | ||
912 | |a GBV_ILN_2007 | ||
912 | |a GBV_ILN_2008 | ||
912 | |a GBV_ILN_2009 | ||
912 | |a GBV_ILN_2010 | ||
912 | |a GBV_ILN_2011 | ||
912 | |a GBV_ILN_2014 | ||
912 | |a GBV_ILN_2015 | ||
912 | |a GBV_ILN_2020 | ||
912 | |a GBV_ILN_2021 | ||
912 | |a GBV_ILN_2025 | ||
912 | |a GBV_ILN_2026 | ||
912 | |a GBV_ILN_2027 | ||
912 | |a GBV_ILN_2031 | ||
912 | |a GBV_ILN_2034 | ||
912 | |a GBV_ILN_2037 | ||
912 | |a GBV_ILN_2038 | ||
912 | |a GBV_ILN_2039 | ||
912 | |a GBV_ILN_2044 | ||
912 | |a GBV_ILN_2048 | ||
912 | |a GBV_ILN_2049 | ||
912 | |a GBV_ILN_2055 | ||
912 | |a GBV_ILN_2057 | ||
912 | |a GBV_ILN_2059 | ||
912 | |a GBV_ILN_2061 | ||
912 | |a GBV_ILN_2064 | ||
912 | |a GBV_ILN_2065 | ||
912 | |a GBV_ILN_2068 | ||
912 | |a GBV_ILN_2088 | ||
912 | |a GBV_ILN_2093 | ||
912 | |a GBV_ILN_2106 | ||
912 | |a GBV_ILN_2107 | ||
912 | |a GBV_ILN_2108 | ||
912 | |a GBV_ILN_2110 | ||
912 | |a GBV_ILN_2111 | ||
912 | |a GBV_ILN_2112 | ||
912 | |a GBV_ILN_2113 | ||
912 | |a GBV_ILN_2118 | ||
912 | |a GBV_ILN_2129 | ||
912 | |a GBV_ILN_2132 | ||
912 | |a GBV_ILN_2143 | ||
912 | |a GBV_ILN_2144 | ||
912 | |a GBV_ILN_2147 | ||
912 | |a GBV_ILN_2148 | ||
912 | |a GBV_ILN_2152 | ||
912 | |a GBV_ILN_2153 | ||
912 | |a GBV_ILN_2188 | ||
912 | |a GBV_ILN_2190 | ||
912 | |a GBV_ILN_2232 | ||
912 | |a GBV_ILN_2336 | ||
912 | |a GBV_ILN_2433 | ||
912 | |a GBV_ILN_2446 | ||
912 | |a GBV_ILN_2470 | ||
912 | |a GBV_ILN_2474 | ||
912 | |a GBV_ILN_2507 | ||
912 | |a GBV_ILN_2522 | ||
912 | |a GBV_ILN_2548 | ||
912 | |a GBV_ILN_4035 | ||
912 | |a GBV_ILN_4037 | ||
912 | |a GBV_ILN_4046 | ||
912 | |a GBV_ILN_4112 | ||
912 | |a GBV_ILN_4125 | ||
912 | |a GBV_ILN_4126 | ||
912 | |a GBV_ILN_4242 | ||
912 | |a GBV_ILN_4246 | ||
912 | |a GBV_ILN_4249 | ||
912 | |a GBV_ILN_4251 | ||
912 | |a GBV_ILN_4277 | ||
912 | |a GBV_ILN_4305 | ||
912 | |a GBV_ILN_4306 | ||
912 | |a GBV_ILN_4307 | ||
912 | |a GBV_ILN_4313 | ||
912 | |a GBV_ILN_4322 | ||
912 | |a GBV_ILN_4323 | ||
912 | |a GBV_ILN_4324 | ||
912 | |a GBV_ILN_4325 | ||
912 | |a GBV_ILN_4326 | ||
912 | |a GBV_ILN_4328 | ||
912 | |a GBV_ILN_4333 | ||
912 | |a GBV_ILN_4334 | ||
912 | |a GBV_ILN_4335 | ||
912 | |a GBV_ILN_4336 | ||
912 | |a GBV_ILN_4338 | ||
912 | |a GBV_ILN_4393 | ||
912 | |a GBV_ILN_4700 | ||
936 | r | v | |a ELIB24 |
936 | b | k | |a 44.81$jOnkologie |q VZ |0 106409433 |0 (DE-625)106409433 |
936 | b | k | |a 44.45$jImmunologie |q VZ |0 106409689 |0 (DE-625)106409689 |
951 | |a AR | ||
952 | |d 71 |j 2022 |e 10 |b 26 |c 02 |h 2405-2420 |