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| Status |
Public on Mar 01, 2023 |
| Title |
Multi-Omics Biomarkers of Response to Immunotherapy in Combination with Epigenetic Modulators |
| Organism |
Homo sapiens |
| Experiment type |
Expression profiling by array
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| Summary |
Epigenetic immunomodulation by association of guadecitabine with ipilimumab (NIBIT-M4 Phase Ib trial, NCT02608437) has been shown to be safe and tolerable in advanced melanoma and to have significant immunomodulatory and antitumor activity [Di Giacomo et al. Clin Cancer Res. 2019 Dec 15;25(24):7351-7362]. Here we carried out a multi-omics assessment of pre-therapy (week 0, w0) and on-treatment (week 4, w4 and week 12, w12) tumor biopsies from enrolled patients looking at the specific parameters that could explain clinical benefit vs treatment failure. Available whole exome sequencing, reduced-representation bisulfite sequencing and RNA sequencing data, together with focused analysis of immune-related signatures by custom NanoString panels, were integrated with existing information on tumor immune contexture data by immunohistochemistry. Results indicated that clinical benefit vs progressive disease could be explained, even at the single patient level, by applying a multifactorial code integrating information from a variety of parameters investigated on sequential biopsies. Crucial parameters included: tumor genomic/transcriptomic landscape, immune structure of the tumor microenvironment (inferred by deconvolution of gene expression data or assessed by immunohistochemistry), profile of genes and molecules relevant for antigen processing and presentation (immunoproteasome subunits, HLA class I molecules on tumor cells), tumor classification by the immunological constant of rejection (Bertucci et al. British Journal of Cancer 2018; 119:1383–1391), genetic immunoediting score (the ratio between the observed versus the expected number of neoantigens), enrichment for differentiation-, metabolism-, proliferation- and immunity-related pathways as well as analysis for signatures related to B cell content and differentiation, TLS formation, follicular T helper cells, TEX subsets, tumor-associated endothelial cells, ICB response and guadecitabine-specific gene upregulation.
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| Overall design |
RNA was extracted from two 12m-thick sections from FFPE blocks of tumor biopsies surgically removed from enrolled patients at three time points: W0 (pre-therapy), W4 and W12 (week 4 and week 12 on-treatment). The custom-designed NanoString panel allowed to test for expression of 364 genes that define the following signatures (numbers identify the signature ID replicated in header 5 of the data matrix): 1. Tertiary lymphoid structures (Cabrita et al., Nature 2020;577:561–565); 2. B cells (Patil et al., Cancer Cell 2022;40:1–12); 3. Follicular B cells (Patil et al., Cancer Cell 2022;40:1–12); 4. Plasma cells (Patil et al., Cancer Cell 2022;40:1–12); 5. Germinal center B cells (Patil et al., Cancer Cell 2022;40:1–12); 6. Germinal center B cellls (Cui et al., Cell 2021;184:1–18); 7. T follicular helper cells (Cui et al., Cell 2021;184:1–18); 8. Antibody secreting cells (Cui et al., Cell 2021;184:1–18); 9. B cells (Zhang, Cancer Cell 2021;39:1578–1593); 10. Tertiary lymphoid structures (Meylan et al., Immunity 2022;55:1–15); 11. Guadecitabine-specific gene signature (Anichini et al. Research Square https://doi.org/10.21203/rs.3.rs-1918233/v1); 12. IFN-gamma-induced ICB response signature (Grasso et al.,Cancer Cell 2020;38:500–515); 13. IFN-gamma-related ICB response signature (Ayers et al., J Clin Invest. 2017;127:2930-2940); 14. ICB response signature (Rodig et al., Sci. Transl. Med. 2018;10:eaar3342); 15. Tumor-associated endotelial cells (Asrir et al., Cancer Cell 2022; 40:318–334); 16. CD8+ exhausted T cells (Zheng et al., Science 2021;374:1462); 17. CD8+ GZMK+ Tex cells (Zheng et al., Science 2021;374:1462); 18. CD8+ terminal Tex (Zheng et al., Science 2021;374:1462); 19. CD8+ OXPHOS+ Tex cells (Zheng et al., Science 2021;374:1462); 20. CD8+ TCF7+ Tex cells (Zheng et al., Science 2021;374:1462).
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| Contributor(s) |
ANICHINI A, MAIO M |
| Citation missing |
Has this study been published? Please login to update or notify GEO. |
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| Submission date |
Aug 19, 2022 |
| Last update date |
Mar 04, 2023 |
| Contact name |
Andrea Anichini |
| E-mail(s) |
andrea.anichini@istitutotumori.mi.it
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| Phone |
+390223902817
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| Organization name |
Fondazione IRCCS Istituto Nazionale dei Tumori
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| Department |
Research
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| Lab |
Human Tumors Immunobiology Unit
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| Street address |
Via Venezian 1
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| City |
Milan |
| ZIP/Postal code |
20133 |
| Country |
Italy |
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| Platforms (1) |
| GPL32584 |
Nanostring nCounter custom immune profiling panel |
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| Samples (40)
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| GSM6481955 |
Patient#3_Pre-therapy sample_Responder |
| GSM6481956 |
Patient#3_On-treatment week 4 sample_Responder |
| GSM6481957 |
Patient#3_On-treatment week 12 sample_Responder |
| GSM6481958 |
Patient#4_Pre-therapy sample_Responder |
| GSM6481959 |
Patient#4_On-treatment week 4 sample_Responder |
| GSM6481960 |
Patient#4_On-treatment week 12 sample_Responder |
| GSM6481961 |
Patient#5_Pre-therapy sample_Responder |
| GSM6481962 |
Patient#5_On-treatment week 4 sample_Responder |
| GSM6481963 |
Patient#5_On-treatment week 12 sample_Responder |
| GSM6481964 |
Patient#11_Pre-therapy sample_Responder |
| GSM6481965 |
Patient#11_On-treatment week 4 sample_Responder |
| GSM6481966 |
Patient#11_On-treatment week 12 sample_Responder |
| GSM6481967 |
Patient#12_Pre-therapy sample_Responder |
| GSM6481968 |
Patient#12_On-treatment week 4 sample_Responder |
| GSM6481969 |
Patient#12_On-treatment week 12 sample_Responder |
| GSM6481970 |
Patient#14_Pre-therapy sample_Responder |
| GSM6481971 |
Patient#14_On-treatment week 4 sample_Responder |
| GSM6481972 |
Patient#14_On-treatment week 12 sample_Responder |
| GSM6481973 |
Patient#1_Pre-therapy sample_Non_Responder |
| GSM6481974 |
Patient#1_On-treatment week 4 sample_Non_Responder |
| GSM6481975 |
Patient#2_Pre-therapy sample_Non_Responder |
| GSM6481976 |
Patient#2_On-treatment week 4 sample_Non_Responder |
| GSM6481977 |
Patient#2_On-treatment week 12 sample_Non_Responder |
| GSM6481978 |
Patient#6_Pre-therapy sample_Non_Responder |
| GSM6481979 |
Patient#6_On-treatment week 4 sample_Non_Responder |
| GSM6481980 |
Patient#7_Pre-therapy sample_Non_Responder |
| GSM6481981 |
Patient#7_On-treatment week 4 sample_Non_Responder |
| GSM6481982 |
Patient#7_On-treatment week 12 sample_Non_Responder |
| GSM6481983 |
Patient#8_Pre-therapy sample_Non_Responder |
| GSM6481984 |
Patient#8_On-treatment week 4 sample_Non_Responder |
| GSM6481985 |
Patient#8_On-treatment week 12 sample_Non_Responder |
| GSM6481986 |
Patient#10_Pre-therapy sample_Non_Responder |
| GSM6481987 |
Patient#10_On-treatment week 4 sample_Non_Responder |
| GSM6481988 |
Patient#10_On-treatment week 12 sample_Non_Responder |
| GSM6481989 |
Patient#13_Pre-therapy sample_Non_Responder |
| GSM6481990 |
Patient#13_On-treatment week 4 sample_Non_Responder |
| GSM6481991 |
Patient#13_On-treatment week 12 sample_Non_Responder |
| GSM6481992 |
Patient#15_Pre-therapy sample_Non_Responder |
| GSM6481993 |
Patient#15_On-treatment week 4 sample_Non_Responder |
| GSM6481994 |
Patient#15_On-treatment week 12 sample_Non_Responder |
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| Relations |
| BioProject |
PRJNA871250 |
| Supplementary file |
Size |
Download |
File type/resource |
| GSE211645_RAW.tar |
230.0 Kb |
(http)(custom) |
TAR (of RCC) |
| Processed data included within Sample table |
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