Quantifying Systemic Immunosuppression to Personalize Cancer Therapy

Breast Cancer Clinical Trial

— Serpentine  

Official title:

Quantifying Systemic Immunosuppression to Personalize Cancer Therapy

Clinical Trial Details — Status: Recruiting

Administrative data

• NCT number: NCT05621837
• Other study ID #: INT 48/21
• Status: Recruiting
• Start date: March 10, 2022
• Est. completion date: May 17, 2024

Study information

• Verified date: September 2022
• Source: Fondazione IRCCS Istituto Nazionale dei Tumori, Milano
• Contact: Licia Rivoltini
• Phone: +3902/23903245
• Email: licia.rivoltini[@]istitutotumori.mi.it
• Is FDA regulated: No
• Study type: Observational

Clinical Trial Summary

The Serpentine (Stratify cancER PatiENTs by ImmuNosupprEssion) project, represents the most consistent effort so far attempted to translate MDSC into clinical practise by producing an off-the-shelf compliant assay for quantifying these cells in peripheral blood.

Description:

The study will demonstrate that this assay helps personalizing cancer therapies by tailoring them to immune patient features. The project will also take advantage of innovative and high-throughput techniques to define additional MDSC related biomarkers and, most importantly, to identify novel drugs for Myeloid-derived Suppressor Cells (MDSC) blocking in predisposed patients. Finally,it will perform the first survey assessing the link between MDSC and "perceived social isolation", an emerging western social problem recently shown to cause myeloid cell dysfunction and immunosuppression though neuroendocrine circuits. Globally, the Serpentine proposal has the ambitious goal to translate into the clinical oncological practise the use of MDSC quantification as a tool for the systematic assessment of systemic immunosuppression, providing at the same time operational insights into the strategies to overcome this pillar mechanism of cancer progression.

Recruitment information / eligibility

• Status: Recruiting
• Enrollment: 1000
• Est. completion date: May 17, 2024
• Est. primary completion date: May 17, 2024
• Accepts healthy volunteers: Accepts Healthy Volunteers
• Gender: All
• Age group: 18 Years to 90 Years

Eligibility

Inclusion Criteria

• Histologically documented diagnosis of metastatic/locally advanced melanoma, hormone-refractory breast cancer, RCC and UC, SCCHN, SCC or NSCLC, stage III resectable NSCLC will also be included

• Will and ability to comply with the protocol

• Willingness and ability to provide an adequate archival Formalin-Fixed Paraffin-Embedded (FFPE) tumor sample available for exploratory biomarker analysis

• Age from 18 to 90 years at the time of recruitment

• ECOG Performance Status <= 2

• Understanding and signature of the informed consent

• Consenting to participate to the socio-economical-psychological survey

Exclusion Criteria

• Known history of HIV infection

• Serious neurological or psychiatric disorders

• Pregnancy or lactation

• Inability or unwillingness of participant to give written informed consent

• Inability or unwillingness to be regularly followed up at the same center

Related Conditions & MeSH terms

• Breast Cancer
• Carcinoma
• Carcinoma, Renal Cell
• Carcinoma, Small Cell
• Melanoma
• NSCLC
• Renal Cell Carcinoma
• Small Cell Carcinoma
• Small Cell Lung Carcinoma
• Squamous Cell Carcinoma of Head and Neck
• Urinary Bladder Cancer
• Urinary Bladder Neoplasms

Intervention

Other:
• MDSC quantification
Blood sample will be collected at baseline and during therapy, and, optionally, in case of disease progression (PD).

Locations

Country	Name	City	State
Italy	Fondazione IRCCS Istituto Nazionale dei Tumori	Milan

Sponsors (1)

Lead Sponsor	Collaborator
Fondazione IRCCS Istituto Nazionale dei Tumori, Milano

Country where clinical trial is conducted

Italy, 

References & Publications (23)

Apetoh L, Tesniere A, Ghiringhelli F, Kroemer G, Zitvogel L. Molecular interactions between dying tumor cells and the innate immune system determine the efficacy of conventional anticancer therapies. Cancer Res. 2008 Jun 1;68(11):4026-30. doi: 10.1158/0008-5472.CAN-08-0427. — View Citation

Blattner C, Fleming V, Weber R, Himmelhan B, Altevogt P, Gebhardt C, Schulze TJ, Razon H, Hawila E, Wildbaum G, Utikal J, Karin N, Umansky V. CCR5+ Myeloid-Derived Suppressor Cells Are Enriched and Activated in Melanoma Lesions. Cancer Res. 2018 Jan 1;78(1):157-167. doi: 10.1158/0008-5472.CAN-17-0348. Epub 2017 Oct 31. — View Citation

Bronte V, Brandau S, Chen SH, Colombo MP, Frey AB, Greten TF, Mandruzzato S, Murray PJ, Ochoa A, Ostrand-Rosenberg S, Rodriguez PC, Sica A, Umansky V, Vonderheide RH, Gabrilovich DI. Recommendations for myeloid-derived suppressor cell nomenclature and characterization standards. Nat Commun. 2016 Jul 6;7:12150. doi: 10.1038/ncomms12150. — View Citation

Cortez-Retamozo V, Etzrodt M, Newton A, Rauch PJ, Chudnovskiy A, Berger C, Ryan RJ, Iwamoto Y, Marinelli B, Gorbatov R, Forghani R, Novobrantseva TI, Koteliansky V, Figueiredo JL, Chen JW, Anderson DG, Nahrendorf M, Swirski FK, Weissleder R, Pittet MJ. Origins of tumor-associated macrophages and neutrophils. Proc Natl Acad Sci U S A. 2012 Feb 14;109(7):2491-6. doi: 10.1073/pnas.1113744109. Epub 2012 Jan 30. — View Citation

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Dumeaux V, Fjukstad B, Fjosne HE, Frantzen JO, Holmen MM, Rodegerdts E, Schlichting E, Borresen-Dale AL, Bongo LA, Lund E, Hallett M. Interactions between the tumor and the blood systemic response of breast cancer patients. PLoS Comput Biol. 2017 Sep 28;13(9):e1005680. doi: 10.1371/journal.pcbi.1005680. eCollection 2017 Sep. — View Citation

Engblom C, Pfirschke C, Pittet MJ. The role of myeloid cells in cancer therapies. Nat Rev Cancer. 2016 Jul;16(7):447-62. doi: 10.1038/nrc.2016.54. — View Citation

Filipazzi P, Huber V, Rivoltini L. Phenotype, function and clinical implications of myeloid-derived suppressor cells in cancer patients. Cancer Immunol Immunother. 2012 Feb;61(2):255-263. doi: 10.1007/s00262-011-1161-9. Epub 2011 Nov 27. Review. — View Citation

Filipazzi P, Valenti R, Huber V, Pilla L, Canese P, Iero M, Castelli C, Mariani L, Parmiani G, Rivoltini L. Identification of a new subset of myeloid suppressor cells in peripheral blood of melanoma patients with modulation by a granulocyte-macrophage colony-stimulation factor-based antitumor vaccine. J Clin Oncol. 2007 Jun 20;25(18):2546-53. doi: 10.1200/JCO.2006.08.5829. — View Citation

Fleming V, Hu X, Weber R, Nagibin V, Groth C, Altevogt P, Utikal J, Umansky V. Targeting Myeloid-Derived Suppressor Cells to Bypass Tumor-Induced Immunosuppression. Front Immunol. 2018 Mar 2;9:398. doi: 10.3389/fimmu.2018.00398. eCollection 2018. — View Citation

Gabrilovich DI. Myeloid-Derived Suppressor Cells. Cancer Immunol Res. 2017 Jan;5(1):3-8. doi: 10.1158/2326-6066.CIR-16-0297. — View Citation

Galluzzi L, Buqué A, Kepp O, Zitvogel L, Kroemer G. Immunological Effects of Conventional Chemotherapy and Targeted Anticancer Agents. Cancer Cell. 2015 Dec 14;28(6):690-714. doi: 10.1016/j.ccell.2015.10.012. Review. — View Citation

Groth C, Hu X, Weber R, Fleming V, Altevogt P, Utikal J, Umansky V. Immunosuppression mediated by myeloid-derived suppressor cells (MDSCs) during tumour progression. Br J Cancer. 2019 Jan;120(1):16-25. doi: 10.1038/s41416-018-0333-1. Epub 2018 Nov 9. — View Citation

Huber V, Vallacchi V, Fleming V, Hu X, Cova A, Dugo M, Shahaj E, Sulsenti R, Vergani E, Filipazzi P, De Laurentiis A, Lalli L, Di Guardo L, Patuzzo R, Vergani B, Casiraghi E, Cossa M, Gualeni A, Bollati V, Arienti F, De Braud F, Mariani L, Villa A, Altevogt P, Umansky V, Rodolfo M, Rivoltini L. Tumor-derived microRNAs induce myeloid suppressor cells and predict immunotherapy resistance in melanoma. J Clin Invest. 2018 Dec 3;128(12):5505-5516. doi: 10.1172/JCI98060. Epub 2018 Nov 5. — View Citation

Ostrand-Rosenberg S. Myeloid derived-suppressor cells: their role in cancer and obesity. Curr Opin Immunol. 2018 Apr;51:68-75. doi: 10.1016/j.coi.2018.03.007. Epub 2018 Mar 13. — View Citation

Peguillet I, Milder M, Louis D, Vincent-Salomon A, Dorval T, Piperno-Neumann S, Scholl SM, Lantz O. High numbers of differentiated effector CD4 T cells are found in patients with cancer and correlate with clinical response after neoadjuvant therapy of breast cancer. Cancer Res. 2014 Apr 15;74(8):2204-16. doi: 10.1158/0008-5472.CAN-13-2269. Epub 2014 Feb 17. — View Citation

Ribas A, Wolchok JD. Cancer immunotherapy using checkpoint blockade. Science. 2018 Mar 23;359(6382):1350-1355. doi: 10.1126/science.aar4060. Epub 2018 Mar 22. Review. — View Citation

Spitzer MH, Carmi Y, Reticker-Flynn NE, Kwek SS, Madhireddy D, Martins MM, Gherardini PF, Prestwood TR, Chabon J, Bendall SC, Fong L, Nolan GP, Engleman EG. Systemic Immunity Is Required for Effective Cancer Immunotherapy. Cell. 2017 Jan 26;168(3):487-502.e15. doi: 10.1016/j.cell.2016.12.022. Epub 2017 Jan 19. — View Citation

Steinberg SM, Shabaneh TB, Zhang P, Martyanov V, Li Z, Malik BT, Wood TA, Boni A, Molodtsov A, Angeles CV, Curiel TJ, Whitfield ML, Turk MJ. Myeloid Cells That Impair Immunotherapy Are Restored in Melanomas with Acquired Resistance to BRAF Inhibitors. Cancer Res. 2017 Apr 1;77(7):1599-1610. doi: 10.1158/0008-5472.CAN-16-1755. Epub 2017 Feb 15. — View Citation

Welters MJ, van der Sluis TC, van Meir H, Loof NM, van Ham VJ, van Duikeren S, Santegoets SJ, Arens R, de Kam ML, Cohen AF, van Poelgeest MI, Kenter GG, Kroep JR, Burggraaf J, Melief CJ, van der Burg SH. Vaccination during myeloid cell depletion by cancer chemotherapy fosters robust T cell responses. Sci Transl Med. 2016 Apr 13;8(334):334ra52. doi: 10.1126/scitranslmed.aad8307. — View Citation

Wesolowski R, Markowitz J, Carson WE 3rd. Myeloid derived suppressor cells - a new therapeutic target in the treatment of cancer. J Immunother Cancer. 2013 Jul 15;1:10. doi: 10.1186/2051-1426-1-10. eCollection 2013. — View Citation

Wilmott JS, Long GV, Howle JR, Haydu LE, Sharma RN, Thompson JF, Kefford RF, Hersey P, Scolyer RA. Selective BRAF inhibitors induce marked T-cell infiltration into human metastatic melanoma. Clin Cancer Res. 2012 Mar 1;18(5):1386-94. doi: 10.1158/1078-0432.CCR-11-2479. Epub 2011 Dec 12. — View Citation

* Note: There are 23 references in all — Click here to view all references

Outcome

Type	Measure	Description	Time frame	Safety issue
Primary	Immunological endpoint	Frequency, in terms of percentage and absolute count of the defined cell subsets in whole blood and stored PBMC	baseline, that is prior to start the therapy (Visit_1)
Primary	Immunological endpoint	Frequency, in terms of percentage and absolute count of the defined cell subsets in whole blood and stored PBMC	around one month/before the time-corresponding treatment cycle (Visit_2)
Primary	Immunological endpoint	Frequency, in terms of percentage and absolute count of the defined cell subsets in whole blood and stored PBMC	around three months/before the time-corresponding treatment cycle (Visit_3)
Primary	Immunological endpoint	Frequency, in terms of percentage and absolute count of the defined cell subsets in whole blood and stored PBMC	Through study completion, an average of 2 year
Primary	Clinical endpoint_PFS	Progression-Free Survival (PFS)	Through study completion, an average of 2 year
Primary	Clinical endpoint_OS	Overall Survival (OS)	Through study completion, an average of 2 year
Primary	Clinical endpoint_ORR	Overall Response Rate (ORR)	Through study completion, an average of 2 year
Secondary	Myeloid Index Score (MIS)	Myeloid Index Score (MIS)=0 vs MIS>0 or higher values	Through study completion, an average of 2 year
Secondary	Index score values	Index score values on plasma cytokine concentration or MDSC-miRs	Through study completion, an average of 2 year
Secondary	Transcriptional signatures_PBMC	Transcriptional signatures identified on PBMC and sorted myeloid cells form whole blood	baseline, that is prior to start the therapy (Visit_1) or at the first disease evaluation (around after three months)
Secondary	Transcriptional signatures_myeloid cells	Transcriptional signatures identified on sorted myeloid cells form whole blood	baseline, that is prior to start the therapy (Visit_1) or at the first disease evaluation (around after three months)
Secondary	Phospho-kinome signature result	Phospho-kinome signature as assessed by Cytof analysis in stored PBMC	Through study completion, an average of 2 year
Secondary	Metabolomic profiles	The concentration of individual metabolites or cluster of metabolites implicated in amino acid and lipid metabolism	Through study completion, an average of 2 year
Secondary	Socio-Economical-Psychological (SEP) score	Socioeconomic and psychological (perceived social isolation) score, calculated through a dedicated questionnaire	Through study completion, an average of 2 year