- ICH GCP
- US Clinical Trials Registry
- Clinical Trial NCT05621837
Quantifying Systemic Immunosuppression to Personalize Cancer Therapy (Serpentine)
April 29, 2025 updated by: Fondazione IRCCS Istituto Nazionale dei Tumori, Milano
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.
Study Overview
Status
Recruiting
Conditions
Intervention / Treatment
Detailed 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.
Study Type
Observational
Enrollment (Estimated)
1000
Contacts and Locations
This section provides the contact details for those conducting the study, and information on where this study is being conducted.
Study Contact
- Name: Licia Rivoltini
- Phone Number: +3902/23903245
- Email: licia.rivoltini@istitutotumori.mi.it
Study Contact Backup
- Name: Paola Frati
- Phone Number: +3902/23903036
- Email: paola.frati@gmail.com
Study Locations
-
-
-
Milan, Italy, 20033
- Recruiting
- Fondazione IRCCS Istituto Nazionale dei Tumori
-
Contact:
- Licia Rivoltini, MD
- Phone Number: +3902/23903245
- Email: licia.rivoltini@istitutotumori.mi.it
-
Contact:
- Paola Frati
- Phone Number: +3902/23903036
- Email: paola.frati@istitutotumori.mi.it
-
-
Participation Criteria
Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.
Eligibility Criteria
Ages Eligible for Study
14 years to 86 years (Adult, Older Adult)
Accepts Healthy Volunteers
Yes
Sampling Method
Probability Sample
Study Population
Patients with five diverse tumor histotypes (n=600) will be collected in parallel clinical case-sets, with power calculation estimated on the basis of MIS validation in melanoma (n=100 patients per histotypes, with the exception of the 200 patients to be enrolled for NSCLC).
In addition, a group of age and gender-matched healthy donors (n=400) will be also included to provide normal values of the myeloid-related parameters under physiological conditions.
Description
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
Study Plan
This section provides details of the study plan, including how the study is designed and what the study is measuring.
How is the study designed?
Design Details
- Observational Models: Case-Control
- Time Perspectives: Prospective
Cohorts and Interventions
Group / Cohort |
Intervention / Treatment |
|---|---|
|
Metastatic melanoma patients
MDSC quantification in Metastatic melanoma patients undergoing first/second-line treatment with BRAF and MEK inhibitors (BRAFi+MEKi) or immune checkpoint inhibitors (antagonists of PD-1 or CTL4, or both) (n=100);
|
Blood sample will be collected at baseline and during therapy, and, optionally, in case of disease progression (PD).
|
|
hormone receptor positive/Human Epidermal growth factor Receptor-2 negative cancer patients
MDSC quantification in Metastatic HR+(hormone receptor positive)/ HER2-(Human Epidermal growth factor Receptor-2 negative) breast cancer patients already treated with a combination of an hormonal agent and a CDK(Cyclin-dependent kinase)4/6 inhibitor and receiving chemotherapy (n=100);
|
Blood sample will be collected at baseline and during therapy, and, optionally, in case of disease progression (PD).
|
|
Advanced RCC(renal cell carcinoma) patients
MDSC quantification Advanced RCC patients receiving immune checkpoint inhibitors (antagonists of PD-1, PD-L1 or CTL4, or combinations) or anti-angiogenics alone or combined with immune checkpoint inhibitors; locally advanced/metastatic UC(Urothelial Carcinoma) patients receiving first-line chemotherapy, immune checkpoint inhibitors or combinations (n=100);
|
Blood sample will be collected at baseline and during therapy, and, optionally, in case of disease progression (PD).
|
|
SCCHN or SCC(Small Cell Carcinoma) patients
MDSC quantification in SCCHN or SCC(Small Cell Carcinoma) patients treated with first-line chemotherapy, cetuximab,immune checkpoint inhibitors or combinations (n=100).
|
Blood sample will be collected at baseline and during therapy, and, optionally, in case of disease progression (PD).
|
|
NSCLC patients
MDSC quantification in NSCLC patients undergoing radical surgery for stage III cancer (n=100);patients with unresectable/metastatic NSCLC receiving first line treatment with chemotherapy, immune checkpoint inhibitors (antagonists of PD-1, PD-L1 or CTL4) or combinations (n=100).
|
Blood sample will be collected at baseline and during therapy, and, optionally, in case of disease progression (PD).
|
|
Age and gender-matched healthy donors
Age and gender-matched healthy donors (n=400) will be enrolled in the study, to allow us investigating the same immunological parameters under physiological conditions and define normal values for the myeloid-related biomarkers here assessed.
|
Blood sample will be collected at baseline and during therapy, and, optionally, in case of disease progression (PD).
|
What is the study measuring?
Primary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
|
Immunological endpoint
Time Frame: baseline, that is prior to start the therapy (Visit_1)
|
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)
|
|
Immunological endpoint
Time Frame: around one month/before the time-corresponding treatment cycle (Visit_2)
|
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)
|
|
Immunological endpoint
Time Frame: around three months/before the time-corresponding treatment cycle (Visit_3)
|
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)
|
|
Immunological endpoint
Time Frame: Through study completion, an average of 2 year
|
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
|
|
Clinical endpoint_PFS
Time Frame: Through study completion, an average of 2 year
|
Progression-Free Survival (PFS)
|
Through study completion, an average of 2 year
|
|
Clinical endpoint_OS
Time Frame: Through study completion, an average of 2 year
|
Overall Survival (OS)
|
Through study completion, an average of 2 year
|
|
Clinical endpoint_ORR
Time Frame: Through study completion, an average of 2 year
|
Overall Response Rate (ORR)
|
Through study completion, an average of 2 year
|
Secondary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
|
Myeloid Index Score (MIS)
Time Frame: Through study completion, an average of 2 year
|
Myeloid Index Score (MIS)=0 vs MIS>0 or higher values
|
Through study completion, an average of 2 year
|
|
Index score values
Time Frame: Through study completion, an average of 2 year
|
Index score values on plasma cytokine concentration or MDSC-miRs
|
Through study completion, an average of 2 year
|
|
Transcriptional signatures_PBMC
Time Frame: baseline, that is prior to start the therapy (Visit_1) or at the first disease evaluation (around after three months)
|
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)
|
|
Transcriptional signatures_myeloid cells
Time Frame: baseline, that is prior to start the therapy (Visit_1) or at the first disease evaluation (around after three months)
|
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)
|
|
Phospho-kinome signature result
Time Frame: Through study completion, an average of 2 year
|
Phospho-kinome signature as assessed by Cytof analysis in stored PBMC
|
Through study completion, an average of 2 year
|
|
Metabolomic profiles
Time Frame: Through study completion, an average of 2 year
|
The concentration of individual metabolites or cluster of metabolites implicated in amino acid and lipid metabolism
|
Through study completion, an average of 2 year
|
|
Socio-Economical-Psychological (SEP) score
Time Frame: Through study completion, an average of 2 year
|
Socioeconomic and psychological (perceived social isolation) score, calculated through a dedicated questionnaire
|
Through study completion, an average of 2 year
|
Collaborators and Investigators
This is where you will find people and organizations involved with this study.
Investigators
- Principal Investigator: Licia Rivoltini, Fondazione IRCCS Istituto Nazionale Tumori - Milan
Publications and helpful links
The person responsible for entering information about the study voluntarily provides these publications. These may be about anything related to the study.
General Publications
- 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.
- Galluzzi L, Buque 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- Gabrilovich DI. Myeloid-Derived Suppressor Cells. Cancer Immunol Res. 2017 Jan;5(1):3-8. doi: 10.1158/2326-6066.CIR-16-0297.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- De Henau O, Rausch M, Winkler D, Campesato LF, Liu C, Cymerman DH, Budhu S, Ghosh A, Pink M, Tchaicha J, Douglas M, Tibbitts T, Sharma S, Proctor J, Kosmider N, White K, Stern H, Soglia J, Adams J, Palombella VJ, McGovern K, Kutok JL, Wolchok JD, Merghoub T. Overcoming resistance to checkpoint blockade therapy by targeting PI3Kgamma in myeloid cells. Nature. 2016 Nov 17;539(7629):443-447. doi: 10.1038/nature20554. Epub 2016 Nov 9.
- 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.
- Crunkhorn S. Cancer: New path to improving immunotherapy. Nat Rev Drug Discov. 2018 Mar;17(3):164. doi: 10.1038/nrd.2018.22. Epub 2018 Feb 16. No abstract available.
- 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.
Study record dates
These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.
Study Major Dates
Study Start (Actual)
March 10, 2022
Primary Completion (Estimated)
December 31, 2026
Study Completion (Estimated)
December 31, 2026
Study Registration Dates
First Submitted
October 3, 2022
First Submitted That Met QC Criteria
November 11, 2022
First Posted (Actual)
November 18, 2022
Study Record Updates
Last Update Posted (Actual)
May 2, 2025
Last Update Submitted That Met QC Criteria
April 29, 2025
Last Verified
April 1, 2025
More Information
Terms related to this study
Additional Relevant MeSH Terms
- Urogenital Diseases
- Urogenital Neoplasms
- Neoplasms by Site
- Neoplasms
- Male Urogenital Diseases
- Kidney Diseases
- Urologic Diseases
- Female Urogenital Diseases
- Female Urogenital Diseases and Pregnancy Complications
- Respiratory Tract Diseases
- Neoplasms by Histologic Type
- Lung Diseases
- Head and Neck Neoplasms
- Neoplasms, Glandular and Epithelial
- Adenocarcinoma
- Respiratory Tract Neoplasms
- Thoracic Neoplasms
- Lung Neoplasms
- Urologic Neoplasms
- Kidney Neoplasms
- Carcinoma, Bronchogenic
- Bronchial Neoplasms
- Urinary Bladder Diseases
- Carcinoma, Squamous Cell
- Squamous Cell Carcinoma of Head and Neck
- Carcinoma
- Carcinoma, Renal Cell
- Small Cell Lung Carcinoma
- Urinary Bladder Neoplasms
- Carcinoma, Small Cell
Other Study ID Numbers
- INT 48/21
Plan for Individual participant data (IPD)
Plan to Share Individual Participant Data (IPD)?
UNDECIDED
Drug and device information, study documents
Studies a U.S. FDA-regulated drug product
No
Studies a U.S. FDA-regulated device product
No
product manufactured in and exported from the U.S.
No
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