Multiomics Approach in Metastatic Clear Renal Cell Carcnoma
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ClinicalTrials.gov Identifier: NCT05782400 |
Recruitment Status :
Recruiting
First Posted : March 23, 2023
Last Update Posted : March 23, 2023
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The choice of the best strategy in treatment-naive metastatic clear-cell renal cell carcinoma (mccRCC) patients is becoming an issue, since no biomarkers are available to guide the treatment allocation strategy. The elucidation of predictive factors to develop tailored strategies of treatment is an urgent unmet clinical need. Recently there has been a great deal of interest in non-invasive liquid biopsy methods for their ability to detect and characterize circulating cell-free DNA (cfDNA), extracellular vescicles associated RNAs and circulating tumor cells and to allow longitudinal evaluation of tumor evolution. An additional field of intense research is also radiomics as a novel approach to develop predictive tools by correlating imaging features to tumor characteristics including histology, tumor grade, genetic patterns and molecular phenotypes, as well as clinical outcomes in patients with renal neoplasms.
The use of computational approaches to integrate informations, obtained from genomic and transcriptomic analysis of neoplastic tissues and of cfDNA) or microvescicle-associated RNA in blood and from radiomics, can be exploited to define an optimal allocation strategy for patients with mccRCC undergoing first-line therapy and to identify novel targets in mccRCC.
Aims of the study are: to identify molecular subtypes, signatures or biomarkers in mccRCC associated with different clinical outcome by applying bioinformatic analysis; to extract descriptive features in mccRCC from radiological imaging data; to integrate omics-driven and clinic-pathological characteristics with radiomic features extracted from the tumor and tumor environment to inform on biological features relevant to therapy outcome.
This multicentric prospective study will evaluate genomics and radiomics in treatment-naïve advanced ccRCC patients. 100 eligible patients will be identified after screening, candidate to receive first-line treatment as investigator choice per clinical practice. Tissue and plasma samples and CT exams will be collected at different intervals to provide a comprehensive molecular profile and radiomic features extrapolation, respectively. Artificial neural networks will be used to build a genomic-radiomic profile of patients to correlate to treatment response. This sample size will allow an exploratory analysis of the prognostic and predictive performance of the multiomic classifier, to be subsequently validated in a larger expansion cohort of patients.
Condition or disease | Intervention/treatment |
---|---|
Metastatic Clear Cell Renal Carcinoma | Radiation: CT scan Biological: Plasma collection |
Study Type : | Observational |
Estimated Enrollment : | 100 participants |
Observational Model: | Other |
Time Perspective: | Prospective |
Official Title: | Multiomics Approach for Patients Stratification and Novel Target Identification in Metastatic Clear Renal Cell Carcnoma |
Actual Study Start Date : | February 28, 2023 |
Estimated Primary Completion Date : | February 28, 2026 |
Estimated Study Completion Date : | September 30, 2027 |
- Radiation: CT scan
CT scan at baseline and then every three months as per clinical practice. The standardization of the procedure of images' collection through a CT- acquisition's protocol has been planned to control bias.
- Biological: Plasma collection
● Blood samples will be collected at baseline, at 1 month and at the first PD. Sixteen ml of blood will be collected in EDTA tubes and centrifuged at 1900×g for 10 min at 4 °C within 2 h after drawing to collect plasma, which will be stored at -80°C until analysis. Plasma samples will be sent to the Laboratory of Pharmacogenetics - Unit of Clinical Pharmacology and Pharmacogenetics - University Hospital of Pisa. Plasma samples will be used to isolate cell free DNA (cfDNA) and microvesicles-derived RNA for molecular analysis.
- Blood and tissue analysis [ Time Frame: 36 Months ]Investigation of the predictive role of circulating miRNAs and gene alterations in patients who respond to first-line treatments versus those who do not respond before treatment, after 1 month (4 weeks), after 3 months (12 weeks), and at the time of disease progression. Tissue and blood samples will be studied with Illumina NextSeq 500 platform and analyzed with the GeneGlobe online software. Methods that combine different clustering algorithms and gene variability metrics will be used to identify robust mccRCC molecular subtypes from expression data and to investigate their association with clinical outcomes.
- Radiomics analysis [ Time Frame: 36 Months ]Characterization of alterations in radiological imaging data in mRCC in radiological imaging data in mRCC through CT segmentation. Through open-source software analysis, we aim to extrapolate from the image patterns of quantitative characteristics (features) not visible to the naked eye, compare different images of the same disease with known diagnosis (ground truth), and develop a predictive computational model of disease. CT scan for Radiomics will be performed at baseline and every three months.
- Computational analysis of mutational, transcriptomic and radiomic data [ Time Frame: 48 Months ]Radio-genomic analysis to identify a Radiomics and a molecular score. An artificial neural network-based approach to creating a combined Genomic plus Radiomics signature. Integration of high-dimensional data obtained with clinical data. For this task, we will incorporate NGS and Radiomics datasets to develop an ad hoc AI-based classification model able to efficiently merge and evaluate the array of available information. The achieved biotechnological signature of mccRCC and its evolution over time will also be assessed to suggest an easily interpretable predictive tool (nomogram) of clinical outcome.
Biospecimen Retention: Samples With DNA
- FFPE samples will be collected at baseline and, when feasible, at the first progression of the disease (PD). FFPE specimens will be sent to the coordinator site (INT). A centralized designated expert pathology will review these specimens to confirm the diagnosis and to identify regions of interest. mRNA and DNA sequencing will be used to dissect the molecular and genomic profiles of this cohort.
- Blood samples will be collected at baseline, at 1 month and at the first PD. Sixteen ml of blood will be collected in EDTA tubes and centrifuged at 1900×g for 10 min at 4 °C within 2 h after drawing to collect plasma, which will be stored at -80°C until analysis.
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Ages Eligible for Study: | 18 Years and older (Adult, Older Adult) |
Sexes Eligible for Study: | Male |
Gender Based Eligibility: | Yes |
Accepts Healthy Volunteers: | No |
Sampling Method: | Non-Probability Sample |
INCLUSION CRITERIA:
- Signed Written Informed Consent
- Male or female subjects aged ≥18 years old
- Histologically confirmed advanced/metastatic RCC with predominantly clear-cell subtype
- Previous nephrectomy is permitted
- Availability of tumor tissue sample for biomarker analysis
- Advanced (not amenable to curative surgery or radiation therapy) or metastatic (AJCC Stage IV) RCC, candidate to receive first-line systemic treatment with monotherapy TKI or IO+TKI or IO+IO
- No prior systemic therapy for RCC with the following exception: prior adjuvant therapy for completely resectable RCC (concluded at least 6 months before study entry)
- All IMDC risk (good, intermediate, poor)
- TC scan performed with and without contrast medium, at baseline (according to protocol guidelines as reported below in Table 1)
- At least one measurable lesion as defined by Response Evaluation Criteria in Solid Tumors (RECIST) version 1.1
- Eastern Cooperative Oncology Group performance status 0 or 1
- Capable of understanding and complying with the protocol requirements.
EXCLUSION CRITERIA:
- Any prior systemic treatment for RCC in the advanced/metastatic settings
- Prior treatment with an anti-PD-1, anti-PD-L1, anti-PD-L2, anti-CD137, or anti-CTLA-4 antibody, or any other antibody or drug specifically targeting T-cell co-stimulation or checkpoint pathways
- Previous exposure to tyrosine kinase inhibitors in the advanced/metastatic settings
- Active seizure disorder or evidence of brain metastases, spinal cord compression, or carcinomatous meningitis
- Diagnosis of any non-RCC malignancy occurring within 2 years prior to the date of the start of treatment except for adequately treated basal cell or squamous cell skin cancer, or carcinoma in situ of the breast or of the cervix or low-grade prostate cancer (≤pT2, N0; Gleason 6) with no plans for treatment intervention
- Radiation therapy for bone metastasis within 2 weeks, any other external radiation therapy within 4 weeks before the start of treatment. Subjects with clinically relevant ongoing complications from prior radiation therapy are not eligible.
To learn more about this study, you or your doctor may contact the study research staff using the contact information provided by the sponsor.
Please refer to this study by its ClinicalTrials.gov identifier (NCT number): NCT05782400
Contact: Giuseppe Procopio, MD | 00390223903813 | giuseppe.procopio@istitutotumori.mi.it | |
Contact: Marco Stellato, MD | 00390223903813 | marco.stellato@istitutotumori.mi.it |
Italy | |
Istituto Tumori | Recruiting |
Milan, Mi, Italy, 20156 | |
Contact: Giuseppe Dr Procopio, MD +39223904450 Giuseppe.Procopio@istitutotumori.mi.it |
Principal Investigator: | Giuseppe Procopio, MD | Fondazione IRCCS istituto Nazionale dei Tumori di Milano |
Responsible Party: | Giuseppe Procopio, Director of Genitourinary Medical Oncology, Fondazione IRCCS Istituto Nazionale dei Tumori, Milano |
ClinicalTrials.gov Identifier: | NCT05782400 |
Other Study ID Numbers: |
INT220-22 |
First Posted: | March 23, 2023 Key Record Dates |
Last Update Posted: | March 23, 2023 |
Last Verified: | March 2023 |
Individual Participant Data (IPD) Sharing Statement: | |
Plan to Share IPD: | Undecided |
Studies a U.S. FDA-regulated Drug Product: | No |
Studies a U.S. FDA-regulated Device Product: | No |
Carcinoma, Renal Cell Kidney Neoplasms Adenocarcinoma Carcinoma Neoplasms, Glandular and Epithelial Neoplasms by Histologic Type Neoplasms Urologic Neoplasms |
Urogenital Neoplasms Neoplasms by Site Female Urogenital Diseases Female Urogenital Diseases and Pregnancy Complications Urogenital Diseases Kidney Diseases Urologic Diseases Male Urogenital Diseases |