Neoplasms

Urinary Tract, Sexual Organs, and Pregnancy Conditions

All Conditions

Rare Diseases

Carcinoma, Renal Cell

Kidney Neoplasms

Carcinoma

Urologic Neoplasms

Urogenital Neoplasms

Urogenital Diseases

Female Urogenital Diseases

Pregnancy Complications

Female Urogenital Diseases and Pregnancy Complications

Kidney Diseases

Urologic Diseases

Male Urogenital Diseases

Adenocarcinoma

Neoplasms, Glandular and Epithelial

Neoplasms by Histologic Type

Renal Cell Carcinoma

Antineoplastic Agents

All Drugs and Chemicals

Fibrinolytic Agents

Anticoagulants

Nivolumab

Everolimus

Axitinib

Heparin

Immunomodulating Agents

Sunitinib

Calcium heparin

FFPE, blood samples (liquid biopsy, heparin and EDTA blood) performed in patients presenting a renal metastatic cancer receiving treatment as standard practice according to physician's choice (2nd or 3rd line of treatment with nivolumab, everolimus, axitinib or cabozantinib \[in France only\], as per product SmPC or 1st line treatment with sunitinib or pazopanib or receiving 2nd or 3rd line of treatment with nivolumab)

Immunological and tumour characterization

BLANC Ellen

BOYLE J Helen, MD

BOYLE Ellen, MD

The BIOREN project aims are to characterize the genetic background of renal cell carcinomas and their immune environment, to try and identify biomarkers of response and to better understand the mechanisms of resistance to nivolumab in renal cancer.

Around 338,000 new cases of renal cell carcinoma (RCC) are diagnosed worldwide per year (1). RCC is one of the most immune responsive human cancers. For a long time the only available treatment were high-dose IL-2 and IFN-α with only a few patients achieving durable responses. Clinical trials conducted in the past 15 years have led to the approval of several anti-angiogenic treatments, mainly vascular endothelial growth factor receptor (VEGFR) inhibitors and mTOR inhibitors. Currently most patients receive first line anti-VEGF therapy.

Recently a better understanding of the mechanisms by which tumours evade the immune system has led to the development of checkpoint inhibitors, such as anti CTLA-4, anti-PD-1 and anti-PD-L1 antibodies that have been tested in various tumour types.

Recently, the US Food and Drug Administration (FDA) and the European Medicines Agency (EMA) have approved the human IgG4 anti-PD1 monoclonal antibody, nivolumab, for advanced/metastatic clear cell RCC (ccRCC) patients who have received prior antiangiogenic therapy. PD-1 is a key immune-checkpoint receptor (ICR) expressed by activated T cells, which mediates immunosuppression primarily in peripheral tissues, where T cells may encounter the immunosuppressive PD-1 ligands, PD-L1 (B7-H1) and PD-L2(B7-DC) on tumour cells, stromal cells or both.

Despite encouraging results, the clinical response to anti-PD1 is not as wide as expected and there are not any biomarkers 1) that are able to predict which patients will respond and 2) that predict response to nivolumab in patients with ccRCC.

BIOREN is a translational, prospective, observational 3-cohort study.

The aims of BIOREN are to characterize the genetic background of the tumours and also their immune environment, to try and identify biomarkers of response and to better understand the mechanisms of resistance to nivolumab in renal cancer. We will focus on:

* Tregs function and modulation of function,
* NK cells known to be regulated by nivolumab,
* The biological rationale for coupling CXCR4 antagonist with anti PD-1 therapy, analysed with mice models,
* To try to identify biomarkers of response by further characterization of the tumours and evaluating the immune status.

The project will enrol patients receiving in 2nd or 3rd line treatment for metastatic ccRCC: Nivolumab but also, as control cohorts, either everolimus or axitinib (approved treatments in this setting), as well as cabozantinib in France (recently approved in 2nd or 3rd line).

French blood samples and archival FFPE (formalin-fixed paraffin embedded) specimens will be analysed in in France, and also sent to the partners of the Transcan project Consortium (Israel, Italy and Spain).

Archival FFPE specimen

Blood samples performed during standard visits and not requiring additional blood tests:

* Heparin blood (4 x 6ml)
* EDTA blood (5 x 6ml)
* Liquid biopsy (EDTA) (5 x 6ml)

BIOREN (Predictive BIOmarkers in Metastatic RENal Cancer)

BIOREN (Predictive BIOmarkers in Metastatic RENal Cancer) - A Translational Study on Immunotherapy for Metastatic Renal Cancer

Ex vivo effect of CXCR4 antagonists (PCT/IB2011/000120/ EP2528936B1/ US2013/0079292A1) and other Tregs targets antagonists (ICOS, CD39/CD73) or agonists (TLR7L) as putative anti-PD1 resistance mechanisms

NK cytotoxicity will be evaluated through NK cell degranulation (CD107a assay), intracellular staining of the lytic proteins, Grz A and GrzB and intracellular cytokines, GM-CSF, IFNγ, IL-10, TNF. NK cell will be characterized for CXCR4; maturation markers: CD16, CD56, CD57, CD62L, NKG2A; activating receptors markers: CD25, CD69, NKp44, NKp30, NKp46, NKG2D. Ex vivo effect of CXCR4 antagonists on NK cytotoxicity.

immunocompetent model (RENCA), human xenograft model (786 cell) and humanized model

Characterization of the tumours using different techniques (RNASeq whole genome, NGS analysis, IHC, HTG focus RNAseq)

Immune status (Multi-IF analysis, TCR sequencing and clonality analysis, Anti-HERV T cell and humoral response)

Centre Leon Berard

Skin and Connective Tissue Diseases

Breast Neoplasms

Breast Diseases

Skin Diseases

Women with radiologically identified lesions, BIRADS-3/4/5, smaller than 2 cm by radiological assessment (i.e., radiological T1), will be enrolled and invited to donate peripheral blood samples and urine samples at baseline. Radiological images as well as demographic and anatomopathological data will be collected.

If bioptically confirmed T1 breast cancer, patients will undergo a second peripheral blood and urine collection after primary breast cancer surgery.

Women with radiologically identified lesions, BIRADS-3/4/5, smaller than 2 cm by radiological assessment (i.e., radiological T1), will be enrolled and invited to donate peripheral blood samples and urine samples at baseline. Radiological images as well as demographic and anatomopathological data will be collected.

If bioptically confirmed benign lesion, no other samples will be collected.

peripheral blood and urine sample collection

Blood and urine molecular analysis (Timing 0)

Blood and urine molecular analysis (Timing 1)

Gabriele Zoppoli, MD, PhD

This is a translational no-profit study. Our proposal aims at creating a noninvasive Horizontal Data Integration (HDI) classifier for early diagnosis of breast cancer, with the final goal of avoiding in most cases useless biopsies of suspect cases encountered during radiological screening.

Women with radiologically identified lesions, BIRADS-3/4/5, smaller than 2 cm by radiological assessment (i.e., radiological T1), will be enrolled and invited to donate peripheral blood samples (35 ml) and urine samples (50 ml). Radiological images as well as demographic and anatomopathological data will be collected.

Objective of this project is to develop a HDI classifier enabling early noninvasive diagnosis of breast cancer with similar accuracy compared to breast biopsies. Such classifier will be developed based on the correlation between the molecular profile of peripheral blood (ctDNA, proteins, exosomes) and urine (ctDNA) collected at T0 (baseline, before diagnostic biopsy) and bioptic diagnosis. The assessment of the profile of peripheral blood (ctDNA, proteins, exosomes) and urine (ctDNA) at two time points for diagnosed pT1 breast cancers (T0: baseline, before biopsy; T1: after diagnosis of pT1 breast cancer) will allow us to distinguish between tumor- and host-specific molecular alterations in connection with the presence/absence of breast cancer.

Background: Currently, early diagnosis of invasive breast cancer relies on the combined use of mammogram and ultrasound. These approaches are still suboptimal in terms of accuracy, and confirmation biopsy or recall tests are needed in case of radiological suspect. Recently, the study of noninvasive biomarkers in cancer has received enormous interest, fostered by the advancement of technologies and the potential for early detection of malignancies. However, no study has so far tried to apply the simultaneous assessment of biologically different analytes and data-characterization algorithms (radiomics approaches) to increase the accuracy of early breast cancer diagnosis.

Hypothesis: Multiple biological analytes must be combined with the refinement of radiomics algorithms to overcome the current limitations of early breast cancer diagnosis. The overall goal of the project is to develop a horizontal data integration (HDI) classifier enabling early noninvasive diagnosis of invasive breast cancer with high accuracy.

Objectives: Aim 1: To test the performance for the diagnosis of small invasive breast cancers of a) ultrasensitive next-generation sequencing on circulating tumor DNA (ctDNA); b) aptamer-base proteomics arrays on plasmatic proteins; c) radiomics machine-learning algorithms. Aim 2: To develop an HDI classifier based on the aforementioned methods with the aim of reducing the needs for invasive procedures in early breast cancer diagnosis. Aim 3: To improve the performance of the HDI classifier by integrating other potentially transformative methods of noninvasive diagnosis.

Experimental Design: Peripheral blood samples and urine samples will be collected from a prospective cohort of 750 patients with radiologically suspect small breast lesions undergoing diagnostic biopsy at the Diagnostics Senology Unit of San Martino Hospital. Ultrasensitive Next Generation Sequencing (NGS) on plasma ctDNA will be performed using a custom tagged-amplicon panel designed by us on a cohort of 3,269 sequenced breast cancer cases from the GENIE initiative. We also will be applied a new protocol termed cell-free methylated DNA immunoprecipitation and high-throughput sequencing (cfMeDIP-seq) in collaboration with Dana Farber Cancer Institute, Boston for methylome analysis of small quantities of ctDNA from plasma and urine. Potential cancer-related plasma proteins will be analyzed using SomaScan aptamer-base protein arrays in collaboration with the Sidra Medical Center, Doha, Qatar. A radiomics classifier developed by the Senology team on an exploratory subgroup of the ASTOUND trial, sponsored by the University of Genoa, will be trained and tested on the same cohort. Other noninvasive diagnostics methods will be assessed as well. An HDI classifier will be generated on ctDNA, proteomics, and radiomics results, using advanced machine learning methods. Our HDI classifier will finally be integrated as needed with other predictors and validated on our cohort.

Expected Results: 1. Assessment of the performance of cutting-edge noninvasive methodologies in the context of early breast cancer diagnosis. 2. Development of a noninvasive HDI classifier for early breast cancer. 3. Novel biological insights on small breast cancers.

Impact On Cancer: 1. Increase in early breast diagnosis accuracy over current methods. 2. Reduction in the need for recall and invasive tests in breast cancer diagnosis. 3. Long-term impact on breast cancer mortality.

Based on the results of breast lesion biopsy, patients are assigned to two different groups:

* Breast Cancer Stage T1 Group
* Benign Breast Lesion Group

Development of a Horizontal Data Integration Classifier for Noninvasive Early Diagnosis of Breast Cancer

Accuracy of a horizontal data integration (HDI) classifier in correctly classifying pT1 breast cancers from benign lesions (i.e., non-invasive breast adenocarcinoma) presenting with similar radiological features (i.e., maximum lesion diameter smaller or equal to 2 cm). The HDI classifier is defined as a variable mixture of features from different radiomics analyses on baseline mammograms and molecular analyses on peripheral blood (ctDNA methylation by cfMeDIPSeq, proteins using the SomaScan® Somalogic platform, miRNA sequencing from exosomes) and urine (ctDNA methylation by cfMeDIPSeq) collected at T0 (baseline, before diagnostic biopsy). This outcome will be compared with the accuracy of diagnostic biopsy on the same patients' cohort.

Accuracy of the HDI classifier when taking into account and after removing host-specific variables by assessing the same variables after surgery.

Analytical and clinical validity of surrogate, less expensive methods to measure the same variables included in the HDI classifier (e.g., methylation-specific PCR assays, ELISA essays for selected proteins, quantitative real-time PCR for miRNAs).

Study title	NCT ID	Conditions	Interventions	Eligibility	Organization
BIOREN (Predictive BIOmarkers in Metastatic RENal Cancer)	NCT03628859	Renal Cancer Me...	Immunological a...	18 Years -	Centre Leon Berard
Development of a Horizontal Data Integration Classifier for Noninvasive Early Diagnosis of Breast Cancer	NCT04781062	Breast Cancer	Blood and urine... Blood and urine...	18 Years -	Ospedale Policlinico San Martino
BIOREN (Predictive BIOmarkers in Metastatic RENal Cancer)	NCT03628859	Renal Cancer Me...	Immunological a...	18 Years -	Centre Leon Berard

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