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Analyzing and Solving Exceptional Long-term Survivors in Solid Tumors With Poor Prognosis

2023-11-01

2025-11-01

2028-05-01

1020

Study Overview

Analyzing and Solving Exceptional Long-term Survivors in Solid Tumors With Poor Prognosis

This is a retrospective, exploratory, multi-center, translational, 3 cohorts case control matched study conducted in patients harboring a solid tumor with poor prognosis who presented a long-term (case) and standard (standard) survival. Patients with: * Cohort A: metastatic pancreatic ductal adenocarcinoma * Cohort B: glioblastoma IDHwt * Cohort C: extensive small cell lung cancer This research aims to integrate data generated from clinical records, imaging, multi-omics and bioinformatics approaches to discriminate case and control and then to identify new therapeutic targets. Analyses will be performed depending on the tumor samples available with at least 3 omics levels and according to scientific advances; genomic, epigenomic, proteomics, metabolomics, transcriptomic, microbiomic.

We propose for the first time to build a large collection of samples from unexpected survivors and controls with standard survival to identify biomarkers of resistance and/or survival which would help developing new cancer therapeutics. Biological samples and clinical records will be collected and then centralised to extract the data of any patients who have survived more than 5 years for the cohorts of PDAC and SCLC and more than 3 years for the cohort of GMB-IDHwt from the day of diagnosis. In addition to the clinical record of the patient describing his/her history (including multiscale imaging, pathology, biological sample analysis), we will collect every point of data possible with current technologies, such as multi-omics including genome, proteome, transcriptome, epigenomic, metabolome and microbiome. The data set of these multi-omic groups are combined and are complementary to identify a certain biological function and its cellular source. Such complementary effects and synergistic interactions between omic layers in the life course can only be captured by integrative study of multiple molecular layers. Artificial intelligence (AI), specifically machine learning algorithms, will also help to understand these multi-omics data. AI can also bring a new layer of biomarker discovery enabling the analysis of whole slide images of biopsies with computer vision and linking those biomarkers to the multi omics genomic features. After interpreting the comprehensive data with our set-up bioinformatics team in coordination with the various centres, we expect to find molecular signatures and consequently therapeutic approaches to address patients and physicians unmet needs.

  • Pancreas Adenocarcinoma
  • Small-cell Lung Cancer
  • Glioblastoma, IDH-wildtype
  • GENETIC: Long term survival multimodal analysis
  • 2022-A02541-42

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 Registration Dates Results Reporting Dates Study Record Updates

2023-11-29  

N/A  

2023-11-29  

2023-11-29  

N/A  

2023-12-07  

2023-12-07  

N/A  

2023-11  

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

Design Details

Primary Purpose:
N/A

Allocation:
N/A

Interventional Model:
N/A

Masking:
N/A

Arms and Interventions

Participant Group/ArmIntervention/Treatment
: PDAC STAGE IV SURVIVORS & CONTROLS

Metastatic pancreatic ductal adenocarcinoma (PDAC) (Other histologies such as adenosquamous carcinoma, hepatoid carcinoma, anaplastic undifferentiated carcinoma and medullary carcinoma, acinar cell carcinoma, neuroendocrine tumors, Solid pseudopapillary n

GENETIC: Long term survival multimodal analysis

  • * To describe global signatures (Digital histology, Radiomic, Genomic, Transcriptomic, Proteomic, (Epigenomic) and clinical signature) that are associated with a patient's unexpected survival compared to standard patients across three cohorts of soli
: SMALL CELL LUNG CANCER EXTENSIVE STAGE SURVIVORS & CONTROLS

Extensive small cell lung cancer (SCLC) (Other histologies excluded: combined SCLC with some areas of non-small cell lung cancer (NSCLC), carcinoid tumors, typical and atypical, large cell neuroendocrine carcinoma of the lung).

GENETIC: Long term survival multimodal analysis

  • * To describe global signatures (Digital histology, Radiomic, Genomic, Transcriptomic, Proteomic, (Epigenomic) and clinical signature) that are associated with a patient's unexpected survival compared to standard patients across three cohorts of soli
: GLIOBLASTOMA SURVIVORS & CONTROLS

Glioblastoma (GBM) (IDH mutated excluded)

GENETIC: Long term survival multimodal analysis

  • * To describe global signatures (Digital histology, Radiomic, Genomic, Transcriptomic, Proteomic, (Epigenomic) and clinical signature) that are associated with a patient's unexpected survival compared to standard patients across three cohorts of soli
Primary Outcome MeasuresMeasure DescriptionTime Frame
EXCEPTIONAL SURVIVALIn this study, the primary endpoint is the long survivorship status (Y/N). Prior to locking the database, a data review meeting will be planned to review individual data and validate the Statistical Analysis Plan (SAP). All the deviations from protocol definitions (if any) will be listed and defined as major or minor deviations in the SAP.54 months
Secondary Outcome MeasuresMeasure DescriptionTime Frame

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: Wolikow Nicolas, Master

Phone Number: 0033772042022

Email: nicolas@cure51.com

Study Contact Backup

Name: Simon Istolainen, Master

Phone Number: 0033626955716

Email: simon@cure51.com

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.

Ages Eligible for Study:
ALL

Sexes Eligible for Study:
18 Years

Accepts Healthy Volunteers:

    Inclusion Criteria:
    FOR SURVIVORS

  • To be eligible the exceptional survivor patients must fulfill the following inclusion criteria:

    • 1. Adult patient (≥18 years old at diagnosis). 2. Three distinct cohorts, one of patients harbouring metastatic pancreatic ductal adenocarcinoma, glioblastoma IDHwt, extensive small cell lung cancer. 3. Long-term survival is defined as an exceptionally long survival ≥ 5 years from stage IV diagnosis for PDAC, extensive SCLC, and ≥ 3 years for GBM-IDHwt. 4. Availability of at least one block sample and associated clinical annotations with following characteristics:

  • One block sample must be of sufficient quality and in sufficient quantity to perform multi-omic analyses, according to requirements specified in Lab manual
  • Any treatment prior to sample acquisition must be reported - all treatments accepted (standard / targeted);
  • Samples should be at least 5 years old for PDAC and SCLC and 3 years old for GBM

    • For CONTROL GROUPS :

  • To be eligible the control patients must fulfill the following inclusion criteria:

    • 1. ≥18 years old at diagnosis. 2. Three distinct cohorts, one of patients suffering from metastatic pancreatic ductal adenocarcinoma, one for glioblastoma, one for extensive small cell lung cancer. 3. Paired to long-term survivors as mentioned in the methodology section 4. Death or median overall survival with a variation of 10% before of beyond as reported in pivotal clinical trials in the specific type disease 5. Availability of at least one tumor sample and associated clinical annotations with following characteristics:

  • Sample must be of sufficient quality and in sufficient quantity to perform multi-omic analyses
  • Any treatment prior to sample acquisition must be reported (treatment-naive samples should be preferred) - all treatments accepted (standard / targeted).

    • Exclusion Criteria for both groups :
  • Patient must not be enrolled if he/she fulfils one of the following non-inclusion criteria:

    • 1. <18 years old at diagnosis. 2. Hematological malignancy or solid tumors, which are not in the scope of tumor types, described in the inclusion criteria. 3. Tumor sample not available or not reaching the required quality for multi-omic analyses.

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

  • Gustave Roussy, Cancer Campus, Grand Paris
  • Centre Leon Berard
  • Vall d'Hebron Institute of Oncology
  • Istituto Europeo di Oncologia
  • Charite University, Berlin, Germany
  • PRINCIPAL_INVESTIGATOR: Julieta Rodriguez, MD, Gustave Roussy, Cancer Campus, Grand Paris

Publications

The person responsible for entering information about the study voluntarily provides these publications. These may be about anything related to the study.

General Publications

No publications available

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