Symptoms and General Pathology

All Conditions

Respiratory Tract (Lung and Bronchial) Diseases

Neoplasms

Diseases and Abnormalities at or Before Birth

Infections

Rare Diseases

Syndrome

Lung Diseases, Obstructive

Pulmonary Disease, Chronic Obstructive

Lung Neoplasms

Lung Diseases

Respiratory Distress Syndrome

Respiratory Distress Syndrome, Newborn

Pulmonary Emphysema

Emphysema

Acute Lung Injury

Bronchitis

Bronchitis, Chronic

Respiratory Tract Neoplasms

Thoracic Neoplasms

Respiratory Tract Diseases

Chronic Graft Versus Host Disease

Respiratory Distress Syndrome, Infant

Acute Respiratory Distress Syndrome

Acute Graft Versus Host Disease

Subjects who provide informed consent and meet the eligibility criteria will have 50 ml of blood collected and sent to Freenome or Freenome's designee for processing, testing, and storage, and will then complete a standard-of-care screening LDCT.

blood draw

April Allison, BS

Harris Naemi, BS / Joye Choy, BS

Study Coordinator

Chuanbo Xu, PhD

Nasibeh Vatankhah, MD

The PROACT LUNG study is a prospective multi-center observational study to validate a blood-based test for the early detection of lung cancer by collecting blood samples from high-risk participants who will undergo a routine, standard-of-care screening Low-Dose Computed Tomography (LDCT).

This is a prospective, multi-center, observational study to evaluate the performance of the Freenome Multiomics Blood Test in screening eligible participants for lung cancer.

Enrollment will be open to all eligible participants for screening chest CT scan as part of the Standard of Care (SOC) for lung cancer. Subjects who meet the eligibility criteria for this study and provide informed consent will be enrolled and blood sample collection must be completed within 30 days of signing the informed consent. Optimally, the screening chest CT will be completed on the same day of the study blood collection, however up to 45 days will be allowed after study blood collection to obtain a screening chest CT.

The study will also collect demographic data and relevant clinical data, such as medical history, lifestyle, occupational and environmental exposure(s), family history, and clinical laboratory data. All reports and clinical notes regarding the diagnostic tests and procedures related to lung cancer diagnosis or lung lesion assessment, such as histopathology and bronchoscopy reports, and diagnostic/follow-up images and imaging reports will be collected as part of follow up to the screening chest CT scan.

All enrolled subjects will be followed prospectively from the date of the baseline screening chest CT until a minimum of 24 months, or until a premature study endpoint inclusive of withdrawal of consent or death.

Blood specimens will be de-identified and used to validate the performance characteristics of the Freenome Multiomics Blood Test

Clinical Validation of Freenome Multiomics Blood Test for Lung Cancer Screening

The PROACT LUNG Study: A Prospective, Observational,Clinical Validation Study of the Freenome Multiomics Blood Test for Lung Cancer Screening (FRNM-007)

Clinical performance of the Freenome Blood Test, including sensitivity and specificity, in detecting lung cancer in subjects with positive and negative lung cancer outcomes during a 12-month follow-up period

Clinical performance of the Freenome Blood Test, including sensitivity and specificity, in detecting lung cancer in subjects with positive and negative lung cancer outcomes during a 24-month follow-up period

Freenome Holdings Inc.

Richard F Schlenk, M.D.

Stefan Fröhling, M.D.

NCT/DKFZ/DKTK MASTER is a prospective, continuously recruiting, multicenter observational study for biology-guided stratification of adults with rare cancers, including rare subtypes of common entities, using comprehensive molecular profiling, and clinical decision-making in a multidisciplinary molecular tumor board.

Molecularly Aided Stratification for Tumor Eradication Research

NCT MASTER Plattform Molecularly Aided Stratification for Tumor Eradication Research

Time period of progression survival from date of multiomics analysis

time period of survival from date of diagnosis

response according to RECIST v.1.1 criteria to antitumor treatment applied after multiomics analysis

German Consortium for Translational Cancer Research

German Cancer Research Center

Blood and Lymph Conditions

Neoplasm Metastasis

Leukemia

Leukemia, Myeloid

Leukemia, Myeloid, Acute

Myeloproliferative Disorders

Neoplasms by Histologic Type

Hematologic Diseases

Bone Marrow Diseases

Myeloid Leukemia

Acute Myeloid Leukemia

Acute Non Lymphoblastic Leukemia

Chronic Myeloproliferative Disorders

120 patients will be studied for :

* Multiomic characterization
* In vitro drug screening

Multiomics analysis include targeted-NGS with a 400-genes panel, RNA-seq and methylome. All the genomic libraries will be constructed at the genomic facility of Angers University Hospital and the sequencing will be performed on a NovaSeq6000 in the GenoBIRD Platform in Nantes. Bioinformatic analysis will be performed and will derive for each sample: SNV/Indel and CNV from DNA sequencing, expression of mRNA and lncRNA, genes fusion and splicing events from RNA-seq, and methylation beta-values from methylome.

Multiomic characterization

The drug screening will be performed on the 'NEXT-AML' platform at St-Louis Hospital, Paris. This platform uses a multiparametric screening strategy based on flow cytometry measurements of cell viability, cell differentiation and stem cell compartment. Primary patient cells will be cultured in a specific niche-like medium with amino-acids, cytokines and stromal cells (Dal Bello et al. 2022). Twenty-five drugs at 6 concentrations covering a 1000-fold concentration range will be studied for each sample.

In vitro drug screening

Damien LUQUE PAZ, PharmD. PhD.

Béatrice GABLE

Myeloproliferative neoplasms (MPN) are chronic myeloid malignancies characterized by a risk of evolution to acute myeloid leukemia (AML). This unpredictable complication is associated with a grim outcome with median overall survival ranging between 2 to 10 months. To date, even allogeneic transplantation fails to significantly improve the prognosis. Biological and molecular mechanisms driving leukemic transformation are complex, ill-defined, and heterogeneous between patients. The investigator hypothesize that deciphering the molecular heterogeneity of post-MPN AML may lead identifying efficient drugs targeting of the most relevant leukemogenic pathways.

Our main objective is to identify new targeted therapeutic approaches in post-MPN AML through in-depth characterization of the dysregulated pathways. The investigator will first characterize in an already annotated cohort of 120 post-MPN AML homogeneous patients subgroups using comprehensive multiomic analyses. Dysregulated pathways will be identified in each subgroup using the omics data and single-cell RNA-sequencing will be performed in a subset of patients in each subgroup. A customised drug-panel will be derived from the dysregulated pathway for an ex vivo drug screening, which will use a flow-cytometry read-out enabling to identity drug effect on cells survival, differentiation, and stemness. The 3 most promising drugs will be validated in a preclinical in vivo model of patient's derived xenograft (PDX) and their impact on clonal architecture will be studied in primary cell cultures using single-cell DNA-sequencing.

Overall, this proposal may provide a better understanding of MPN leukemic transformation mechanisms and provide a path for personalized therapies. Our findings may therefore pave the way to drugs development in post-MPN AML that would provide a rationale for implementation of early clinical trials in these dreadful diseases.

Patients samples and clinical data:

The investigator will study samples from 120 patients with a post-MPN acute myeloid leukemia. These samples and the corresponding clinical data are available through FIMBANK, a national network of biological resources for myeloproliferative neoplasms (grant INCa, BCB 2013, Pr Valérie Ugo) and through the prospective phase II clinical trial CPX351-TA-SMP testing CPX351 monotherapy in post-MPN AML (NCT04992949, inclusions started in 01-2022).

WP1: Deciphering the heterogeneity of post-MPN AML (primary objective) To answer these objectives, the investigator will conduct a multi-omics approach including targeted-NGS with a 400-genes panel, RNA-seq and methylome in a total of 120 post-MPN AML samples. All the genomic libraries will be constructed at the genomic facility of Angers University Hospital and the sequencing will be performed on a NovaSeq6000 in the GenoBIRD Platform in Nantes. Bioinformatic analysis will be performed by teams #1 and #3 and will derive for each sample: SNV/Indel and CNV from DNA sequencing, expression of mRNA and lncRNA, genes fusion and splicing events from RNA-seq, and methylation beta-values from methylome.

In order to identify homogeneous subgroups from the genomic data, the investigator will perform unsupervised clustering analyses of each layer of genomic data. Then, all layers will be combined for integration of clusters using the Cluster Of Clusters Analysis (COCA) method (Wilkerson and Hayes, 2010).

WP2: Identify the mechanisms of transformation and putative targets for therapy For this purpose, the investigator will analyze omics data generated in WP1 to identify the main molecular mechanisms driving the leukemic transformation of MPN. The investigator will perform a 2-step procedure: first by analyzing each genomic dataset separately and then, by analyzing all datasets together in an integrated multiblock analysis using the MOGSA method (Integrative Single Sample Gene-set).

A total of 60 samples originating from a subset of patients classified in WP1 will be tested for ex vivo drug screening. The investigator will design a custom-made drug panel including standards of care, several drugs in clinical development in AML and, more importantly, a selection of drugs specifically targeting potential leukemic vulnerabilities identified.

WP3: Confirm the efficacy of selected best drugs and their impact on clonal architecture To further validate the translational relevance of post-MPN AML deregulated pathways, the three most promising drug candidates will then be evaluated in a set of five post-MPN PDX models including at least 2 TP53-mutated post-MPN AML. The investigator will also evaluate how the drugs identified in WP2 may impact clonal evolution of the disease which is a key step towards understanding and improving the treatment of post-MPN AML. The 3 best candidate drugs or combinations identified in WP2 will be studied in cells from 5 selected patients with a complex molecular profile to evaluate the response of various subclones.

Patients will be recruited in the French biobank of MPN (BCB INCa FIMBANK) and the FILO's national biobank of acute leukemias (FILOthèque). All clinical and biological data are anonymized.

MultiOmic characteriZation of Acute Myeloid Leukemia Evolving From myelopRoliferative Neoplasm to Identify New Targeted Therapeutic Strategies

Decipher the heterogeneity of post-MPN AML to identify homogeneous subgroups

Identify the oncogenic molecular mechanisms among each subgroup of post-MPN AML

Identify efficient in vitro therapies targeting the dysregulated pathways of post-MPN AML

Confirm the efficacy of the most promising newly identified candidate drugs or therapeutic combinations in vivo in PDX models

Absolute change of the proportion of each leukemic clone in single-cell DNA-sequencing of in vitro culture

University Hospital, Brest

Institut Paoli-Calmettes

Saint-Louis Hospital, Paris, France

Gustave Roussy, Cancer Campus, Grand Paris

University Hospital, Angers

Urinary Tract, Sexual Organs, and Pregnancy Conditions

Carcinoma

Carcinoma, Renal Cell

Kidney Neoplasms

Neoplasms, Glandular and Epithelial

Adenocarcinoma

Urologic Neoplasms

Urogenital Neoplasms

Urogenital Diseases

Female Urogenital Diseases

Pregnancy Complications

Female Urogenital Diseases and Pregnancy Complications

Kidney Diseases

Urologic Diseases

Male Urogenital Diseases

Renal Cell Carcinoma

Clear Cell Renal Cell Carcinoma

Data collection

Valérie SARTORI

Manon VOEGELIN

Jean-Christophe Bernhard, MD, PhD

Aurore Coulomb, MD, PhD

Nathalie Rioux-Leclercq, MD, PhD

Gabriel MALOUF, MD, PhD

Microphthalmia transcription factor (MiT) family translocation renal cell carcinomas (TRCC) are rare subtypes of kidney cancers, which often arise in children and young adults. TRCC are characterized by translocations affecting transcription factors: Transcription Factor Binding To Immunoglobulin Heavy Constant Mu Enhancer 3 (TFE3) and Transcription Factor EB (TFEB). Little is known about TRCC molecular heterogeneity, in particular their transcriptomic and epigenetic subtype classification. Clinical behavior of TRCC is varying with age and Tumor, Node, Metastasis (TNM) stage. However, the biological basis of this aggressiveness is poorly understood.

PURPOSE: The primary goal of this study is to decipher specific alterations in aggressive TRCC, defined as cases with metastatic dissemination at diagnosis. To tackle this problem, a retrospective cohort of TRCC cases in children and young adults will be created. We will then perform integrative comprehensive multi-omics analysis of these tumors to identify genetic, epigenetic and immune biomarkers associated with metastatic behavior in a training and validation datasets. Comparison of the multi-omics data will be compared to other type of rare Kidney tumors as well as clear-cell renal cell carcinomas

This retrospective cohort study aims to allow tumor collection of TRCC from three different networks: the French research network in renal cancer (UroCCR), the International Society of Paediatric Oncology (SIOP) database and the network for rare renal carcinomas (CARARE). Those samples will be divided in training and validation datasets. We will also collect samples from patients with other rare kidney cancers and clear-cell renal cell carcinomas allowing comparisons of similarity and differences between these tumors.

Integrative Molecular Characterization Of MiT Family Translocation Renal Cell Carcinomas (IMCOR)

Tumor aggressiveness is defined as TRCC cases with metastatic dissemination at diagnosis. Comparison of recurrent genetic aberration identified between metastatic and localized cases.

Testing for association between molecular tumor features and clinico-pathological patients outcome, PFS, according to the identity of TFE fusion partner

Testing for association between molecular tumor features and clinico-pathological patients outcome, OS, according to the identity of TFE fusion partner

Proportion of patients with metastatic disease in each DNA methylation and messenger RNA (mRNA) cluster using hierarchical unsupervised subtype classifications

National Cancer Institute, France

Ministry of Health, France

Institut de cancérologie Strasbourg Europe

Skin and Connective Tissue Diseases

Breast Neoplasms

Phyllodes Tumor

Breast Diseases

Skin Diseases

Sarcoma

Neoplasms, Connective and Soft Tissue

Phyllodes Tumor of the Breast

Soft Tissue Sarcoma

Patients diagnosed with phyllodes tumor of breast

Patient medical imaging materials including ultrasound, mammography, CT, MRI

imaging

Yan Nie, Prof.Dr.

Feng Ye, Prof.Dr.

Hui Mai, Prof.Dr.

Yu Tan, Prof.Dr.

Breast phyllodes tumor (PT) is a rare fibroepithelial tumor, accounting for 1% to 3% of all breast tumors, categorized by the WHO into benign, borderline, and malignant, based on histopathology features such as tumor border, stromal cellularity, stromal atypia, mitotic activity and stromal overgrowth. Malignant PTs account for 18%-25%, with high local recurrence (up to 65%) and distant metastasis rates (16%-25%). Benign PT could progress to malignancy after multiple recurrences. Therefore, Early, accurate diagnosis and identification of therapeutic targets are crucial for improving outcomes and survival rates.

In recent years, there has been growing interest in the application of artificial intelligence (AI) in medical diagnostics. AI can integrate clinical information, histopathological images, and multi-omics data to assist in pathological and clinical diagnosis, prognosis prediction, and molecular profiling.AI has shown promising results in various areas, including the diagnosis of different cancers such as colorectal cancer, breast cancer, and prostate cancer. However, PT differs from breast cancer in diagnosis and treatment approach. Therefore, establishing an AI-based system for the precise diagnosis and prognosis assessment of PT is crucial for personalized medicine.

The research team, led by Dr. Nie Yan, is one of the few in Guangdong Province and even nationally, specializing in PT research. Their team has been conducting research on the malignant progression, metastasis mechanisms, and molecular markers for PT. The team has identified key mechanisms, such as fibroblast-to-myofibroblast differentiation, and the role of tumor-associated macrophages in promoting this differentiation. They have also identified molecular markers, including miR-21, α-SMA, CCL18, and CCL5, which are more accurate in predicting tumor recurrence risk compared to traditional histopathological grading.

The project has collected high-quality data from nearly a thousand breast PT patients, including imaging, histopathology, and survival data, and has performed transcriptome gene sequencing on tissue samples. They aim to build a comprehensive multi-omics database for breast PT and create an AI-based model for early diagnosis and prognosis prediction. This research has the potential to improve the diagnosis and treatment of breast PT, address the disparities in breast PT care across different regions in China, and contribute to the development of new therapeutic targets.

AI-Assisted System for Accurate Diagnosis and Prognosis of Breast Phyllodes Tumors

Development of an Artificial Intelligence-Based System for Precise Diagnosis and Prognosis of Breast Phyllodes Tumors

no plan to make individual participant data available to other researchers.

The probability of a positive test result, conditional on it being truly positive.

Determine the odds of testing negative in a positive population.

The probability of a negative test result conditional on a true negative.

Determine the odds of testing positive in a negative population.

The ROC curve is a curve based on a series of different dichotomous classifications (cut-off values or decision thresholds), with the rate of true positives (sensitivity) as the vertical coordinate and the rate of false positives (1-specificity) as the horizontal coordinate.

AUC is defined as the area under the ROC curve enclosed with the axes, and the closer the AUC is to 1.0, the more authentic the assay is.

Sun Yat-sen University

Peking University Shenzhen Hospital

Guangdong Provincial Maternal and Child Health Hospital

The Third Affiliated Hospital of Guangzhou Medical University

Sun Yat-Sen Memorial Hospital of Sun Yat-Sen University

Principal Investigator

* Collect Subject Data
* Collect Blood Specimen

Participants who provide informed consent, meet the eligibility criteria and provide a blood sample for this study will be enrolled.

Freenome Test

Victoria Sumner

This protocol is a prospective, case-control multi-center diagnostic study to assess the sensitivity and specificity of blood-based screening tests for the early detection of multiple cancers.

Blood specimens will be de-identified and used to validate the performance characteristics of the Freenome test

The Sanderson Study: A Case Control Study for the Development of Multiomics Blood Tests for Cancer Screening

The Sanderson Study: A Diagnostic Case-Control Study for the Development of Multiomics Blood Tests for Cancer Screening in a Real World Setting

To compare blood samples from cancer case and non-cancer control subjects in order to develop and characterize blood-based multiomics tests in specific cancer types or in a combination of multiple cancers.

Study title	NCT ID	Conditions	Interventions	Eligibility	Organization
Clinical Validation of Freenome Multiomics Blood Test for Lung Cancer Screening	NCT06122077	Lung Cancer Dia...	blood draw	50 Years -	Freenome Holdings Inc.
Molecularly Aided Stratification for Tumor Eradication Research	NCT05852522	Rare Cancers Multiomics		18 Years -	German Cancer Research Center
MultiOmic characteriZation of Acute Myeloid Leukemia Evolving From myelopRoliferative Neoplasm to Identify New Targeted Therapeutic Strategies	NCT06022341	Myeloproliferat... Secondary Leuke...	Multiomic chara... In vitro drug s...	18 Years -	University Hospital, Angers
Integrative Molecular Characterization Of MiT Family Translocation Renal Cell Carcinomas (IMCOR)	NCT05456074	Renal Carcinoma	Data collection	-	Institut de cancérologie Strasbourg Europe
AI-Assisted System for Accurate Diagnosis and Prognosis of Breast Phyllodes Tumors	NCT06286267	Phyllodes Breas... Artificial Inte... Multiomics Prognostic Canc... Diagnosis	imaging	-	Sun Yat-Sen Memorial Hospital of Sun Yat-Sen University
Molecularly Aided Stratification for Tumor Eradication Research	NCT05852522	Rare Cancers Multiomics		18 Years -	German Cancer Research Center
The Sanderson Study: A Case Control Study for the Development of Multiomics Blood Tests for Cancer Screening	NCT05516927	Newly-diagnosed... Non-cancer Cont...	Freenome Test	30 Years -	Freenome Holdings Inc.
AI-Assisted System for Accurate Diagnosis and Prognosis of Breast Phyllodes Tumors	NCT06286267	Phyllodes Breas... Artificial Inte... Multiomics Prognostic Canc... Diagnosis	imaging	-	Sun Yat-Sen Memorial Hospital of Sun Yat-Sen University

Spots Global Cancer Trial Database for multiomics

Every month we try and update this database with for multiomics cancer trials from around the world to help patients and their families find trials that might be right for them.
We offer this 100% free of charge and do not endorse any of the trials listed here, we hope it helps you or a loved one.

Spots Global Cancer Trial Database for multiomics

Every month we try and update this database with for multiomics cancer trials from around the world to help patients and their families find trials that might be right for them. We offer this 100% free of charge and do not endorse any of the trials listed here, we hope it helps you or a loved one.

Every month we try and update this database with for multiomics cancer trials from around the world to help patients and their families find trials that might be right for them.
We offer this 100% free of charge and do not endorse any of the trials listed here, we hope it helps you or a loved one.