Neoplasms

Respiratory Tract (Lung and Bronchial) Diseases

All Conditions

Carcinoma, Non-Small-Cell Lung

Lung Neoplasms

Carcinoma

Respiratory Tract Neoplasms

Thoracic Neoplasms

Lung Diseases

Respiratory Tract Diseases

Carcinoma, Bronchogenic

Bronchial Neoplasms

All Drugs and Chemicals

Immunomodulating Agents

Treatment naive patients with metastatic NSCLC (stage four) with life expectancy of more than three months.

Treatment naive patients diagnosed with NSCLC.

Participants in the aRECIST group will undergo a blood draw for liquid biopsy analysis at baseline and follow up visits

Liquid biopsy

Lise Barbeaux

Mariaelena Occhipinti, MD PhD

Jan P Van Meerbeeck, MD

SALMON is a prospective, multi-center, multi-country, biomarker validation study that synergizes an extensive non-interventional biomarker discovery study on diagnostic images and tissue biopsies of non-small cell lung cancer NSCLC (rATLAS) with a smaller biomarker minimally interventional study on patients with metastases who undergo liquid biopsy and imaging follow-up for 2 years (aRECIST). A total of 1120 patients will be screened to get 1000 participants enrolled in rATLAS, and a subset of 250 participants will be screened to then recruit 150 participants also for aRECIST. The study will end after one visit for participants in rATLAS while there is a 2-years follow-up period for participants in aRECIST. Participants will not receive any treatment specific for this study, but might receive standard of care therapy or investigational products in the framework of another clinical study following the baseline visit.

The objectives of optimizing AI based tools for the assessment of EGFR status (rATLAS) and automated Response Evaluation Criteria in Solid Tumours 1.1 (RECIST 1.1) (aRECIST) will be achieved using a trial design that combines a biomarker discovery study design (cross-sectional for rATLAS) with a reader study design (follow-up study in aRECIST). Medical treatments in the aRECIST cohort are not dictated by study protocol, rather determined by the clinicians in line with standard clinical practice.

Lung cancer is the leading cause of cancer-related death worldwide, accounting for an estimated 2.1 million deaths in 2018. About 80%-85% of lung cancers are NSCLC. The main subtypes of NSCLC are adenocarcinoma, squamous cell carcinoma, and large cell carcinoma. These subtypes, which start from different types of lung cells, are grouped together as NSCLC. For these reasons, the choice of NSCLC for this trial is the most relevant, as there is a clear societal burden / clinical need that will be addressed in SALMON.

A pressing need exists to uncover the genetic and molecular composition of tumors, as this information would accelerate the development of more effective cancer therapies. Since tumors differ in their biological makeup, treatments can now often be tailored towards individual patients, in a strategy termed personalized medicine. NSCLC perfectly illustrates this paradigm, with treatments either targeted at well-defined oncogenic pathways (epidermal growth factor receptor (EGFR) mutations, Anaplastic lymphoma kinase (ALK) \& receptor tyrosine kinase 1 (ROS1) gene rearrangements, B-Rapidly Accelerated Fibrosarcoma gene (BRAF) mutations), and for so-called "wild-type" NSCLC, immunotherapy (with or without chemotherapy). The recent development of different types of immunotherapy has led to promising advances in the treatment of patients with NSCLC in advanced or metastatic disease.

Medical imaging plays a pivotal role in the assessment of tumors, including lung cancer, as it provides non-invasively the features to identify, characterize and stage the local tumor and its overall metastatic burden. The information provided by imaging can be still improved with a thorough post-processing analysis of the images, with "radiomics" being the most sophisticated tool for quantitative imaging. Through radiomics the imaging data obtained can be linked to specific biological properties of the tumor, acquired either from tissue or liquid biopsies. However, the knowledge on this is fragmented to date.

The first objective of this trial is to generate a radiomics atlas (rATLAS) that provides a broader link between biological descriptors and medical imaging features in NSCLC, to eventually identify oncologic pathways through medical images and quantify the overall burden of specific markers for targeted therapies. In particular, imaging biomarkers that can predict immunosensitivity and more accurately predict the prognosis than the existing ones will be assessed on the medical images and compared to tissue and liquid biopsies.

Apart from NSCLC diagnosis and staging, imaging plays a key role also in the evaluation of patient's follow-up, representing the gold standard for the assessment of response to therapy. However, the evaluation of medical images is amenable to radiologist's interpretation and many attempts have been made to face this issue in the last decades. The RECIST is a one-dimensional measure (shortest/longest diameter in the plane of measurement) created in 2000, updated in 2009 (RECIST 1.1), with a branch for immunotherapy finalized in 2017 (iRECIST). RECIST, in all its different declination, is used to assess whether a tumor in cancer patients is progressing, regressing or did not change before and after some event, such as therapy. RECIST criteria are recognized both in the EU and in US. Although representing an international attempt to overcome the subjective evaluation of tumor response to cancer treatment, biases of measurements remain as it relies on human assessments. In 1976 Moertel and Hanley acknowledged that "the culmination of most experimental therapeutic trials for solid tumors occurs when a \[physician\] places a ruler or caliper over a lump and attempts to estimate its size," and with this measurement comes the inevitable component of human error. In 2021 this issue is still present in clinical practice, but in the last years Artificial Intelligence (AI) has demonstrated remarkable progress in image-recognition tasks in research.

Thus, the investigators propose to eliminate the shortcomings of measurement biases with the second objective of our trial that is focused on the validation of a new automated RECIST (aRECIST) workflow for the assessment of therapy response.

A signed and dated informed consent form will be obtained from each patient before any screening procedures are conducted. The participants will be prospectively enrolled to rATLAS only, to both rATLAS and aRECIST, or considered as screen failure. If enrolled then a unique study-specific subject number shall be assigned, Informed consent form will be signed and the following evaluations will be included:

The following data will be obtained for each participant from medical files and records:

* Demographic data (Age, Gender, Race, country);
* Anthropometric data (Weight in kg, Height in cm, body mass index (BMI) in kg/m\^2);
* Medical history (comorbidities, oncology-related history, Chronic obstructive pulmonary disease (COPD), Interstitial lung disease (ILD), Pulmonary vascular disease, history related to NSCLC);
* Substance use (cigarettes/e-cigarettes/alcohol), duration and dose/frequency \[smoking required, others optional\];
* Concomitant treatment only linked to immunotherapy, chemotherapy, radiotherapy, and targeted therapy (subtype, drug name, line of treatment (first/second/third line), reason for discontinuation (completed regimen/completed response/progression disease/toxicity/other);
* Eastern Cooperative Oncology Group (ECOG) performance status (0 to 5);
* Histological diagnosis (adenocarcinoma, squamous cell carcinoma, large cell carcinoma, adenosquamous cell carcinoma, other);
* Laboratoristic data: Hematology (hemoglobin, hematocrit, leukocytes, neutrophils, eosinophils, basophils, lymphocytes, monocytes, platelets) and Chemistry (sodium, bicarbonate, chloride, calcium, albumin, magnesium, phosphate, blood urea nitrogen, protein, urea, potassium, creatinine, estimated glomerular filtration rate, bilirubin, direct bilirubin, aspartate aminotransferase (AST), alanine aminotransferase (ALT), alkaline phosphatase, lactate dehydrogenase (LDH), carcinoembryonic antigen (CEA), squamous cell carcinoma (SCC)).

From clinical examination and imaging (and multidisciplinary discussion report if available) the following data will be recorded per participant: Clinical Tumor Staging (cTNM) upon initial diagnosis.

From Radiology department the following data will be recorded per participant: The staging computed tomography (CT) scan data already performed at the site per standard of care (SoC) will be pseudo-anonymized and sent to the central reader, along with Positron Emission Tomography (PET)/CT and brain magnetic resonance imaging (MRI) scans obtained per patient staging, when available.

Then, depending on group (aRECIST or rATLAS), the following steps will also be considered:

rATLAS: Diagnostic samples of tissue biopsy (ideally 1 block or 25 slides - minimum required: 10 slides) performed at the participating site per standard of care will be shipped to the central laboratory for testing on oncogenic biomarkers. After this baseline visit all participants in rATLAS may start their treatment as per SoC. rATLAS study ends after this baseline and enrolment visit.

aRECIST: A liquid biopsy will be obtained (blood sample, 1 tube of 10 ml) and shipped within 2 days to the central laboratory for oncogenic biomarker testing. In order not to influence therapeutic decision making, biomarker results will be shared with the sites only after the decision concerning NSCLC therapy has been made. Diagnostic samples of tissue biopsy which have been obtained for ATLAS (ideally 1 block or 25 slides - minimum required: 10 slides) performed at the participating site per standard of care will be shipped to the central laboratory for oncogenetic biomarker testing. In those cases where standard tissue biopsy is not obtained, fine needle biopsy and cells obtained per SoC by fine needle aspiration could be analyzed and send to the central laboratory following specific procedures. Enough material should be available to be analyzed, otherwise the genetic testing would not be possible.

After baseline all participants of the aRECIST group will undergo standard chemotherapy and/or immunotherapy and will be followed up for a maximum of 2 years to investigate a possible treatment response (manual local \& central and automated RECIST) by imaging parameters and liquid biopsy. These participants will need to return to the clinic for liquid biopsies (2 tubes of 10 mL) at 3, 6, 12 and 24 months within 5 days (before or after) of their imaging follow-up as per SoC. It is the site staff that will be responsible for providing a copy of all relevant post-treatment CT-scans (and PET/CT scan if available) as taken per SoC together with local RECIST scoring, NSCLC treatment(s) information (class, dose, duration) and NSCLC-related events. The data will be collected at time-points as per standard of care (at 3, 6, 12, and 24 months approximately). The participant's participation to aRECIST will end 2 years after baseline or earlier in case of death or any event that in the opinion of the investigator requires an early termination.

In particular, the site staff will be responsible to provide a liquid biopsy (2 tubes of 10ml each) and to share the following data at 3 (visit1), 6 (visit 2), 12 (visit 3), and 24 (visit 4) months):

* A copy of all relevant post-treatment CT scans - and PET/CT scans if available - as taken per SoC
* Detailed description of CT acquisition for each participant, including contrast media injection characteristics
* Local reading of treatment response by using RECIST 1.1 criteria (manual local reading), along with the time needed for evaluating each participant,
* A liquid biopsy (2 tubes of 10 ml each) within 5 days of the CT scan performed for participant follow up
* NSCLC treatment(s) information (class, dose, duration, specific timeframes)
* NSCLC-related events.

Any rATLAS participant are considered as having completed the study after performing the initial baseline visit (Day 0), except for those also participating to aRECIST. Participants of aRECIST are considered as having completed the study after the 2-year follow-up period, or earlier, in case of death or any event that in the opinion of the investigator requires an early termination.

Blood sample for liquid biopsy analysis (DNA and RNA analysis, immunohistochemistry) Tumor biopsy sample (DNA and RNA analysis, immunohistochemistry)

Artificial Intelligence for Help Non-Small Cell Lung Cancer: Measure Cancer Biology and Treatment Response Via Imaging

Artificial Intelligence to Help Non-Small Cell Lung Cancer Patients: Measure Lung Cancer Biology and Treatment Response Via Imaging

Equivalence will be assessed by comparing manual RECIST target response (central readings) with the target response as generated by the automated Radiomics aRECIST workflow. Categorical similarity measures between central panel RECIST and aRECIST will be computed through Cohen's kappa coefficient. aRECIST is considered successful if kappa is at least 0.7 (lower bound), in the full dataset of 150 patients.

A radiomics-based EGFR mutation prediction model will be trained and tested. The EGFR mutation prediction model is considered successful if its AUC of ROC is ≥ 0.65 in the independent test set of 200 patients.

Statistical testing on the performance difference between models predicting survival at 24 months will be performed to compare the prognostic value of aRECIST to that of RECIST. Categorical similarity measures between central panel RECIST and local RECIST will be computed through Cohen's kappa coefficient. Inter-reader agreement within the central panel will be computed trough the kappa coefficient.

This is assessed by comparing biomarker results from solid biopsies with CT-scan imaging features collected at the baseline visit. A customized radiomics approach to identify statistically significant differences in radiomics features between numerous genomic/biological statuses will be used to map the rATLAS.

University Hospital, Antwerp

OncoRadiomics

Symptoms and General Pathology

Rare Diseases

Glioblastoma

Disease Progression

Astrocytoma

Glioma

Neoplasms, Neuroepithelial

Neuroectodermal Tumors

Neuroectodermal Tumors, Primitive

Neoplasms, Germ Cell and Embryonal

Neoplasms by Histologic Type

Neoplasms, Glandular and Epithelial

Neoplasms, Nerve Tissue

Neuroepithelioma

Antineoplastic Agents

Bevacizumab

Magnetic Resonance Imaging (MRI) will be used to compare bevacizumab to the images of vessel and tumor structure.

Magnetic Resonance Imaging (MRI)

Pierre Giglio, MD

This study is for subjects with a diagnosis of a brain tumor called glioblastoma that is being treated with bevacizumab. This study will use a new MRI technique to compare the images of blood vessels and tumor structure to the effectiveness of bevacizumab.

This study is for subjects with a diagnosis of a brain tumor called glioblastoma that is being treated with bevacizumab. Bevacizumab is a drug that your doctor believes is the best treatment option available to subjects at this time for this type of tumor. Bevacizumab affects the growth of blood vessels by tumors such as glioblastoma, thus effectively starving the tumor of oxygen and food.

Magnetic Resonance Imaging (MRI) is a test done by a machine in the radiology department that takes pictures of your body using special magnets, rather than X-rays. With a new MRI scan technique the investigators can take very, very detailed images of the vessel and tumor structure. This project will allow us to compare the images of vessel and tumor structure to the effectiveness of Bevacizumab as a treatment option. With this project the investigators will hopefully develop an accurate way to predict whether or not Bevacizumab will be an effective treatment option for patients.

Imaging Biomarkers of Tissue Microstructure and Vasculature as Predictors of Glioblastoma Multiforme

Imaging Biomarkers of Tissue Microstructure and Vasculature as Predictors of Glioblastoma Multiforme Response to Treatment With Bevacizumab for Progressive Disease

The MRI parameters will help show the differences between bevacizumab-responsive and bevacizumab non-responsive recurrent glioblastoma

The progression of the subject's disease will be evaluated at 3 months.

Medical University of South Carolina

Pharmaceutical Solutions

The 13C-glucose solution will be given intravenously. It will be started at about the same time as the start of surgery, according to the study guidelines.

The 13C-glucose IV solution will be stopped once the surgeon has removed the tumor tissue.

Want to see if using 13C-glucose helps in detecting cancer and deciding on a treatment plan.

Imaging Biomarkers

Ebele Mbanugo, Ed.D, CCRP

Kemp H Kernstine, MD

The purpose of this research study is to develop a method of using magnetic resonance imaging (MRI) to evaluate lung tumors and other thoracic malignancies. An MRI is a scanning device that uses magnets to make images (pictures) of the body. This study is being done to determine what series of reactions (metabolic pathways) pulmonary nodules use as they burn sugar as fuel for growth. The manner in which the tumor burns (metabolizes) sugar for fuel is being investigated by using a natural, slightly modified, sugar solution (13C-glucose) and studying a small sample of the tumor once it is removed at the time of surgery.

The recent report of the findings of the National Lung Screening Trial indicates that screening a high-risk population using low dose CT results in a 20% reduction in lung cancer mortality. At our institution, some of positive nodules that are 1 cm or larger would be imaged using combined fluoro-deoxyglucose positron emission tomography (FDG PET)/CT. Highly suspicious nodules would be biopsied if the risks were manageable. Otherwise, the suspicious nodules not eligible for biopsy and so-called "indeterminate" nodules are followed using CT to be evaluated for interval growth.

The overall goal of this project is to assess several very promising imaging biomarkers that can reflect either the physiological or metabolic status of these nodules in order to develop more accurate imaging algorithms for follow-up that are either less invasive or do not use ionizing radiation or both. Based on our experience with other cancers and our preliminary results in lung cancer, we have identified four potential imaging studies that we believe have the potential to result in validated "imaging biomarkers" that can either individually, or in combination, characterize malignancies. Since tumors tend to exhibit angiogenesis and altered vascular permeability, we and others, have found that analyses of dynamic contrast enhanced MRI (DCEMRI) can be employed as "imaging biomarkers" for malignancy. Tumors often exhibit higher cellularity than benign or normal tissue suggesting that pixel-by-pixel ADC values derived from diffusion weighted MRI could be useful imaging biomarkers. Finally, measuring alterations in metabolic fluxes through the use of pathway specific C-13 labeled compounds, a technique pioneered here at the Advanced Imaging Research Center (AIRC) at UT Southwestern, has shown the capability of providing metabolic fingerprints for malignant and benign tissue. This approach, while invasive, could identify and validate markers that can be detected non-invasively in future studies. We will also employ advanced metabolomics methods to identify potential signature "onco-metabolites" in these lung cancers.

Metabolic Biomarkers in Thoracic Cancers

Physicians and researchers will review the results of the imaging to determine if the patient will receive the \[U-13C\] glucose infusion.

Employ C-13 isotopomer analysis and metabolomics on specimens obtained from resected tissue of suitable patients in this cohort to determine the metabolic alterations present in lung cancer.

University of Texas Southwestern Medical Center

PROFESSOR

Urinary Tract, Sexual Organs, and Pregnancy Conditions

Prostatic Neoplasms

Genital Neoplasms, Male

Urogenital Neoplasms

Genital Diseases

Genital Diseases, Male

Urogenital Diseases

Prostatic Diseases

Male Urogenital Diseases

Daily collection of breath and blood before and after each of the 5 radiotherapy treatment sessions. Before and after daily cone beam CT image collection

Stereotactic Body Radiotherapy

Susan Forman

Duncan B McLaren, MBBS

Personalisation of radiotherapy dose based on real-time assessments of normal tissue and tumour response would maximise cure and minimise treatment related toxicity. During a 5 fraction course of prostate Stereotactic Body Radiotherapy (SBRT) this pilot study will assess whether a number of different biomarker approaches can predict for normal tissue and tumour response. Firstly the investigators will analyse volatile organic compounds released within the breath with each fraction of treatment. Secondly the investigators will analyse cell free normal tissue and tumour DNA released during treatment. Thirdly the investigators will develop imaging processing algorithms to look for imaging biomarkers predicting rectal wall toxicity using pre and post treatment cone beam CT verification images. Each of these approaches will be assessed against prostate specific antigen (PSA), Common Terminology Criteria for Adverse Events (CTCAE v4.0) criteria and Expanded Prostate Cancer Index Composite (EPIC-26) patient reported outcomes with a maximum of 24 months of follow up.

Radiotherapy scheduling and prescription dose does not take into account individual patient heterogeneity in normal tissue response or tumour response. Personalisation of radiotherapy dose based on real-time assessments of normal tissue and tumour response would maximise cure and minimise treatment related toxicity. During a 5 fraction course of prostate Stereotactic Body Radiotherapy (SBRT) this pilot study will assess whether a number of different biomarker approaches can predict for normal tissue and tumour response. Firstly the investigators will analyse volatile organic compounds released within the breath with each fraction of treatment using Gas Chromatography Ion Mobility Spectroscopy (GC-IMS). The investigators have extensive experience in this area within the TOXI-Triage research program (www.toxi-triage.eu/) including deep learning and machine learning techniques to interrogate the metabolomics data generated. Secondly the investigators will analyse cell free normal tissue and tumour DNA released during treatment to assess both tumour and normal tissue response. Radiotherapy releases large amounts in to the blood stream allowing easier quantitative analysis. Thirdly the investigators will look for imaging biomarkers of rectal wall toxicity using imaging analysis algorithms of on-treatment cone beam verification CT images taken before and after each radiotherapy treatment. The RayPilot® system made by Micropos Medical Ltd tracks prostate motion throughout the SBRT delivery to ensure that the treatment dose is delivered with great precision. The potential of each biomarker approach for predicting normal tissue and tumour response will be assessed against PSA and CTCAE v 4.0 toxicity criteria and EPIC-26 patient reported outcome measures after 24 months of patient follow up.

Volatile Organic Compound Breath Analysis, Cell-Free DNA normal tissue and tumour DNA, Cone Beam CT pre and post each fraction of radiotherapy, Genomic saliva analysis.

Using Breath, Cell Free DNA and Image Analysis to PRedIct Normal TissUe and Tumour Response During Prostate Cancer SBRT

Using Breath,Cell Free DNA and Image Analysis to PRedIct Normal TissUe and Tumour Response During Prostate Cancer SBRT With RayPilot® Motion Management

The pilot data will be used to inform a larger study cohort and to establish the optimal methodology and time points for sample collection

Measurement of the change in the 3D chromatogram of volatile organic compound GC-IMS Spectra detected from baseline pre-treatment, to completion of SBRT at each time point, for each patient. Each 3D chromatogram GC-IMS printout is generated from the readings of each axis. The y axis is associated with GC separation of VOC's, the x axis measures the movement of the generated ions (IMS drift time) and the z axis ion detector response equating to concentration. These 3 values separate, identify and quantify the VOC compounds detected.

Change in the density of 90-150 base pair fragment size cfDNA from baseline pre-treatment to completion of SBRT for each time point, for each patient

Dose calculation in cGy between expected and observed actual dose to the rectal wall using pre and post each fraction radiotherapy linear accelerator treatment verification cone beam CT scans

Common Terminology Criteria for Adverse Events CTCAE v 4.0 scores for urinary and bowel treatment related toxicity. Scale runs form Grade 1 mild requiring no intervention to grade 5 death

Expanded Prostate Cancer Index Composite EPIC-26 patient reported outcomes questionnaire. A clinical tool to assess urinary, bowel, sexual and vitality health. The score from each of the 5 domains runs from 0 (none) to 12 (severe) impact on quality of life. Each domain score when added together gives an overall score of zero (unaffected) to 60 (severely affected)

Study title	NCT ID	Conditions	Interventions	Eligibility	Organization
Artificial Intelligence for Help Non-Small Cell Lung Cancer: Measure Cancer Biology and Treatment Response Via Imaging	NCT05254132	Non Small Cell ...	Liquid biopsy	18 Years -	OncoRadiomics
Imaging Biomarkers of Tissue Microstructure and Vasculature as Predictors of Glioblastoma Multiforme	NCT01604590	Glioblastoma	Magnetic Resona...	18 Years - 80 Years	Medical University of South Carolina
Metabolic Biomarkers in Thoracic Cancers	NCT02095808	Lung Cancer	Imaging Biomark...	18 Years -	University of Texas Southwestern Medical Center
Using Breath, Cell Free DNA and Image Analysis to PRedIct Normal TissUe and Tumour Response During Prostate Cancer SBRT	NCT04081428	Prostate Cancer Radiotherapy Si... Volatile Organi... DNA Damage	Stereotactic Bo...	18 Years - 80 Years	NHS Lothian

Spots Global Cancer Trial Database for imaging biomarkers