Neoplasms

Digestive System Diseases

All Conditions

Symptoms and General Pathology

Rare Diseases

Stomach Neoplasms

Atrophy

Gastritis, Atrophic

Gastritis

Pathological Conditions, Anatomical

Gastroenteritis

Gastrointestinal Diseases

Stomach Diseases

Gastrointestinal Neoplasms

Digestive System Neoplasms

Chronic Graft Versus Host Disease

Stomach Cancer

Corpus-dominant chronic atrophic gastritis was characterized by a PGI/PGII ratio of less than 3.

Healthy participants in the TwinGene cohort were included.

Metabolomic profiling using serum samples was performed based on Nightingale Blood Biomarker Analysis platform; Proteomic profiling will be performed by both Scanning SWATH and OLINK® Explore 384 Oncology panel.

Metabolomic profiling

The overall aim is to utilize multi-omics approach to identify novel etiopathogenesis and early detection biomarkers for stomach cancer precursor lesions. To achieve this aim, first the investigators will use stored serum samples to perform metabolomics profiling among 12,599 twin subjects, among whom 1034 were deemed to have chronic atrophic gastritis based on measured pepsinogen I and II levels. Logistic regression will be used to search for metabolites related to the risk of chronic atrophic gastritis. Second, the investigators will further measure serum proteome by using two quantitatively precise proteomics assays, among the above-mentioned twin subjects. Identified protein biomarkers will be combined with metabolomics biomarkers to create a prediction model for chronic atrophic gastritis. The results will hopefully improve our understanding of the etiological factors and provide promising early detection biomarkers for stomach cancer precursor lesions.

The study population is part of the Swedish Twin Registry (STR), which has since its establishment in the late 1950s collected questionnaire data from all twins born after 1886. The data in this specific study is a subset of the Screening Across the Lifespan (SALT) study within the STR, in which all twins born between 1911-1958 were interviewed between 1998-2002. The subcohort named TwinGene was set-up between the years 2004 and 2008 when participants were invited to respond to a questionnaire on common diseases and provide a blood sample. Samples were collected from 12,618 twins born 1958 or earlier, of which blood sample from 12,609 were available. After excluding 10 samples which were unable to link to the available environmental data, a total of 12,599 blood samples were analyzed. Corpus-dominant CAG was characterized by a PGI/PGII ratio of less than 3. Metabolomic profiling using serum samples has been performed based on Nightingale Blood Biomarker Analysis platform. Proteomic profiling will be performed by both Scanning SWATH and OLINK® Explore 384 Oncology panel. History of H. pylori infection is examined by measuring serum IgG antibodies against H. pylori, using ELISA. Detailed lifestyle information collected by questionnaires includes education, smoking, snuff dipping, alcohol drinking, drug use, diet, and height/weight, etc. Metabolites will be log transformed prior to analyses, due to its usually skewed distribution. For each metabolite, firstly, CAG patients will be compared with all the CAG-free controls. Wilcoxon-Mann-Whitney test or Kruskal-Wallis test will be used for comparing differences of protein expressions between CAG and non-CAG groups, and multiple comparisons will be adjusted using Bonferroni correction. Generalized estimation equation (GEE) models with the robust option will be fitted to estimate the odds ratios (ORs). Second, in the comparison with MZ co-twin controls and DZ co-twin controls, only complete twin pairs with discordant CAG will be included in the study. Specifically, conditional logistic regression models will be used to control for the matching within co-twin pairs. The investigators will further combine metabolomics and proteomics data, and try to build up a CAG prediction model. Covariates will include age, sex, H. pylori seropositivity, education level, smoking, snuff dipping, and alcohol drinking. Joint effects of different metabolites and interaction with other covariates will also be examined.

Participants from TwinGene provided blood samples.

Multi-omics Analyses on Etiology and Early Detection of Stomach Cancer Precursor Lesions

Multi-omics Approach for Identification of Etiopathogenesis and Early Detection Biomarkers of Stomach Cancer Precursor Lesions

Karolinska Institutet

Professor

Blood and Lymph Conditions

Hematologic Neoplasms

Hematologic Diseases

Patients on this study must have either a suspected or confirmed solid tumor or hematological cancer. The intervention performed in this study is the molecular analysis of cancer. The samples will be taken at the time of the patient's planned diagnostic or staging procedure. If the patient is scheduled for surgery a sample of tissue not required for their diagnosis will be obtained and used for this research study. If the patient has undergone a previous diagnostic procedure, some of the stored tissue from that procedure will be submitted for molecular analysis as well.

The intervention performed in this study is the molecular analysis of cancer. Samples to be tested for genetic alterations will be collected during the course of a routine diagnostic procedure such as a surgery or tumor biopsy. Samples that have been stored from previous diagnostic procedures will be analyzed as well. This testing will be performed by the Department of Pathology at Rhode Island Hospital or an outside laboratory designated by Rhode Island Hospital. The extent of molecular testing will be different in each individual case. For example, in some cases, study of genetic alterations will start with whole genome or exome sequencing and will be confirmed by targeted Sanger resequencing, single nucleotide polymorphism, and transcriptome analysis. In other cases targeted multigene panel sequencing or targeted amplicon Sanger sequencing will be the initial and only step.

Molecular Analysis of Cancer

Andrew Schumacher, M.S.

Allison Jean, B.A.

Priscilla Merriam, M.D.

Howard Safran, M.D.

Maria Constantinou, M.D.

Anthony Mega, M.D.

Kimberly Perez, M.D.

Amy Pilotte, N. P.

Humera Khurshid, M.D.

Evgeny Yakirevich, M.D.

Murray Resnick, M.D.

James Butera, M.D.

Mary Anne Fenton, M.D.

Lucia Fontes-Bortes, N.P.

Peter Quesenberry, M.D.

Matthew Quesenberry, M.D.

John Reagan, M.D.

Eric Winer, M.D.

Thomas DiPetrillo, M.D.

Jaroslaw Hepel, M.D.

Kara Lynne Leonard, M.D.

David Tracey, P.A.

Inna Yakirevich, N.P.

Sharon Benson, N.P.

Heinrich Elinzano, M.D.

Timothy Kinsella, M.D.

Thomas Ng, M.D.

Maureen Jean, R.N.

Diane Martel, R.N.

Jennifer Collins, N.P.

Irene Kolberg, N.P.

Jodi Layton, M.D.

Fred Schiffman, M.D.

Edward Wittles, M.D.

Angela Taber, M.D.

Camille Higel-McGovern, N.P.

Amy Pilotte, N.P.

Xristin Maestri, N.P.

The purpose of this study is to discover genetic changes associated with different cancers. With the information from this study the investigators hope to provide better ways to prevent, detect and treat many cancers.

Many diseases can result from changes in a person's genetic material that causes cells to not work properly. Currently, researchers and doctors know some of the genetic changes that can cause disease, but they do not know all of the genetic changes that can cause disease.

This project is designed to identify genetic changes that can cause cancer in humans. Specimens will be collected from a scheduled diagnostic or routine (i.e. blood draw for counts) procedure and may include samples from the tissue itself (surgery), bone marrow, blood, saliva, urine, spinal fluid, sputum, joint fluid, seminal fluid, ascites (a fluid that fills up in the abdomen), and/or pleural fluid (fluid in the lung cavity), to either confirm the diagnosis of cancer or to help to decide how best to treat cancer or other illness. Additionally archived tissue may be analyzed. Samples may be stored for future use in later experiments. The Department of Pathology at Rhode Island Hospital will store the samples.

Information from the medical record, such as responses to treatments or family history of cancer, will be collected.

Complex, progressive, multigenic, somatic mutations of the genome are now widely accepted as the primary driving force in the evolution of cancer initiation, growth, metastasis and pharmacoresistance. Different types of tumors are associated with mutations in distinct sets of genes, and there is a pressing need for a sequencing-based method of analyzing panels of candidate genes that differ for each tumor type.

Traditional approaches to sequence analysis employing capillary electrophoresis-based Sanger sequencing are widely used to guide therapy for patients with lung and colorectal cancer and for melanoma, sarcomas, leukemias and lymphomas. This technology is limited in throughput, scalability, speed, and resolution. The emerging technology such as next-generation sequencing (NGS) - holds a number of advantages over traditional methods, including the ability to fully sequence large numbers of genes in a single test and simultaneously detect deletions, insertions, copy number alterations, translocations, and exome-wide base substitutions in all known cancer-related genes.

Sequencing the whole genome is financially prohibitive for many potentially valuable applications. One alternative to whole genome methods is target enrichment, such as exome sequencing, which captures and sequences only protein coding regions. The exome represents 1-2% of the human genome; however contains the vast majority of disease causing alterations. In addition to exome sequencing, full-length transcriptome (mRNA) sequencing offers a fast and inexpensive alternative. It is an easier method to identify coding sequences and capture variants in genes that are expressed, as well as to generate additional information, such as gene expression level and splicing patterns.

The goal of this study is to investigate genomic, transcriptomic and proteomic alterations in human solid cancers and hematologic malignancies.

Patients \>18 y.o. diagnosed with cancer (including any solid tumor or hematologic malignancy) or patients who are undergoing a procedure for the diagnosis of a presumed cancer are eligible.

The research analysis will be performed by the department of pathology or the division of hematology oncology. The body/blood tissue analyzed will be from extra tissue/blood that is not needed for diagnosis or evaluation of the patient's cancer. All samples will be de-identified. Samples will be stored for an indefinite period of time or until all samples are utilized.

Molecular Testing of Cancer by Integrated Genomic, Transcriptomic, and Proteomic Analysis

MOLECULAR TESTING OF CANCER BY INTEGRATED GENOMIC, TRANSCRIPTOMIC, AND PROTEOMIC ANALYSIS

Rhode Island Hospital

Gland and Hormone Related Diseases

Pancreatic Neoplasms

Endocrine Gland Neoplasms

Pancreatic Diseases

Endocrine System Diseases

Pancreatic Cancer

Gastrointestinal Agents

All Drugs and Chemicals

Pancrelipase

Pancreatin

Sequencing of cfDNA methylation and proteomic analysis of two sets of capsular fluid samples

cfDNA methylation sequencing and proteome analysis

Kaixuan Wang

Kaixuan Wang, MD

Shiyu Li

Chengye Pan

The goal of this observational study is to test in patients with cystic tumor of pancreas. The main questions it aims to answer are:

Screening of molecular diagnostic markers for pancreatic cystic tumors by cfDNA methylation sequencing of pancreatic cystic fluid and proteomic assays to distinguish benign from malignant and mucinous/non-mucinous, correlate with pathological features, and find molecular features associated with the degree of malignancy.

Participants will Provide post-operative cyst fluid specimens.

Patients with pancreatic cystic tumors were divided into control, mucinous tumor and non-mucinous tumor groups, and cfDNA molecules and protein molecules that were significantly altered between different groups were found by cfDNA methylation sequencing of pancreatic cystic fluid and proteomic detection techniques. Multi-omics analysis was performed to construct a more efficient molecular diagnostic marker model. Correlating models with pathological features to find molecular features associated with the degree of malignancy.

Construction of Molecular Diagnostic Marker Model for Pancreatic Cystic Tumors Based on Pancreatic Cystic Fluid Samples

Construction of Molecular Diagnostic Marker Models for Pancreatic Cystic Tumors Based on cfDNA Methylation Sequencing and Proteomic Analysis of Pancreatic Cystic Fluid Samples

cfDNA methylation data and proteome analysis data

Identification of protein and circulating gene methylation species in cyst fluid and quantification of their concentrations using mass spectrometry. Characterize cfDNA methylation and proteomics of cyst fluid in patients with pancreatic cystic neoplasm (PCN).

A machine learning approach was used to further screen for characteristically methylated cfDNA and proteins in PCN patients.Establishment of a diagnostic model for pancreatic cystic tumors.

A machine learning approach was used to further screen for characteristically methylated cfDNA and proteins in PCN patients.To establish a model for the identification of mucinous and non-mucinous.

A machine learning approach was used to further screen for characteristically methylated cfDNA and proteins in PCN patients.Development of a progression benign malignancy prediction model.

Zhaoshen Li

Director of Gastroenterology Department of Changhai Hospital

Individuals receiving radiation therapy as definitive or neo-adjuvant therapy for selected malignancies, including head and neck, lung, esophageal, rectal cervical and prostate cancers.

Kas R Badiozamani, MD

The purpose of this study is to determine whether specific assays of DNA damage repair proteins can be used in patients undergoing radiation therapy. The ultimate goal of this research is to develop clinically useful biomarkers from blood samples that could be used to customize radiation treatment for individuals, leading to reduced side effects and improved outcomes.

Pilot Study of Biomarkers for Radiation Therapy

Investigating Proteomic Biomarkers of Radiation Therapy Outcome: A Pilot Study

Virginia Mason Hospital/Medical Center

Fred Hutchinson Cancer Center

Benaroya Research Institute

Kas Badiozamani

Urinary Tract, Sexual Organs, and Pregnancy Conditions

Diseases and Abnormalities at or Before Birth

Syndrome

Polycystic Ovary Syndrome

Hyperandrogenism

Amenorrhea

Gonadal Disorders

Cysts

Ovarian Cysts

Ovarian Diseases

Adnexal Diseases

Genital Diseases, Female

Genital Diseases

Urogenital Diseases

Female Urogenital Diseases

Pregnancy Complications

Female Urogenital Diseases and Pregnancy Complications

Menstruation Disturbances

Hypoglycemic Agents

Vasoconstrictor Agents

Respiratory System Agents

Insulin

Insulin, Globin Zinc

Hormones

Epinephrine

Racepinephrine

Epinephryl borate

10 women with exercise-associated hypothalamic amenorrhea

5 lean women with hyperandrogenic polycystic ovary syndrome. 5 women with weight excess and hyperandrogenic polycystic ovary syndrome.

5 lean women with non-hyperandrogenic polycystic ovary syndrome 5 women with weight excess and non-hyperandrogenic polycystic ovary syndrome

10 women who exercise as intensively as women with exercise-associated hypothalamic amenorrhea but with normal ovulatory cycles.

10 women matched by age and body mass index with women with polycystic ovary syndrome who do not perform physical activity on a regular basis

* Weight and height.
* Waist-to-hip ratio.
* Body composition: Bioelectrical impedance and \[Dual energy X-ray absorptiometry (DEXA)\].

Anthropometric and physical examination

Indirect calorimetry, accelerometer and seven-day dietary recall

* Lipid profile.
* Oral glucose tolerance test: plasma glucose and insulin, insulin sensitivity indices, gastrointestinal hormones, adipokines, oxidative stress markers.
* Sex steroid profile.
* Hypothalamic-pituitary-adrenal axis study.
* Ferrokinetic study.
* Subclinical chronic inflammatory markers.

Biochemical, hormonal and metabolic phenotyping

* Polycystic ovarian morphology.
* Carotid intima-media thickness.
* Eco-FAT: Ultrasound measurements of adipose tissue depots including sc, preperitoneal, intraperitoneal (ip), mesenteric, and perirenal fat thickness.

Sonographic studies

A\&D TM2430EX oscillometric devices (A\&D Company Limited, Tokyo, Japan).

24-hour Ambulatory blood pressure monitoring

Subcutaneous fat tissue and muscle tissue for proteomics an gene expression studies.

Percutaneous biopsy

Parasympathetic and sympathetic responses to deep breathing, Valsalva's maneuver and orthostatism.

Cardiovascular autonomic function studies

Oral smear and feces specimen

Elena Fernández Durán

Héctor F Escobar-Morreale, PhD, MD

Manuel Luque-Ramírez, PhD, MD

Reproduction requires from women enough energy depots to warrant an adequate nutritional supply to the fetus. Hence, adipose tissue is able to communicate with female hypothalamic-pituitary-ovary axis. The hypothesis of the project is that abnormalities in the quantity (absolute and relative to lean body mass), distribution and/or function of adipose tissue are associated with functional forms of female gonadal dysfunction in predisposed women, in a spectrum of anomalies that go from hypothalamic amenorrhea to the polycystic ovary syndrome (PCOS). To challenge this hypothesis, the investigators will study 5 groups of 10 women each: women with exercise-associated hypothalamic amenorrhea, women without ovulatory dysfunction that exercise equally, non-hyperandrogenic patients with PCOS, hyperandrogenic patients with PCOS, and healthy control women comparable to those with PCOS. The aims of the study will be:

Primary objective: To identify novel signalling factors originating from adipose tissue and muscle using targeted and nontargeted evaluation of the proteome and of gene expression of superficial subcutaneous fat, deep subcutaneous fat (which mimics visceral adipose tissue) and skeletal muscle.

Secondary objectives:

1. To study the serum adipokine profile - including those identified by the primary objective - and circulating gut hormones during fasting and after a glucose load in the 5 groups of women, and their associations with sexual hormones and body fat distribution.
2. To study body composition and body fat distribution in these women and their relationships with:

2.1, Sex steroid profiles.

2.2. Classic cardiovascular risk factors: carbohydrate metabolism, lipid profiles and blood pressure.

2.3 Markers of low-grade chronic inflammation.

2.4. Oxidative stress markers.

2.5. Cardiovascular autonomic function.

2.6. Surrogate markers of subclinical atherosclerosis.

2.7. Circulating concentrations of endocrine disruptors.

2.8. Oral and gut microbiome.

The results will provide a better understanding of the mechanisms linking body energy depots with the female reproductive axis and, hopefully, the identification of potential biomarkers for the diagnosis and treatment of the disorders studied here.

Serum Plasma Whole blood samples Subcutaneous adipose tissue by percutaneous biopsy Muscle tissue by percutaneous biopsy Feces Oral smear

Body Fat as Determinant of Female Gonadal Dysfunction

Amount, Distribution and Dysfunction of Body Fat as Determinants of Female Gonadal Dysfunction: From Functional Hypothalamic Amenorrhea to the Polycystic Ovary Syndrome

The investigators will deposit any datasets and supplemental materials to a generalist repository. The investigators will refer to the deposited material as an item in the bibliography of any manuscript and number the reference appropriately within the text.

At fasting and after an oral glucose challenge: Circulating concentrations of Leptin, Adiponectin, Chemerin, Lipocalin-2, Adipsin, Plasminogen Activator Inhibitor (PAI)-1, Monocyte Chemoattractant Protein (MCP)-1, and Soluble Leptin Receptor by multianalyte profiling on the Luminex Magpix system (Luminex Technologies, Austin, USA.).

At fasting and after an oral glucose challenge: Circulating concentrations of Amylin, C-Peptide, Ghrelin, Gastric Inhibitory Peptide (GIP), Glucagon-Like Peptide (GLP)-1, Glucagon, IL-6, Insulin, Pancreatic Polypeptide (PP), Peptide YY, Tumor Necrosis Factor (TNF)-α by multianalyte profiling on the Luminex Magpix system (Luminex Technologies, Austin, USA.).

Body mass index in in kg/m\^2. Sex steroids (including circulating total testosterone, estradiol, androstenedione, dehydroepiandrosterone-sulphate and estrone) measured by liquid chromatography tandem mass spectrometry (LC-MS/MS). Free testosterone will be calculated from total testosterone and sex hormone binding globulin levels.

Fat mass% by bioelectric impedanciometry and DEXA. Sex steroids (including circulating total testosterone, estradiol, androstenedione, dehydroepiandrosterone-sulphate and estrone) measured by liquid chromatography tandem mass spectrometry (LC-MS/MS). Free testosterone will be calculated from total testosterone and sex hormone binding globulin levels.

Lean mass% by bioelectric impedanciometry and DEXA. Sex steroids (including circulating total testosterone, estradiol, androstenedione, dehydroepiandrosterone-sulphate and estrone) measured by liquid chromatography tandem mass spectrometry (LC-MS/MS). Free testosterone will be calculated from total testosterone and sex hormone binding globulin levels.

Adipose tissue depots will be estimated using a Toshiba Nemio XG SSA-580A Diagnostic Ultrasound System. Minimum sc and preperitoneal fat thicknesses will be measured at the level of the xyphoid process. Maximum sc fat thickness will be measured at the level of the umbilicus. Intraperitoneal fat thickness will be measured placing a probe transversally in the midline of abdomen, 2 cm above the umbilicus. Three measures of ip fat thickness will be obtained: the distance from the fascia of rectus abdominis muscle to the vertebral column, the distance from the peritoneum to the vertebral column, and the distance from the linea alba to the vertebral column. Perirenal fat thickness will be estimated as the distance from the perirenal fascia to the renal surface. Sex steroids will be measured as previously described.

Fat mass, lean mass and body fat depots will be measured as previously described. Fasting glucose and insulin levels will be used for calculating the homeostasis model assessment of insulin resistance (HOMA-IR), and the composite insulin sensitivity index will be estimated from the glucose and insulin concentrations measured during the oral glucose tolerance test. Sex steroids will be measured as previously described.

Fat mass, lean mass and body fat depots will be measured as previously described. Circulating HDL-cholesterol and phospholipid levels will be measured by enzymatic methods after precipitation of plasma with phosphotungstic acid and Mg2+. Total cholesterol and triglyceride levels will be determined by enzymatic methods. LDL-cholesterol concentrations will be estimated by Friedewald's equation. Circulating apolipoprotein (Apo) AI, Apo B100, and lipoprotein (a) levels will be determined by kinetic immunonephelometry. Sex steroids will be measured as previously described.

Fat mass, lean mass and body fat depots will be measured as previously described. Office blood pressure will be determined as the mean of three manual sphygmomanometer readings in the sitting position. Sex steroids will be measured as previously described.

Fat mass, lean mass and body fat depots will be measured as previously described. Twenty-four-hour ambulatory blood pressure monitoring will be performed using an A\&D TM2430EX oscillometric device (A\&D Co., Ltd., Tokyo, Japan). The cuff (12 × 22 cm for lean participants, 14 × 30 cm for overweight or obese participants) will placed on the nondominant arm in every woman. The period from 0700 to 2300 h will be considered daytime, and from 2300 until 0700 h the next day will be considered nighttime, reflecting the usual sleeping habits of Spaniards. Systolic, diastolic, and mean blood pressure as well as heart rate will be measured every 20 min during daytime and every 30 min during nighttime. Sex steroids will be measured as previously described.

Fat mass, lean mass and body fat depots will be measured as previously described. Cardiovascular autonomic function will be assessed by the blood pressure and heart rate responses to active standing, and Ewing and Clarke's tests. Sex steroids will be measured as previously described.

Fat mass, lean mass and body fat depots will be measured as previously described. Imaging will be conducted using a high-resolution 7.5-MHz phased-array transducer by the same trained operator in all the participants. Sex steroids will be measured as previously described.

Fat mass, lean mass and body fat depots will be measured as previously described. Oxidative stress profile will be measured by enzymatic assays: Plasma thiobarbituric acid reactive substances, total antioxidant capacity, nitrotyrosine, protein carbonyl groups and erythrocyte glutathione peroxidase levels. Sex steroids will be measured as previously described.

Participants will be instructed to collect fecal and salivary samples. DNA samples wil be used for massive sequencing of 16S ribosomal DNA (rDNA) amplicons in a MiSeq platform (Illumina). The bacterial diversity will be estimated by using Shannon, Chao 1, Jaccard, and Sorensen indexes with their SDs. Taxonomic affiliations will be assigned by using the RDP_classifier from the Ribosomal Database Project (RDP), and readings with RDP score value \<0.8 will be assigned to the upper taxonomic rank, leaving the last rank as unidentified. Sex steroids will be measured as previously described.

Study title	NCT ID	Conditions	Interventions	Eligibility	Organization
Multi-omics Analyses on Etiology and Early Detection of Stomach Cancer Precursor Lesions	NCT06267703	Chronic Atrophi...	Metabolomic pro...	46 Years - 97 Years	Karolinska Institutet
Molecular Testing of Cancer by Integrated Genomic, Transcriptomic, and Proteomic Analysis	NCT02213822	Solid Tumors Hematological M...	Molecular Analy...	18 Years -	Rhode Island Hospital
Molecular Testing of Cancer by Integrated Genomic, Transcriptomic, and Proteomic Analysis	NCT02213822	Solid Tumors Hematological M...	Molecular Analy...	18 Years -	Rhode Island Hospital
Construction of Molecular Diagnostic Marker Model for Pancreatic Cystic Tumors Based on Pancreatic Cystic Fluid Samples	NCT05737953	Pancreatic Neop... DNA Methylation Proteome	cfDNA methylati...	18 Years -	Changhai Hospital
Multi-omics Analyses on Etiology and Early Detection of Stomach Cancer Precursor Lesions	NCT06267703	Chronic Atrophi...	Metabolomic pro...	46 Years - 97 Years	Karolinska Institutet
Pilot Study of Biomarkers for Radiation Therapy	NCT01050725	Cancer		18 Years -	Benaroya Research Institute
Body Fat as Determinant of Female Gonadal Dysfunction	NCT03841981	Polycystic Ovar... Hypothalamic Am...	Anthropometric ... Indirect calori... Biochemical, ho... Sonographic stu... 24-hour Ambulat... Percutaneous bi... Cardiovascular ... Oral smear and ...	18 Years - 40 Years	Fundacion para la Investigacion Biomedica del Hospital Universitario Ramon y Cajal
Construction of Molecular Diagnostic Marker Model for Pancreatic Cystic Tumors Based on Pancreatic Cystic Fluid Samples	NCT05737953	Pancreatic Neop... DNA Methylation Proteome	cfDNA methylati...	18 Years -	Changhai Hospital
Pilot Study of Biomarkers for Radiation Therapy	NCT01050725	Cancer		18 Years -	Benaroya Research Institute
Molecular Testing of Cancer by Integrated Genomic, Transcriptomic, and Proteomic Analysis	NCT02213822	Solid Tumors Hematological M...	Molecular Analy...	18 Years -	Rhode Island Hospital

Spots Global Cancer Trial Database for proteome

Every month we try and update this database with for proteome 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 proteome

Every month we try and update this database with for proteome 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 proteome 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.