Detection of Lung Cancer by Plasma Lipids

NCT04287712 | Completed

• 1 other identifier: 2018PHB233-01
• Study Type: observational
• Target: 558
• Locations: 1 country
• Sites: 1

Brief Summary

There are no reliable blood-based tests currently available for early-stage lung cancer diagnosis. We try to establish a highly accurate method for detecting early-stage lung cancer by combining machine learning with untargeted and targeted metabolomics .

Conditions

Early-Stage Lung Cancer

Keywords

Early-Stage Lung Cancer; Plasma Metabolomics; Lipids; Machine Learning

Outcome Measures

Primary Outcomes (1)

• Plasma Lipids

  A detection model based on 9 lipids were developed, including 3 lysophosphatidylcholines, 5 phosphatidylcholines, and a triglyceride. The 9 lipids were detected by targeted metabolomics by mass spectrometry.

  All samples were detected together after participants recruitment and sample collection. All samples were detected within 18 months from sample collection.

Study Arms (1)

Participants received surgery

Patients who underwent surgery at the Department of Thoracic Surgery of Peaking University People's Hospital, Jiangsu Cancer Hospital, and Beijing Haidian Hospital were enrolled with the following criteria: 1) pathologically confirmed lung cancer; 2) no history of other malignancies; 3) no anti-cancer treatment (chemotherapy, radiotherapy, targeted therapy, etc.) before surgery. Plasma samples were collected before surgery and plasma lipids were detected by mass spectrometry. Pathological diagnosis and clinical characteristics of enrolled participants were retrieved.

Diagnostic Test: Plasma lipids

Interventions

Plasma lipids DIAGNOSTIC_TEST

Plasma lipids were detected by an Ultimate 3000 ultra-high-performance liquid chromatography (UHPLC) system coupled with Q-Exactive MS (Thermo Scientific) . Then a detection model was built based on plasma lipids using machine learning algorithm.

Participants received surgery

Eligibility Criteria

• Age: 18 Years+
• Sex: all
• Healthy Volunteers: Yes
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Non-Probability Sample

Study Population

Patients who with pulmonary nodules or opacity and underwent surgery at the Department of Thoracic Surgery of Peaking University People's Hospital, Jiangsu Cancer Hospital, and Beijing Haidian Hospital were enrolled

You may qualify if:

• pulmonary nodules or opacity
• plan to receive surgery

You may not qualify if:

• history of other malignancies
• received anti-cancer treatment (chemotherapy, radiotherapy, targeted therapy, etc.) before surgery

Sponsors & Collaborators

• Peking University People's Hospital: lead
• Beijing Haidian Hospital: collaborator
• Jiangsu Cancer Institute & Hospital: collaborator
• Peking University Health Science Center: collaborator

Study Sites (1)

Peking University People's Hospital

Beijing, Beijing Municipality, 100044, China

Location

Biospecimen

Retention: SAMPLES WITHOUT DNA

For enrolled participants, 4 ml of peripheral blood were collected in tubes containing EDTA and all participants had fasted at least 8 hr before blood collection. Whole blood was centrifuged at 1600 g for 10 min followed by centrifugation at 16000 g for 10 min. Plasma aliquots were transferred into cryovials and stored at -80 °C.

MeSH Terms

Conditions

Lung Neoplasms

Condition Hierarchy (Ancestors)

Respiratory Tract Neoplasms; Thoracic Neoplasms; Neoplasms by Site; Neoplasms; Lung Diseases; Respiratory Tract Diseases

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: PROSPECTIVE
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: Prof

Study Record Dates

• First Submitted: February 13, 2020
• First Posted: February 27, 2020
• Study Start: December 13, 2018
• Primary Completion: October 31, 2019
• Study Completion: May 20, 2020
• Last Updated: June 4, 2020

Record last verified: 2020-06

Locations

CN (1)