From September 9 to 12, 2023, the 2023 World Conference on Lung Cancer (WCLC), organized by the International Association for the Study of Lung Cancer (IASLC), was held in Singapore. WCLC is a multidisciplinary oncology conference dedicated to lung cancer and other thoracic malignancies, bringing together more than 7,000 experts and scholars from over 100 countries around the world to jointly discuss frontier achievements and diagnosis and treatment technologies for lung cancer and other thoracic malignancies. As a leader in clinical proteomics, ProteinT was invited to present its collaborative research results on the clinical translation of early lung cancer based on proteomics at this grand event.
This WCLC conference coincided with the 10th anniversary of the establishment of the WCLC Joint Session, a collaboration among three major societies—the International Association for the Study of Lung Cancer (IASLC), the Chinese Society of Clinical Oncology (CSCO), and the China Anti-Cancer Association Lung Cancer Alliance (CAALC). Many scholars called it a "China Special Session," with the theme "Innovation-Driven Lung Cancer Management." Professor Wu Yilong, Professor Bai Chunxue, Professor Zhou Caicun, and Professor Karen Kelly served as conference chairs.
Professor Wu Yilong (left) and Dr. Song Lei of ProteinT (right)
The content of this special session mainly consisted of two parts. The first part invited four Chinese and Western scholars to give keynote reports from European, American, and Chinese perspectives on topics such as early diagnosis of lung cancer, perioperative immunotherapy, the development of novel immunotherapeutics, and clinical trials for rare driver gene-positive cases. The second part featured oral presentations and poster sharing by Chinese experts. During the poster discussion session, the research results jointly conducted by ProteinT and Professor Yang Haihong's team at the First Affiliated Hospital of Guangzhou Medical University were honored to be selected as one of the six selected posters from China, receiving in-depth discussion and exchange with experts and scholars.
Exhibited Posters
Proteomics-based Predictive Model for the Increased Brain Metastasis Risk in Resected Lung Adenocarcinoma with EGFR Mutation
Yang Haihong | The First Affiliated Hospital of Guangzhou Medical University
Chinese title: A Proteomics-based Model for Predicting the Increased Risk of Postoperative Brain Metastasis in Patients with EGFR-Mutant Lung Adenocarcinoma
Patients with brain metastasis have a poor prognosis. Identifying high-risk patients for brain metastasis and carrying out effective intervention is of great significance for reducing or delaying the occurrence of brain metastasis. Professor Yang Haihong's team constructed a protein biomarker prediction model to precisely predict the risk of postoperative brain metastasis in patients with lung adenocarcinoma carrying EGFR mutations, which is of great significance for individualized precision treatment of patients after initial surgery. The study also found that lipid metabolism may be closely related to brain metastasis recurrence in patients with EGFR-mutant non-small cell lung cancer.
A Proteomics-Annotated Risk Model to Predict Recurrence in Stage Ⅰ Non-Small Cell Lung Cancer
Huang Ying | The First Affiliated Hospital of Guangzhou Medical University
Chinese title: A Proteomics-based Risk Prediction Model for Postoperative Recurrence of Stage I Non-Small Cell Lung Cancer
The integration of tumor proteomics and clinicopathological features can improve the accuracy of predicting postoperative recurrence risk in patients with stage I non-small cell lung cancer. Stratifying the recurrence risk of postoperative patients will help physicians develop personalized follow-up plans for patients, including the review cycle and the application of adjuvant therapy.
Postoperative Recurrence Risk Prediction Product for Stage I Lung Cancer Patients
PT-L1™
ProteinT-Lung1™ (PT-L1™) uses liquid chromatography-tandem mass spectrometry (LC-MS/MS) technology to perform proteomics detection on patients' tumor tissues, and calculates patients' recurrence risk scores based on ProteinT's independently developed stage I lung cancer recurrence risk model to assess patients' 5-year postoperative recurrence risk. Based on PT-L1™ predictions, the 5-year disease-free survival rates for patients with low, medium, and high recurrence risk were 98.8%, 64.3%, and 13.3%, respectively, with a negative predictive value (NPV) as high as 98.75%. For patients with medium-to-high recurrence risk predicted by the model, the frequency of follow-up and re-examination should be increased, and reasonable intervention can achieve early diagnosis and treatment of recurrence, prolong survival, and avoid treatment delays; for patients with low recurrence risk, following the routine follow-up plan can reduce screening costs and alleviate patients' psychological stress and financial burden. This provides a basis for clinicians and patients to develop more personalized screening plans and intervention measures.
The good news keeps coming. As a national high-tech enterprise focusing on the frontier multi-omics field of precision medicine, the approval of several of ProteinT's independently developed in vitro diagnostic products marks that the safety and efficacy of the products have been recognized by the state. In the future, the company will continue to deepen its work in proteomics and other multi-omics fields, develop more technologically innovative products, and provide physicians and patients with higher-quality products and services.
