Tumor Markers in Lung Cancer: Current Progress, Role in Targeted Therapy and Further Direction

A special issue of Cancers (ISSN 2072-6694). This special issue belongs to the section "Tumor Microenvironment".

Deadline for manuscript submissions: closed (4 January 2024) | Viewed by 1646

Special Issue Editor


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Guest Editor
Department of Pathology, Johns Hopkins Medical Institutions, Baltimore, MD 21224, USA
Interests: genetic biomarkers; lung cancer; early detection of lung and prostate cancer

Special Issue Information

Dear Colleagues,

Lung cancer is one of the leading cancer-related causes of death worldwide. The  five-year survival rate of patients is around 50% without metastasis, while only about 5% of patients with distant tumors survive. Other than personal living habits, early diagnosis and proper treatment highly affect the quality of life of patients. Effective biomarkers could provide novel therapeutic opportunities, targeting therapy, immunotherapy, etc., that could significantly prolong the outcomes of patients. For example, overexpressed PD-L1 on the tumor surface is associated with metastasis of tumor cells, which leads to the development of anti-PD-L1 monoclonal antibodies or vaccines that block PD-1/PD-L1 signaling. For this Special Issue, papers discussing any biomarkers related to lung cancer, circulating tumor cells, tumor-free DNA, circulating miRNAs, small molecules, cytokines, checkpoint markers, PD-L1, exosomes, and so on are welcome.

This Special Issue will focus on publishing high-quality works related to the biomarkers for the early diagnosis of lung cancer, prediction of treatment resistance, and prevention of the recurrence of tumors that might raise and promote novel diagnostic and/or therapeutic strategies for daily clinical practice to benefit patients.

Prof. Dr. Qing Kay Li
Guest Editor

Manuscript Submission Information

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Keywords

  • lung cancer
  • NSCLC
  • SCLC
  • biomarker
  • early screening
  • diagnosis
  • PD-1/PD-L1

Published Papers (1 paper)

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Research

16 pages, 2759 KiB  
Article
Validation of a Proteomic Signature of Lung Cancer Risk from Bronchial Specimens of Risk-Stratified Individuals
by S.M. Jamshedur Rahman, Sheau-Chiann Chen, Yi-Ting Wang, Yuqian Gao, Athena A. Schepmoes, Thomas L. Fillmore, Tujin Shi, Heidi Chen, Karin D. Rodland, Pierre P. Massion, Eric L. Grogan and Tao Liu
Cancers 2023, 15(18), 4504; https://doi.org/10.3390/cancers15184504 - 10 Sep 2023
Cited by 1 | Viewed by 1369
Abstract
A major challenge in lung cancer prevention and cure hinges on identifying the at-risk population that ultimately develops lung cancer. Previously, we reported proteomic alterations in the cytologically normal bronchial epithelial cells collected from the bronchial brushings of individuals at risk for lung [...] Read more.
A major challenge in lung cancer prevention and cure hinges on identifying the at-risk population that ultimately develops lung cancer. Previously, we reported proteomic alterations in the cytologically normal bronchial epithelial cells collected from the bronchial brushings of individuals at risk for lung cancer. The purpose of this study is to validate, in an independent cohort, a selected list of 55 candidate proteins associated with risk for lung cancer with sensitive targeted proteomics using selected reaction monitoring (SRM). Bronchial brushings collected from individuals at low and high risk for developing lung cancer as well as patients with lung cancer, from both a subset of the original cohort (batch 1: n = 10 per group) and an independent cohort of 149 individuals (batch 2: low risk (n = 32), high risk (n = 34), and lung cancer (n = 83)), were analyzed using multiplexed SRM assays. ALDH3A1 and AKR1B10 were found to be consistently overexpressed in the high-risk group in both batch 1 and batch 2 brushing specimens as well as in the biopsies of batch 1. Validation of highly discriminatory proteins and metabolic enzymes by SRM in a larger independent cohort supported their use to identify patients at high risk for developing lung cancer. Full article
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