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Biomedicines
Special Issues
Advances in Lung Cancer: From Bench to Bedside
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Advances in Lung Cancer: From Bench to Bedside

A special issue of Biomedicines (ISSN 2227-9059). This special issue belongs to the section "Cancer Biology and Oncology".

Deadline for manuscript submissions: 31 July 2025 | Viewed by 392

Special Issue Editor

Dr. Seung Hyeun Lee

E-Mail Website
Guest Editor
Division of Pulmonary, Allergy, and Critical Care Medicine, Department of Internal Medicine, Kyung Hee University Hospital, Kyung Hee University College of Medicine, Seoul 02447, Republic of Korea
Interests: lung cancer; immunotherapy; targeted therapy

Special Issue Information

Dear Colleagues,

Lung cancer remains one of the most prevalent malignancies globally and is the leading cause of cancer-related mortality. Current statistics indicate that the 5-year survival rate for lung cancer patients is below 21%, influenced by factors such as the asymptomatic nature of early disease, advanced patient age, and respiratory dysfunction. Over the past decade, the survival outcomes for non-small cell lung cancer (NSCLC) have significantly improved due to the advent of immunotherapy and targeted therapies. These novel approaches involve the identification of predictive biomarkers, the transformation of standard practices in pathology and oncology, and enabling substantial survival benefits in patients with NSCLC. Currently, therapeutic decisions are informed by genetic alterations such as EGFR, ALK, and KRAS, as well as PD-L1 protein expression. A number of clinical trials are actively exploring new molecular targets, innovative drugs, and combination treatment protocols to combat lung cancer.

This Special Issue will highlight recent breakthroughs in oncology research and cutting-edge developments in diagnosis and interventions in lung cancer.

For this Special Issue, we welcome original research articles and reviews. Research areas may include (but are not limited to) the following: biomarkers, multiomics, big data, and translational research on lung cancer.

We look forward to receiving your contributions. 

Dr. Seung Hyeun Lee
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Biomedicines is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • lung cancer
  • immunotherapy
  • targeted therapy
  • translational oncology
  • biomarkers
  • EGFR
  • ALK
  • ROS1

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Further information on MDPI's Special Issue policies can be found here.

Published Papers (2 papers)

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Research

11 pages, 1631 KiB  
Article
SpO2/FiO2 Correlates with PaO2/FiO2 (P/F) and Radiological Biomarkers of Severity: A Retrospective Study on COVID-19 Pneumonia Patients
by Alberto Marra, Vito D’Agnano, Raffaella Pagliaro, Fabio Perrotta, Ilaria Di Fiore, Antonio D’Orologio, Filippo Scialò, Angela Schiattarella, Andrea Bianco and Roberto Parrella
Biomedicines 2025, 13(5), 1072; https://doi.org/10.3390/biomedicines13051072 - 28 Apr 2025
Abstract
Background: In patients with COVID-19 pneumonia, the estimation of PaO2 represents the method of choice for monitoring a patient’s oxygenation status and assessing disease severity. The aim of this study is, therefore, to investigate the correlation between SpO2/FiO2 and [...] Read more.
Background: In patients with COVID-19 pneumonia, the estimation of PaO2 represents the method of choice for monitoring a patient’s oxygenation status and assessing disease severity. The aim of this study is, therefore, to investigate the correlation between SpO2/FiO2 and PaO2/FiO2, as well as radiological and laboratory biomarkers of severity. Methods: In this monocentric observational, analytical, retrospective large cohort study, consecutive patients with a confirmed diagnosis of pneumonia from SARS-CoV-2, hospitalized at the Cotugno Hospital—AORN dei Colli—of Naples, between 1 September 2020 and 28 February 2022 were considered for study inclusion. Patients with missing data were excluded. Results: We included 585 patients (median age 63 [22–95]). Mean PaO2/FiO2 was 203 [66–433], whilst mean SpO2/FiO2 was 240 [81–471]. We found that P/F ratio could be predicted from S/F ratio, as described by the linear regression equation (P/F = 13.273 + 0.790 × S/F). In addition, we found that SpO2/FiO2 ratio significantly correlated with HRCT score and laboratory markers of severity, including IL-6, D-Dimer, and NLR. Conclusions: SpO2/FiO2 ratio represents a highly useful resource as a valid surrogate of P/F ratio in patients with COVID pneumonia, also correlating with other biomarkers of severity, such as HRCT score and key laboratory markers. Full article
(This article belongs to the Special Issue Advances in Lung Cancer: From Bench to Bedside)
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20 pages, 10006 KiB  
Article
Prognostic Significance of Modified Shine and Lal Index in Patients with Non-Small Cell Lung Cancer Undergoing Surgical Resection
by Soomin An, Wankyu Eo and Sookyung Lee
Biomedicines 2025, 13(4), 937; https://doi.org/10.3390/biomedicines13040937 - 11 Apr 2025
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Abstract
Background: Although white blood cell-related indices are established prognostic markers in lung cancer, the prognostic significance of red blood cell (RBC) indices—mean corpuscular volume (MCV), mean corpuscular hemoglobin (MCH), and mean corpuscular hemoglobin concentration (MCHC)—remains unclear. This study assessed the prognostic value [...] Read more.
Background: Although white blood cell-related indices are established prognostic markers in lung cancer, the prognostic significance of red blood cell (RBC) indices—mean corpuscular volume (MCV), mean corpuscular hemoglobin (MCH), and mean corpuscular hemoglobin concentration (MCHC)—remains unclear. This study assessed the prognostic value of RBC indices for predicting survival outcomes in patients who underwent curative-intent surgery for stage I–IIIA non-small cell lung cancer (NSCLC). Methods: This retrospective analysis of 437 patients evaluated the prognostic significance of MCV, MCH, MCHC, and the modified Shine and Lal Index (mSLI), calculated as (MCV2 × MCH) × 0.0001, using Cox regression analysis. Model performance was evaluated using various metrics, including the concordance index (C-index) and integrated discrimination improvement (IDI). Results: In the multivariate Cox regression analysis, each RBC index was tested separately as an overall survival (OS) predictor in models that consistently included age, American Society of Anesthesiologists Physical Status (ASA-PS), pleural invasion, tumor–node–metastasis (TNM) stage, and the Noble and Underwood (NUn) score. Given its superior predictive performance, the mSLI model, which incorporates mSLI in addition to other covariates, was finalized and outperformed the baseline TNM staging model (C-index: 0.840 vs. 0.708, p < 0.001) and demonstrated significant improvements in IDI at 3 and 5 years (p < 0.001). Compared to the intermediate model—comprising the same covariates as the mSLI model except for mSLI—the mSLI model showed a slightly higher C-index (0.840 vs. 0.835, p = 0.554) and significant improvements in IDI at 3 years (p = 0.008) and 5 years (p = 0.020). Conclusions: mSLI was an independent prognostic marker for OS in stage I–IIIA NSCLC, enhancing risk stratification and providing incremental predictive value beyond that of traditional models. Incorporating mSLI into prognostic frameworks may improve clinical decision-making. However, external validation is required to confirm its clinical utility. Full article
(This article belongs to the Special Issue Advances in Lung Cancer: From Bench to Bedside)
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