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Biomedicines
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The Biology of Non-small Cell Lung Cancer
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The Biology of Non-small Cell Lung Cancer

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

Deadline for manuscript submissions: closed (31 May 2023) | Viewed by 8451

Special Issue Editors

Dr. Mumtaz V. Rojiani

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Guest Editor
Department of Pharmacology, Penn State University College of Medicine, Hershey, PA 17033, USA
Interests: lung cancer; tumor microenvironment; TIMP-1; chemoresistance
Special Issues, Collections and Topics in MDPI journals
Dr. Ravindra Kolhe

E-Mail Website
Guest Editor
Department of Pathology, Medical College of Georgia, Augusta University, Augusta, GA 30912, USA
Interests: molecular markers
Special Issues, Collections and Topics in MDPI journals
Dr. Pankaj Ahluwalia

E-Mail Website
Guest Editor
Department of Pathology, Medical College of Georgia, Augusta University, Augusta, GA 30912, USA
Interests: pathology; COVID-19, neutrophils; lymphoid cells; genome sequencing; nucleic acid; testing; cancer
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

A devastating disease, lung cancer, especially NSCLC, is responsible for the most cancer-related deaths globally. NSCLC is the major subtype at 85% of all cases, and under this umbrella is a heterogeneous group of histological subtypes. The 5-year survival rate of NSCLC hovers at 16%, and therapeutic options are limited, primarily because of late diagnosis and cancer progression. Platinum-based chemotherapy is the mainstay of treatment or a valuable adjuvant along with radiation. However, its utility is limited due to the development of chemoresistance. Moreover, amongst patients with advanced NSCLC, only a small proportion are candidates for molecular-targeted therapies.

Understanding the biology of these tumors is crucial for the design of next-generation therapeutics. To reach these goals, it will be pivotal to identify new driver mutations which may facilitate a better stratification of patients for molecular-targeted therapies. Additionally, contributions from the tumor microenvironment towards tumor behavior, chemoresistance, and failure of targeted therapies need to be examined to overcome these challenges.

This Special Issue will seek contributions of research articles and reviews covering a broad spectrum of NSCLC studies, including, but not limited to:

  1. Cancer biology—including the characterization of novel driver mutations, molecular mediators of transformation and metastasis, metabolic reprogramming, and the role of stromal elements within the tumor microenvironment;
  2. Cancer biomarkers—characterization and validation of diagnostic, prognostic, and predictive biomarkers;
  3. Cancer classification—new approaches for the classification of tumors through the incorporation of genomics, transcriptomics, and proteomics. Incorporation of emerging methodologies from the fields of computational biology, machine learning, and/or quantitative modeling;
  4. Cancer management—new approaches to enhance molecular interrogation techniques, and promising approaches to overcome resistance using a variety of in silico, in vitro, and in vivo models. Advances in research discussing chemotherapy, targeted therapy, and immunotherapy.

Dr. Mumtaz Rojiani
Dr. Ravindra Kolhe
Dr. Pankaj Ahluwalia
Guest Editors

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

  • novel driver mutations
  • biomarkers
  • genomics
  • transcriptomics
  • proteomics
  • computational biology
  • targeted therapies
  • immunotherapy
  • chemoresistance

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

Published Papers (3 papers)

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Research

15 pages, 2743 KiB  
Article
Stable Isotope-Assisted Untargeted Metabolomics Identifies ALDH1A1-Driven Erythronate Accumulation in Lung Cancer Cells
by Jie Zhang, Mark A. Keibler, Wentao Dong, Jenny Ghelfi, Thekla Cordes, Tamara Kanashova, Arnaud Pailot, Carole L. Linster, Gunnar Dittmar, Christian M. Metallo, Tim Lautenschlaeger, Karsten Hiller and Gregory Stephanopoulos
Biomedicines 2023, 11(10), 2842; https://doi.org/10.3390/biomedicines11102842 - 19 Oct 2023
Cited by 1 | Viewed by 2377
Abstract
Using an untargeted stable isotope-assisted metabolomics approach, we identify erythronate as a metabolite that accumulates in several human cancer cell lines. Erythronate has been reported to be a detoxification product derived from off-target glycolytic metabolism. We use chemical inhibitors and genetic silencing to [...] Read more.
Using an untargeted stable isotope-assisted metabolomics approach, we identify erythronate as a metabolite that accumulates in several human cancer cell lines. Erythronate has been reported to be a detoxification product derived from off-target glycolytic metabolism. We use chemical inhibitors and genetic silencing to define the pentose phosphate pathway intermediate erythrose 4-phosphate (E4P) as the starting substrate for erythronate production. However, following enzyme assay-coupled protein fractionation and subsequent proteomics analysis, we identify aldehyde dehydrogenase 1A1 (ALDH1A1) as the predominant contributor to erythrose oxidation to erythronate in cell extracts. Through modulating ALDH1A1 expression in cancer cell lines, we provide additional support. We hence describe a possible alternative route to erythronate production involving the dephosphorylation of E4P to form erythrose, followed by its oxidation by ALDH1A1. Finally, we measure increased erythronate concentrations in tumors relative to adjacent normal tissues from lung cancer patients. These findings suggest the accumulation of erythronate to be an example of metabolic reprogramming in cancer cells, raising the possibility that elevated levels of erythronate may serve as a biomarker of certain types of cancer. Full article
(This article belongs to the Special Issue The Biology of Non-small Cell Lung Cancer)
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11 pages, 2065 KiB  
Article
A Nomogram Based on Atelectasis/Obstructive Pneumonitis Could Predict the Metastasis of Lymph Nodes and Postoperative Survival of Pathological N0 Classification in Non-small Cell Lung Cancer Patients
by Yi-Han Liu, Lei-Lei Wu, Jia-Yi Qian, Zhi-Xin Li, Min-Xing Shi, Zi-Ran Wang, Long-Yan Xie, Yu’e Liu, Dong Xie and Wei-Jun Cao
Biomedicines 2023, 11(2), 333; https://doi.org/10.3390/biomedicines11020333 - 24 Jan 2023
Cited by 7 | Viewed by 2439
Abstract
The eighth TNM staging system proposal classifies lung cancer with partial or complete atelectasis/obstructive pneumonia into the T2 category. We aimed to develop nomograms to predict the possibility of lymph node metastasis (LNM) and the prognosis for NSCLC based on atelectasis and obstructive [...] Read more.
The eighth TNM staging system proposal classifies lung cancer with partial or complete atelectasis/obstructive pneumonia into the T2 category. We aimed to develop nomograms to predict the possibility of lymph node metastasis (LNM) and the prognosis for NSCLC based on atelectasis and obstructive pneumonitis. Methods: NSCLC patients over 20 years old diagnosed between 2004 and 2015 were selected from the Surveillance, Epidemiology, and End Results (SEER) database. The nomograms were based on risk factors that were identified by Logistic regression. The area under the receiver operating characteristic (ROC) curve (AUC) was performed to confirm the predictive values of our nomograms. Cox proportional hazards analysis and Kaplan–Meier survival analysis were also used in this study. Results: A total of 470,283 patients were enrolled. Atelectasis/obstructive pneumonitis, age, gender, race, histologic types, grade, and tumor size were defined as independent predictive factors; then, these seven factors were integrated to establish nomograms of LNM. The AUC is 0.70 (95% CI: 0.694–0.704). Moreover, the Cox proportional hazards analysis and Kaplan–Meier survival analysis showed that the scores derived from the nomograms were significantly correlated with the survival of pathological N0 classification. Conclusion: Nomograms based on atelectasis/obstructive pneumonitis were developed and validated to predict LNM and the postoperative prognosis of NSCLC. Full article
(This article belongs to the Special Issue The Biology of Non-small Cell Lung Cancer)
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18 pages, 2162 KiB  
Article
Identification of the Transcriptional Regulatory Role of RUNX2 by Network Analysis in Lung Cancer Cells
by Beatriz Andrea Otálora-Otálora, Cristian González Prieto, Lucia Guerrero, Camila Bernal-Forigua, Martin Montecino, Alejandra Cañas, Liliana López-Kleine and Adriana Rojas
Biomedicines 2022, 10(12), 3122; https://doi.org/10.3390/biomedicines10123122 - 3 Dec 2022
Cited by 4 | Viewed by 2803
Abstract
The use of a new bioinformatics pipeline allowed the identification of deregulated transcription factors (TFs) coexpressed in lung cancer that could become biomarkers of tumor establishment and progression. A gene regulatory network (GRN) of lung cancer was created with the normalized gene expression [...] Read more.
The use of a new bioinformatics pipeline allowed the identification of deregulated transcription factors (TFs) coexpressed in lung cancer that could become biomarkers of tumor establishment and progression. A gene regulatory network (GRN) of lung cancer was created with the normalized gene expression levels of differentially expressed genes (DEGs) from the microarray dataset GSE19804. Moreover, coregulatory and transcriptional regulatory network (TRN) analyses were performed for the main regulators identified in the GRN analysis. The gene targets and binding motifs of all potentially implicated regulators were identified in the TRN and with multiple alignments of the TFs’ target gene sequences. Six transcription factors (E2F3, FHL2, ETS1, KAT6B, TWIST1, and RUNX2) were identified in the GRN as essential regulators of gene expression in non-small-cell lung cancer (NSCLC) and related to the lung tumoral process. Our findings indicate that RUNX2 could be an important regulator of the lung cancer GRN through the formation of coregulatory complexes with other TFs related to the establishment and progression of lung cancer. Therefore, RUNX2 could become an essential biomarker for developing diagnostic tools and specific treatments against tumoral diseases in the lung after the experimental validation of its regulatory function. Full article
(This article belongs to the Special Issue The Biology of Non-small Cell Lung Cancer)
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