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Lung cancer is the second most common type of cancer and is the leading cause of cancer death globally. In 2018, almost 2.1 million new cases were diagnosed, accounting for ∼12% of the cancer burden worldwide (
There are two main types of lung cancer, the non-small cell lung cancer (NSCLC) and the small cell lung cancer (SCLC). Genomic studies have indicated that more than 80% of lung malignancies are classified as NSCLC, of which adenocarcinoma is the predominant subtype. In metastatic patients, although significant progress has been made for tumors harboring druggable mutations such as EGFR, the majority of those is lacking of such mutations and the prognosis remains poor. Platinum doublet chemotherapy has been the mainstay first-line treatment for patients who are diagnosed with metastatic lung adenocarcinoma without a targetable mutation (
In recent years, immunotherapy has emerged as a treatment option that has shown a strong response in a subset of patients. The immune agents block crucial checkpoints and regulate the immune response, but the tumor cells evade the patient’s immune system. By blocking these receptor–ligand interactions, a particular subset of T cells is activated to recognize and respond to tumor cells. While such responses to immunotherapy are promising, they have only been effective in ∼20% of patients (
Therefore, there is an urgent need to understand the underlying mechanism of lung adenocarcinoma from genome to immunotherapy. To address this unmet need, this Research Topic will focus on advancements related to lung adenocarcinoma (LUAD) and the identification of novel biomarkers as new therapy-determining or companion prognostic tools for the development of precise mechanism-based treatments.
The original articles published in the present Research Topic updated about novel prognostic biomarkers in lung adenocarcinoma patients through
Similarly, Zhou X et al. investigated the expression of indolethylamine N-methyltransferase (INMT) and its clinical value as a prognostic biomarker in LUAD based on TCGA and Gene Expression Omnibus (GEO) databases (
Song Y et al. highlighted the association of necroptosis with LUAD and its potential use in guiding immunotherapy based on transcriptomic and clinical data of patients from TCGA and GEO databases (
Additionally, Zhu X’s group focused their attention on the role of basement membranes (BMs) and their related genes for prognosis prediction in LUAD patients from TCGA and GEO databases (
Finally, Liu R’s group has dedicated its work to studying the correlation between neutrophils and tumor development in LUAD based on data from the TCGA database and
The present Research Topic also contains interesting, unusual, and noteworthy case reports that can help clinicians and scientists identify new trends, evaluate new therapeutic effects, as well as create new research questions. In particular, Hodges A et al. presented a 62-year female with Lynch syndrome, who developed an EGFR-positive lung adenocarcinoma highlighting the complex interplay of genetic cancer predisposition syndromes and the development of spontaneous driver mutations in the disease course and the subsequent management of tumors arising (
Last but not least, Quanqing L et al. presented a 67-year female with a squamous cell carcinoma (NSCLC) that transforms into small cell carcinoma (SCLC) after five cycles of immunotherapy targeting PD-1 treatment (Sintilimab) of NSCLC (
In conclusion, this Research Topic highlights the importance of good prognostic biomarkers in determining the most effective treatment and revolutionizing cancer precision medicine. The Research Topic of articles provides a comprehensive overview of current advancements in prognostic and therapeutic lung cancer biomarkers offering a substantive framework that informs ongoing scientific inquiry and clinical practice, aiming to improve the understanding and management of LUAD patients.
YM: Conceptualization, Validation, Writing–original draft, Writing–review and editing. MP: Conceptualization, Data curation, Validation, Writing–original draft, Writing–review and editing. EF: Conceptualization, Data curation, Supervision, Writing–original draft, Writing–review and editing.
The author(s) declare that no financial support was received for the research, authorship, and/or publication of this article.
We deeply thank all the authors and reviewers who have participated in this Research Topic.
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
The author(s) declared that they were an editorial board member of Frontiers, at the time of submission. This had no impact on the peer review process and the final decision.
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