Lung Cancer Research Research Articles

Exploiting Tertiary Lymphoid Structures to Stimulate Antitumor Immunity and Improve Immunotherapy Efficacy.

Tumor-associated tertiary lymphoid structures (TLS) have been associated with favorable clinical outcomes and response to immune checkpoint inhibitors in many cancer types, including non-small cell lung cancer. Although the detailed cellular and molecular mechanisms underlying these clinical associations have not been fully elucidated, growing preclinical and clinical studies are helping to elucidate the mechanisms at the basis of TLS formation, composition, and regulation of immune responses. However, a major challenge remains how to exploit TLS to enhance naïve and treatment-mediated antitumor immune responses. Here, we discuss the current understanding of tumor-associated TLS, preclinical models that can be used to study them, and potential therapeutic interventions to boost TLS formation, with a particular focus on lung cancer research.

Understand how machine learning impact lung cancer research from 2010 to 2021: A bibliometric analysis.

Advances in lung cancer research applying machine learning (ML) technology have generated many relevant literature. However, there is absence of bibliometric analysis review that aids a comprehensive understanding of this field and its progress. Present article for the first time performed a bibliometric analysis to clarify research status and focus from 2010 to 2021. In the analysis, a total of 2,312 relevant literature were searched and retrieved from the Web of Science Core Collection database. We conducted a bibliometric analysis and further visualization. During that time, exponentially growing annual publication and our model have shown a flourishing research prospect. Annual citation reached the peak in 2017. Researchers from United States and China have produced most of the relevant literature and strongest partnership between them. Medical image analysis and Nature appeared to bring more attention to the public. The computer-aided diagnosis, precision medicine, and survival prediction were the focus of research, reflecting the development trend at that period. ML did make a big difference in lung cancer research in the past decade.

Epidemiology and Outcomes of Non–Small Cell Lung Cancer in South Korea

Valuable evidence regarding clinical characteristics, treatments, and outcomes for non-small cell lung cancer (NSCLC) is limited to individual hospital databases or national-level registries. The common data and federated analysis framework developed through the Extensible Platform for Observational Research in Lung Cancer (EXPLORE-LC) initiative allows for research across multiple high-quality data sources, which may provide a deeper understanding of the NSCLC landscape and identification of unmet needs of subpopulations. To describe clinical characteristics, initial treatment patterns, subsequent treatment, and overall survival (OS) of patients with NSCLC in South Korea. This multicenter cohort study included patients aged 18 years and older who were diagnosed with NSCLC between 2014 and 2019 and followed up until March 2020 at 3 tertiary hospitals in South Korea. Clinical data were collected using a common data model and clinical data warehouse. Patients who had an initial diagnosis of nonsquamous (NSQ) or squamous (SQ) NSCLC and who had received at least 1 treatment for NSCLC were included in the study. Data were analyzed from June through November 2022. The primary outcome was clinical OS for patients with NSCLC. Secondary outcomes were clinical characteristics and treatment patterns subsequent to the diagnosis of NSCLC. Among 22 101 patients with NSCLC who received anticancer treatment analyzed in this study, 17 350 patients (78.5%) had NSQ and 4751 patients (21.5%) had SQ NSCLC. Clinical characteristics and outcomes and treatment patterns were assessed for 13 084 patients with NSQ cancer who had known EGFR and ALK status (75.4%; mean [SD] 62.2 [10.5] years; 6552 males [50.1%]) and all 4751 patients with SQ cancer (mean [SD] age, 67.1 [8.6] years; 4427 males [93.2%]). More than half of patients with NSQ cancer were never smokers (7399 patients [56.6%]). Patients with SQ cancer were mostly males and former or current smokers (4235 patients [89.1%]) and were diagnosed at a later clinical stage than patients with NSQ cancer (eg, stage I: 1165 patients [24.5%] vs 5388 patients [41.2%]). Patients with EGFR-positive and ALK-positive NSQ cancer diagnosed between 2017 and 2019 had better median OS than similar patients diagnosed between 2014 and 2016 (EGFR-positive: not reached [95% CI, 35.9 months to not reached] vs 28.4 months [95% CI, 25.8 to 30.0 months]; P < .001; ALK-positive: not reached [95% CI, not reached] vs 49.5 months [95% CI, 35.1 months to not reached]; P < .001). No significant difference was observed in OS from first-line treatment for patients with SQ cancer. This study, which pooled medical data from multiple clinical data warehouses to produce a large study cohort, may provide meaningful insights into the clinical practice of NSCLC and underscores the value of a common data model approach. The analyzable dataset may hold great promise for future comprehensive identification of subpopulations and unmet needs.

The role of silymarin and MAPK pathway in the regulation of proliferation and invasion of non-small cell lung cancer cells.

We aimed to explore the role of silymarin and mitogen-activated protein kinase (MAPK) pathway in the regulation of proliferation and invasion of non-small cell lung cancer cells. Non-small cell lung cancer cells were cultured and divided into groups and treated with drugs, and A blank control group was set up. The concentration of silymarin in the experimental group was 10 mg/L, 20 mg/L and 40 mg/L, respectively, which were recorded as groups A, B and C, and three repeated experiments were performed in each group. Absorbance (A value), survival rate and number of invasions were measured at 490 nm 24 h and 48 h after treatment, and the protein expression levels of MMP-2, MMP-9, p-p38, p-JNK and p-ERK 1/2 of cells in each group were detected. There were differences in the A value (control group > Group A > Group B > Group C), cell survival rate (control group < group A < group B < group C) and the number of cell invasions (control group > Group A > Group B > group C) at 24h and 48h among all groups (P<0.05). After 24h of administration, the mRNA expression of MMP-2 and MMP-9, P-P38 and P-JNK protein expression were significantly different among groups, and the control group was > group A > Group B > group C (P<0.05). There were no significant differences in protein expression levels of p38, JNK, ERK 1/2 and P-ERK 1/2 among all groups (P>0.05). Silymarin may inhibit the proliferation and invasion of non-small cell lung cancer cells by inhibiting the activity of MAPK pathway, and the higher the concentration, the more obvious the inhibition effect, which provides a basis for further research and treatment of non-small cell lung cancer.

Regulatory effects of miRNAs targeting PI3K/AKT signaling pathway in the pathogenesis of lung cancer

In the contemporary world, lung cancer has become the most frequent type of cancer in humankind. Recent studies revealed that lung cancer proliferation is correlated with microRNA (miRNA) dysregulation. Several studies have identified PI3K/AKT signaling pathway as the key target of certain miRNAs and play a fundamental role in cellular activities involved in lung cancer cell invasion and metastasis. For lung cancer research, miRNAs and their interrelated target genes could be a capable novel field in its diagnosis as well as in therapy. This review highlights the role of regulatory miRNAs targeting the PI3K/AKT signaling pathway in lung carcinogenesis.

The integration of multi-omics analysis and machine learning for the identification of prognostic assessment and immunotherapy efficacy through aging-associated genes in lung cancer.

Recent years revealed key molecules in lung cancer research, yet their exact roles in disease onset and progression remain uncertain. Lung cancer's heterogeneity complicates prognosis prediction. This study integrates pivotal molecules to evaluate patient prognosis and immunotherapy efficacy. The WGCNA algorithm identified module genes linked to immunity. The Lasso-Cox method built a prognostic model for outcome prediction. GO and KEGG analyses explored gene pathways. ssGSEA quantified immune cell types and functions. The riskScore predicts the effectiveness of immunotherapy based on its correlation with DNA repair and immune checkpoint genes. Single-cell sequencing examined key gene expression across cell types. Using WGCNA, we identified the MEbrown module related to immunity. Lasso-Cox selected "BLK," "ITGB4," "PRKCH," and "SNAI1" for the prognostic model. MF analysis revealed enriched functions including antigen binding, GTPase regulator activity. In terms of BP, processes like immune signaling and mitotic division were enriched. CC enrichment included immunoglobulin complexes and chromosomal regions. Enriched pathways encompassed Cell cycle, Focal adhesion, Cellular senescence, and p53 signaling. ssGSEA evaluated immune cell abundance. RiskScore correlated with CTLA4 and PD1 through MMR and immune checkpoint analysis. Single-cell analysis indicated gene expression across cell types for BLK, ITGB4, PRKCH, and SNAI1. In summary, our developed prognostic model utilizing age-related genes effectively predicts lung cancer prognosis and the efficacy of immune therapy.

The Application of Artificial Intelligence in Lung Cancer Research.

The advent of artificial intelligence in healthcare is transforming medical research and clinical practice, with significant advancements in the areas of oncology. This commentary explores the pivotal role artificial intelligence plays in lung cancer research, offering insights into its current applications and future potential.

Charting the course of ferroptosis research in lung cancer: Insights from a bibliometric analysis

BackgroundLung cancer, a major cause of cancer-related mortality globally, necessitates innovative therapeutic strategies. Ferroptosis, an iron-dependent, non-apoptotic cell death form, has risen as a crucial therapeutic target. This study aims to conduct a comprehensive bibliometric analysis of ferroptosis in lung cancer, highlighting principal research trends, influential publications, and prospective future directions. MethodsThis study utilized bibliometric tools such as VOSviewer, CiteSpace, and the R package “bibliometrix” to thoroughly analyze 488 articles on ferroptosis in lung cancer from 2014 to October 2023. Data from the Web of Science Core Collection were analyzed to determine spatial and temporal trends, identify prominent authors and seminal works, and uncover emerging hotspots and frontiers of the field. The literature was segmented into coherent thematic groups through cluster analysis. ResultsOur analysis revealed a significant exponential growth in publications from 2019 to 2023, mirroring the increasing interest in this area. Predominantly, the influential research was published in high-impact journals, with Scott J. Dixon's works being the most cited. The study identified four primary research themes: Lung Cancer Specifics; Biomarker Identification and Prognosis; Cellular Death Mechanisms and Metabolic Regulation; and Cancer Stem Cells and Therapeutic Resistance. Recent studies have increasingly focused on areas such as the immune microenvironment and mitochondrial dysfunction. Furthermore, the analysis highlighted the field's global collaborative nature, with significant contributions from China, the USA, and Germany. ConclusionThis extensive bibliometric analysis emphasizes the growing importance of ferroptosis in lung cancer research. The identified themes and emerging topics underline the field's complexity and suggest new research avenues. This study promotes a holistic research approach, advocating for the exploration of innovative ferroptosis-targeting therapies that could revolutionize lung cancer treatment.

Metabolomics Analysis and Diagnosis of Lung Cancer: Insights from Diverse Sample Types.

Lung cancer is a highly fatal disease that poses a significant global health burden. The absence of characteristic clinical symptoms frequently results in the diagnosis of most patients at advanced stages of lung cancer. Although low-dose computed tomography (LDCT) screening has become increasingly prevalent in clinical practice, its high rate of false positives continues to present a significant challenge. In addition to LDCT screening, tumor biomarker detection represents a critical approach for early diagnosis of lung cancer; unfortunately, no tumor marker with optimal sensitivity and specificity is currently available. Metabolomics has recently emerged as a promising field for developing novel tumor biomarkers. In this paper, we introduce metabolic pathways, instrument platforms, and a wide variety of sample types for lung cancer metabolomics. Specifically, we explore the strengths, limitations, and distinguishing features of various sample types employed in lung cancer metabolomics research. Additionally, we present the latest advances in lung cancer metabolomics research that utilize diverse sample types. We summarize and enumerate research studies that have investigated lung cancer metabolomics using different metabolomic sample types. Finally, we provide a perspective on the future of metabolomics research in lung cancer. Our discussion of the potential of metabolomics in developing new tumor biomarkers may inspire further study and innovation in this dynamic field.

Exosomal Proteomics: Unveiling Novel Insights into Lung Cancer.

Although significant progress has been made in early lung cancer screening over the past decade, it remains one of the most prevalent and deadliest forms of cancer worldwide. Exosomal proteomics has emerged as a transformative field in lung cancer research, with the potential to redefine diagnostics, prognostic assessments, and therapeutic strategies through the lens of precision medicine. This review discusses recent advances in exosome-related proteomic and glycoproteomic technologies, highlighting their potential to revolutionise lung cancer treatment by addressing issues of heterogeneity, integrating multiomics data, and utilising advanced analytical methods. While these technologies show promise, there are obstacles to overcome before they can be widely implemented, such as the need for standardization, gaps in clinical application, and the importance of dynamic monitoring. Future directions should aim to overcome the challenges to fully utilize the potential of exosomal proteomics in lung cancer. This promises a new era of personalized medicine that leverages the molecular complexity of exosomes for groundbreaking advancements in detection, prognosis, and treatment.

Bridging the Gap: Engaging Black Men in Lung Cancer Research Through Barbershop Collaboration.

Health disparities persist among Black men, notably in the context of lung cancer and stress-related health outcomes. This study explores these disparities through a community-based participatory research (CBPR) approach, citizen science, and social network theory, leveraging the expertise and trust of Black barbers as community leaders. The purpose is to understand the nuanced connections between stress and lung cancer in this demographic. Engaging 161 Black men across four Chicago neighborhoods, the study successfully collected hair samples and survey data, emphasizing the importance of culturally sensitive recruitment strategies. Findings highlight the effectiveness of the collaboration, showcasing the role of barbershops as community hubs for research. The study concludes by advocating for sustained partnerships with community leaders, emphasizing transparency in research communication, and promoting culturally grounded approaches to address health disparities and enhance research participation among underrepresented populations.

The most common methods applied for in vitro research in non-small cell lung cancer in the last decade

The most common methods applied for in vitro research in non-small cell lung cancer in the last decade

Understanding the current landscape of lung cancer research and treatment: A systematic review

Understanding the current landscape of lung cancer research and treatment: A systematic review

CT Predictors of Visceral Pleural Invasion in Patients with Non-Small Cell Lung Cancers 30 mm or Smaller.

Background CT-defined visceral pleural invasion (VPI) is an important indicator of prognosis for non-small cell lung cancer (NSCLC). However, there is a lack of studies focused on small subpleural NSCLCs (≤30 mm). Purpose To identify CT features predictive of VPI in patients with subpleural NSCLCs 30 mm or smaller. Materials and Methods This study is a retrospective review of patients enrolled in the Initiative for Early Lung Cancer Research on Treatment (IELCART) at Mount Sinai Hospital between July 2014 and February 2023. Subpleural nodules 30 mm or smaller were classified into two groups: a pleural-attached group and a pleural-tag group. Preoperative CT features suggestive of VPI were evaluated for each group separately. Multivariable logistic regression analysis adjusted for sex, age, nodule size, and smoking status was used to determine predictive factors for VPI. Model performance was analyzed with the area under the receiver operating characteristic curve (AUC), and models were compared using Akaike information criterion (AIC). Results Of 379 patients with NSCLC with subpleural nodules, 37 had subsolid nodules and 342 had solid nodules. Eighty-eight patients (22%) had documented VPI, all in solid nodules. Of the 342 solid nodules (46% in male patients, 54% in female patients; median age, 71 years; IQR: 66, 76), 226 were pleural-attached nodules and 116 were pleural-tag nodules. VPI was more frequent for pleural-attached nodules than for pleural-tag nodules (31% [69 of 226] vs 16% [19 of 116], P = .005). For pleural-attached nodules, jellyfish sign (odds ratio [OR], 21.60; P < .001), pleural thickening (OR, 6.57; P < .001), and contact surface area (OR, 1.05; P = .01) independently predicted VPI. The jellyfish sign led to a better VPI prediction (AUC, 0.84; 95% CI: 0.78, 0.90). For pleural-tag nodules, multiple tags to different pleura surfaces enabled independent prediction of VPI (OR, 9.30; P = .001). Conclusions For patients with solid NSCLC (≤30 mm), CT predictors of VPI were the jellyfish sign, pleural thickening, contact surface area (pleural-attached nodules), and multiple tags to different pleura surfaces (pleural-tag nodules). © RSNA, 2024 Supplemental material is available for this article. See also the editorial by Nishino in this issue.

Fifteen years of precision medicine in the lung cancer management: Perspectives and Challenges

Precision medicine has revolutionized lung cancer management – particularly non-squamous cell carcinomas – with a broader genomic comprehension and the possibility of offering tailored treatments guided by oncogenic driver mutations – the basis of precision medicine. Since the publication of the IPASS trial in 2009 a new Era of molecular actionability began for lung cancer research and treatment. The remarkable past fifteen years were characterized by advances on genomic testing methodologies, the emergence of new biomarkers and targeted therapies, and the widespread of precision medicine in lung cancer care from advanced to earlier stages – specially for the adenocarcinoma histology, a heterogeneous disease with unprecedent improvements in outcomes. Nonetheless, several barriers need to be overcome with the adoption of cutting-edge technologies, such as the high cost of new diagnostic and therapeutical technologies and their discrepant accessibility, mainly in low- and middle-income countries. Moreover, there is still a lack of clear clinical actionability for squamous cell carcinoma and small cell lung cancer in which ideal biomarkers are yet to be discovered and validated. Herein, we aimed to discuss several aspects on how precision medicine positively impacted on lung cancer management and the lessons learned. Additionally, we scoped future perspectives on precision oncology in lung cancer as technology advances.

Advances in the role of microRNAs associated with the PI3K/AKT signaling pathway in lung cancer.

Cancer has long been a topic of great interest in society and a major factor affecting human health. Breast, prostate, lung, and colorectal cancers are the top four tumor types with the greatest incidence rates in 2020, according to the most recent data on global cancer incidence. Among these, lung cancer had the highest fatality rate. Extensive research has shown that microRNAs, through different signaling pathways, play crucial roles in cancer development. It is considered that the PI3K/AKT signaling pathway plays a significant role in the development of lung cancer. MicroRNAs can act as a tumor suppressor or an oncogene by altering the expression of important proteins in this pathway, such as PTEN and AKT. In order to improve the clinical translational benefit of microRNAs in lung cancer research, we have generalized and summarized the way of action of microRNAs linked with the PI3/AKT signaling pathway in this review through literature search and data analysis.

Current status and prospect of PET-related imaging radiomics in lung cancer.

Lung cancer is highly aggressive, which has a high mortality rate. Major types encompass lung adenocarcinoma, lung squamous cell carcinoma, lung adenosquamous carcinoma, small cell carcinoma, and large cell carcinoma. Lung adenocarcinoma and lung squamous cell carcinoma together account for more than 80% of cases. Diverse subtypes demand distinct treatment approaches. The application of precision medicine necessitates prompt and accurate evaluation of treatment effectiveness, contributing to the improvement of treatment strategies and outcomes. Medical imaging is crucial in the diagnosis and management of lung cancer, with techniques such as fluoroscopy, computed radiography (CR), digital radiography (DR), computed tomography (CT), magnetic resonance imaging (MRI), positron emission tomography (PET)/CT, and PET/MRI being essential tools. The surge of radiomics in recent times offers fresh promise for cancer diagnosis and treatment. In particular, PET/CT and PET/MRI radiomics, extensively studied in lung cancer research, have made advancements in diagnosing the disease, evaluating metastasis, predicting molecular subtypes, and forecasting patient prognosis. While conventional imaging methods continue to play a primary role in diagnosis and assessment, PET/CT and PET/MRI radiomics simultaneously provide detailed morphological and functional information. This has significant clinical potential value, offering advantages for lung cancer diagnosis and treatment. Hence, this manuscript provides a review of the latest developments in PET-related radiomics for lung cancer.

Applications and advancements of CRISPR-Cas in the treatment of lung cancer.

Lung cancer is one of the most malignant diseases and a major contributor to cancer-related deaths worldwide due to the deficiency of early diagnosis and effective therapy that are of great importance for patient prognosis and quality of life. Over the past decade, the advent of clustered regularly interspaced short palindromic repeats/CRISPR associated protein (CRISPR/Cas) system has significantly propelled the progress of both fundamental research and clinical trials of lung cancer. In this review, we review the current applications of the CRISPR/Cas system in diagnosis, target identification, and treatment resistance of lung cancer. Furthermore, we summarize the development of lung cancer animal models and delivery methods based on CRISPR system, providing novel insights into clinical diagnosis and treatment strategies of lung cancer.

Diagnostic Utility of Next-Generation Sequencing in Circulating Free DNA and a Comparison With Matched Tissue in Gallbladder Carcinoma

Mutation detection for therapy monitoring in cell-free DNA (cfDNA) is used clinically for some malignancies. Gallbladder carcinoma (GBC) presents a diagnostic challenge and has limited late-stage treatment options. To our knowledge, this novel study examines, for the first time, genomic alterations in cfDNA from GBC to assess diagnostic accuracy and therapeutic options. The concordance of somatic genomic changes in cfDNA and DNA from paired tumor tissue was analyzed. Paired serum and tissue samples from 40 histologically proven GBC, 20 cholecystitis, and 4 normal (noninflamed gallbladder) controls were included. Targeted next-generation sequencing with a 22-gene panel (Colon and Lung Cancer Research Panel v2, Thermo Scientific) in cfDNA and tumor tissue with high depth and uniform coverage on ION Personal Genome Machine (ION, PGM) was performed. A spectrum of 223 mutations in cfDNA and 225 mutations in formalin-fixed paraffin-embedded tissue DNA were identified in 22 genes. Mutations ranged from 1 to 17 per case. In cfDNA frequent alterations were in TP53 (85.0%), EGFR (52.5%), MET (35%) CTNNB1, SMAD4, BRAF (32.5%), PTEN (30%), FGFR3 and PIK3CA (27.5%), NOTCH1 (25.0%), and FBXW7 and ERBB4 (22.5%). At least one clinically actionable mutation was identified in all cfDNA samples. Paired samples shared 149 of 225 genetic abnormalities (66.2%). Individual gene mutation concordance ranged from 44.44% to 82.0% and was highest for EGFR (82.0%), BRAF and NOTCH1 (80.0%), TP53 (73.08%), MET (72.22%), and ERBB4 (71.42%) with a significant level of correlation (Spearman r = 0.91, P ≤ .0001). The sensitivity and specificity of the TP53 gene at the gene level was the highest (94.44% and 100.0%, respectively). Overall survival was higher for ERBB4 and ERBB2 mutant tumors. The adenocarcinoma subtype revealed specific genetic changes in ERBB4, SMAD4, ERBB2, PTEN, KRAS, and NRAS. NGS-based cfDNA mutation profiling can be used to diagnose GBC before surgery to guide treatment decisions. Targeted therapy identified in GBC included SMAD4, ERBB2, ERBB4, EGFR, KRAS, BRAF, PIK3CA, MET, and NRAS.

Unraveling the Intricacies of CD73/Adenosine Signaling: The Pulmonary Immune and Stromal Microenvironment in Lung Cancer

CD73 and adenosine have gained prominence in lung cancer research. The NT5E gene encodes CD73, known as an ectonucleotidase, which plays a crucial role within tumor cells, with immune-suppressive properties. Beyond cancer, CD73 exerts an influence on cardiac, neural, and renal functions, affecting cardiac, neural, and renal functions. CD73’s significance lies in its production of extracellular adenosine. It is notably expressed across diverse cell types within the immune and stromal lung microenvironment. CD73 expression amplifies in lung tumors, especially non-small cell lung cancer (NSCLC), often aligned with key oncogenic drivers like mutant EGFR and KRAS. CD73/adenosine pathway seems to be involved in tumoral immunoevasion, hampering the use of the immune checkpoint inhibitor (ICI) and correlating with therapy resistance. Despite the partial success of current ICI therapies, the CD73/adenosine pathway offers promise in enhancing their effectiveness. This comprehensive review explores recent insights into lung cancer’s CD73/adenosine pathway. It explores roles within tumor cells, the lung’s stromal environment, and the immune system. Ranging from pre-clinical models to clinical trials, potential therapies targeting the adenosine pathway for lung cancer treatment are discussed below.