Background: Lung cancer is the leading cause of cancer-related death worldwide, and the timely and serial assessment of low-dose computed tomography (LDCT) in high-risk populations remains a challenge. Furthermore, testing a single biomarker for the diagnosis of lung cancers is of relatively low effectiveness. Thus, a stronger diagnostic combination of blood biomarkers is needed to improve the diagnosis of non-small cell lung cancer (NSCLC). Methods: The blood levels of individual biomarkers [IDH1, DNA methylation of short stature homeobox 2 gene (SHOX2), and prostaglandin E receptor 4 gene (PTGER4)] were measured and statistically analyzed in samples from healthy controls and patients with lung cancer. In total, 221 candidates were enrolled and randomly assigned into two groups for the training and validation of a diagnostic panel. Additionally, a subgroup analysis was performed in the whole cohort. Results: A newly combined 3-marker diagnostic model for lung cancers was established and validated with area under the receiver operating characteristic (ROC) curve (AUC) values ranging from 0.835 to 0.905 in independent groups showing significantly stronger diagnostic value compared with a single tested biomarker. The sensitivity of the diagnostic model was as high as 86.1% and 80.0% in the training and validation sets, respectively. Although no apparent differences were found between the 3-marker and 2-marker models, the high clinical T-stage and histological type specificity of IDH1 and two other methylated DNA biomarkers were demonstrated in the subgroup analysis. Conclusions: The combination of single biomarkers with high stage-specificity and histological type specificity (SHOX2 and PTGER4 DNA methylation and IDH1) showed better diagnostic performance in the detection of lung cancers compared with single marker assessment. A greater clinical utility of the panel may be developed by adding demographic/epidemiologic characteristics.

Cancer remains a leading cause of mortality globally, highlighting the need for novel biomarkers to enhance prognosis and therapeutic strategies. Pleckstrin-2 (PLEK2), a member of the pleckstrin family, has been implicated in processes critical to tumor progression, but its role across cancers remains underexplored. This study systematically examined the expression patterns, prognostic relevance, and functional impact of PLEK2 across multiple cancer types. Using data from The Cancer Genome Atlas (TCGA), Genotype Tissue Expression Project (GTEx), and the Human Protein Atlas, we analyzed PLEK2 expression in both cancerous and normal tissues, revealing significant overexpression of PLEK2 in various cancers at the mRNA and protein levels. Single-cell RNA sequencing further indicated predominant expression of PLEK2 in tumor cells and macrophages within the tumor microenvironment. Survival analysis demonstrated that elevated PLEK2 expression correlated with poor prognosis in specific cancers, though its impact varied across cancer types. Functional assays showed that PLEK2 knockdown inhibited proliferation and migration in human cancer cell lines. In vivo studies using a Lewis lung carcinoma (LLC) model confirmed that PLEK2 knockdown suppressed tumor growth and enhanced the efficacy of PD-1 immunotherapy. Mechanistically, PLEK2 knockdown was associated with reduced AKT pathway activation, diminished tumor-associated macrophage infiltration, and increased CD8 T cell presence. Compounds like Navitoclax were also identified as potential PLEK2 inhibitors. In conclusion, PLEK2 played a multifaceted role in cancer progression and immune response modulation. Targeting PLEK2 might suppress tumor growth and overcome immunotherapy resistance, offering a promising biomarker and therapeutic target to improve cancer treatment outcomes.

The emergence of epidermal growth factor receptor-tyrosine kinase inhibitors (EGFR-TKIs) revolutionized the treatment of advanced-stage non-small cell lung cancer (NSCLC). Detected in more than 50% of late-stage lung adenocarcinoma in Asian patients, the EGFR mutation was regarded as a golden mutation for Asians. However, resistance to TKIs seems inevitable and severely hinders patients from getting further benefits from treatment. Even though resistance caused by EGFR T790M could be effectively managed by third-generation EGFR-TKIs currently, resistance to third-generation EGFR-TKIs is still a troublesome issue faced by both clinicians and patients. Various efforts have been made to maximize the benefits of patients from EGFR-TKIs therapy. Thus, new requirements and challenges have been posed to clinicians of this era. In this review, we summarized the clinical evidence on the efficacy of third-generation EGFR-TKIs in patients with EGFR-mutated NSCLC. Then, we discussed advancements in sequential treatment aiming to delay the onset of resistance. Moreover, the resistance mechanisms and features were depicted to help us better understand our enemies. Lastly, we put forward future strategies, including recent approaches involving the utilization of antibody drug conjugates against resistance and research directions about shaping the evolution of NSCLC as a core idea in the management of NSCLC.

Background: Neoadjuvant chemoimmunotherapy has reshaped the treatment landscape for non-small cell lung cancer (NSCLC), yet critical gaps remain in real-time monitoring and personalized adaptation. Methods: In this observational study, patients were evaluated via imaging and multidisciplinary review for subsequent surgery or radiotherapy after neoadjuvant chemoimmunotherapy. Serial plasma samples for circulating tumor DNA (ctDNA) dynamics and mutational analyses were collected. The endpoint was event-free survival (EFS). A pognostic mutational signature was developed using the Least Absolute Shrinkage and Selection Operator (LASSO) regression. Results: Among the 138 patients, 46.4% and 52.2% underwent surgery and radiotherapy, respectively. Compared to patients with persistently positive ctDNA, the ctDNA non-shedder exhibited a numerically longer EFS (hazard ratio [HR] 0.26, 95% CI: 0.06–1.25, p = 0.062), and the clearance group exhibited a statistically longer EFS (HR 0.33, 95% CI: 0.11–0.97, p = 0.040). Patients with positive ctDNA before surgery/radiotherapy showed a shorter EFS (HR 3.38, 95% CI: 1.26–9.08, p = 0.010), and positive ctDNA was correlated with a numerically shorter EFS (HR 9.72, 95% CI: 0.98–95.96, p = 0.051) in patients assessed as stable disease (SD) of high heterogeneity in the exploratory subgroup analysis. For patients with post-C1 negative ctDNA, no EFS difference was observed between those receiving 3–4 versus 2 cycles of chemoimmunotherapy (HR 1.54, 95% CI: 0.56–4.26, p = 0.41). For patients with post-C1 positive ctDNA, the post-C1 quantity was associated with clearance (AUC = 0.72, 95% CI: 0.55–0.89, p = 0.019). After balancing clinical characteristics, LASSO-Cox regression selected four genes (SLX4, IRF4, TP53, and SOX2) to construct a prognostic signature for EFS. The AUC at 36 months was 0.75, 0.71, 0.74 in the training, validation and full cohort. The high-risk group demonstrated a shorter EFS ( p = 0.0002). Conclusions: Longitudinal ctDNA assessment identified high-risk subgroups in neoadjuvant NSCLC, particularly by refining prognosis in heterogeneous SD populations. An exploratory gene-based mutational signature provided potential molecular risk stratification.