Search Results (279)

Objectives: Circulating tumor DNA (ctDNA) has emerged as a reliable prognostic biomarker in both early- and late-stage non-small cell lung cancer (NSCLC) patients. However, its role in NSCLC with pleural dissemination (M1a), a subset of disease with indolent biology, remains to be elucidated. Methods: We collected 41 M1a patients with serial ctDNA and CEA monitoring. Progression-free survival (PFS) was assessed between patients with different levels of ctDNA and CEA. An independent cohort of 61 M1a patients was included for validation. Results: At the diagnostic landmark, the detection rates for ctDNA and CEA were 22% and 55%, respectively. Among patients who experienced disease progression with pleural metastases, only ten had detectable ctDNA in longitudinal timepoints, resulting in a sensitivity of 50%. Moreover, there was no significant difference in PFS between patients with longitudinally detectable and undetectable ctDNA (HR: 0.86, 95% CI 0.33–2.23, p = 0.76). In contrast, patients with a decreasing CEA trend within 3 months after diagnosis were associated with an improved PFS (HR: 0.22; 95% CI, 0.03–1.48, p = 0.004). This finding is confirmed in an independent M1a patient cohort. Conclusions: Together, our findings suggest that M1a NSCLC with isolated pleural dissemination may represent a “non-shedding” tumor type, where ctDNA shows limited diagnostic and prognostic value. Monitoring early changes in CEA could be a more cost-effective predictor of disease progression. Full article

Background: Cell-free DNA (cfDNA) has become a cornerstone of liquid biopsy applications, offering promise for early disease detection and monitoring. However, its widespread clinical adoption is limited by variability in pre-analytical processing, especially during isolation. Current extraction methods face challenges in yield, purity, and reproducibility. Methods: We developed and optimized SafeCAP 2.0, a novel magnetic bead-based cfDNA extraction kit, focusing on efficient recovery, minimal genomic DNA contamination, and PCR compatibility. Optimization involved systematic evaluation of magnetic bead chemistry, buffer composition, and reagent volumes. Performance was benchmarked against a commercial reference kit (Apostle MiniMax) using spiked oligonucleotides and plasma from patients with stage IV NSCLC. Results: The optimized protocol demonstrated superior recovery with a limit of detection (LoD) as low as 0.3 pg/µL and a limit of quantification (LoQ) of 1 pg/μL with no detectable PCR inhibition. In comparative studies, SafeCAP 2.0 showed equivalent or improved performance over the commercial kit. Clinical validation using 47 patient plasma samples confirmed robust cfDNA recovery and fragment integrity. Conclusions: SafeCAP 2.0 offers a cost-effective, high-performance solution for cfDNA extraction in both research and clinical workflows. Its design and validation address key pre-analytical barriers, supporting integration into routine diagnostics and precision medicine platforms. Full article

Introduction: Radiomics is the extraction of non-invasive and reproducible quantitative imaging features, which may yield mineable information for clinical practice implementation. Quantification of lung function through radiomics could play a role in the management of patients with pulmonary lesions. The aim of this study is to test the capability of radiomic features to predict pulmonary function parameters, focusing on the diffusing capacity of lungs to carbon monoxide (DL_CO). Methods: Retrospective data were retrieved from electronical medical records of patients treated with Stereotactic Body Radiation Therapy (SBRT) at a single institution. Inclusion criteria were as follows: (1) SBRT treatment performed for primary early-stage non-small cell lung cancer (ES-NSCLC) or oligometastatic lung nodules, (2) availability of simulation four-dimensional computed tomography (4DCT) scan, (3) baseline spirometry data availability, (4) availability of baseline clinical data, and (5) written informed consent for the anonymized use of data. The gross tumor volume (GTV) was segmented on 4DCT reconstructed phases representing the moment of maximum inhalation and maximum exhalation (Phase 0 and Phase 50, respectively), and radiomic features were extracted from the lung parenchyma subtracting the lesion/s. An iterative algorithm was clustered based on correlation, while keeping only those most associated with baseline and post-treatment DL_CO. Three models were built to predict DL_CO abnormality: the clinical model—containing clinical information; the radiomic model—containing the radiomic score; the clinical-radiomic model—containing clinical information and the radiomic score. For the models just described, the following were constructed: Model 1 based on the features in Phase 0; Model 2 based on the features in Phase 50; Model 3 based on the difference between the two phases. The AUC was used to compare their performances. Results: A total of 98 patients met the inclusion criteria. The Charlson Comorbidity Index (CCI) scored as the clinical variable most associated with baseline DL_CO (p = 0.014), while the most associated features were mainly texture features and similar among the two phases. Clinical-radiomic models were the best at predicting both baseline and post-treatment abnormal DL_CO. In particular, the performances for the three clinical-radiomic models at predicting baseline abnormal DL_CO were AUC₁ = 0.72, AUC₂ = 0.72, and AUC₃ = 0.75, for Model 1, Model 2, and Model 3, respectively. Regarding the prediction of post-treatment abnormal DL_CO, the performances of the three clinical-radiomic models were AUC₁ = 0.91, AUC₂ = 0.91, and AUC₃ = 0.95, for Model 1, Model 2, and Model 3, respectively. Conclusions: This study demonstrates that radiomic features extracted from healthy lung parenchyma on a 4DCT scan are associated with baseline pulmonary function parameters, showing that radiomics can add a layer of information in surrogate models for lung function assessment. Preliminary results suggest the potential applicability of these models for predicting post-SBRT lung function, warranting validation in larger, prospective cohorts. Full article

The tumor microenvironment (TME) in advanced solid tumors is determined by immune checkpoints (PD-1, CTLA-4, and CD95) and cytokine networks (IL-2, IL-10, and TNF-α) that drive CD8+ T cell exhaustion, metabolic reprogramming, and apoptosis resistance, enabling immune evasion. Some studies revealed PD-1/CD95 co-expression is a marker of T cell dysfunction, while CTLA-4 upregulation correlates with suppressed early T cell activation. IL-10 has emerged as a potential biomarker for chemoresistance and tumor aggressivity, consistent with its role in promoting anti-apoptotic signaling in cancer stem cells (CSCs). Engineered IL-2 variants and TNF-α modulation are highlighted as promising strategies to revitalize exhausted CD8+ T cells and disrupt CSC niches. This prospective single-center study investigated the dynamic TME alterations in 16 patients with immunotherapy-naïve stage IV non-small-cell lung cancer (NSCLC) and metastatic melanoma treated with anti-PD-1 nivolumab. The longitudinal immunophenotyping of peripheral blood lymphocytes (via flow cytometry) and serum cytokine analysis (via ELISA) were performed at the baseline, >3, and >6 months post-treatment to evaluate immune checkpoint co-expression (PD-1/CD95 and CTLA-4/CD8+) and the cytokine profiles (IL-2, IL-10, and TNF-α). Full article

Background/Objectives: The clinical value of KRAS mutations in lung adenocarcinoma, alone or in combination with other mutations, has been assessed especially in advanced stages. This study evaluates how KRAS and the presence of co-mutations could affect survival in early-stage lung. Methods: We analyzed a real-world cohort including all staged NSCLC patients diagnosed and treated from 2018 to 2022 at our Institute with availability of NGS molecular data. Statistical analyses were made using log-rank test, the two-tailed Fisher’s exact test and Kaplan-Meier survival curves. Results: KRAS mutations were observed in 179/464 cases (38.6%). The majority of KRAS co-mutations were in TP53 (74%) and STK11 (14.3%) genes. KRAS+TP53 co-mutations were more frequent compared to KRAS-only tumors in stage IV NSCLC (p = 0.01). In early stage and locally advanced cases (stage I-III), better prognosis was associated to KRAS-only mutated NSCLC and to KRAS+STK11 mutated cases compared to KRAS+TP53 (p = 0.008). In particular, patients carrying KRAS+TP53 in stage I and II displayed a shorter survival, similar to patients diagnosed at stage III. Conclusions: Routine NGS provides important information for potential actionable mutations but also for the prognostic and predictive role of the presence of co-occurring mutations. In particular, the presence of KRAS+TP53 in stage I and II NSCLC may be considered an unfavorable prognostic marker possibly leading to adapt the perioperative chemo-immunotherapy. Full article

Resectable non-small cell lung cancer (NSCLC) continues to pose significant challenges with high recurrence and mortality rates, despite traditional platinum-based chemotherapy yielding only an approximate 5% improvement in 5-year overall survival when administered preoperatively or postoperatively. In recent years, the integration of immune checkpoint inhibitors (ICIs), such as nivolumab, durvalumab and pembrolizumab, with platinum-based regimens in the perioperative setting has emerged as a transformative strategy. Our comprehensive review, based on a systematic bibliographic search of PubMed, Google Scholar, EMBASE, Cochrane Library, and clinicaltrials.gov, targeting pivotal clinical trials from the past two decades, examines the impact of these neoadjuvant and adjuvant chemoimmunotherapy approaches on major pathological response rates and overall survival in early-stage NSCLC. Although these perioperative strategies represent a paradigm shift in treatment, promising durable responses are offset by persistent recurrence, emphasizing the necessity for optimized treatment sequencing, duration, and the identification of predictive biomarkers. Collectively, our findings underscore the critical role of the perioperative schema, particularly the neoadjuvant component, which enables the evaluation of novel biomarkers as surrogates for overall survival, in improving patient outcomes and delineating future research directions aimed at reducing mortality and enhancing the quality of life for patients with resectable NSCLC. Full article

Stereotactic Body Radiotherapy (SBRT) has emerged as a pivotal treatment modality for early-stage non-small cell lung cancer (NSCLC), offering highly precise, high-dose radiation delivery. However, several clinical challenges remain, particularly in the treatment of central or ultracentral tumors, which are located near critical structures such as the heart, bronchi, and great vessels. The introduction of MRI-guided SBRT has significantly improved targeting precision, allowing for better assessment of tumor motion and adjacent organ structures. Additionally, SBRT has demonstrated efficacy in multifocal NSCLC, providing an effective option for patients with multiple primary tumors. Recent advances also highlight the role of SBRT in locally advanced NSCLC, where it is increasingly used as a complementary approach to concurrent chemotherapy or in cases where surgery is not feasible. Moreover, the combination of SBRT with immunotherapy has shown promising potential, enhancing tumor control and immunological responses. Furthermore, SBRTs application in SCLC is gaining momentum as a palliative and potentially curative option for selected patients. This narrative review explores these evolving clinical scenarios, the technical innovations supporting SBRT, and the integration of immunotherapy, providing an in-depth look at the new frontiers of SBRT in lung cancer treatment. Despite the challenges, the ongoing development of personalized approaches and technological advancements continues to push the boundaries of SBRTs clinical utility in lung cancer. Full article

Background/Objectives: The fat mass and obesity-associated (FTO) protein demethylates nuclear N6-Methyladenosine (m6A) on mRNA, facilitates tumor growth, and contributes to therapeutic resistance in multiple cancer types. Recent evidence demonstrates several roles of FTO in tumorigenesis. In this study, we seek to explore the role of FTO in non-small cell lung cancer (NSCLC) tumorigenicity and its relationship with epidermal growth factor receptor (EGFR) tyrosine kinase resistance. Methods: We performed qPCR, immunoblotting, viability assays, migration assays, and ATP assays to investigate the functions of FTO in EGFR tyrosine kinase inhibitor (TKI) resistance, specifically to erlotinib, in three NSCLC cell lines harboring either wild-type or mutant EGFR. We also performed immunohistochemistry on lung tumor tissues from patients diagnosed at different stages of NSCLC. Results: Our study found an upregulation of FTO in erlotinib-resistant (ER) cell lines at both the gene and protein levels. FTO inhibition and knockdown significantly reduced cell viability of erlotinib-resistant H2170 and PC9 cells by over 30% when treated with 0.8 µM of Dac51 and about 20% when treated with siFTO. FTO inhibition also slowed down the migration of ER cells, and the effect was even more pronounced when combined with erlotinib. Furthermore, FTO was found to be overexpressed in late-stage NSCLC tumor tissues compared to early-stage tumors, and it was upregulated in patients who smoked. Conclusions: These findings suggest FTO might mediate resistance and tumor growth by augmenting cell proliferation. In addition, FTO can be a potential prognostic marker in NSCLC patients. Full article

Historically, systemic therapy for resectable non-small cell lung cancer (NSCLC) has been associated with a modest impact on overall survival. The current treatment options for early-stage resectable NSCLC include neoadjuvant, adjuvant, and perioperative immunotherapy in combination with chemotherapy. In this review, we explore the current treatment paradigms and emerging opportunities for improved survival outcomes from using immunotherapeutic approaches in the treatment of early-stage resectable NSCLC. The incorporation of immunotherapy into neoadjuvant, adjuvant, and perioperative treatment of surgically resectable NSCLC has yielded improved outcomes beyond chemotherapy-alone approaches. Despite this, there remains a margin for improving survival outcomes for patients. Clinical trials utilizing novel agents and approaches that modulate the anti-tumor immune response are currently ongoing and will likely inform the future treatment landscape for early-stage surgically resectable NSCLC. Full article

Background: Surgical resection remains the standard treatment for early-stage non-small-cell lung cancer (NSCLC). Traditionally, lobectomy has been considered the procedure of choice; however, emerging evidence suggests that trisegmentectomy may offer comparable outcomes. This meta-analysis evaluates whether left upper lobe trisegmentectomy provides non-inferior or superior oncologic outcomes compared to left upper lobectomy, with particular attention to recurrence patterns. Methods: Following PRISMA guidelines, we included comparative studies evaluating left upper lobectomy versus trisegmentectomy. Outcomes assessed included recurrence (locoregional and distant), morbidity, and the length of hospital stay. A meta-analysis was conducted using the metabin function from the R meta package. Results: Of 14 identified articles, 9 met the inclusion criteria. No significant differences were observed in locoregional recurrence. However, distant recurrence was significantly lower in the trisegmentectomy group (OR 0.58; 95% CI 0.41–0.82). While overall morbidity showed no significant difference (OR 0.95), analysis of matched studies favored trisegmentectomy (OR 0.73; 95% CI 0.56–0.96). Hospital stay was significantly shorter in the trisegmentectomy group (OR –0.94; 95% CI –1.26 to –0.63). Conclusions: Trisegmentectomy and lobectomy exhibit distinct recurrence patterns, with lobectomy associated with a higher rate of distant recurrence. Trisegmentectomy may provide oncologic and perioperative advantages in appropriately selected patients. The systematic review and meta-analysis are registered in PROSPERO (registration number: CRD420251066445). Full article

Background: With rising life expectancy and widespread lung cancer screening, early-stage non-small cell lung cancer (NSCLC) incidence has increased. While surgery is the standard treatment for operable stage I NSCLC, many patients are ineligible due to age or comorbidities. Stereotactic body radiotherapy (SBRT) has achieved good primary tumor control rates and overall survival. This study compares the outcomes of SBRT and surgery for stage I NSCLC using propensity score overlap-weighted dataset. Methods: This retrospective study analyzed clinical stage I NSCLC patients treated at a tertiary hospital from 2012 to 2021. Baseline differences between SBRT and surgery groups were adjusted using overlap weighting. AI-based CT analysis (CT AI-CAD) assessed tumor characteristics, verified by radiologists. Primary outcomes were 5-year cumulative incidence of recurrence and overall survival, with subgroup analyses based on tumor features. Results: Of 1474 patients, 1258 underwent surgery, and 216 received SBRT. After overlap weighting, baseline characteristics were well balanced. The 5-year cumulative incidence of recurrence and OS showed no statistically significant differences between SBRT and surgery groups (recurrence: 16.2% vs. 16.1%; OS: 80.5% vs. 82.9%). Further AI-based CT subgroup analysis showed no significant differences in recurrence rates across tumor features. A solid tumor diameter associated with a significant increase in recurrence was identified as 16.6 mm for SBRT and 18.6 mm for surgery. Conclusions: After overlap weighting, SBRT and surgery showed no statistically significant differences in treatment outcomes in stage I NSCLC. These findings may help guide the timing and selection of safe and effective treatment approaches. Full article

Non-small-cell lung cancer (NSCLC) remains the leading cause of cancer-related deaths worldwide with only approximately 30% of new diagnoses manifesting with localized stages IA–IIA. Osimertinib is a third-generation inhibitor of the epidermal growth factor receptor (EGFR), which is used for treating metastatic, locally advanced, and early-stage NSCLC expressing common EGFR mutations. Two phase III clinical trials supported yresectable locally advanced disease, consisting of the ADAURA and LAURA studies, respectively. On the other hand, conflicting data on neoadjuvant efficacy led to the design of the ongoing Neo-ADAURA trial. In this review, we describe the pivotal trials that led to the approval of osimertinib use as an adjuvant treatment in radically resected NSCLC patients and as maintenance therapy after chemoradiotherapy. We also summarize the principal ongoing clinical trials in the neoadjuvant and adjuvant settings. Finally, we analyze several issues about the use of osimertinib in those different early settings while also depicting future perspectives and the potential evolution of treatment strategies. Full article

(1) Background: The hemostatic system and tumor biology display a tight and reciprocal interaction where clotting products enhance tumor growth and dissemination, and the tumor, in turn, triggers a hypercoagulable and inflammatory state. Evaluating circulating biomarkers related to thrombo-inflammatory may provide a promising tool for predicting tumor outcomes, especially in non-small cell lung cancer (NSCLC) characterized by unfavorable outcomes. (2) Aim: In a prospective cohort of NSCLC patients, we evaluated whether thromboinflammatory biomarkers could predict early disease progression (DP) during the first 6 months of first-line anticancer treatment. (3) Methods: 719 newly diagnosed advanced-stage NSCLC patients were included. Complete blood cell count, high-sensitivity C-reactive protein (hs-CRP), FVIII, fibrinogen, D-dimer, thrombin-antithrombin (TAT) complexes, and prothrombin fragment1+2(F1+2) were tested in blood samples collected before starting chemotherapy. DP was gathered during follow-up. (4) Results: The 6-month cumulative incidence rate for DP was 49%. Univariable Cox regression analysis identified metastatic status, BMI, hemoglobin, leukocytes, hs-CRP, FVIII, fibrinogen, TAT, and D-dimer as significant predictors of DP. In a multivariable analysis that included all previously significant variables, only hs-CRP and D-Dimer levels remained strongly associated with DP. The two variables were used to establish a risk stratification model that significantly identified patients at high risk of DP at 6 months (HR 2.9; 95% CI, 2.3–3.7), which can be applied to 3, 9, and 12 months. (5) Conclusions: Our model easily and precisely estimates early DP during chemotherapy. If externally validated, this model can significantly enhance the allocation of medical resources in managing advanced NSCLC, ensuring that patients receive the most effective care possible. Full article

Background/Objectives: The early detection of high levels of CBC-derived inflammatory biomarkers and cellular lines, as well as their variations across different histological subtypes of lung cancer, may aid in the early identification of high-risk lung cancer patients and further guide their clinical approach. Methods: A retrospective descriptive study was conducted and included 202 patients diagnosed with lung carcinoma at the Clinical County Hospital Mureș. The main analyzed parameters were the histological subtype and the stage of the tumor at diagnosis, white blood cell counts, and platelet counts, as well as nine CBC-derived inflammatory indexes like neutrophil-to-lymphocyte ratio (NLR), derived neutrophil-to-lymphocyte ratio (d-NLR), monocyte-to-lymphocyte ratio (MLR), platelet-to-lymphocyte ratio (PLR), eosinophil-to-neutrophil ratio (ENR), eosinophil-to-monocyte ratio (EMR), systemic inflammatory index (SII), systemic inflammatory response index (SIRI), and aggregate index of systemic inflammation (AISI). The statistical analysis was performed using the MedCalc software, version 23.0.2. Logarithmic ANOVA was used to compare groups. Normality was tested using the Shapiro–Wilk test. The Chi-square test compared categorical variables, while the independent Mann-Whitney test was used for continuous variables. Results: The inflammatory response increased as disease severity progressed, with NSCLC-NOS being the histological subtype with the most numerous patients outside the normal ranges. Eosinophil count differed significantly across the histologic subtypes of NSCLC, with adenocarcinoma and adenosquamous patients exhibiting the highest values. In adenocarcinoma patients, we observed that NLR and MLR levels increased progressively as the tumor stage advanced. Based on severity, differences were observed across the histological subtypes of lung cancer in stage III patients for ENR, EMR, AISI, eosinophil count, and platelet count, as well as in stage IV patients for AISI, SIRI, and SII. Disease severity impacts the associated inflammatory response in all histologic subtypes of lung cancer to varying degrees. Conclusions: Histological subtype might have a decisive role in shaping the systemic inflammatory profile of lung cancer patients. CBC-derived indices serve as accessible, cost-effective biomarkers for early risk assessment, aiding in the prognosis evaluation and monitoring of therapeutic response. Future studies are needed to further evaluate the histology-specific inflammatory profiles as adjunctive tools in precision oncology. Full article

Background/Objectives: Lung cancer recurrence, particularly in NSCLC, remains a major challenge, with 30–70% of patients relapsing post-treatment. Traditional predictors like TNM staging and histopathology fail to account for tumor heterogeneity and immune dynamics. This review evaluates AI models integrating gene biomarkers (TP53, KRAS, FOXP3, PD-L1, and CD8) to enhance the recurrence prediction and improve the personalized risk stratification. Methods: Following the PRISMA guidelines, we systematically reviewed AI-driven recurrence prediction models for lung cancer, focusing on genomic biomarkers. Studies were selected based on predefined criteria, emphasizing AI/ML approaches integrating gene expression, radiomics, and clinical data. Data extraction covered the study design, AI algorithms (e.g., neural networks, SVM, and gradient boosting), performance metrics (AUC and sensitivity), and clinical applicability. Two reviewers independently screened and assessed studies to ensure accuracy and minimize bias. Results: A literature analysis of 18 studies (2019–2024) from 14 countries, covering 4861 NSCLC and small cell lung cancer patients, showed that AI models outperformed conventional methods. AI achieved AUCs of 0.73–0.92 compared to 0.61 for TNM staging. Multi-modal approaches integrating gene expression (PDIA3 and MYH11), radiomics, and clinical data improved accuracy, with SVM-based models reaching a 92% AUC. Key predictors included immune-related signatures (e.g., tumor-infiltrating NK cells and PD-L1 expression) and pathway alterations (NF-κB and JAK-STAT). However, small cohorts (41–1348 patients), data heterogeneity, and limited external validation remained challenges. Conclusions: AI-driven models hold potential for recurrence prediction and guiding adjuvant therapies in high-risk NSCLC patients. Expanding multi-institutional datasets, standardizing validation, and improving clinical integration are crucial for real-world adoption. Optimizing biomarker panels and using AI trustworthily and ethically could enhance precision oncology, enabling early, tailored interventions to reduce mortality. Full article