Translational lung cancer research最新文献

Background: Osimertinib is the standard first-line treatment for non-small cell lung cancer (NSCLC) patients with epidermal growth factor receptor (EGFR) sensitizing mutations. However, the response duration varies among patients, meaning predictive biomarkers are needed. Therefore, this study explores the role of co-occurring genomic alterations in predicting survival outcomes.

Methods: Clinical data were extracted from electronic medical records. We retrospectively analyzed next-generation sequencing (NGS) data for EGFR-mutant NSCLC patients treated with first-line osimertinib treatment.

Results: Among the patients who underwent first-line osimertinib treatment, baseline NGS data were analyzed from treatment-naïve tissue for 48 patients. Alterations in TP53 were the most common co-mutation event (62.5%). Patients with mutations in TP53 exon 5, which encodes a critical region in the DNA-binding domain, exhibited a reduced treatment period [hazard ratio (HR) =7.67; 95% confidence interval (CI): 1.77-33.32; P=0.007] and overall survival (OS) (HR =9.29; 95% CI: 2.06-41.86; P=0.004) compared to EGFR-mutant NSCLC patients possessing the wild-type TP53. In particular, co-expression of programmed death-ligand 1 (PD-L1) with TP53 exon 5 mutation showed worse time to treatment discontinuation (TTD) (HR =9.27; 95% CI: 1.42-60.34; P=0.02) and OS (HR =14.54; 95% CI: 2.03-104.32; P=0.008).

Conclusions: Mutations in TP53 exon 5 are associated with a shorter first-line osimertinib treatment duration and OS. These findings might provide insight into a combination strategy for the first-line treatment of EGFR mutant NSCLC patients or a patient selection strategy for adjuvant osimertinib.

Background: Circulating tumor DNA (ctDNA) has recently garnered attention as a promising prognostic biomarker in cancer patients. This review aimed to evaluate the prognostic significance of ctDNA in patients with non-small cell lung cancer (NSCLC) at different treatment timepoints.

Methods: A comprehensive search of PubMed, Web of Science, Embase, Cochrane Library, Scopus, ClinicalTrials.gov and World Health Organization International Clinical Trials Registry Platform (WHO-ICTRP) was performed covering the period from January 2016 to May 2022, with updates monitored until June 2024. Studies reporting ctDNA positivity versus negativity and associated survival outcomes were included. Hazard ratios (HRs) or risk ratios (RRs) were pooled using random-effects models for relapse-free survival (RFS), overall survival (OS), and recurrence risk. The risk of bias of observational studies was assessed by the Newcastle-Ottawa Scale (NOS).

Results: Fifty-two studies were included. Total sample sizes of these studies ranged from 12 to 330 participants. Baseline ctDNA positivity was associated with worse RFS [HR =2.23, 95% confidence interval (CI): 1.82-2.75] in all NSCLCs. Among resectable NSCLC, postoperative ctDNA was strongly associated with inferior RFS (HR =5.64, 95% CI: 3.88-8.19) and OS (HR =4.17, 95% CI: 2.22-7.84). Similar trends were noted after full-course treatment for both resectable and unresectable patients. CtDNA detection often preceded radiographic or clinical recurrence, supporting its potential as an early indicator of relapse.

Conclusions: CtDNA positivity serves as a robust prognostic marker of worse survival and higher recurrence in NSCLC patients throughout the treatment cycle. Early ctDNA detection may facilitate timely therapeutic interventions and improve patient outcomes.

Background: Drugs for systemic therapy to advanced or recurrent non-small cell lung cancer (NSCLC) are determined by the type of driver oncogenes and programmed death-ligand 1 (PD-L1) immunostaining. In this study, we investigated the potential for artificial intelligence to assist in detecting epidermal growth factor receptor (EGFR) mutation, which is one of the most frequent and important driver oncogenes, and predicting the efficacy of EGFR-tyrosine kinase inhibitors (TKIs) in patients with NSCLC.

Methods: We built an ensemble model that combined machine learning models (logistic regression, Bernoulli naive Bayes and Gaussian naive Bayes) for clinical information and tumor characteristics analysis, and a deep convolutional neural network for analyzing computed tomography (CT) images. The convolutional neural network was trained from scratch on our imaging dataset. Clinical and imaging features were analyzed separately within their respective models and subsequently integrated in the ensemble framework. The models were trained to predict EGFR mutation and the response of EGFR-TKI using cross-entropy loss. The performance of the proposed model was evaluated by 5-fold cross-validation.

Results: One hundred and fifty consecutive evaluable patients were included in this study. Among them, 61 patients had EGFR mutation, including 59 patients with common EGFR mutation and 2 patients with uncommon EGFR mutation. The ensemble model predicted EGFR mutation with an area under the curve (AUC) of 0.88 [95% confidence interval (CI): 0.79-0.97]. Each sub-model integrated into the ensemble model predicted EGFR mutation with AUC of 0.83 (95% CI: 0.71-0.95), 0.88 (95% CI: 0.79-0.97), 0.87 (95% CI: 0.79-0.94), and 0.84 (95% CI: 0.72-0.96) for logistic regression, Bernoulli naive Bayes, Gaussian naive Bayes and deep neural network respectively. The predictive accuracy of the ensemble model was 0.56. Specifically, the ensemble model reported that the predictive accuracy of the Del19 EGFR mutation was higher than that of the L858R EGFR mutation, with overall response rate predictive accuracy (AUC) of 0.67 versus 0.52, and disease control rate AUC of 0.88 versus 0.53.

Conclusions: The ensemble model demonstrated strong performance in predicting EGFR mutations and showed higher predictive treatment response for EGFR exon 19 deletions than for L858R mutations. These findings suggest that ensemble learning may enhance the non-invasive prediction of EGFR mutation status and EGFR genotype-specific therapeutic outcomes in NSCLC, although further validation in larger cohorts is warranted.

Background: Immune checkpoint inhibitors (ICIs) have markedly improved outcomes in lung cancer but may lead to immune-related adverse events (irAEs). Among them, endocrine irAEs (e-irAEs) are frequent, yet their risk factors and prognostic implications remain unclear. This study aimed to investigate the incidence, predictors, and clinical outcomes of e-irAEs in patients with advanced lung cancer receiving ICIs.

Methods: In this single-center retrospective cohort study, we analyzed patients with advanced lung cancer who received at least 2 cycles of ICIs from January 2019 to October 2023 at West China Hospital of Sichuan University. Patients were categorized into e-irAE and no e-irAE groups. The cumulative incidence of e-irAE was estimated using the Aalen-Johansen method, accounting for death as a competing risk. Risk factors for e-irAEs were assessed using Fine-Gray subdistribution hazard model and logistic regression, while a time-dependent Cox model was employed to evaluate the impact of e-irAEs on progression-free survival (PFS) and overall survival (OS).

Results: Our analysis included 603 patients in total, 60 (10.0%) developed e-irAEs, predominantly hypothyroidism (73.3%) and thyrotoxicosis (23.3%), with a median onset of 4.0 months. During follow-up, 261 (43.3%) patients died. Female sex [subdistribution hazard ratio (SHR), 2.27; 95% confidence interval (CI), 1.23-4.21; P=0.009], lung metastasis (SHR, 1.79; 95% CI, 1.07-3.02; P=0.03), elevated thyroid stimulating hormone (TSH) (SHR, 1.04; 95% CI, 1.02-1.06; P<0.001), increased eosinophil count (SHR, 1.66; 95% CI, 1.32-2.10; P<0.001), and objective response (SHR, 2.23; 95% CI, 1.25-3.97; P=0.007) were associated with higher risk of e-irAE development. Patients with e-irAEs had superior OS (median 42.0 vs. 27.0 months; P=0.04) and a trend toward improved PFS (median PFS 14.0 vs. 12.0 months; P=0.08). Time-dependent cox analysis indicated that e-irAE was associated with a favorable trend in both PFS [hazard ratio (HR), 0.77; 95% CI, 0.50-1.19; P=0.24] and OS (HR, 0.84; 95% CI, 0.52-1.36; P=0.48).

Conclusions: e-irAEs occurred in approximately 10% of advanced lung cancer patients receiving ICIs. Predictors of e-irAE development included female sex, lung metastasis, increased eosinophil count, elevated TSH, and objective response to ICIs. Patients with e-irAE occurrence tended to have a favorable survival outcome.

Background: The optimal surgical extent for clinical T1c solid-dominant non-small cell lung cancer (NSCLC) remains debated. This study aimed to compare the recurrence-free survival (RFS) and overall survival (OS) between segmentectomy and lobectomy in patients with clinical T1c solid-dominant NSCLC.

Methods: We retrospectively analyzed 888 patients with clinical T1c solid-dominant NSCLC [tumor diameter: 2-3 cm; consolidation-to-tumor ratio (CTR) >0.5] who underwent segmentectomy of the dominant pulmonary segment or lobectomy. Clinical characteristics, 5-year RFS, and 5-year OS were evaluated. Propensity score matching (PSM, 1:1) and subgroup Cox regression models were employed to adjust for confounders.

Results: Of the 888 eligible cases, segmentectomy and lobectomy were performed in 55 and 833 patients, respectively. The difference in the 5-year OS between segmentectomy and lobectomy was found to be statistically significant (91.7% vs. 84.3%, P=0.02), which was also showed in the propensity score analysis (91.7% vs. 90.0%; P=0.08), with a median follow-up time of 46 months. The 5-year RFS did differ significantly between segmentectomy and lobectomy (89.46% vs. 71.50%; P=0.02), but it shown no difference in the propensity score analysis (89.46% vs. 81.5%; P=0.26).

Conclusions: The results indicate that segmentectomy of dominant pulmonary segment is superior to lobectomy in terms of OS for solid-dominant NSCLC cases with a tumor diameter between 2 and 3 cm.

Background: Computed tomography-guided radiofrequency ablation combined with video-assisted thoracoscopic surgery (VATS) hybrid surgery (HBD) treats multiple primary lung nodules by simultaneously ablating satellite nodules and resecting the primary lesion. However, its postoperative patient-centered recovery trajectories remain unclear compared to standard VATS. This study aims to illustrate the patient-reported outcomes (PROs) of HBD and VATS, and to investigate whether a hybrid approach can serve as a safe and effective alternative for cases traditionally deemed challenging, thereby potentially expanding the indications for minimally invasive therapy.

Methods: A longitudinal cohort study included 183 patients with a primary clinical stage 0/IA non-small cell lung cancer (NSCLC) and at least one additional ipsilateral nodule (118 VATS, 65 HBD) treated at a national cancer center was conducted (April 2024-December 2024). PROs were assessed using the MD Anderson Symptom Inventory-Lung Cancer (MDASI-LC) preoperatively and at 17 timepoints postoperatively (days 1-90). Moderate-to-severe symptoms/functional impairment was defined as scores ≥4/10. Mixed-effects models and Kaplan-Meier analyses evaluated recovery trajectories.

Results: A total of 183 patients with stage 0/IA NSCLC (118 VATS, 65 HBD) treated at a national cancer center were selected. Both groups showed similar baseline characteristics except sex distribution (HBD: 83.1% female vs. VATS: 64.4%, P=0.01). Pain (45.9%), fatigue (40.7%), and dyspnea (40.0%) were the top 3 moderate-to-severe symptoms in early recovery. The PRO trajectories were broadly similar between groups for most symptoms, but HBD exhibited persistently higher coughing burden [postoperative day 3 (POD3) difference +29.8%, P=0.06]. VATS showed a gradual slowing recovery in work (interaction estimate: 0.0096, P=0.040) and walking (interaction estimate: 0.0115, P=0.006). HBD patients experienced faster recovery of numbness (P=0.02) and early psychological distress. Complication rates were low in both groups (HBD: 12.31% vs. VATS: 10.17%, P=0.82).

Conclusions: HBD achieves comparable PRO-based recovery to VATS while preserving lung parenchyma, though with distinct symptom trade-offs.

Background: Limited evidence exists on the role of protein glycosylation, particularly O-GlcNAcylation (O-GlcNAc), in predicting radiotherapy (RT) response in non-small cell lung cancer (NSCLC). This study aimed to investigate O-GlcNAc expression, glucose metabolism indicators, and their associations with RT response and prognosis in NSCLC.

Methods: We conducted a retrospective cohort study of 216 NSCLC patients who underwent RT and positron emission tomography-computed tomography (PET-CT) imaging. O-GlcNAc expression in pretreatment primary tumor specimens was evaluated by immunohistochemistry (IHC), and patients were categorized into high- and low-expression groups. All patients were matched for age, sex, diagnosis, and pathological stage. Clinical features were reviewed, and multivariable logistic regression was applied to analyze associations between O-GlcNAc levels and clinical parameters. The conditional logistic regression was used to calculate odds ratios (ORs) with 95% confidence intervals (CIs). Kaplan-Meier analysis was performed to evaluate the prognostic impact of O-GlcNAc expression. Pretreatment blood glucose levels and primary tumor glucose uptake [maximum standardized uptake value (SUVmax)] from PET-CT were also assessed, and correlation analyses were conducted to determine their relationships with RT response and survival outcomes.

Results: Low O-GlcNAc expression was independently associated with poor RT response (P=0.005; OR =2.47; 95% CI: 1.32-4.64) and significantly predicted shorter progression-free survival (PFS; log-rank P=0.049) and overall survival (OS; log-rank P=0.008). In contrast, blood glucose levels (P=0.59) and primary tumor SUVmax (P=0.38) showed no association with RT response, and neither blood glucose nor SUVmax correlated with PFS; however, high SUVmax was predictive of shorter OS (log-rank P=0.03).

Conclusions: High O-GlcNAc expression was a predictor of favorable RT response and improved PFS and OS in NSCLC patients.

Background: Real-world data on the application of trastuzumab deruxtecan (T-DXd) in human epidermal growth factor receptor 2 (HER2)-mutant non-small cell lung cancer (NSCLC) are scarce. This study observed the effectiveness and safety of T-DXd for the treatment of Chinese patients with HER2-mutant advanced NSCLC in the real-world setting.

Methods: This retrospective study was conducted at two centers in China. Clinical data were reviewed in patients who received T-DXd treatment. The primary outcomes were progression-free survival (PFS) and objective response rate (ORR).

Results: Between April 2023 and January 2025, 35 patients were included. All patients had stage IV lung adenocarcinoma. Median age was 58 years (range, 33-87 years), and 18 (51.4%) patients were female. All patients received T-DXd as second- or further-line treatment. Most patients [24 (68.6%)] had HER2 exon 20 mutations. With a median follow-up of 9.7 months (range, 2.0-22.1 months), the median PFS was 7.85 months [95% confidence interval (CI): 6.64-15.05]. ORR was 51.4% (95% CI: 34.0-68.6%). Patients with previous anti-angiogenic therapy (n=11) had numerically worse prognosis (median PFS, 6.37 months; ORR, 36.4%). Elderly patients (n=10) achieved PFS benefit (median, 7.18 months) and ORR (60.0%) similar to the total population. Adverse events (AEs) were reported in 23 (65.7%) patients, with the most common being fatigue [14 (40.0%)]. No grade ≥3 AEs occurred.

Conclusions: This study firstly supplements real-world evidence on T-DXd treatment in Chinese patients with previously treated HER2-mutant advanced NSCLC. The results preliminarily showed the favorable antitumor activity and acceptable safety profile of T-DXd in clinical practice.