Translational lung cancer research最新文献

Background: Low-dose chest computed tomography (LDCT) screening improves early detection of lung cancer but poses challenges such as false positives and overdiagnosis, especially for nodules smaller than 8 mm where follow-up guidelines are unclear. Traditional risk prediction models have limitations, and deep learning (DL) algorithms offer potential improvements but often require large datasets. This study aimed to develop a DL-based, label-free lung cancer risk prediction model using alternative LDCT images and validate it in individuals without non-calcified solid pulmonary nodules larger than 8 mm.

Methods: We utilized LDCT scans from individuals without non-calcified solid nodules larger than 8 mm to develop a DL-based lung cancer risk prediction model. An alternative training dataset included 1,064 LDCT scans: 380 from patients with pathologically confirmed lung cancer and 684 from control individuals without lung cancer development over 5 years. For the lung cancer group, only the contralateral lung (without the tumor) was analyzed to represent high-risk individuals without large nodules. The LDCT scans were randomly divided into training and validation sets in a 3:1 ratio. Four three-dimensional (3D) convolutional neural networks (CNNs; 3D-CNN, MobileNet v2, SEResNet18, EfficientNet-B0) were trained using densely connected U-Net (DenseUNet)-segmented lung parenchyma images. The models were validated on a real-world test dataset comprising 1,306 LDCT scans (1,254 low-risk and 52 high-risk individuals) and evaluated using the area under the receiver operating characteristic (ROC) curve (AUC), Brier scores, and calibration measures.

Results: In the validation dataset, the AUC values were 0.801 for 3D-CNN, 0.802 for MobileNet v2, 0.755 for EfficientNet-B0, and 0.833 for SEResNet18. Corresponding Brier scores were 0.169, 0.175, 0.217, and 0.156, respectively, indicating good calibration, especially for SEResNet18. In the test dataset, the AUC values were 0.769 for 3D-CNN, 0.753 for MobileNet v2, 0.681 for EfficientNet-B0, and 0.820 for SEResNet18, with Brier scores of 0.169, 0.180, 0.202, and 0.138, respectively. The SEResNet18 model demonstrated the best performance, achieving the highest AUC and lowest Brier score in both validation and test datasets.

Conclusions: Our study demonstrated that DL-based, label-free lung cancer risk prediction models using alternative LDCT images can effectively predict lung cancer development in individuals without non-calcified solid pulmonary nodules larger than 8 mm. By analyzing lung parenchyma on LDCT images without relying on nodule detection, these models may enhance the efficiency of LDCT screening programs. Further prospective studies are needed to determine their clinical utility and impact on screening protocols, and validation in larger, diverse populations is necessary to ensure generalizability.

Background: With increased early lung cancer screening, synchronous multiple pulmonary nodules are more frequently detected. However, due to the lack of standardized treatment strategies, their management remains contentious. This study utilizes patient-reported outcomes (PROs) to assess early postoperative symptoms and functionality, aiming to determine the optimal resection extent for unilateral multiple pulmonary nodules.

Methods: In this longitudinal cohort study, 550 patients undergoing single-port video-assisted thoracoscopic surgery (VATS) for pulmonary nodules were categorized into two groups based on resection extent: single-lobe and multiple-lobe. The Perioperative Symptom Assessment for Patients Undergoing Lung Surgery (PSA-Lung) scale was used to measure symptom severity, functional status, and short-term outcomes preoperatively, daily from postoperative days 1-4, and weekly up to four weeks post-surgery. Mixed-effects models were used to compare the differences in PRO scores over time.

Results: Among the participants, 416 had single-lobe and 134 had multiple-lobe surgeries. The multiple-lobe group reported significantly worse symptoms of pain (P=0.04), shortness of breath (P<0.001), disturbed sleep (P=0.007), and fatigue (P=0.01), along with greater functional impairments in walking (P=0.002) and daily activities (P=0.002). We then analyzed the distribution of postoperative moderate-severe symptoms and functional impairment in both groups. We found that the proportion of patients with moderate-to-severe shortness of breath (P<0.001), disturbed sleep (P<0.001), difficulty in walking (P=0.001), and difficulty in daily activities (P<0.001) was significantly higher in the multiple-lobe group than in the single-lobe group. Moreover, patients with multiple-lobe surgeries had a longer recovery time from pain (P=0.02) and drowsiness (P=0.005) than those with single lobe surgeries. As a matter of course, surgical times were significantly longer in the multiple-lobe group than in the single-lobe group.

Conclusions: Multiple-lobe surgery patients faced more severe postoperative symptoms and functional impairments, with extended recovery times. These results advocate for a conservative surgical approach, favoring long-term monitoring over extensive resection for patients with unilateral multiple nodules without clear signs of malignancy or progression.

Background: Postoperative recurrence is a significant problem in patients with early-stage non-small cell lung cancer (NSCLC), with recurrence rates of 35% for stage IB and 50% for stage IIA. This study aimed to evaluate the efficacy of tegafur-uracil (UFT) as an adjuvant therapy in NSCLC patients with poor prognostic factors.

Methods: A retrospective analysis was conducted of 330 patients with stage IB/IIA NSCLC who underwent lung resection between 2000 and 2019. Patients were divided into two groups based on the presence of poor prognostic factors (vascular, lymphatic, or pleural invasion or high pathological grade). Recurrence-free survival (RFS) and overall survival (OS) were compared between the UFT-treated and untreated groups using a Kaplan-Meier analysis.

Results: Among these patients, 85.8% had poor prognostic factors. In patients with poor prognostic factors, the 5-year RFS rates in the UFT and non-UFT groups were 74.3% and 62.6%, respectively (P=0.048), and the 5-year OS was 85.6% and 62.4%, respectively (P<0.001). In patients without poor prognostic factors, UFT significantly extended OS (90.2% vs. 57.2%, P=0.03), but did not significantly affect RFS (P=0.40).

Conclusions: Postoperative adjuvant therapy with UFT significantly improved both RFS and OS in patients with stage IB/IIA NSCLC with poor prognostic factors. The administration of UFT should be considered in patients with high-risk early-stage NSCLC.

Background: Cytological examination is of suboptimal sensitivity but high specificity for the diagnosis of malignant pleural effusions (MPEs). Pleural fluid extracellular vesicles (PFEVs) are enriched with disease-specific microRNAs (miRNAs) which may improve the diagnostic yield for MPE. Our previous study demonstrated the feasibility of isolating miRNAs from PFEVs and profiling PFEV miRNAs by Nanostring nCounter^® Human v3 miRNA expression assay. Here, we interrogated in a small cohort to evaluate the diagnostic potential of PFEV miRNAs to differentiate between benign pleural effusion and MPE.

Methods: Extracellular vesicles (EVs) from pleural fluids were isolated by two sequential ultracentrifugation steps. PFEVs were extracted and characterised by western blotting analysis, particle analysis by tunable resistive pulse sensing (TRPS) technology, and transmission electron microscopy (TEM). Total RNAs (including miRNAs) were extracted from PFEVs and profiled by the Nanostring nCounter^® 827 probe miRNA expression assay. Differential expression analysis of the miRNA expression assays on PFEV samples was performed using the Bioconductor DESeq2 package.

Results: EVs from pleural fluids were evident by staining of positive EV-associated protein markers, particle size distribution within the expected parameters, and the cup-shaped morphology by TEM. Employing Nanostring nCounter^® Human v3 miRNA expression assay, this proof-of-principle study demonstrated PFEV miRNAs were differentially expressed between benign effusions and malignant effusions [malignant pleural mesothelioma (MPM) or lung adenocarcinoma metastatic to pleura (metLUAD)]. The expression of six miRNAs (hsa-miR-1246, hsa-miR-136-5p, hsa-miR-141-3p, hsa-miR-145-5p, hsa-miR-200c-3p, and hsa-miR-9-5p) significantly differed between benign and malignant effusions, or between MPM and metLUAD, at adjusted P<0.05 and log₂fold change ≥1.0.

Conclusions: The miRNAs identified from this study could be interrogated further for their utility as a single biomarker candidate or to be tested simultaneously in a panel to complement pleural effusion diagnostics. PFEV miRNAs represent a novel bioresource with potential to aid in the diagnosis of pleural effusions. Larger prospective studies are needed to confirm their diagnostic utility.

Background: Cone beam computed tomography (CBCT) is a standard imaging modality in the management of lung cancer with radiation therapy. The optimal frequency of CBCT imaging during a course of radiotherapy is not currently strongly defined for many anatomical sites, including lung, and in clinical practice typically ranges from daily to weekly. There is a trade-off between clinical benefit derived from optimal soft tissue targeting with daily CBCT and the increased non-therapeutic dose that such imaging regimen entails. The aim of this study is to address this matter by proposing a new image-guided radiation therapy (IGRT) protocol and a patient classification method to achieve an optimal CBCT frequency for conventionally fractionated lung cancer radiation therapy.

Methods: This Institutional Review Board (IRB)-approved study analyzes 110 lung cancer patients, with a total of 1616 CBCTs during treatment. The in-house IGRT protocol involves daily CBCT for the first three fractions followed by weekly CBCT for soft tissue alignment, along with daily kV-orthogonal for bony anatomy alignment. The eligibility of patient of using this IGRT protocol is determined by a criterion based on numbers of CBCT position matches (equal to 3 fractions match in the first three CBCTs, or great than or equal to 3 fractions match in the first four CBCTs). The fraction matching threshold values 40-70% of protocol-eligible group (eGroup) were applied, as well as the setup threshold (ST) values of 3, 4, and 5 mm were applied, respectively. Sensitivities, specificities and accuracies were computed to quantitate our proposed classification method.

Results: With ST at 3, 4, and 5 mm, with the best fraction matching threshold of 50% found in current dataset, the eGroup included 83.5%, 96.2%, and 98.7% of patients, respectively. More patients are eligible to IGRT protocol if a larger pre-defined ST is used. Sensitivities for identifying a protocol-ineligible group (iGroup) patient were 0.69, 1.0, and 1.0, specificities for identifying an eGroup patient were 0.85, 0.93, and 0.96, while accuracies were 0.82, 0.94 and 0.96, respectively.

Conclusions: We have proposed a new patient classification approach in the context of an IGRT protocol with optimized CBCT frequency for conventionally fractionated lung cancer radiation therapy. The first three CBCT helps predict patient eligibility of this IGRT protocol. We have evaluated different threshold criteria and found high sensitivity, specificities and accuracies are achievable. This study supports that weekly CBCT is sufficient for the most of the lung patients. The same method, proposed adaptive classification approach in this study, might also be applied for other anatomic sites.

Background: Uncommon epidermal growth factor receptor (EGFR) gene mutant locally advanced non-small cell lung cancer (NSCLC) has been poorly documented in the literature. Our study aimed to investigate the clinical features and outcomes associated with these mutations.

Methods: A multi-center retrospective study was conducted to review 511 patients with EGFR mutant unresectable stage III lung adenocarcinoma, treated between 2012 and 2018 across 12 Chinese institutions. The patients were categorized into three groups based on their primary treatment: chemoradiotherapy (CRT), EGFR-TKIs (tyrosine kinase inhibitors), and radiotherapy (RT) combined with EGFR-TKIs.

Results: Among the 511 patients, 49 (9.6%) had uncommon EGFR mutations. Of these, 37 had detailed systemic treatment information. The uncommon mutations included exon 18 G719X (22.4%), exon 20 insertion (18.4%), exon 20 S768I (8.2%), T790M (8.2%), and exon 21 L861Q (4.1%). Compound mutations were identified in 34.7% of patients. There was a significant difference in progression-free survival (PFS) for uncommon and common mutation group (median 11.9 vs. 17.5 months, P=0.005). However, no significant difference was observed in overall survival (OS, P=0.14). The median PFS for the uncommon mutation group was 11.9 months for CRT (n=12, 32.4%), 5.0 months for EGFR-TKIs (n=16, 43.2%), and 14.8 months for RT combined with TKIs (n=9, 23.4%) (P=0.02). The median OS for the same groups were 43.6 months, 30.9 months, and not reached, respectively (P=0.18). Compared to EGFR-TKIs, both CRT and RT combined with TKIs significantly improved PFS (P=0.02, 0.04, respectively), and showed a trend toward superior OS compared to EGFR-TKIs (P=0.49, 0.06, respectively).

Conclusions: This study was the first to systematically summarize the clinical features and outcomes of unresectable locally advanced lung adenocarcinoma, with uncommon EGFR mutations. RT combined with sensitivity EGFR-TKIs may be a promising treatment option, while CRT remains the primary treatment choice.

Background: Lung cancer remains a global health challenge, with an incidence of 23% and an overall 5-year survival of only 19%, as nearly half newly diagnosed cases are at the advanced stages. Among Asian patients, over 50% of lung cancer cases carry epidermal growth factor receptor (EGFR) mutations, highlighting the significance of targeted therapy, mainly EGFR tyrosine kinase inhibitors (TKIs). However, acquired resistance to EGFR-TKIs inevitably occurs, representing a persisting challenge in cancer therapy. Malignant pleural effusion, characterized by lack of blood circulation in the pleural cavity, is commonly found in patients who develop resistance to EGFR-TKIs. Therefore, with traditional drug administration methods, primarily oral or intravenous, drug concentration within the pleural cavity is often insufficient. Hence, traditional therapy, which consists of oral and intravenous medication, along with pleural cavity drainage, often fails to yield a satisfactory outcome.

Case description: We report a case in which hyperthermic intrathoracic chemotherapy (HITHOC) was administered in a 50-year-old male patient with malignant pleural effusion and resistance to third-generation TKIs. HITHOC significantly reduced the tumor burden of the patient and helped restore sensitivity to third-generation TKIs.

Conclusions: We believe that HITHOC can efficiently improve the drug concentration within the pleural cavity, thereby reducing the tumor burden and eliminating potential TKI-resistant tumor subclones in the patient. This mode of therapy may prove valuable in overcoming TKI resistance.