Translational lung cancer research最新文献

For over a century, we have appreciated that the biochemical processes through which micro- and macronutrients are anabolized and catabolized-collectively referred to as "cellular metabolism"-are reprogrammed in malignancies. Cancer cells in lung tumors rewire pathways of nutrient acquisition and metabolism to meet the bioenergetic demands for unchecked proliferation. Advances in precision medicine have ushered in routine genotyping of patient lung tumors, enabling a deeper understanding of the contribution of altered metabolism to tumor biology and patient outcomes. This paradigm shift in thoracic oncology has spawned a new enthusiasm for dissecting oncogenotype-specific metabolic phenotypes and creates opportunity for selective targeting of essential tumor metabolic pathways. In this review, we discuss metabolic states across histologic and molecular subtypes of lung cancers and the additional changes in tumor metabolic pathways that occur during acquired therapeutic resistance. We summarize the clinical investigation of metabolism-specific therapies, addressing successes and limitations to guide the evaluation of these novel strategies in the clinic. Beyond changes in tumor metabolism, we also highlight how non-cellular autonomous processes merit particular consideration when manipulating metabolic processes systemically, such as efforts to disentangle how lung tumor cells influence immunometabolism. As the future of metabolic therapeutics hinges on use of models that faithfully recapitulate metabolic rewiring in lung cancer, we also discuss best practices for harmonizing workflows to capture patient specimens for translational metabolic analyses.

Background: Stereotactic body radiation therapy (SBRT) is crucial for treating early-stage inoperable non-small cell lung cancer (NSCLC) due to its precision and high-dose delivery. This study aimed to investigate the dosimetric deviations in gated (GR) versus non-gated radiotherapy (NGR), analyzing the impact of tumor location, target volume, and tumor motion range on dose distribution accuracy.

Methods: Sixty patients treated with either gated (n=30) or non-gated (n=30) SBRT for early-stage NSCLC were retrospectively analyzed. The planned dose distributions were determined using four-dimensional computed tomography simulations to account for breathing motion, while the actual dose delivered was determined by accumulating each fractional dose with synthetic computed tomography (sCT) methods. The deviations between the planned and actual accumulated doses were statistically analyzed for both groups. The effects of tumor location and volume on dose distribution were also assessed.

Results: Gated SBRT showed significantly higher dosimetric precision with median relative changes in the minimum dose within the ITV (ITV_D_min), mean dose received by the ITV (ITV_D_mean), and maximum dose within the ITV (ITV_D_max) of -0.44%, -0.33%, and -0.49%, respectively. Non-gated SBRT presented with larger median relative changes in these parameters (P<0.001 for the ITV_D_min). In gated SBRT, the PTV_D_min (minimum dose within the PTV) and PTV_D_mean (mean dose received over the entire PTV) differences were significantly lower favoring gated SBRT (P=0.01 and P=0.007, respectively), and for the prescribed dose volumes, the volume of PTV receiving 90% prescription dose (PTV_V_90%PD) and the volume of PTV receiving 100% prescription dose (PTV_V_100%PD) were more accurately delivered, also favoring gated SBRT (P=0.006 and P=0.03, respectively). The tumor location and volume analyses demonstrated that the dosimetric benefits of gated SBRT were particularly significant in the smaller internal target volumes (ITVs) and in the left lower central lung region (P<0.001 for the ITV_D_min in small volumes).

Conclusions: Gated SBRT affords dosimetric accuracy compared to non-gated SBRT, and thus could improve the therapeutic outcomes of NSCLC patients. These results should advocate for the preferential use of gated SBRT in cases requiring precise dose delivery due to large respiratory motion or small target volumes.

Background: Spread through air spaces (STAS) in lung adenocarcinoma (LUAD) is a distinct pattern of intrapulmonary metastasis where tumor cells disseminate within the pulmonary parenchyma beyond the primary tumor margins. This phenomenon was officially included in the World Health Organization (WHO)'s classification of lung tumors in 2015. STAS is characterized by the spread of tumor cells in three forms: single cells, micropapillary clusters, and solid nests. Clinical studies have linked STAS to a poorer prognosis, higher recurrence risk, and more advanced clinicopathological staging in LUAD patients. In this study, we constructed radiomics models and deep learning models based on computed tomography (CT) for predicting preoperative STAS status in LUAD.

Methods: A total of 395 (57.19±11.40 years old) patients with pathologically confirmed LUAD from two centers were enrolled in this retrospective study, in which STAS was detected in 146 patients (36.96%). The general clinical data, preoperative CT images, and the results of pathology reports of all patients were collected. Two experienced radiologists independently segmented the lesions by medical imaging interaction toolkit (MITK) software. The CT-based models only, the clinical-based models only, and the fusion model based on the two were constructed using radiomics and deep learning methods, respectively. The diagnostic performance of the different models was evaluated by comparing the area under the curve (AUC) of the subjects' receiver operating characteristics (ROCs).

Results: The deep learning model based on CT images achieved satisfactory discriminative performance in predicting STAS and outperformed the radiomics model and the clinical-radiomics model. The AUC of deep learning model was 0.918 for the internal test set and 0.766 for the external test set. The radiomics model had an AUC of 0.851 for the internal test set and an AUC of 0.699 for the external test set. The clinical-radiomics deep learning model was slightly less effective than the deep learning model (internal AUC =0.915, external AUC =0.773).

Conclusions: The constructed deep learning model based on preoperative chest CT can be used to determine the STAS status of LUAD patients with good diagnostic performance and is superior to radiomics models.

Background: Superior segmentectomies for clinical T1N0 non-small cell lung cancer (NSCLC) often suffer from inadequate surgical margins. Our study aimed to enhance the precision of superior segmentectomies by focusing on the anatomical features of the superior segmental vein (V⁶) branches, and assess the relevant outcomes.

Methods: The clinical data of 646 patients with cT1N0 NSCLC who underwent video-assisted thoracic surgery (VATS) from August 2020 to August 2021 were retrospectively analyzed. A total of 521 patients were enrolled for analyzing the prevalence and drainage patterns of V⁶b utilizing three-dimensional reconstruction images. Then, 162 patients who underwent segmentectomy were included to analyze the outcomes of superior segmentectomy. Disease-free survival (DFS) was estimated using the Kaplan-Meier method and compared across groups with the log-rank test.

Results: The prevalence of V⁶b2 (a type of intersegmental vein between S⁶ and S⁹) and V⁶b3 (between S⁶ and S⁸) were 91.2% (475/521) and 66.2% (345/521), respectively, both primarily converging with other branches of V⁶. The segmentectomy groups showed no significant differences in surgical margins, tumor size, or other malignancy-related factors, such as TNM stage. Correspondingly, during a median follow-up of 3.23 years [interquartile range (IQR), 2.99-3.61 years], the patients who underwent superior segment (S⁶) resection achieved an overall survival (OS) rate of 100% (68/68) and a DFS rate of 97.1% (66/68), demonstrating outcomes comparable to other segmentectomies (P>0.05).

Conclusions: High prevalence of V⁶b2 and V⁶b3 was observed with minimal variation in drainage patterns. Emphasizing these veins to ensure sufficient margins and potentially reducing aggressiveness through early detection, the outcomes of superior segmentectomies in this study are comparable to other segmentectomies and superior to those reported in previous studies.

Background: Visceral pleural invasion (VPI) is associated with a poor outcome in early-stage non-small cell lung cancer (NSCLC). Preoperative prediction of VPI could have an impact on surgical planning. The aim of this study was to establish a nomogram model based on computed tomography (CT) features to predict VPI in early-stage NSCLC.

Methods: This study is a retrospective review of patients enrolled with surgically pathologically confirmed NSCLC between December 2019 and June 2022. Patients were divided into training and testing cohorts at a ratio of 7:3. Clinicopathologic and radiologic characteristics such as types of tumor pleura relationships (types I-V) were recorded. Multivariable logistic regression analysis was used to identify independent risk factors for VPI, and the optimized variables were used to build a nomogram model. Model performance was evaluated with receiver operating characteristic (ROC) curves and calibration curves. The clinical utility of the nomogram was determined using decision curve analysis (DCA).

Results: Of the 766 patients [56.9% female patients; median age, 59 years; interquartile range (IQR): 53, 66] with early-stage NSCLC, VPI was confirmed in 250 patients (32.6%). There were 536 individuals in the training cohort (172 with VPI and 364 without VPI), and 230 individuals in the testing cohort (78 with VPI and 152 without VPI). The preoperative CT features related to VPI were tumor pleura relationship of type I and type III, solid, maximum diameter of tumor, lobulation, and lymphadenopathy. There was good discriminative power in the nomogram that included these six features. The training and testing cohorts' areas under the ROC curve (AUCs) were 0.815 and 0.825, respectively, with well-fitting calibration curves. DCA demonstrated that the nomogram was clinically useful.

Conclusions: The nomogram established with the identified CT features has the potential to assist with the prediction of VPI preoperatively in early-stage NSCLC and facilitate the selection of a rational treatment strategy.

Background: The combination therapy of the B-Raf proto-oncogene (BRAF) inhibitor dabrafenib and the mitogen-activated protein kinase kinase (MEK) inhibitor Trametinib has shown favorable outcomes in patients initially identified with BRAF^V600E mutations. However, there are currently no large-scale study data focusing on the use of a triple therapy regimen of epidermal growth factor receptor tyrosine kinase inhibitor (EGFR-TKI) plus dabrafenib and trametinib in patients with newly concomitant BRAF mutations after acquiring resistance to EGFR-TKIs. Our study aimed to explore the efficacy and safety of the triple therapy regimen through a multi-center real-world experience.

Methods: We reviewed the medical records of 1,861 patients who were treated with EGFR-TKI targeted drugs at three major medical centers in Shanghai between June 2015 and August 2024. Among 1,288 patients who developed disease progression, we identified 14 patients who were treated with a triple therapy regimen of EGFR-TKI plus dabrafenib and trametinib due to newly acquired BRAF^V600E mutation after EGFR-TKI resistance. The assessments comprised progression-free survival (PFS), overall survival (OS), objective response rate (ORR), disease control rate (DCR), and adverse events (AEs). We also performed further subgroup analysis to aid in identifying potential factors that influence treatment outcomes and enhance clinical decision-making.

Results: At the time of the data cutoff (August 1, 2024), the estimated median PFS was 6.7 months [95% confidence interval (CI): 2.5-not evaluated (NE)]. The median OS was not reached in 14 patients. ORR was 35.7% (95% CI: 14.0-64.4%) and DCR was 78.6% (95% CI: 52.4-92.4%). Three patients (21.4%) reported progressive disease (PD) and that was the best response. The median PFS was 8.35 months (95% CI: 2.0-NE) in 8 patients receiving third-generation TKI followed by first-/second-generation EGFR-TKIs and 6.9 months (95% CI: 2.5-NE) in 6 patients receiving third-generation TKI as first-line treatment directly. There was no significant difference in PFS between the two groups of patients receiving third-generation TKIs in different treatment sequences above [hazard ratio (HR): 1.107; 95% CI: 0.318-3.854; P=0.85]. Subgroup analysis indicated that a complex genetic mutation background may be a potential factor contributing to poorer PFS. No unexpected adverse effects were reported. Apart from pyrexia, gastrointestinal-related adverse reactions and skin-related adverse reactions warrant close attention.

Conclusions: The triple therapy regimen of EGFR-TKI plus dabrafenib and trametinib was found to have substantial and durable clinical benefit, with a manageable safety profile, in patients with newly concomitant BRAF^V600E mutations after osimertinib failure.

Background: Ground-glass opacity (GGO) on computed tomography (CT) has been suggested as a potential prognostic factor in lung adenocarcinoma (LUAD), but its significance in patients with pathological stage IA3 LUAD, particularly in relation to micropapillary (MIP) status, remains unclear. This study addresses the clinical need to stratify patients based on GGO and MIP status to optimize prognosis prediction and follow-up strategies.

Methods: A multicenter retrospective study was conducted on 411 patients with pathological stage IA3 LUAD, enrolled between July 2012 and July 2020. Patients were divided into two groups based on the presence of GGO. The association of GGO with recurrence-free survival (RFS) and cancer-specific survival (CSS) of patients with different MIP status was assessed, stratified by MIP status (MIP ≥5% was classified as positive, and MIP <5% as negative). A life-table analysis was used to calculate dynamic recurrence curves of subgroups formed by GGO and MIP and to establish a personalized follow-up strategy.

Results: The analysis indicated that GGO was associated with prolonged RFS (P<0.001) and CSS (P=0.006) in MIP-negative patients but not for MIP-positive patients. Time-dependent Cox multivariate analysis further showed that GGO was a favorable prognostic factor for RFS (P=0.03) and CSS (P=0.04) even at 2 years postoperatively. Based on GGO components and MIP status, patients were categorized into the four following subgroups: MIP(+)-GGO(+), MIP(+)-GGO(-), MIP(-)-GGO(+), and MIP(-)-GGO(-); the recommended number of follow-up visits for these four subgroups within 5 years were 3, 9, 3, and 11, respectively.

Conclusions: The GGO component demonstrated a beneficial prognostic effect primarily in MIP-negative patients with pathological stage IA3 LUAD, sustained for up to 2 years. The variation in recurrence risk across subgroups underscores the importance of personalized follow-up strategies based on GGO and MIP status to optimize patient monitoring and care.

Background and objective: As the most common cancer to progress to brain metastases (BMs), lung cancer presents with intracranial involvement in approximately 20% of patients at the time of diagnosis and lung cancer BMs constitute approximately half of all BMs. The current clinical strategy for managing lung cancer BMs involves a combination of systemic anticancer therapies with local radiation or surgical interventions. The efficacy of systemic treatments is often constrained by the blood-brain barrier (BBB) and the poor inhibition effect of the drug itself. Despite these treatments, the median survival for patients with lung cancer BMs frequently does not exceed 2 years, underscoring the urgent need for novel and effective therapeutic approaches. Antibody-drug conjugate (ADC) consists of three components: monoclonal antibodies, payload, and linkers. Novel ADCs have demonstrated therapeutic advantages in a variety of tumors, including BMs. This review aims to summarize the latest advancements of ADCs in lung cancer BM.

Methods: For this review, we searched the literature published in the field of ADCs for lung cancer BMs over the past 10 years.

Key content and findings: New-generation ADCs, represented by trastuzumab deruxtecan (T-DXd) and others, have demonstrated prominent intracranial antitumor activities and have shown significant therapeutic advantages on lung or breast cancer BMs in both preclinical and clinical studies. Several factors may contribute to the efficacies of ADCs in the intracranial cancers including specific payload, a higher and uniform drug:antibody ratio (DAR) as well as potent bystander effect. Whether intracranial tumors express these target antigens should also be taken into consideration.

Conclusions: ADCs have demonstrated promising antitumor activities in non-small cell lung cancer (NSCLC) patients with BMs and could offer a new systemic treatment option for this subset population of patients. More research exploring the efficacy, safety and mechanism of ADCs in BMs are needed. Combining ADCs with conventional treatments for BMs, such as radiotherapy and immunotherapy, may be a new direction for future treatment.

Background: The current standard for the surgical management of lung cancer involves anatomic lung resection combined with systemic lymph node dissection/sampling. The purpose of this study was to investigate the patterns of pathological lymph nodes in invasive non-small cell lung cancer (NSCLC), explore the occurrence in lymph node metastasis (LNM), and provide recommendations for optimal lymph node resection/sampling in lung cancer operation.

Methods: There were 1,678 patients with NSCLC who underwent lobectomy between 2018 and 2021 at the Taizhou Hospital of Zhejiang Province were reviewed retrospectively. The location and incidence of LNM and postoperative pathological findings were studied. We analysed the metastasis rates of lymph node dissection stations using Pearson's χ² and Fisher's exact tests.

Results: There were 1,308 patients assessed as eligible and included in the study. The median number of lymph nodes cleared in the cohort was 11.2±5.1. In patients with lung adenocarcinoma, the rate of LNM was significantly higher in central than in peripheral lung cancer, especially in 2R/2L, L7, L9, L10, L11, and L12. Lung cancer patients with tumors ≤1 cm had no N2 lymph node metastases but few (2/191, 1.1%) N1 lymph node metastases. The likelihood of N2 metastasis increased (T1a, 0%, 0/191; T1b 3.5%, 22/625; T1c, 5.6%, 14/249; T2 and above, 18.9%, 46/243) with increasing tumor diameter. Thirty-four patients with stage N2 lung adenocarcinoma and 1-3 cm tumors displayed lobe-specific lymph node metastases in the mediastinum. In patients diagnosed with squamous cell carcinoma, no significant differences were observed in mediastinal LNM across various parameters (central versus peripheral location, tumor site, and tumor size).

Conclusions: Our study proposes recommendations for lymph node resection according to the pathological type of lung cancer, tumor location, lung lobes affected and tumor size, which may provide a certain reference value for the clinical work.