Differences of molecular events driving pathological and radiological progression of lung adenocarcinoma

Clinical and Genetic Characteristics of Early-Onset Lung Adenocarcinoma in a Large Chinese Cohort

BACKGROUND

The characteristics of early-onset lung adenocarcinoma (EOLA) have not been extensively studied. Our research aimed to comprehensively assess the clinical and genetic features of EOLA.

METHODS

We conducted a retrospective analysis of surgically resected lung adenocarcinoma patients, categorizing them into the EOLA group (aged <40 years) and the late-onset lung adenocarcinoma (LOLA) group (aged >60 years). A comparative investigation of clinical, germline, and genomic features was conducted. Propensity score matching was used to balance baseline characteristics for gene mutation analysis.

RESULTS

We enrolled 487 EOLA and 2507 LOLA patients. EOLA patients exhibited a higher female-to-male ratio (2.55 vs 1.19) and a higher proportion of family history of lung cancer in the ground-grass opacity subgroup (12.7% vs 8.9%). The EOLA group exhibited higher rates of earlier stage in the ground-grass opacity subgroup and solid subgroup. Preinvasive adenocarcinoma was the dominant histologic subtype in the EOLA group within the ground-glass opacity subgroup (73.8% vs 25.6%). After propensity score matching, we analyzed 241 stage 0/I patients with available genetic test results. Significant disparities in gene mutation rates emerged between the EOLA and LOLA patients, including Erb-B2 receptor tyrosine kinase 2 (ERBB2; 38.0% vs 2.8%), epidermal growth factor receptor (EGFR; 36.0% vs 64.5%), MET (0.0% vs 7.1%), neurofibromin 1 (NF1; 0.0% vs. 5.7%), and anaplastic lymphoma kinase (ALK) fusion (10.0% vs 1.4%).

CONCLUSIONS

EOLA patients exhibited distinct clinical and genetic characteristics compared with LOLA patients.

Radiomics-Based Support Vector Machine Distinguishes Molecular Events Driving the Progression of Lung Adenocarcinoma

INTRODUCTION

An increasing number of early-stage lung adenocarcinomas (LUAD) are detected as lung nodules. The radiological features related to LUAD progression warrant further investigation. Exploration is required to bridge the gap between radiomics-based features and molecular characteristics of lung nodules.

METHODS

Consensus clustering was applied to the radiomic features of 1212 patients to establish stable clustering. Clusters were illustrated using clinicopathological and next-generation sequencing. A classifier was constructed to further investigate the molecular characteristics in patients with paired computed tomography and RNA sequencing data.

RESULTS

Patients were clustered into four clusters. Cluster 1 was associated with a low consolidation-to-tumor ratio, preinvasion, grade I disease, and good prognosis. Clusters 2 and 3 reported increasing malignancy with a higher consolidation-to-tumor ratio, higher pathologic grade, and poor prognosis. Cluster 2 possessed more spread through air spaces and cluster 3 reported a higher proportion of pleural invasion. Cluster 4 had similar clinicopathological features as cluster 1 except but a proportion of grade II disease. RNA sequencing indicated that cluster 1 represented nodules with indolent growth and good differentiation, whereas cluster 4 reported progression in cell development but still had low proliferative activity. Nodules with high proliferation were classified into clusters 2 and 3. In addition, the radiomics classifier distinguished cluster 2 as nodules harboring an activated immune environment, whereas cluster 3 represented nodules with a suppressive immune environment. Furthermore, signatures associated with the prognosis of early-stage LUAD were validated in external datasets.

CONCLUSIONS

Radiomics features can manifest molecular events driving the progression of LUAD. Our study provides molecular insight into radiomics features and assists in the diagnosis and treatment of early-stage LUAD.

Validation of T stage classification strategy for >2 cm ground-glass opacity non-small cell lung cancer: a retrospective cohort study

Background

The Lung Cancer Staging Program of the International Association for the Study of Lung Cancer (IASLC) has proposed using solid component size, rather than overall tumor size, for T-staging. However, studies focusing on patients with ground-glass opacity (GGO) lesions with a diameter larger than 2 cm are limited. This study aims to validate the T stage classification strategy recommended by IASLC in this specific and less-studied patient group.

Methods

Patients diagnosed with primary non-small cell lung cancer (NSCLC) who underwent lobectomy between December 2009 and December 2018 were included in this study. Clinical, pathological, and prognostic data were prospectively collected and retrospectively reviewed. Patients were eligible if they were confirmed to have NSCLC, underwent lobectomy, had complete follow-up data, and were not diagnosed with any other malignancies. The propensity score matching (PSM) method was employed to ensure baseline characteristic balance. Two groups of patients matched with the GGO group at baseline were stratified based on overall tumor size (group matched by overall size) and solid component size (group matched by solid component size), respectively. Overall survival (OS) and recurrence-free survival (RFS) were analyzed using the Cox proportional model and Kaplan-Meier method. Follow-up was conducted regularly to assess these outcomes. The T-staging applied was based on the solid component size according to the 8th edition IASLC staging guidelines.

Results

A total of 4,472 NSCLC patients who underwent lobectomy were included in the study (including 4,083 cases of solid lesions and 389 cases of subsolid lesions). The median follow-up time was 75.4 months. Patients in the GGO group had significantly better OS and RFS than those in the solid group [OS: hazard ratio (HR) =0.55, 95% confidence interval (CI): 0.40-0.73, P<0.001; RFS: HR =0.53, 95% CI: 0.42-0.67, P<0.001]. Comparing patients' PSM by overall size, the GGO group still had better OS and RFS (OS: HR =0.60, 95% CI: 0.43-0.85, P=0.004; RFS: HR =0.59, 95% CI: 0.44-0.79, P<0.001). After PSM by solid component size, no significant difference was detected between the GGO group and the group matched by solid component size on OS and RFS (OS: HR =0.89, 95% CI: 0.61-1.28, P=0.52; RFS: HR =0.92, 95% CI: 0.67-1.26, P=0.61). In subgroup analysis, after PSM by solid component size, the results showed no difference in OS and RFS between the restaged patients (c-T1 and c-T2) and the corresponding patients in the solid group (for OS, HR =1.06, 95% CI: 0.61-1.83, P=0.83; HR =1.11, 95% CI: 0.60-2.07, P=0.73, respectively; and RFS, HR =1.17, 95% CI: 0.75-1.82, P=0.49; HR =0.80, 95% CI: 0.48-1.34, P=0.39, respectively).

Conclusions

The T stage classification strategy proposed by ISALC remains applicable in patients with GGOs larger than 2 cm.

Tumor immune microenvironment analysis of non-small cell lung cancer development through multiplex immunofluorescence

Background

Emerging evidence has underscored the crucial role of infiltrating immune cells in the tumor immune microenvironment (TIME) of non-small cell lung cancer (NSCLC) development and progression. With the implementation of screening programs, the incidence of early-stage NSCLC is rising. However, the high risk of recurrence and poor survival rates associated with this disease necessitate a deeper understanding of the TIME and its relationship with driver alterations. The aim of this study was to provide an in-depth analysis of immune changes in early-stage NSCLC, highlighting the significant transitions in immune response during disease progression.

Methods

Tumor tissues were collected from 105 patients with precancerous lesions or stage I-III NSCLC. Next-generation sequencing (NGS) was used to detect cancer driver alterations. Multiplex immunofluorescence (mIF) was performed to evaluate immune cell density, percentage, and spatial proximity to cancer cells in the TIME. Next Among these patients, 64 had NGS results, including three with adenocarcinoma in situ (AIS), 10 with minimally invasive adenocarcinoma (MIA), and 51 with stage I invasive cancers. Additionally, three patients underwent neoadjuvant immuno-chemotherapy and tumor tissue specimens before and after treatment were obtained.

Results

Patients with stage I invasive cancer had significantly higher density (P=0.01) and percentage (P=0.02) of CD8+ T cells and higher percentages of M1 macrophages (P=0.04) and immature natural killer (NK) cells (P=0.041) in the tumor parenchyma compared to those with AIS/MIA. Patients with mutated epidermal growth factor receptor (EGFR) gene exhibited decreased NK cell infiltration, increased M2 macrophage infiltration, and decreased aggregation of CD4+ T cells near tumor cells compared to EGFR wild-type patients. As NSCLC progressed from stage I to III, CD8+ T cell density and proportion increased, while PD-L1+ tumor cells were in closer proximity to PD-1+CD8+ T cells, potentially inhibiting CD8+ T cell function. Furthermore, M1 macrophages decreased in density and proportion, and the number of NK cells, macrophages, and B cells around tumor cells decreased. Additionally, patients with tertiary lymphoid structures (TLSs) had significantly higher proportion of M1 macrophages and lymphocytes near tumor cells, whereas those without TLS had PD-L1+ tumor cells more densely clustered around PD-1+CD8+ T cells. Notably, neoadjuvant immuno-chemotherapy induced the development of TLS.

Conclusions

This study offers an in-depth analysis of immune changes in NSCLC, demonstrating that the transition from AIS/MIA to invasive stage I NSCLC leads to immune activation, while the advancement from stage I to stage III cancer results in immune suppression. These findings contribute to our understanding of the molecular mechanisms underlying early-stage NSCLC progression and pave the way for the identification of potential treatment options.

Differentiating the Invasiveness of Lung Adenocarcinoma Manifesting as Ground Glass Nodules: Combination of Dual-energy CT Parameters and Quantitative-semantic Features

RATIONALE AND OBJECTIVES

To evaluate the diagnostic performance of dual-energy CT (DECT) parameters and quantitative-semantic features for differentiating the invasiveness of lung adenocarcinoma manifesting as ground glass nodules (GGNs).

MATERIALS AND METHODS

Between June 2022 and September 2023, 69 patients with 74 surgically resected GGNs who underwent DECT examinations were included. CT numbers on virtual monochromatic images were calculated at 40-130 keV generated from DECT. Quantitative morphological measurements and semantic features were evaluated on unenhanced CT images and compared between pathologically confirmed adenocarcinoma in situ (AIS)-minimally invasive adenocarcinoma (MIA) and invasive lung adenocarcinoma (IAC). Multivariable logistic regression analysis was used to identify independent predictors. The diagnostic performance was assessed by the area under the receiver operating characteristic curve (AUC) and compared using DeLong's test.

RESULTS

Monochromatic CT numbers at 40-130 keV were significantly higher in IAC than in AIS-MIA (all P < 0.05). Multivariate logistic analysis revealed that CT number of 130 keV (odds ratio [OR] = 1.02, P = 0.013), maximum cross-sectional long diameter (OR =1.40, P = 0.014), deep or moderate lobulation sign (OR =19.88, P = 0.005), and abnormal intranodular vessel morphology (OR = 25.57, P = 0.017) were independent predictors of IAC. The combined prediction model showed a favorable differentiation performance with an AUC of 0.966 (95.2% sensitivity, 94.3% specificity, 94.8% accuracy), which was significantly higher than that for each risk factor (AUC = 0.791-0.822, all P < 0.05).

CONCLUSION

A multi-parameter combined prediction model integrating monochromatic CT numbers from DECT and quantitative-semantic features is promising for the preoperative discrimination of IAC and AIS-MIA in GGN-predominant lung adenocarcinoma.

Integrated whole-exome and bulk transcriptome sequencing delineates the dynamic evolution from preneoplasia to invasive lung adenocarcinoma featured with ground-glass nodules

OBJECTIVE

The genomic and molecular ecology involved in the stepwise continuum progression of lung adenocarcinoma (LUAD) from adenocarcinoma in situ (AIS) to minimally invasive adenocarcinoma (MIA) and subsequent invasive adenocarcinoma (IAC) remains unclear and requires further elucidation. We aimed to characterize gene mutations and expression landscapes, and explore the association between differentially expressed genes (DEGs) and significantly mutated genes (SMGs) during the dynamic evolution from AIS to IAC.

METHODS

Thirty-five patients with ground-glass nodules (GGNs) lung adenocarcinomas were enrolled. Whole-exome sequencing (WES) and transcriptome sequencing (RNA-Seq) were conducted on all patients, encompassing both tumor samples and corresponding noncancerous tissues. Data obtained from WES and RNA-Seq were subsequently analyzed.

RESULTS

The findings from WES delineated that the predominant mutations were observed in EGFR (49%) and ANKRD36C (17%). SMGs, including EGFR and RBM10, were associated with the dynamic evolution from AIS to IAC. Meanwhile, DEGs, including GPR143, CCR9, ADAMTS16, and others were associated with the entire process of invasive LUAD. We found that the signaling pathways related to cell migration and invasion were upregulated, and the signaling pathways of angiogenesis were downregulated across the pathological stages. Furthermore, we found that the messenger RNA (mRNA) levels of FAM83A, MAL2, DEPTOR, and others were significantly correlated with CNVs. Gene set enrichment analysis (GSEA) showed that heme metabolism and cholesterol homeostasis pathways were significantly upregulated in patients with EGFR/RBM10 co-mutations, and these patients may have poorer overall survival than those with EGFR mutations. Based on the six calculation methods for the immune infiltration score, NK/CD8+ T cells decreased, and Treg/B cells increased with the progression of early LUAD.

CONCLUSIONS

Our findings offer valuable insights into the unique genomic and molecular features of LUAD, facilitating the identification and advancement of precision medicine strategies targeting the invasive progression of LUAD from AIS to IAC.

Integrative Omics Analysis Reveals Metabolic Features of Ground-Glass Opacity-Associated Lung Cancer

Background: Ground-glass opacity (GGO)-associated cancers are increasingly prevalent, exhibiting unique clinical and molecular features that suggest the need for a distinct treatment strategy. However, the metabolic characteristics and vulnerabilities of GGO-associated lung cancers remain unexplored. Methods: We conducted metabolomic and transcriptomic analyses on 40 pairs of GGO-associated lung cancer tissues and adjacent normal tissues. By integrating data from TCGA database and single-cell RNA sequencing, we aimed to identify aberrant metabolic pathways, establish a metabolite-associated gene signature, and pinpoint key metabolic genes. The physiological effect of key genes was detected in vitro and vivo assays. Results: We identified a 30-gene metabolite-associated signature and discovered aberrant metabolic pathways for GGO-associated lung cancer at both metabolic and transcriptional levels. Patients with this signature displayed specific prognostic and molecular features. Cox regression analysis, based on the Cancer Genome Atlas Program (TCGA) data, further narrowed down the metabolite-related gene signature, resulting in a 5-gene signature. Confirmed by single-cell RNA sequencing (GSE203360), the 5-gene signature was mainly expressed in cancer cells of GGO tissue. Real-time quantitative PCR (RT-qPCR) further validated the differential expression of these genes between GGO and adjacent normal tissue obtained from pulmonary surgery. Finally, our integrative analysis unveiled aberrant histidine metabolism at both the multi-omics and single-cell levels. Moreover, we identified MAOB as a key metabolic gene, demonstrating its ability to suppress cell proliferation, migration, and invasion in LUAD cell lines, both in vitro and in vivo. Conclusions: We identified a specific metabolite-associated gene signature and identified aberrant histidine metabolism in GGO-associated lung cancer from multiple perspectives. Notably, MAOB, a crucial component in histidine metabolism, demonstrated a significant inhibitory effect on the proliferation and metastasis of LUAD, indicating its potential significance in pathogenesis and therapeutic interventions.