Global evolution of the tumor microenvironment associated with progression from preinvasive invasive to invasive human lung adenocarcinoma

The identification of hub genes associated with pure ground glass nodules using weighted gene co-expression network analysis

BACKGROUND

Whether there are invasive components in pure ground glass nodules(pGGNs) in the lungs is still a huge challenge to forecast. The objective of our study is to investigate and identify the potential biomarker genes for pure ground glass nodule(pGGN) based on the method of bioinformatics analysis.

METHODS

To investigate differentially expressed genes (DEGs), firstly the data obtained from the gene expression omnibus (GEO) database was used.Next Weighted gene co-expression network analysis (WGCNA) investigate the co-expression network of DEGs. The black key module was chosen as the key one in correlation with pGGN. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways analyses were done. Then STRING was uesd to create a protein-protein interaction (PPI) network, and the chosen module genes were analyzed by Cytoscape software.In addition the polymerase chain reaction (PCR) was used to evaluate the value of these hub genes in pGGN patients' tumor tissues compared to controls.

RESULTS

A total of 4475 DEGs were screened out from GSE193725, then 225 DEGs were identified in black key module, which were found to be enriched for various functions and pathways, such as extracellular exosome, vesicle, ribosome and so on. Among these DEGs, 6 overlapped hub genes with high degrees of stress method were selected. These hub genes include RPL4, RPL8, RPLP0, RPS16, RPS2 and CCT3.At last relative expression levels of CCT3 and RPL8 mRNA were both regulated in pGGN patients' tumor tissues compared to controls.

CONCLUSIONS

To summarize, the determined DEGs, pathways, modules, and overlapped hub genes can throw light on the potential molecular mechanisms of pGGN.

Multidimensional biological characteristics of ground glass nodules

The detection rate of ground glass nodules (GGNs) has increased in recent years because of their malignant potential but relatively indolent biological behavior; thus, correct GGN recognition and management has become a research focus. Many scholars have explored the underlying mechanism of the indolent progression of GGNs from several perspectives, such as pathological type, genomic mutational characteristics, and immune microenvironment. GGNs have different major mutated genes at different stages of development; EGFR mutation is the most common mutation in GGNs, and p53 mutation is the most abundant mutation in the invasive stage of GGNs. Pure GGNs have fewer genomic alterations and a simpler genomic profile and exhibit a gradually evolving genomic mutation profile as the pathology progresses. Compared to advanced lung adenocarcinoma, GGN lung adenocarcinoma has a higher immune cell percentage, is under immune surveillance, and has less immune escape. However, as the pathological progression and solid component increase, negative immune regulation and immune escape increase gradually, and a suppressive immune environment is established gradually. Currently, regular computer tomography monitoring and surgery are the main treatment strategies for persistent GGNs. Stereotactic body radiotherapy and radiofrequency ablation are two local therapeutic alternatives, and systemic therapy has been progressively studied for lung cancer with GGNs. In the present review, we discuss the characterization of the multidimensional molecular evolution of GGNs that could facilitate more precise differentiation of such highly heterogeneous lesions, laying a foundation for the development of more effective individualized treatment plans.

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.

Hydrogel-Embedded Precision-Cut Lung Slices Model Lung Cancer Premalignancy Ex Vivo

Lung cancer is the leading global cause of cancer-related deaths. Although smoking cessation is the best prevention, 50% of lung cancer diagnoses occur in people who have quit smoking. Research into treatment options for high-risk patients is constrained to rodent models, which are time-consuming, expensive, and require large cohorts. Embedding precision-cut lung slices (PCLS) within an engineered hydrogel and exposing this tissue to vinyl carbamate, a carcinogen from cigarette smoke, creates an in vitro model of lung cancer premalignancy. Hydrogel formulations are selected to promote early lung cancer cellular phenotypes and extend PCLS viability to six weeks. Hydrogel-embedded PCLS are exposed to vinyl carbamate, which induces adenocarcinoma in mice. Analysis of proliferation, gene expression, histology, tissue stiffness, and cellular content after six weeks reveals that vinyl carbamate induces premalignant lesions with a mixed adenoma/squamous phenotype. Putative chemoprevention agents diffuse through the hydrogel and induce tissue-level changes. The design parameters selected using murine tissue are validated with hydrogel-embedded human PCLS and results show increased proliferation and premalignant lesion gene expression patterns. This tissue-engineered model of human lung cancer premalignancy is the foundation for more sophisticated ex vivo models that enable the study of carcinogenesis and chemoprevention strategies.

Current status of National Institutes of Health funding for thoracic surgeons in the United States: Beacon of hope or candle in the wind?

OBJECTIVE

Increasing forces threaten the viability of thoracic surgeon-initiated research, a core component of our academic mission. National Institutes of Health funding is a benchmark of research productivity and innovation. This study examined the current status of National Institutes of Health funding for thoracic surgeons.

METHODS

Thoracic surgeon principal investigators on National Institutes of Health-funded grants during June 2010, June 2015, and June 2020 were identified using National Institutes of Health iSearchGrants (version 2.4). American Association of Medical Colleges data were used to identify all surgeons in the United States. Types and total costs of National Institutes of Health-funded grants were compared relative to other surgical specialties.

RESULTS

A total of 61 of 4681 (1.3%), 63 of 4484 (1.4%), and 60 of 4497 (1.3%) thoracic surgeons were principal investigators on 79, 76, and 87 National Institutes of Health-funded grants in 2010, 2015, and 2020, respectively; these rates were higher than those for most other surgical specialties (P ≤ .0001). Total National Institutes of Health costs for Thoracic Surgeon-initiated grants increased 57% from 2010 to 2020, outpacing the 33% increase in total National Institutes of Health budget. Numbers and types of grants varied among cardiovascular, transplant, and oncology subgroups. Although the majority of grants and costs were cardiovascular related, increased National Institutes of Health expenditures primarily were due to funding for transplant and oncology grants. Per-capita costs were highest for transplant-related grants during both years. Percentages of R01-to-total costs were constant at 55%. Rates and levels of funding for female versus male thoracic surgeons were comparable. Awards to 5 surgeons accounted for 33% of National Institutes of Health costs for thoracic surgeon principal investigators in 2020; a similar phenomenon was observed for 2010 and 2015.

CONCLUSIONS

Long-term structural changes must be implemented to more effectively nurture the next generation of thoracic surgeon scientists.

Predicting the pathological invasiveness in patients with a solitary pulmonary nodule via Shapley additive explanations interpretation of a tree-based machine learning radiomics model: a multicenter study

Background

Radiomics models could help assess the benign and malignant invasiveness and prognosis of pulmonary nodules. However, the lack of interpretability limits application of these models. We thus aimed to construct and validate an interpretable and generalized computed tomography (CT) radiomics model to evaluate the pathological invasiveness in patients with a solitary pulmonary nodule in order to improve the management of these patients.

Methods

We retrospectively enrolled 248 patients with CT-diagnosed solitary pulmonary nodules. Radiomic features were extracted from nodular region and perinodular regions of 3 and 5 mm. After coarse-to-fine feature selection, the radiomics score (radscore) was calculated using the least absolute shrinkage and selection operator logistic method. Univariate and multivariate logistic regression analyses were performed to determine the invasiveness-related clinicoradiological factors. The clinical-radiomics model was then constructed using the logistic and extreme gradient boosting (XGBoost) algorithms. The Shapley additive explanations (SHAP) method was then used to explain the contributions of the features. After removing batch effects with the ComBat algorithm, we assessed the generalization of the explainable clinical-radiomics model in two independent external validation cohorts (n=147 and n=149).

Results

The clinical-radiomic XGBoost model integrating the radscore, CT value, nodule length, and crescent sign demonstrated better predictive performance than did the clinical-radiomics logistic model in assessing pulmonary nodule invasiveness, with an area under the receiver operating characteristic (ROC) curve (AUC) of 0.889 [95% confidence interval (CI), 0.848-0.927] in the training cohort. The SHAP algorithm illustrates the contribution of each feature in the final model. The specific model decision process was visualized using a tree-based decision heatmap. Satisfactory generalization performance was shown with AUCs of 0.889 (95% CI, 0.823-0.942) and 0.915 (95% CI, 0.851-0.963) in the two external validation cohorts.

Conclusions

An interpretable and generalized clinical-radiomics model for predicting pulmonary nodule invasibility was constructed to help clinicians determine the invasiveness of pulmonary nodules and devise assessment strategies in an easily understandable manner.

TIMP1 is an early biomarker for detection and prognosis of lung cancer

BACKGROUND

Lung cancer remains the major cause of cancer-related deaths worldwide. Early stages of lung cancer are characterized by long asymptomatic periods that are ineffectively identified with the current screening programs. This deficiency represents a lost opportunity to improve the overall survival of patients. Serum biomarkers are among the most effective strategies for cancer screening and follow up.

METHODS

Using bead-based multiplexing assays we screened plasma and tumours of the KrasG12D/+; Lkb1f/f (KL) mouse model of lung cancer for cytokines that could be used as biomarkers. We identified tissue inhibitor of metalloproteinase 1 (TIMP1) as an early biomarker and validated this finding in the plasma of lung cancer patients. We used immunohistochemistry (IHC), previously published single-cell RNA-seq and bulk RNA-seq data to assess the source and expression of TIMP1in the tumour. The prognostic value of TIMP1 was assessed using publicly available human proteomic and transcriptomic databases.

RESULTS

We found that TIMP1 is a tumour-secreted protein with high sensitivity and specificity for aggressive cancer, even at early stages in mice. We showed that TIMP1 levels in the tumour and serum correlate with tumour burden and worse survival in mice. We validated this finding using clinical samples from our institution and publicly available human proteomic and transcriptomic databases. These data support the finding that high tumour expression of TIMP1 correlates with an unfavorable prognosis in lung cancer patients.

CONCLUSION

TIMP1 is a suitable biomarker for lung cancer detection.

Exosome nanovesicles as potential biomarkers and immune checkpoint signaling modulators in lung cancer microenvironment: recent advances and emerging concepts

Lung cancer remains the leading cause of cancer-related deaths globally, and the survival rate remains low despite advances in diagnosis and treatment. The progression of lung cancer is a multifaceted and dynamic phenomenon that encompasses interplays among cancerous cells and their microenvironment, which incorporates immune cells. Exosomes, which are small membrane-bound vesicles, are released by numerous cell types in normal and stressful situations to allow communication between cells. Tumor-derived exosomes (TEXs) possess diverse neo-antigens and cargoes such as proteins, RNA, and DNA and have a unique molecular makeup reflecting tumor genetic complexity. TEXs contain both immunosuppressive and immunostimulatory factors and may play a role in immunomodulation by influencing innate and adaptive immune components. Moreover, they transmit signals that contribute to the progression of lung cancer by promoting metastasis, epithelial-mesenchymal transition (EMT), angiogenesis, and immunosuppression. This makes them a valuable resource for investigating the immune environment of tumors, which could pave the way for the development of non-invasive biomarkers that could aid in the prognosis, diagnosis, and immunotherapy of lung cancer. While immune checkpoint inhibitor (ICI) immunotherapy has shown promising results in treating initial-stage cancers, most patients eventually develop adaptive resistance over time. Emerging evidence demonstrates that TEXs could serve as a prognostic biomarker for immunotherapeutic response and have a significant impact on both systemic immune suppression and tumor advancement. Therefore, understanding TEXs and their role in lung cancer tumorigenesis and their response to immunotherapies is an exciting research area and needs further investigation. This review highlights the role of TEXs as key contributors to the advancement of lung cancer and their clinical significance in lung immune-oncology, including their possible use as biomarkers for monitoring disease progression and prognosis, as well as emerging shreds of evidence regarding the possibility of using exosomes as targets to improve lung cancer therapy.

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

BACKGROUND

Ground-glass opacity (GGO)-like lung adenocarcinoma (LUAD) has been detected increasingly in the clinic and its inert property and superior survival indicate unique biological characteristics. However, we do not know much about them, which hampers identification of key reasons for the inert property of GGO-like LUAD.

METHODS

Using whole-exome sequencing and RNA sequencing, taking into account both radiological and pathological classifications of the same 197 patients concomitantly, we systematically interrogate genes driving the progression from GGO to solid nodule and potential reasons for the inertia of GGO. Using flow cytometry and IHC, we validated the abundance of immune cells and activity of cell proliferation.

FINDINGS

Identifying the differences between GGO and solid nodule, we found adenocarcinoma in situ/minimally invasive adenocarcinoma (AIS/MIA) and GGO-like LUAD exhibited lower TP53 mutation frequency and less active cell proliferation-related pathways than solid nodule in LUAD. Identifying the differences in GGO between AIS/MIA and LUAD, we noticed that EGFR mutation frequency and CNV load were significantly higher in LUAD than in AIS/MIA. Regulatory T cell was also higher in LUAD, while CD8+ T cell decreased from AIS/MIA to LUAD. Finally, we constructed a transcriptomic signature to quantify the development from GGO to solid nodule, which was an independent predictor of patients' prognosis in 11 external LUAD datasets.

INTERPRETATION

Our results provide deeper insights into the indolent nature of GGO and provide a molecular basis for the treatment of GGO-like LUAD.

FUNDING

This study was supported in part by the National Natural Science Foundation of China (32170657), the National Natural Science Foundation of China (82203037), and Shanghai Sailing Program (22YF1408900).

Volume imaging to interrogate cancer cell-tumor microenvironment interactions in space and time

Volume imaging visualizes the three-dimensional (3D) complexity of tumors to unravel the dynamic crosstalk between cancer cells and the heterogeneous landscape of the tumor microenvironment (TME). Tissue clearing and intravital microscopy (IVM) constitute rapidly progressing technologies to study the architectural context of such interactions. Tissue clearing enables high-resolution imaging of large samples, allowing for the characterization of entire tumors and even organs and organisms with tumors. With IVM, the dynamic engagement between cancer cells and the TME can be visualized in 3D over time, allowing for acquisition of 4D data. Together, tissue clearing and IVM have been critical in the examination of cancer-TME interactions and have drastically advanced our knowledge in fundamental cancer research and clinical oncology. This review provides an overview of the current technical repertoire of fluorescence volume imaging technologies to study cancer and the TME, and discusses how their recent applications have been utilized to advance our fundamental understanding of tumor architecture, stromal and immune infiltration, vascularization and innervation, and to explore avenues for immunotherapy and optimized chemotherapy delivery.

Tumor Microenvironmental Cytokines Drive NSCLC Cell Aggressiveness and Drug-Resistance via YAP-Mediated Autophagy

Dynamic reciprocity between cellular components of the tumor microenvironment and tumor cells occurs primarily through the interaction of soluble signals, i.e., cytokines produced by stromal cells to support cancer initiation and progression by regulating cell survival, differentiation and immune cell functionality, as well as cell migration and death. In the present study, we focused on the analysis of the functional response of non-small cell lung cancer cell lines elicited by the treatment with some crucial stromal factors which, at least in part, mimic the stimulus exerted in vivo on tumor cells by microenvironmental components. Our molecular and functional results highlight the role played by the autophagic machinery in the cellular response in terms of the invasive capacity, stemness and drug resistance of two non-small lung cancer cell lines treated with stromal cytokines, also highlighting the emerging role of the YAP pathway in the mutual and dynamic crosstalk between tumor cells and tumor microenvironment elements. The results of this study provide new insights into the YAP-mediated autophagic mechanism elicited by microenvironmental cytokines on non-small cell lung cancer cell lines and may suggest new potential strategies for future cancer therapeutic interventions.

Tissue-engineered models of lung cancer premalignancy

Lung cancer is the leading global cause of cancer-related deaths. Although smoking cessation is the best preventive action, nearly 50% of all lung cancer diagnoses occur in people who have already quit smoking. Research into treatment options for these high-risk patients has been constrained to rodent models of chemical carcinogenesis, which are time-consuming, expensive, and require large numbers of animals. Here we show that embedding precision-cut lung slices within an engineered hydrogel and exposing this tissue to a carcinogen from cigarette smoke creates an in vitro model of lung cancer premalignancy. Hydrogel formulations were selected to promote early lung cancer cellular phenotypes and extend PCLS viability up to six weeks. In this study, hydrogel-embedded lung slices were exposed to the cigarette smoke derived carcinogen vinyl carbamate, which induces adenocarcinoma in mice. At six weeks, analysis of proliferation, gene expression, histology, tissue stiffness, and cellular content revealed that vinyl carbamate induced the formation of premalignant lesions with a mixed adenoma/squamous phenotype. Two putative chemoprevention agents were able to freely diffuse through the hydrogel and induce tissue-level changes. The design parameters selected using murine tissue were validated with hydrogel-embedded human PCLS and results showed increased proliferation and premalignant lesion gene expression patterns. This tissue-engineered model of human lung cancer premalignancy is the starting point for more sophisticated ex vivo models and a foundation for the study of carcinogenesis and chemoprevention strategies.

Expression of PD-L1 through evolution phase from pre-invasive to invasive lung adenocarcinoma

BACKGROUND

This study evaluated programmed cell death-ligand 1 (PD-L1) expression from pre-invasive adenocarcinoma to invasive lung adenocarcinoma, aimed to investigate the potential association of PD-L1 pathway with lung adenocarcinoma early evolution.

METHODS

We evaluated PD-L1 expression in 1123 resected lung specimens of adenocarcinoma in situ (AIS), minimally invasive adenocarcinoma (MIA) and invasive adenocarcinoma (IAC) of stage IA1-IA3. PD-L1 expression was defined based on the proportion of stained tumor cells using the tumor proportion score:  < 1% (negative),  ≥ 1% (positive) and  ≥ 50% (strongly positive). Correlations between PD-L1 expression and T stage, pathological subtype, adenocarcinoma grade, spread through air space (STAS), vascular invasion, lymphatic invasion and driven genes were analyzed.

RESULTS

There was almost no PD-L1 expression in AIS or MIA. However, PD-L1 expression was correlated with invasiveness of lung adenocarcinoma. The percentages of PD-L1 positive in IA1-IA3 were 7.22%, 11.29%, and 14.20%, respectively. The strongly positive rates of PD-L1 were 0.38%, 1.64%, and 3.70% in IA1-IA3, respectively. PD-L1 expression and positive rate were also associated with poor pathological subtype and poor biological behavior, such as adenocarcinoma Grade 3, micropapillary or solid dominant subtype, STAS and vascular invasion. Finally, PD-L1 positive rate seems also corrected with driven gene ALK, ROS-1 and KRAS.

CONCLUSIONS

PD-L1 expression was positively correlated with the emergence of invasiveness and poor pathological subtype or biological behavior of early-stage lung adenocarcinoma. PD-L1 pathway may be involved in the early evolution of lung adenocarcinoma from AIS to IAC.

Tumor-intrinsic IRE1α signaling controls protective immunity in lung cancer

IRE1α-XBP1 signaling is emerging as a central orchestrator of malignant progression and immunosuppression in various cancer types. Employing a computational XBP1s detection method applied to TCGA datasets, we demonstrate that expression of the XBP1s mRNA isoform predicts poor survival in non-small cell lung cancer (NSCLC) patients. Ablation of IRE1α in malignant cells delays tumor progression and extends survival in mouse models of NSCLC. This protective effect is accompanied by alterations in intratumoral immune cell subsets eliciting durable adaptive anti-cancer immunity. Mechanistically, cancer cell-intrinsic IRE1α activation sustains mPGES-1 expression, enabling production of the immunosuppressive lipid mediator prostaglandin E2. Accordingly, restoring mPGES-1 expression in IRE1αKO cancer cells rescues normal tumor progression. We have developed an IRE1α gene signature that predicts immune cell infiltration and overall survival in human NSCLC. Our study unveils an immunoregulatory role for cancer cell-intrinsic IRE1α activation and suggests that targeting this pathway may help enhance anti-tumor immunity in NSCLC.

Toll-like receptor 2 orchestrates a tumor suppressor response in non-small cell lung cancer

Targeting early-stage lung cancer is vital to improve survival. However, the mechanisms and components of the early tumor suppressor response in lung cancer are not well understood. In this report, we study the role of Toll-like receptor 2 (TLR2), a regulator of oncogene-induced senescence, which is a key tumor suppressor response in premalignancy. Using human lung cancer samples and genetically engineered mouse models, we show that TLR2 is active early in lung tumorigenesis, where it correlates with improved survival and clinical regression. Mechanistically, TLR2 impairs early lung cancer progression via activation of cell intrinsic cell cycle arrest pathways and the proinflammatory senescence-associated secretory phenotype (SASP). The SASP regulates non-cell autonomous anti-tumor responses, such as immune surveillance of premalignant cells, and we observe impaired myeloid cell recruitment to lung tumors after Tlr2 loss. Last, we show that administration of a TLR2 agonist reduces lung tumor growth, highlighting TLR2 as a possible therapeutic target.