Genomic and immune profiling of pre-invasive lung adenocarcinoma

Comprehensive analysis of prognosis and tumor immune microenvironment of cuproptosis-related gene CDKN2A in lung adenocarcinoma

BACKGROUND

Recent research has increasingly highlighted the significance of various forms of cell death in contributing to tumor heterogeneity and modulating anti-tumor immunity. However, the potential implications of cuproptosis-related genes (CRGs) in lung adenocarcinoma (LUAD) remains poorly explored.

METHODS

We conducted a comprehensive analysis of the expression profiles of 19 CRGs in LUAD based on The Cancer Genome Atlas (TCGA). Utilizing consensus clustering, we stratified the TCGA cohort into two distinct LUAD subtypes (Cluster 1 and Cluster 2). The expression of CDKN2A was further validated across multiple datasets, including TCGA, GEO, Cancer Cell Line Encyclopedia (CCLE), and the Human Protein Atlas (HPA). The prognostic value of the CDKN2A was evaluated through univariate, multivariate, and survival analyses. Gene set enrichment analysis (GSEA) was performed to elucidate the molecular mechanisms associated with the CDKN2A. Additionally, we assessed the levels of immune cell infiltration in LUAD using the CIBERSORT, ESTIMATE, and XCELL algorithms.

RESULTS

By systematically analyzing the genetic alterations of 19 CRGs in LUAD, we found 15 differentially expressed genes between LUAD and adjacent normal tissues. Subsequently, using the consensus clustering method, we classified LUAD patients into two molecular subtypes and cluster 2 had a poor prognosis. CDKN2A emerged as a key gene of interest, exhibiting elevated expression in LUAD and correlating with adverse patient outcomes. Moreover, immunoinfiltration analysis revealed differential levels of immune cell infiltration between the CDKN2A high and CDKN2A low expression groups.

CONCLUSIONS

Our findings indicate that CDKN2A may serve as an effective prognostic biomarker for LUAD and may offer valuable insights into potential immunotherapeutic strategies for these patients.

CLINICAL TRIAL NUMBER

Not applicable.

p53 transcriptionally activates DCP1B to suppress tumor progression and enhance tumor sensitivity to PI3K blockade in non-small cell lung cancer

Non-small cell lung cancer (NSCLC), which accounts for approximately 85% of lung cancer patients, is characterized by its aggressive nature and poor prognosis. In this study, we identify decapping mRNA 1B (DCP1B) as a tumor suppressor gene that is transcriptionally regulated by p53. DCP1B is found to inhibit the growth and migration of NSCLC cells. Consistently, the level of DCP1B expression is decreased in NSCLC tissues, and its low expression is associated with NSCLC patients' unfavorable outcomes. Mechanistic investigations reveal that DCP1B promotes the turnover of mitogen-activated protein kinase 4 (MAPK4) mRNA, and the activation of p53 reduces the expression level of MAPK4 partially through DCP1B. Notably, overexpression of MAPK4 can drive AKT phosphorylation independent of phosphoinositide 3-kinase (PI3K), thus neutralizing the anti-tumor activity of the PI3K inhibitor in NSCLC cells. Moreover, the p53 agonist combined with the PI3K inhibitor can suppress NSCLC proliferation synergistically in vitro and in vivo. Collectively, this study not only uncovers the function and mechanism of the p53-DCP1B-MAPK4 axis in suppressing NSCLC progression but also suggests a promising combination strategy for treating NSCLC.

Amplified dosage of the NKX2-1 lineage transcription factor controls its oncogenic role in lung adenocarcinoma

Amplification-mediated oncogene overexpression is a critical and widespread driver event in cancer, yet our understanding of how amplification and dosage mediate oncogene regulation is limited. Here, we find that the most significant focal amplification event in lung adenocarcinoma (LUAD) targets a lineage "super-enhancer" near the NKX2-1 lineage transcription factor. The NKX2-1 super-enhancer is targeted by focal and co-amplification with NKX2-1 and controls NKX2-1 expression and regulation. We find that NKX2-1 directly controls enhancer accessibility to drive a lineage-addicted state in LUAD. We precisely map the effects of NKX2-1 dosage modulation upon both overexpression and knockdown and identify both linear and non-linear regulation by NKX2-1 dosage. We find that NKX2-1 is a widespread dependency in LUAD cell lines and that NKX2-1 confers persistence to EGFR inhibitors. Our data suggest a defining role for dosage in the oncogenic regulation of amplified NKX2-1 and that amplified NKX2-1 lineage addiction defines LUAD tumors.

Identification of cellular senescence-associated genes for predicting the diagnosis, prognosis and immunotherapy response in lung adenocarcinoma via a 113-combination machine learning framework

BACKGROUND

Lung adenocarcinoma (LUAD) is a prevalent malignant tumor of the respiratory system, with high incidence and mortality rates. Cellular senescence (CS) widely affects the tumor microenvironment (TME) and tumor growth, and is related to the invasion and immune escape of tumor cells. This study aims to develop a robust CS-related signature of LUAD.

METHODS

Using the GSE140797, GSE42458, GSE75037, and GSE85841 datasets, in combination with cellular senescence databases, 75 LUAD CS-related differentially expressed genes (LUAD-CSDEGs) were identified through the weighted gene co-expression network analysis (WGCNA) method. Subsequently, we developed a novel machine learning framework that incorporated 12 machine learning algorithms and their 113 combinations to construct a LUAD CS-related signature (LUAD-CSRS), which were assessed in both training and validation cohorts. A LUAD-CSRS-integrated nomogram was constructed to provide a quantitative tool for predicting prognosis in clinical practice. Finally, the difference of immune infiltration and response to immunotherapy in patients with high and low risk of LUAD were evaluated.

RESULTS

Based on a 113-combination machine learning framework, we finally identified a LUAD-CSRS containing eight genes: RECQL4, TIMP1, ANLN, SFN, MDK, KIF2C, AGR2, ITGB4. We also confirmed that it was significantly associated with survival, immune cell infiltration, prognosis, and response to immunotherapy in LUAD patients. Additionally, we found it is related to the activation of immune responses and may be involved in regulating the balance between immune cells in the TME.

CONCLUSION

In summary, our study constructed a novel LUAD-CSRS, which is not only expected to be a powerful tool for assisting diagnosis and prognosis evaluation of LUAD, but also may provide guidance for personalized immunotherapy programs.

Proteogenomic characterization reveals tumorigenesis and progression of lung cancer manifested as subsolid nodules

Lung adenocarcinoma (LUAD) radiologically displayed as subsolid nodules (SSNs) is prevalent. Nevertheless, the precise clinical management of SSNs necessitates a profound understanding of their tumorigenesis and progression. Here, we analyze 66 LUAD displayed as SSNs covering 3 histological stages including adenocarcinoma in situ (AIS), minimally invasive adenocarcinoma (MIA) and invasive adenocarcinoma (IAC) by incorporating genomics, proteomics, phosphoproteomics and glycoproteomics. Intriguingly, cholesterol metabolism is aberrantly regulated in the preneoplastic AIS stage. Importantly, target ablation of proprotein convertase subtilisin/kexin type 9 (PCSK9) promotes the initiation of LUAD. Furthermore, sustained endoplasmic reticulum stress is demonstrated to be a hallmark and a reliable biomarker of AIS progression to IAC. Consistently, target promotion of ER stress profoundly retards LUAD progression. Our study provides comprehensive proteogenomic landscape of SSNs, sheds lights on the tumorigenesis and progression of SSNs and suggests preventive and therapeutic strategies for LUAD.

CENPF (+) cancer cells promote malignant progression of early-stage TP53 mutant lung adenocarcinoma

The prevention and precise treatment of early-stage lung adenocarcinoma (LUAD) characterized by small nodules (stage IA) remains a significant challenge for clinicians, which is due largely to the limited understanding of the oncogenic mechanisms spanning from preneoplasia to invasive adenocarcinoma. Our study highlights the pivotal role of cancer cells exhibiting high expression of centromere protein F (CENPF), driven by TP53 mutations, which become increasingly prevalent during the transition from preneoplasia to invasive LUAD. Biologically, cancer cells (CENPF+) exhibited robust proliferative and stem-like capabilities, thereby propelling the malignant progression of early-stage LUAD. Clinically, autoantibodies against CENPF in the serum and elevated cancer cells (CENPF+) in tissue correlated positively with the progression of early-stage LUAD, especially those in stage IA. Our findings suggest that cancer cells (CENPF+) play a central role in orchestrating the malignant evolution of LUAD and hold potential as a novel biomarker for early-stage detection and management of the disease.

Molecular subtyping of stage I lung adenocarcinoma via molecular alterations in pre-invasive lesion progression

BACKGROUND

Patients with adenocarcinoma in situ (AIS) and minimally invasive (MIA) lung adenocarcinoma (LUAD) are curable by surgery, whereas 20% stage I patients die within five years after surgery. We hypothesize that poor-prognosis stage I patients may exhibit key molecular characteristics deviating from AIS/MIA. Therefore, we tried to reveal molecularly and prognostically distinct subtypes of stage I LUAD by applying key molecular alterations from AIS/MIA to invasive LUAD progression.

METHODS

The RNA and whole-exome sequencing data of 197 tumor-normal matched samples from patients with AIS, MIA, and invasive LUAD were analyzed. ddPCR quantified 202 samples from 182 patients at the absolute expression level. Immunohistochemical quantified the protein expression levels of ACTA2. RNA-seq data from 954 LUAD patients, including 541 stage I patients, along with 12 published datasets comprising 1,331 stage I LUAD patients, were used to validate our findings.

RESULTS

Focal adhesion (FA) was identified as the only pathway significantly perturbed at both genomic and transcriptomic levels by comparing 98 AIS/MIA and 99 LUAD. Then, two FA genes (COL11A1 and THBS2) were found strongly upregulated from AIS/MIA to stage I while steadily expressed from normal to AIS/MIA. Furthermore, unsupervised clustering separated stage I patients into two molecularly and prognostically distinct subtypes (S1 and S2) based on COL11A1 and THBS2 expressions (FA2). Subtype S1 resembled AIS/MIA, whereas S2 exhibited more somatic alterations and activated cancer-associated fibroblast. Immunohistochemistry on 73 samples also observed that CAF was more active in S2 compared to S1 and AIS/MIA. The prognostic value of these two genes identified from our knowledge-driven process was confirmed by 541 stage I patients in a prospective dataset, ddPCR and 12 published datasets.

CONCLUSIONS

We successfully revealed two molecularly and prognostically distinct subtypes of stage I LUAD by applying key molecular alterations from AIS/MIA to invasive LUAD progression. Our model may help reliably identify high-risk stage I patients for more intensive post-surgery treatment.

Translating premalignant biology to accelerate non-small-cell lung cancer interception

Over the past decade, substantial progress has been made in the development of targeted and immune-based therapies for patients with advanced non-small-cell lung cancer. To further improve outcomes for patients with lung cancer, identifying and intercepting disease at the earliest and most curable stages are crucial next steps. With the recent implementation of low-dose computed tomography scan screening in populations at high risk, there is an emerging unmet need for new diagnostic, prognostic and therapeutic tools to help treat patients suspected of harbouring premalignant lesions and minimally invasive non-small-cell lung cancer. Continued advances in the identification of the earliest drivers of lung carcinogenesis are poised to address these unmet needs. Employing multimodal approaches to chart the temporal and spatial maps of the molecular events driving lung premalignant lesion progression will refine our understanding of early carcinogenesis. Elucidating the molecular drivers of premalignancy is critical to the development of biomarkers to detect those incubating a premalignant lesion, to stratify risk for progression to invasive cancer and to identify novel therapeutic targets to intercept that process. In this Review, we summarize emerging insights into the earliest cellular and molecular events associated with lung squamous and adenocarcinoma carcinogenesis and highlight the growing opportunity for translating these insights into clinical tools for early detection and disease interception to transform the outcomes for those at risk for lung cancer.

Pulmonary enteric adenocarcinoma with progression disease after second - line therapy: a case report

Pulmonary enteric adenocarcinoma (PEAC, also known as Enteric-type adenocarcinoma of the lung, lung - ETAC) is a rare subtype of non-small cell lung cancer (NSCLC) that has the same morphological and immunohistochemical characteristics as colorectal adenocarcinoma and requires gastroenteroscopy to rule out lesions of enteric origin. As a rare solid tumor in lung cancer, PEAC has unique clinical outcome, imaging, pathological and molecular characteristics, and poor prognosis. However, the molecular characteristics and therapeutic biomarkers of PEAC are unclear, and its treatment remains challenging. In this case, we describe a 61-year-old man diagnosed with advanced primary PEAC with KRAS mutation. In the case of unknown PD-L1 expression status, first-line treatment was given to lung adenocarcinoma regimen (immunotherapy combined with chemotherapy), progression occurred after 2 cycles, and progression-free survival (PFS) was 1.5 months. Then the second-line XELOX regimen (oxaliplatin combined with capecitabine) was adjusted. The lesions were significantly reduced after 2 and 4 cycles, and the disease progressed again after 6 cycles, with a PFS of 4.5 months. Anlotinib targeted drugs were selected for third-line treatment, but considering the overall poor condition of the patient, the patient himself refused further treatment. Finally, after discharge, the patient went to the local hospital for nutritional support and symptomatic treatment. The results suggest that standard first-line therapies (immunotherapy plus chemotherapy) and colorectal cancer regimens may have a relatively limited impact on survival in KRAS-driver positive advanced PEAC.

Highly proliferating cancer cells function as novel prognostic biomarkers for lung adenocarcinoma with particular usefulness for stage IA risk stratification

BACKGROUND

The refinement of risk stratification in lung adenocarcinoma (LUAD) plays a pivotal role in advancing precision medicine; however, the current staging classification falls short of comprehensiveness, particularly in the case of stage IA patients. We aimed to molecularly stratify LUAD patients especially for stage IA.

METHODS

We analysed tumour heterogeneity and identified highly proliferating cancer cells (HPCs) in LUAD by performing single-cell RNA sequencing (scRNA-seq) analysis, immunohistochemical (IHC) staining using a tissue microarray, flow cytometry and biological experiments. Then, we quantified the content of HPCs in nine LUAD datasets by single-sample gene set enrichment analysis and evaluated the relationship between the percentage of HPCs and overall survival (OS). Next, we analysed the OS predictive effect of HPCs at different LUAD stages, especially for stage I risk stratification. Furthermore, we established a prognostic prediction model based on HPC-associated genes for clinical application. The above findings were validated in another five LUAD datasets. Finally, we explored the relationship between HPCs and the progressive pathological evolution of early-stage LUAD and the driving mutations by scRNA-seq, bulk RNA-seq and IHC staining.

RESULTS

LUAD tissues carry a small proportion of HPCs, which show potential for malignant proliferation and intense interactions with the microenvironment. A high HPC content is an independent risk factor for OS in LUAD patients, even in stage IA patients. HPCs can be used to establish a cut-off point for the prognosis of stage IA disease, with patients with a higher risk showing a prognosis similar to that of patients with stage IB disease. We built an R package (HSurADs) based on HPC-associated genes, which exhibited good efficacy for the prognostic prediction of LUAD. HPCs gradually increase with the pathological evolution of early-stage LUAD, which may be affected by TP53 mutations.

CONCLUSION

The HPC content can be used as a novel prognostic factor for LUAD, especially for stage IA risk stratification.

Acquisition of discrete immune suppressive barriers contributes to the initiation and progression of preinvasive to invasive human lung cancer

Computerized chest tomography (CT)-guided screening in populations at risk for lung cancer has increased the detection of preinvasive subsolid nodules, which progress to solid invasive adenocarcinoma. Despite the clinical significance, there is a lack of effective therapies for intercepting the progression of preinvasive to invasive adenocarcinoma. To uncover determinants of early disease emergence and progression, we used integrated single-cell approaches, including scRNA-seq, multiplexed imaging mass cytometry and spatial transcriptomics, to construct the first high-resolution map of the composition, lineage/functional states, developmental trajectories and multicellular crosstalk networks from microdissected non-solid (preinvasive) and solid compartments (invasive) of individual part-solid nodules. We found that early disease initiation and subsequent progression are associated with the evolution of immune-suppressive cellular phenotypes characterized by decreased cytotoxic CD8 T and NK cells, increased T cell exhaustion and accumulation of immunosuppressive regulatory T cells (Tregs) and M2-like macrophages expressing TREM2. Within Tregs, we identified a unique population of 4-1BB+ Treg subset enriched for the IL2-STAT5 suppressive pathway with transcription profiles supporting discrete metabolic alterations. Spatial analysis showed increased density of suppressive immune cells around tumor cells, increased exhaustion phenotype of both CD4 and CD8 T cells expressing chemokine CXCL13, and spatial microcomplex of endothelial and lymphocyte interactions within tertiary lymphoid structures. The single-cell architecture identifies determinants of early disease emergence and progression, which may be developed not only as diagnostic/prognostic biomarkers but also as targets for disease interception. Additionally, our dataset constitutes a valuable resource for the preinvasive lung cancer research community.

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.

Multimodal integration to identify the invasion status of lung adenocarcinoma intraoperatively

Evaluating the invasiveness of lung adenocarcinoma is crucial for determining the appropriate surgical strategy, impacting postoperative outcomes. This study developed a multimodality model combining radiomics, intraoperative frozen section (FS) pathology, and clinical indicators to predict invasion status. The study enrolled 1,424 patients from two hospitals, divided into multimodal training, radiology testing, and pathology testing cohorts. A prospective validation cohort of 114 patients was selected between March and May 2023. The radiomics + pathology + clinical indicators multimodality model (multi-RPC model) achieved an area under the curve (AUC) of 0.921 (95% confidence interval [CI] 0.899-0.939) in the multimodal training cohort and 0.939 (95% CI 0.878-0.975) in the validation cohort, outperforming single- and dual-modality models. The multi-RPC model's predictive accuracy of 0.860 (95% CI 0.782-0.918) suggests that it could significantly reduce inappropriate surgical procedures, enhancing precision oncology by integrating multimodal information to guide surgical decisions.

In silico neoantigen screening and HLA multimer-based validation identify immunogenic neopeptide in multifocal lung adenocarcinoma

Background

Mutations commonly occur in cancer cells, arising neoantigen as potential targets for personalized immunotherapy of lung adenocarcinoma (LUAD). However, the substantial heterogeneity observed among individuals and distinct foci within the same patient presents significant challenges in formulating immunotherapy strategies. The aim of the work is to characterize the mutation pattern and identify neopeptides across different patients and diverse foci within the same patients with LUAD.

Methods

Seven lung adenocarcinoma samples and matched tissues/blood are collected from 4 patients with LUAD for whole exome sequencing, mutation signature analysis, HLA binding prediction and neoantigen screening. Dimeric HLA-A2 molecules were prepared by Bac-to-Bac baculovirus expression system to establish a T cell stimulation system based on HLA-A2-coated artificial antigen-presenting cells for the validation of immunogenic neopeptides.

Results

Similar mutation pattern with predominant missense mutation and high tumor mutation burden was observed across individuals with lung adenocarcinomas and between non-invasive and invasive foci. We screened and identified 3 consistent mutated genes among 100 top genes with highest mutation scores contributed across 4 patients, and 3 mutated peptides among 30 with highest HLA-A2 binding affinity distributed in at least 2 out of 4 foci in the same patient. Notably, LUAD-7-MT peptide encoded by NANOGNB demonstrated higher immunogenicity in promoting CD8+ T cells proliferation and IFN-γ secretion than the corresponding wildtype peptide.

Conclusions

This study provides an in-depth analysis of mutation characteristics of LUAD and establishes a neoantigen screening and validation system for identifying immunogenicity neopeptide across individual patients and diverse foci in the same patient with multifocal LUAD.

Genomic Landscape Features of Minimally Invasive Adenocarcinoma and Invasive Lung Adenocarcinoma

Background  The widespread implementation of computed tomography has significantly increased the detection of small pulmonary nodules, including atypical adenomatous hyperplasia, minimally invasive adenocarcinoma (MIA), and invasive adenocarcinoma (IAC). Few studies have focused on the genomic differences between MIA and IAC. Methods  We retrospectively analyzed patients with lung adenocarcinoma (LUAD) who underwent surgery from January 2020 to December 2023. Patients were categorized into MIA and IAC groups. The mutation status of common driver genes was assessed using next-generation sequencing. Results  A total of 422 LUAD patients were included in the study, comprising 119 MIA cases and 303 IAC cases. MIA patients were younger and predominantly female compared with IAC patients. EGFR mutations were detected in 251 patients (59.5%), with the frequency of EGFR mutations increasing from 37.0% in MIA to 68.3% in IAC ( p  < 0.001). TP53 mutations were found in 108 patients (25.6%), with 7 patients (5.9%) in MIA and 101 patients (33.3%) in IAC ( p  < 0.001). ERBB2 mutations were identified in 23 MIA patients (19.3%) and 20 IAC patients (6.6%) ( p  < 0.001). Additionally, CDKN2A mutations were detected in 23 IAC patients (7.6%), while no mutations in this gene were found in the MIA group. Moreover, ALK and RET gene fusions were identified in 11 patients, respectively. Conclusion  ERBB2 mutations and RET fusions are early genomic events in LUAD, while TP53 and CDKN2A mutations and ALK fusions occur later. Genomic intratumor heterogeneity likely arises early, before invasive characteristics develop.

Identification of histopathological classification and establishment of prognostic indicators of gastric adenocarcinoma based on deep learning algorithm

The aim of this study is to establish a deep learning (DL) model to predict the pathological type of gastric adenocarcinoma cancer based on whole-slide images(WSIs). We downloaded 356 histopathological images of gastric adenocarcinoma (STAD) patients from The Cancer Genome Atlas database and randomly divided them into the training set, validation set and test set (8:1:1). Additionally, 80 H&E-stained WSIs of STAD were collected for external validation. The CLAM tool was used to cut the WSIs and further construct the model by DL algorithm, achieving an accuracy of over 90% in identifying and predicting histopathological subtypes. External validation results demonstrated the model had a certain generalization ability. Moreover, DL features were extracted from the model to further investigate the differences in immune infiltration and patient prognosis between the two subtypes. The DL model can accurately predict the pathological classification of STAD patients, and provide certain reference value for clinical diagnosis. The nomogram combining DL-signature, gene-signature and clinical features can be used as a prognostic classifier for clinical decision-making and treatment.

Defining precancer: a grand challenge for the cancer community

The term 'precancer' typically refers to an early stage of neoplastic development that is distinguishable from normal tissue owing to molecular and phenotypic alterations, resulting in abnormal cells that are at least partially self-sustaining and function outside of normal cellular cues that constrain cell proliferation and survival. Although such cells are often histologically distinct from both the corresponding normal and invasive cancer cells of the same tissue origin, defining precancer remains a challenge for both the research and clinical communities. Once sufficient molecular and phenotypic changes have occurred in the precancer, the tissue is identified as a 'cancer' by a histopathologist. While even diagnosing cancer can at times be challenging, the determination of invasive cancer is generally less ambiguous and suggests a high likelihood of and potential for metastatic disease. The 'hallmarks of cancer' set out the fundamental organizing principles of malignant transformation but exactly how many of these hallmarks and in what configuration they define precancer has not been clearly and consistently determined. In this Expert Recommendation, we provide a starting point for a conceptual framework for defining precancer, which is based on molecular, pathological, clinical and epidemiological criteria, with the goal of advancing our understanding of the initial changes that occur and opportunities to intervene at the earliest possible time point.

Unraveling the immune landscape of lung adenocarcinoma: insights for tailoring therapeutic approaches

Lung adenocarcinoma (LUAD), a prevalent type of non-small cell lung cancer (NSCLC), was known for its diversity and intricate tumor microenvironment (TME). Comprehending the interaction among human immune-related genes (IRGs) and the TME is vital in the creation of accurate predictive models and specific treatments. We created a risk score based on IRGs and designed a nomogram to predict the prognosis of LUAD accurately. This involved a thorough examination of TME and the infiltration of immune cells in both high-risk and low-risk LUAD groups. Furthermore, the examination of the association between characteristic genes (BIRC5 and BMP5) and immune cells, along with immune checkpoints in the TME, was also conducted. The findings of our research unveiled unique immune profiles and interactions among individuals in the high- and low-risk categories, which contribute to variations in prognosis. LUAD demonstrated significant associations between BIRC5, BMP5, immune cells, and checkpoints, suggesting their involvement in disease advancement and resistance to medication. Furthermore, by correlating our findings with a multidrug database, we identified specific LUAD patient subsets that might benefit from tailored treatments. Our study establishes a groundbreaking prognostic model for LUAD, which not only underscores the importance of the immune context in LUAD but also paves the way for advancing precision medicine strategies in this complex malignancy.

Genomic and immune heterogeneity of multiple synchronous lung adenocarcinoma at different developmental stages

Multiple synchronous lung cancers (MSLCs) constitute a unique subtype of lung cancer. To explore the genomic and immune heterogeneity across different pathological stages of MSLCs, we analyse 16 MSLCs from 8 patients using single-cell RNA-seq, single-cell TCR sequencing, and bulk whole-exome sequencing. Our investigation indicates clonally independent tumours with convergent evolution driven by shared driver mutations. However, tumours from the same individual exhibit few shared mutations, indicating independent origins. During the transition from pre-invasive to invasive adenocarcinoma, we observe a shift in T cell phenotypes characterized by increased Treg cells and exhausted CD8+ T cells, accompanied by diminished cytotoxicity. Additionally, invasive adenocarcinomas exhibit greater neoantigen abundance and a more diverse TCR repertoire, indicating heightened heterogeneity. In summary, despite having a common genetic background and environmental exposure, our study emphasizes the individuality of MSLCs at different stages, highlighting their unique genomic and immune characteristics.

Lung cancer screening in never smokers

PURPOSE OF REVIEW

Low-dose computed tomography (LDCT) lung cancer screening has been established in smokers, but its role in never smokers remains unclear. The differences in lung cancer biology between smokers and nonsmokers highlight the importance of a discriminated approach. This overview focuses on the emerging data and implementation challenges for LDCT screening in nonsmokers.

RECENT FINDINGS

The first LDCT screening study in nonsmokers enriched with risk factors demonstrated a lung cancer detection rate double that of the phase 3 trials in smokers. The relative risk of lung cancer detected by LDCT has also been found to be similar amongst female never smokers and male ever smokers in Asia. Majority of lung cancers detected through LDCT screening are stage 0/1, leading to concerns of overdiagnosis. Risk prediction models to enhance individual selection and nodule management could be useful to enhance the utility of LDCT screening in never smokers.

SUMMARY

With appropriate risk stratification, LDCT screening in never smokers may attain similar efficacy as compared to smokers. A global effort is needed to generate evidence surrounding optimal screening strategies, as well as health and economic benefits to determine the suitability of widespread implementation.

Premalignant Progression in the Lung: Knowledge Gaps and Novel Opportunities for Interception of Non-Small Cell Lung Cancer. An Official American Thoracic Society Research Statement

Rationale: Despite significant advances in precision treatments and immunotherapy, lung cancer is the most common cause of cancer death worldwide. To reduce incidence and improve survival rates, a deeper understanding of lung premalignancy and the multistep process of tumorigenesis is essential, allowing timely and effective intervention before cancer development. Objectives: To summarize existing information, identify knowledge gaps, formulate research questions, prioritize potential research topics, and propose strategies for future investigations into the premalignant progression in the lung. Methods: An international multidisciplinary team of basic, translational, and clinical scientists reviewed available data to develop and refine research questions pertaining to the transformation of premalignant lung lesions to advanced lung cancer. Results: This research statement identifies significant gaps in knowledge and proposes potential research questions aimed at expanding our understanding of the mechanisms underlying the progression of premalignant lung lesions to lung cancer in an effort to explore potential innovative modalities to intercept lung cancer at its nascent stages. Conclusions: The identified gaps in knowledge about the biological mechanisms of premalignant progression in the lung, together with ongoing challenges in screening, detection, and early intervention, highlight the critical need to prioritize research in this domain. Such focused investigations are essential to devise effective preventive strategies that may ultimately decrease lung cancer incidence and improve patient outcomes.

Patterns of Aneuploidy and Signaling Consequences in Cancer

Aneuploidy, or a change in the number of whole chromosomes or chromosome arms, is a near-universal feature of cancer. Chromosomes affected by aneuploidy are not random, with observed cancer-specific and tissue-specific patterns. Recent advances in genome engineering methods have allowed the creation of models with targeted aneuploidy events. These models can be used to uncover the downstream effects of individual aneuploidies on cancer phenotypes including proliferation, apoptosis, metabolism, and immune signaling. Here, we review the current state of research into the patterns of aneuploidy in cancer and their impact on signaling pathways and biological processes.

Tuberculosis to lung cancer: application of tuberculosis signatures in identification of lung adenocarcinoma subtypes and marker screening

Background: There is an association between LUAD and TB, and TB increases the risk of lung adenocarcinogenesis. However, the role of TB in the development of lung adenocarcinoma has not been clarified. Methods: DEGs from TB and LUAD lung samples were obtained to identify TB-LUAD-shared DEGs. Consensus Clustering was performed on the TCGA cohort to characterize unique changes in TB transcriptome-derived lung adenocarcinoma subtypes. Prognostic models were constructed based on TB signatures to explore the characterization of subgroups. Finally, experimental validation and single-cell analysis of potential markers were performed. Results: We characterized three molecular subtypes with unique clinical features, cellular infiltration, and pathway change manifestations. We constructed and validated TB-related Signature in six cohorts. TB-related Signature has characteristic alterations, and can be used as an effective predictor of immunotherapy response. Prognostically relevant novel markers KRT80, C1QTNF6, and TRPA1 were validated by RT-qPCR. The association between KRT80 and lung adenocarcinoma disease progression was verified in Bulk transcriptome and single-cell transcriptome. Conclusion: For the first time, a comprehensive bioinformatics analysis of tuberculosis signatures was used to identify subtypes of lung adenocarcinoma. The TB-related Signature predicted prognosis and identified potential markers. This result reveals a potential pathogenic association of tuberculosis in the progression of lung adenocarcinoma.

Harnessing DNA replication stress to target RBM10 deficiency in lung adenocarcinoma

The splicing factor RNA-binding motif protein 10 (RBM10) is frequently mutated in lung adenocarcinoma (LUAD) (9-25%). Most RBM10 cancer mutations are loss-of-function, correlating with increased tumorigenesis and limiting the efficacy of current LUAD targeted therapies. Remarkably, therapeutic strategies leveraging RBM10 deficiency remain unexplored. Here, we conduct a CRISPR-Cas9 synthetic lethality (SL) screen and identify ~60 RBM10 SL genes, including WEE1 kinase. WEE1 inhibition sensitizes RBM10-deficient LUAD cells in-vitro and in-vivo. Mechanistically, we identify a splicing-independent role of RBM10 in regulating DNA replication fork progression and replication stress response, which underpins RBM10-WEE1 SL. Additionally, RBM10 interacts with active DNA replication forks, relying on DNA Primase Subunit 1 (PRIM1) that synthesizes Okazaki RNA primers. Functionally, we demonstrate that RBM10 serves as an anchor for recruiting Histone Deacetylase 1 (HDAC1) to facilitate H4K16 deacetylation and R-loop homeostasis to maintain replication fork stability. Collectively, our data reveal a role of RBM10 in fine-tuning DNA replication and provide therapeutic arsenal for targeting RBM10-deficient tumors.

Novel molecular subtypes of METex14 non-small cell lung cancer with distinct biological and clinical significance

Not all MET exon 14 skipping (METex14) NSCLC patients benefited from MET inhibitors. We hypothesized an inter-tumoral heterogeneity in METex14 NSCLC. Investigations at genomic and transcriptomic level were conducted in METex14 NSCLC samples from stage I-III and recurrent/metastatic patients as discovery and validation cohort. Four molecular subtypes were discovered. MET-Driven subtype, with the worst prognosis, displayed MET overexpression, enrichment of MET-related pathways, and higher infiltration of fibroblast and regulatory T cells. Immune-Activated subtype having the most idea long-term survival, had higher tertiary lymphoid structures, spatial co-option of PD-L1+ cancer cells, and GZMK+ CD8+ T cell. FGFR- and Bypass-Activated subtypes displayed FGFR2 overexpression and enrichments of multiple oncogenic pathways respectively. In the validation cohort, patients with MET-Driven subtype had better response to MET inhibitors than those with MET overexpression. Thus, molecular subtypes of METex14 NSCLC with distinct biological and clinical significance may indicate more precise therapeutic strategies for METex14 NSCLC patients.

Consensus clustering and novel risk score model construction based on m6A methylation regulators to evaluate the prognosis and tumor immune microenvironment of early-stage lung adenocarcinoma

BACKGROUND

The aim of this study was to investigate the correlation between m6A methylation regulators and cell infiltration characteristics in tumor immune microenvironment (TIME), so as to help understand the immune mechanism of early-stage lung adenocarcinoma (LUAD).

METHODS

The expression and consensus cluster analyses of m6A methylation regulators in early-stage LUAD were performed. The clinicopathological features, immune cell infiltration, survival and functional enrichment in different subtypes were analyzed. We also constructed a prognostic model. Clinical tissue samples were used to validate the expression of model genes through real-time polymerase chain reaction (RT-PCR). In addition, cell scratch assay and Transwell assay were also performed.

RESULTS

Expression of m6A methylation regulators was abnormal in early-stage LUAD. According to the consensus clustering of m6A methylation regulators, patients with early-stage LUAD were divided into two subtypes. Two subtypes showed different infiltration levels of immune cell and survival time. A prognostic model consisting of HNRNPC, IGF2BP1 and IGF2BP3 could be used to predict the survival of early-stage LUAD. RT-PCR results showed that HNRNPC, IGF2BP1 and IGF2BP3 were significantly up-regulated in early-stage LUAD tissues. The results of cell scratch assay and Transwell assay showed that overexpression of HNRNPC promotes the migration and invasion of NCI-H1299 cells, while knockdown HNRNPC inhibits the migration and invasion of NCI-H1299 cells.

CONCLUSIONS

This work reveals that m6A methylation regulators may be potential biomarkers for prognosis in patients with early-stage LUAD. Our prognostic model may be of great value in predicting the prognosis of early-stage LUAD.

Comprehensive analysis of PPP4C's impact on prognosis, immune microenvironment, and immunotherapy response in lung adenocarcinoma using single-cell sequencing and multi-omics

Background

Elevated PPP4C expression has been associated with poor prognostic implications for patients suffering from lung adenocarcinoma (LUAD). The extent to which PPP4C affects immune cell infiltration in LUAD, as well as the importance of associated genes in clinical scenarios, still requires thorough investigation.

Methods

In our investigation, we leveraged both single-cell and comprehensive RNA sequencing data, sourced from LUAD patients, in our analysis. This study also integrated datasets of immune-related genes from InnateDB into the framework. Our expansive evaluation employed various analytical techniques; these included pinpointing differentially expressed genes, constructing WGCNA, implementing Cox proportional hazards models. We utilized these methods to investigate the gene expression profiles of PPP4C within the context of LUAD and to clarify its potential prognostic value for patients. Subsequent steps involved validating the observed enhancement of PPP4C expression in LUAD samples through a series of experimental approaches. The array comprised immunohistochemistry staining, Western blotting, quantitative PCR, and a collection of cell-based assays aimed at evaluating the influence of PPP4C on the proliferative and migratory activities of LUAD cells.

Results

In lung cancer, elevated expression levels of PPP4C were observed, correlating with poorer patient prognoses. Validation of increased PPP4C levels in LUAD specimens was achieved using immunohistochemical techniques. Experimental investigations have substantiated the role of PPP4C in facilitating cellular proliferation and migration in LUAD contexts. Furthermore, an association was identified between the expression of PPP4C and the infiltration of immune cells in these tumors. A prognostic framework, incorporating PPP4C and immune-related genes, was developed and recognized as an autonomous predictor of survival in individuals afflicted with LUAD. This prognostic tool has demonstrated considerable efficacy in forecasting patient survival and their response to immunotherapeutic interventions.

Conclusion

The involvement of PPP4C in LUAD is deeply intertwined with the tumor's immune microenvironment. PPP4C's over-expression is associated with negative clinical outcomes, promoting both tumor proliferation and spread. A prognostic framework based on PPP4C levels may effectively predict patient prognoses in LUAD, as well as the efficacy of immunotherapy strategy. This research sheds light on the mechanisms of immune interaction in LUAD and proposes a new strategy for treatment.

Integrating machine learning and single-cell analysis to uncover lung adenocarcinoma progression and prognostic biomarkers

The progression of lung adenocarcinoma (LUAD) from atypical adenomatous hyperplasia (AAH) to invasive adenocarcinoma (IAC) involves a complex evolution of tumour cell clusters, the mechanisms of which remain largely unknown. By integrating single-cell datasets and using inferCNV, we identified and analysed tumour cell clusters to explore their heterogeneity and changes in abundance throughout LUAD progression. We applied gene set variation analysis (GSVA), pseudotime analysis, scMetabolism, and Cytotrace scores to study biological functions, metabolic profiles and stemness traits. A predictive model for prognosis, based on key cluster marker genes, was developed using CoxBoost and plsRcox (CPM), and validated across multiple cohorts for its prognostic prediction capabilities, tumour microenvironment characterization, mutation landscape and immunotherapy response. We identified nine distinct tumour cell clusters, with Cluster 6 indicating an early developmental stage, high stemness and proliferative potential. The abundance of Clusters 0 and 6 increased from AAH to IAC, correlating with prognosis. The CPM model effectively distinguished prognosis in immunotherapy cohorts and predicted genomic alterations, chemotherapy drug sensitivity, and immunotherapy responsiveness. Key gene S100A16 in the CPM model was validated as an oncogene, enhancing LUAD cell proliferation, invasion and migration. The CPM model emerges as a novel biomarker for predicting prognosis and immunotherapy response in LUAD patients, with S100A16 identified as a potential therapeutic target.

GMILT: A Novel Transformer Network That Can Noninvasively Predict EGFR Mutation Status

Noninvasively and accurately predicting the epidermal growth factor receptor (EGFR) mutation status is a clinically vital problem. Moreover, further identifying the most suspicious area related to the EGFR mutation status can guide the biopsy to avoid false negatives. Deep learning methods based on computed tomography (CT) images may improve the noninvasive prediction of EGFR mutation status and potentially help clinicians guide biopsies by visual methods. Inspired by the potential inherent links between EGFR mutation status and invasiveness information, we hypothesized that the predictive performance of a deep learning network can be improved through extra utilization of the invasiveness information. Here, we created a novel explainable transformer network for EGFR classification named gated multiple instance learning transformer (GMILT) by integrating multi-instance learning and discriminative weakly supervised feature learning. Pathological invasiveness information was first introduced into the multitask model as embeddings. GMILT was trained and validated on a total of 512 patients with adenocarcinoma and tested on three datasets (the internal test dataset, the external test dataset, and The Cancer Imaging Archive (TCIA) public dataset). The performance (area under the curve (AUC) =0.772 on the internal test dataset) of GMILT exceeded that of previously published methods and radiomics-based methods (i.e., random forest and support vector machine) and attained a preferable generalization ability (AUC =0.856 in the TCIA test dataset and AUC =0.756 in the external dataset). A diameter-based subgroup analysis further verified the efficiency of our model (most of the AUCs exceeded 0.772) to noninvasively predict EGFR mutation status from computed tomography (CT) images. In addition, because our method also identified the "core area" of the most suspicious area related to the EGFR mutation status, it has the potential ability to guide biopsies.

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.

Facts and Hopes in Immunotherapy Strategies Targeting Antigens Derived from KRAS Mutations

In this commentary, we advance the notion that mutant KRAS (mKRAS) is an ideal tumor neoantigen that is amenable for targeting by the adaptive immune system. Recent progress highlights key advances on various fronts that validate mKRAS as a molecular target and support further pursuit as an immunological target. Because mKRAS is an intracellular membrane localized protein and not normally expressed on the cell surface, we surmise that proteasome degradation will generate short peptides that bind to HLA class I (HLA-I) molecules in the endoplasmic reticulum for transport through the Golgi for display on the cell surface. T-cell receptors (TCR)αβ and antibodies have been isolated that specifically recognize mKRAS encoded epitope(s) or haptenated-mKRAS peptides in the context of HLA-I on tumor cells. Case reports using adoptive T-cell therapy provide proof of principle that KRAS G12D can be successfully targeted by the immune system in patients with cancer. Among the challenges facing investigators is the requirement of precision medicine to identify and match patients to available mKRAS peptide/HLA therapeutics and to increase the population coverage by targeting additional mKRAS epitopes. Ultimately, we envision mKRAS-directed immunotherapy as an effective treatment option for selected patients that will complement and perhaps synergize with small-molecule mKRAS inhibitors and targeted mKRAS degraders.

The evolution of lung adenocarcinoma precursors is associated with chromosomal instability and transition from innate to adaptive immune response/evasion

Studying lung adenocarcinoma (LUAD) early carcinogenesis is challenging, primarily due to the lack of LUAD precursors specimens. We amassed multi-omics data from 213 LUAD and LUAD precursors to identify molecular features underlying LUAD precancer evolution. We observed progressively increasing mutations, chromosomal aberrations, whole genome doubling and genomic instability from precancer to invasive LUAD, indicating aggravating chromosomal instability (CIN). Telomere shortening, a crucial genomic alteration linked to CIN, emerged at precancer stage. Moreover, later-stage lesions demonstrated increasing cancer stemness and decreasing alveolar identity, suggesting epithelial de-differentiation during early LUAD carcinogenesis. The innate immune cells progressively diminished from precancer to invasive LUAD, concomitant with a gradual recruitment of adaptive immune cells (except CD8+ and gamma-delta T cells that decreased in later stages) and upregulation of numerous immune checkpoints, suggesting LUAD precancer evolution is associated with a shift from innate to adaptive immune response and immune evasion mediated by various mechanisms.

Genomic landscape and tumor mutational features of resected preinvasive to invasive lung adenocarcinoma

Introduction

Adenocarcinoma in situ (AIS) and minimally invasive adenocarcinoma (MIA) are considered pre-invasive forms of lung adenocarcinoma (LUAD) with a 5-year recurrence-free survival of 100%. We investigated genomic profiles in early tumorigenesis and distinguished mutational features of preinvasive to invasive adenocarcinoma (IAC) for early diagnosis.

Methods

Molecular information was obtained from a 689-gene panel in the 90 early-stage LUAD Chinese patients using next-generation sequencing. Gene signatures were identified between pathology subtypes, including AIS/MIA (n=31) and IAC (n=59) in this cohort. Mutational and clinicopathological information was also obtained from the Cancer Genome Atlas (TCGA) as a comparison cohort.

Results

A higher mutation frequency of TP53, RBM10, MUC1, CSMD, MED1, LRP1B, GLI1, MAP3K, and RYR2 was observed in the IAC than in the AIS/MIA group. The AIS/MIA group showed higher mutation frequencies of ERBB2, BRAF, GRIN2A, and RB1. Comparable mutation rates for mutually exclusive genes (EGFR and KRAS) across cohorts highlight the critical transition to invasive LUAD. Compared with the TCGA cohort, EGFR, KRAS, TP53, and RBM10 were frequently mutated in both cohorts. Despite limited gene mutation overlap between cohorts, we observed variant mutation types in invasive LUAD. Additionally, the tumor mutation burden (TMB) values were significantly lower in the AIS/MIA group than in the IAC group in both the Chinese cohort (P=0.0053) and TCGA cohort (P<0.01).

Conclusion

These findings highlight the importance of distinguishing preinvasive from invasive LUAD in the early stages of LUAD and both pathology and molecular features in clinical practice, revealing genomic tumor heterogeneity and population differences.

Advancements in the diagnosis and treatment of sub‑centimeter lung cancer in the era of precision medicine (Review)

Lung cancer is the malignancy with the highest global mortality rate and imposes a substantial burden on society. The increasing popularity of lung cancer screening has led to increasing number of patients being diagnosed with pulmonary nodules due to their potential for malignancy, causing considerable distress in the affected population. However, the diagnosis and treatment of sub-centimeter grade pulmonary nodules remain controversial. The evolution of genetic detection technology and the development of targeted drugs have positioned the diagnosis and treatment of lung cancer in the precision medicine era, leading to a marked improvement in the survival rate of patients with lung cancer. It has been established that lung cancer driver genes serve a key role in the development and progression of sub-centimeter lung cancer. The present review aimed to consolidate the findings on genes associated with sub-centimeter lung cancer, with the intent of serving as a reference for future studies and the personalized management of sub-centimeter lung cancer through genetic testing.

Targeted next-generation sequencing of 491 lung cancers in clinical practice: Implications for future detection strategy and targeted therapy

Although lung cancer remains the most common cause of global cancer-related mortality, the identification of oncogenic driver alterations and the development of targeted drugs has dramatically altered the therapeutic landscape. In this retrospective study, we found that 97.7% samples carried at least one mutation in the 25 genes tested in our cohort. 53.6% samples were positive for EGFR mutations, followed by TP53 (41.1%), KRAS (11.8%), ERBB2 (4.3%). EGFR mutations were mainly found in female adenocarcinomas, while TP53 was mainly found in male non-adenocarcinomas. Significant differences can be found in the mutation rate of EGFR (60.9% vs 11.9%), KRAS (12.2% vs 25.0%), STK11 (1.5% vs 11.9%), FGFR3 (2.4% vs 0.0%) and ERBB4 (1.2% vs 6.1%) between adenocarcinoma in our cohort and TCGA-LUAD data (all p < 0.001). What's more, we found that the mutation of EGFR increased significantly from adenocarcinomas in situ (AIS, 21.4%) to microinvasive adenocarcinomas (MIA, 52.4%) and invasive adenocarcinomas (IA, 61.1%), while the mutation of ERBB2 dropped markedly from AIS (21.4%) to MIA (9.5%) and IA (4.1%). At last, comparations between targeted NGS and ARMS-based single gene test in the detection of EGFR showed a 94.6% consistence. In conclusion, targeted NGS can provide a comprehensive mutational profile of lung cancer. Considering the high mutation rate of EGFR in NSCLC of Asian populations, a specialized detection strategy should be conducted.

Single-cell RNA sequencing integrated with bulk RNA sequencing analysis identifies a tumor immune microenvironment-related lncRNA signature in lung adenocarcinoma

BACKGROUND

Recently, long non-coding RNAs (lncRNAs) have been demonstrated as essential roles in tumor immune microenvironments (TIME). Nevertheless, researches on the clinical significance of TIME-related lncRNAs are limited in lung adenocarcinoma (LUAD).

METHODS

Single-cell RNA sequencing and bulk RNA sequencing data are integrated to identify TIME-related lncRNAs. A total of 1368 LUAD patients are enrolled from 6 independent datasets. An integrative machine learning framework is introduced to develop a TIME-related lncRNA signature (TRLS).

RESULTS

This study identified TIME-related lncRNAs from integrated analysis of single‑cell and bulk RNA sequencing data. According to these lncRNAs, a TIME-related lncRNA signature was developed and validated from an integrative procedure in six independent cohorts. TRLS exhibited a robust and reliable performance in predicting overall survival. Superior prediction performance barged TRLS to the forefront from comparison with general clinical features, molecular characters, and published signatures. Moreover, patients with low TRLS displayed abundant immune cell infiltration and active lipid metabolism, while patients with high TRLS harbored significant genomic alterations, high PD-L1 expression, and elevated DNA damage repair (DDR) relevance. Notably, subclass mapping analysis of nine immunotherapeutic cohorts demonstrated that patients with high TRLS were more sensitive to immunotherapy.

CONCLUSIONS

This study developed a promising tool based on TIME-related lncRNAs, which might contribute to tailored treatment and prognosis management of LUAD patients.

An immune cell map of human lung adenocarcinoma development reveals an anti-tumoral role of the Tfh-dependent tertiary lymphoid structure

The immune responses during the initiation and invasion stages of human lung adenocarcinoma (LUAD) development are largely unknown. Here, we generated a single-cell RNA sequencing map to decipher the immune dynamics during human LUAD development. We found that T follicular helper (Tfh)-like cells, germinal center B cells, and dysfunctional CD8+ T cells increase during tumor initiation/invasion and form a tertiary lymphoid structure (TLS) inside the tumor. This TLS starts with an aggregation of CD4+ T cells and the generation of CXCL13-expressing Tfh-like cells, followed by an accumulation of B cells, and then forms a CD4+ T and B cell aggregate. TLS and its associated cells are correlated with better patient survival. Inhibiting TLS formation by Tfh or B cell depletion promotes tumor growth in mouse models. The anti-tumoral effect of the Tfh-dependent TLS is mediated through interleukin-21 (IL-21)-IL-21 receptor signaling. Our study establishes an anti-tumoral role of the Tfh-dependent TLS in the development of LUAD.

Pulmonary Adenocarcinoma In Situ and Minimally Invasive Adenocarcinomas in European Patients Have Less KRAS and More EGFR Mutations Compared to Advanced Adenocarcinomas

Pulmonary adenocarcinoma (ADC) is a very diverse disease, both genetically and histologically, which displays extensive intratumor heterogeneity with numerous acquired mutations. ADC is the most common type of lung cancer and is believed to arise from adenocarcinoma in situ (AIS) which then progresses to minimally invasive adenocarcinoma (MIA). In patients of European ethnicity, we analyzed genetic mutations in AIS (n = 10) and MIA (n = 18) and compared the number of genetic mutations with advanced ADC (n = 2419). Using next-generation sequencing, the number of different mutations detected in both AIS (87.5%) and MIA (94.5%) were higher (p < 0.001) than in advanced ADC (53.7%). In contrast to the high number of mutations in Kirsten rat sarcoma virus gene (KRAS) in advanced ADC (34.6%), there was only one case of AIS with KRAS G12C mutation (3.5%; p < 0.001) and no cases of MIA with KRAS mutation (p < 0.001). In contrast to the modest prevalence of epidermal growth factor receptor (EGFR) mutations in advanced ADC (15.0%), the fraction of EGFR mutant cases was higher in both in AIS (22.2%) and MIA (59.5%; p < 0.001). The EGFR exon 19 deletion mutation was more common in both MIA (50%; n = 6/12) and ADC (41%; n = 149/363), whereas p.L858R was more prevalent in AIS (75%; n = 3/4). In contrast to pulmonary advanced ADC, KRAS driver mutations are less common, whereas mutations in EGFR are more common, in detectable AIS and MIA.

Systemic immune index predicts tumor-infiltrating lymphocyte intensity and immunotherapy response in small cell lung cancer

Background

Despite recent progresses in immune checkpoint blockade (ICB) in small-cell lung cancer (SCLC), a lack of understanding regarding the systemic tumor immune environment (STIE) and local tumor immune microenvironment (TIME) makes it difficult to accurately predict clinical outcomes and identify potential beneficiaries from ICB therapy.

Methods

We enrolled 191 patients with stage I-III SCLC and comprehensively evaluated the prognostic role of STIE by several quantitative measurements, and further integrate it with a local immune score system (LISS) established by eXtreme Gradient Boosting (XGBoost) machine learning algorithm. We also test the value of STIE in beneficiary selection in our independent advanced SCLC cohort receiving programmed cell death 1 ligand 1 (PD-L1) blockade therapy.

Results

Among several systemic immune markers, the STIE as assessed by prognostic nutritional index (PNI) was correlated with disease-free survival (DFS) and overall survival (OS), and remained as an independent prognostic factor for SCLC patients [hazard ratio (HR): 0.473, 95% confidence interval (CI): 0.241-0.929, P=0.030]. Higher PNI score was closely associated with inflamed SCLC molecular subtype and local tumor-infiltrating lymphocytes (TILs). We further constructed a LISS which combined top three important local immune biomarkers (CD8+ T-cell count, PD-L1 expression on CD8+ T-cell and CD4+ T-cell count) and integrated it with the PNI score. The final integrated immune risk system was an independent prognostic factor and achieved better predictive performance than Tumor Node Metastasis (TNM) stages and single immune biomarker. Furthermore, PNI-high extensive-stage SCLC patients achieved better clinical response and longer progression-free survival (PFS) (11.8 vs. 5.9 months, P=0.012) from PD-L1 blockade therapy.

Conclusions

This study provides a method to investigate the prognostic value of overall immune status by combining the PNI with local immune biomarkers in SCLC. The promising clinical application of PNI in efficacy prediction and beneficiary selection for SCLC immunotherapy is also highlighted.

M6A RNA methylation in biliary tract cancer: the function roles and potential therapeutic implications

Biliary tract cancers (BTCs) are relatively rare malignancies with a poor prognosis. For advanced BTCs, the efficacy of current chemotherapeutic approaches is limited. Consequently, there is an urgent need to deepen our understanding of the molecular mechanisms underlying BTC tumorigenesis and development for the exploration of effective targeted therapies. N6-methyladenosine (m6A), the most abundant RNA modifications in eukaryotes, is found usually dysregulated and involved in tumorigenesis, progression, and drug resistance in tumors. Numerous studies have confirmed that aberrant m6A regulators function as either oncogenes or tumor suppressors in BTCs by the reversible regulation of RNA metabolism, including splicing, export, degradation and translation. In this review, we summarized the current roles of the m6A regulators and their functional impacts on RNA fate in BTCs. The improved understanding of m6A modification in BTCs also provides a reasonable outlook for the exploration of new diagnostic strategies and efficient therapeutic targets.

An Investigation of the Immune Microenvironment and Genome during Lung Adenocarcinoma Development

Background: Adenocarcinoma in situ (AIS) and minimally invasive adenocarcinoma (MIA) are two consecutive pathological processes that occur before invasive lung adenocarcinoma (LUAD). However, our understanding of the immune editing patterns during the progression of LUAD remains limited. Furthermore, we know very little about whether alterations in driver genes are involved in forming the tumor microenvironment (TME). Therefore, it is necessary to elucidate the regulatory role of TME in LUAD development from multiple dimensions, including immune cell infiltration, molecular mutation events, and oncogenic signaling pathways. Methods: We collected 145 surgically resected pulmonary nodule specimens, including 28 cases of AIS, 52 cases of MIA, and 65 cases of LUAD. Immunohistochemistry (IHC) was used to detect the expression of immune markers CD3, CD4, CD8, CD68 and programmed death ligand 1 (PD-L1). Genomic data and TMB generated by targeted next-generation sequencing (NGS). Results: LUAD exhibited higher levels of immune cell infiltration, tumor mutation burden (TMB), and activation of oncogenic pathways compared to AIS and MIA. In LUAD, compared to epidermal growth factor receptor (EGFR) single mutation and wild-type (WT) samples, cases with EGFR co-mutations showed a more pronounced rise in the CD4/CD8 ratio and CD68 infiltration. Patients with low-density lipoprotein (LDL) receptor-related protein 1B (LRP1B) mutation have higher TMB and PD-L1 expression. The transition from AIS to LUAD tends to shift the TME towards the PD-L1+CD8+ subtype (adaptive resistance). Progression-associated mutations (PAMs) were enriched in the lymphocyte differentiation pathway and related to exhausted cells' phenotype. Conclusion: Tumor-infiltrating immune cells tend to accumulate as the depth of LUAD invasion increases, but subsequently develop into an immune exhaustion and immune escape state. Mutations in EGFR and LRP1B could potentially establish an immune niche that fosters tumor growth. PAMs in LUAD may accelerate disease progression by promoting T cell differentiation into an exhausted state.

Evolutionary proteogenomic landscape from pre-invasive to invasive lung adenocarcinoma

Lung adenocarcinoma follows a stepwise progression from pre-invasive to invasive. However, there remains a knowledge gap regarding molecular events from pre-invasive to invasive. Here, we conduct a comprehensive proteogenomic analysis comprising whole-exon sequencing, RNA sequencing, and proteomic and phosphoproteomic profiling on 98 pre-invasive and 99 invasive lung adenocarcinomas. The deletion of chr4q12 contributes to the progression from pre-invasive to invasive adenocarcinoma by downregulating SPATA18, thus suppressing mitophagy and promoting cell invasion. Proteomics reveals diverse enriched pathways in normal lung tissues and pre-invasive and invasive adenocarcinoma. Proteomic analyses identify three proteomic subtypes, which represent different stages of tumor progression. We also illustrate the molecular characterization of four immune clusters, including endothelial cells, B cells, DCs, and immune depression subtype. In conclusion, this comprehensive proteogenomic study characterizes the molecular architecture and hallmarks from pre-invasive to invasive lung adenocarcinoma, guiding the way to a deeper understanding of the tumorigenesis and progression of this disease.

A gene-based score for the risk stratification of stage IA lung adenocarcinoma

OBJECTIVE

We aim to molecularly stratify stage IA lung adenocarcinoma (LUAD) for precision medicine.

METHODS

Twelve multi-institution datasets (837 cases of IA) were used to classify the high- and low-risk types (based on survival status within 5 years), and the biological differences were compared. Then, a gene-based classifying score (IA score) was trained, tested and validated by several machine learning methods. Furthermore, we estimated the significance of the IA score in the prognostic assessment, chemotherapy prediction and risk stratification of stage IA LUAD. We also developed an R package for the clinical application. The SEER database (15708 IA samples) and TCGA Pan-Cancer (1881 stage I samples) database were used to verify clinical significance.

RESULTS

Compared with the low-risk group, the high-risk group of stage IA LUAD has obvious enrichment of the malignant pathway and more driver mutations and copy number variations. The effect of the IA score on the classification of high- and low-risk stage IA LUAD was much better than that of classical clinicopathological factors (training set: AUC = 0.9, validation set: AUC = 0.7). The IA score can significantly predict the prognosis of stage IA LUAD and has a prognostic effect for stage I pancancer. The IA score can effectively predict chemotherapy sensitivity and occult metastasis or invasion in stage IA LUAD. The R package IAExpSuv has a good risk probability prediction effect for both groups and single stages of IA LUAD.

CONCLUSIONS

The IA score can effectively stratify the risk of stage IA LUAD, offering good assistance in precision medicine.

High TLX1 Expression Correlates with Poor Prognosis and Immune Infiltrates in Patients with Lung Adenocarcinoma

BACKGROUND

To develop optimal personalized therapy for lung adenocarcinoma (LUAD), potential biomarkers associated with the prognosis are urgently needed. It is unclear what role T Cell Leukemia Homeobox 1 (TLX1) plays in LUAD.

OBJECTIVE

In this study, TLX1's relationship with LUAD was investigated using TCGA database analysis, bioinformatics analysis, and experimental validation.

METHODS

We examined the expression of TLX1 in pan cancer and LUAD, the relationship between TLX1 expression and clinical features, immune infiltration, its diagnostic and prognostic value, as well as TLX1 related pathways. The analysis included various statistical methods, including the Kaplan-Meier method, Cox regression analysis, GSEA, and immune infiltration analysis. TLX1 expression in LUAD cell lines was validated using qRT-PCR.

RESULT

In LUAD patients, high expression of TLX1 was associated with T stage (P<0.001). High TLX1 expression was associated with worse overall survival (OS) (HR: 1.57; 95% CI: 1.18-2.1; P=0.002). And TLX1 HR: 1.619; 95% CI: 1.012-2.590; P=0.044) was independently correlated with OS in LUAD patients. TLX1 expression was associated with the pathways, including Rho GTPase effectors, DNA repair, TCF dependent signaling in response to WNT, signaling by Nuclear Receptors, signaling by Notch, chromatin-modifying enzymes, ESR-mediated signaling, cellular senescence, and transcriptional regulation by Runx1. TLX1 expression was correlated with aDC, Tcm, and TReg cells. The expression of TLX1 was significantly increased in LUAD cells compared to BEAS-2B cells.

CONCLUSION

An association between high TLX1 expression and poor survival and immune infiltration was found in LUAD patients. There may be a potential role for TLX1 in diagnosis, prognosis, and immunotherapy for LUAD.

Molecular pathology of non-small cell carcinoma

Currently, lung cancer is treated by the highest number of therapeutic options and the benefits are based on multiple large-scale sequencing studies, translational research and new drug development, which has promoted our understanding of the molecular pathology of lung cancer. According to the driver alterations, different characteristics have been revealed, such as differences in ethnic prevalence, median age and alteration patterns. Consequently, beyond traditional chemoradiotherapy, molecular-targeted therapy and treatment with immune check-point inhibitors (ICI) also became available major therapeutic options. Interestingly, clinical results suggest that the recently established therapies target distinct lung cancer proportions, particularly between the EGFR/ALK and PD-1/PD-L1-positive subsets, e.g. the kinase inhibitors target driver mutation-positive tumours, whereas driver mutation-negative tumours respond to ICI treatment. These therapeutic efficacy-related differences might be explained by the molecular pathogenesis of lung cancer. Addictive driver mutations promote tumour formation with powerful transformation performance, resulting in a low tumour mutation burden, reduced immune surveillance, and subsequent poor response to ICIs. In contrast, regular tobacco smoke exposure repeatedly injures the proximal airway epithelium, leading to accumulated genetic alterations. In the latter pathway, overgrowth due to alteration and immunological exclusion against neoantigens is initially balanced. However, tumours could be generated from certain clones that outcompete immunological exclusion and outgrow the others. Consequently, this cancer type responds to immune check-point treatment. These pathogenic differences are explained well by the two-compartment model, focusing upon the anatomical and functional composition of distinct cellular components between the terminal respiratory unit and the air-conducting system.

Clinical characteristics and progression of pre-/minimally invasive lung adenocarcinoma harboring ALK or RET rearrangements: a retrospective cohort study

Background

Patients harboring anaplastic lymphoma kinase (ALK) or rearranged during transfection (RET) rearrangements are usually diagnosed at a relatively late stage with nodal and distant metastasis, and rapid progression course of ALK/RET fusion-positive lung cancer were well-known. However, clinical characteristics and course of pre-/minimally invasive lung adenocarcinoma harboring ALK or RET fusions are poorly described. Identifying patients with gene fusions at early stage may offer surgical options that could cure those patients.

Methods

We retrospectively included patients with surgically resected pre-/minimally invasive lung adenocarcinomas harboring epidermal growth factor receptor (EGFR) mutations or ALK/RET rearrangements, and further compared the patient clinical characteristics, nodule natural course, and survival outcomes. Radiological characteristics including ground-glass component, cystic airspace, pleural attachment, etc. were specially assessed for this study. EGFR (exons 18-22) was detected by Sanger sequencing and quantitative real-time polymerase chain reaction (qRT-PCR) was used to analyze the ALK/RET rearrangements. Lung cancer-specific survival (LCSS), relapse-free survival (RFS), and overall survival (OS) were all evaluated.

Results

Of 238 patients with pre-/minimally invasive lung adenocarcinomas, 226 patients had EGFR mutations, 7 patients had ALK fusions, and 5 patients had RET fusions. Average age at surgery was 45.3 years for ALK/RET-positive group and 52.6 years for EGFR-positive group (P=0.049). Radiologically, among the 12 patients with ALK/RET fusions, the majority of lesions (10/12) manifested as mixed ground-glass opacities (mGGOs), which was significantly more prevalent when compared with patients with EGFR mutations (83.4% vs. 24.3%, P<0.001). Moreover, a substantial proportion of cystic airspace was found in ALK/RET-positive group but not in EGFR-positive group (66.7% vs. 14.2%, P<0.001). Among four patients with ALK/RET fusions undergoing surveillance over 1 year before surgery, two of them developed rapid radiologic progression. The 5-year LCSS and RFS were 100%, 100% for ALK/RET-positive group, and 100%, 100% for EGFR-positive group, respectively.

Conclusions

ALK/RET-positive pre-/minimally invasive lung adenocarcinomas were mostly characterized as mGGOs with cystic airspace developing rapid nodule progression, and no recurrence occurred during long-term follow-up after resection. This provides insights into proper curative surgery timing in the management of patients with gene fusions. However, these findings must be treated with caution and validated in future multi-center studies with larger sample size.

Whole-genome sequencing reveals the molecular implications of the stepwise progression of lung adenocarcinoma

The mechanism underlying the development of tumors, particularly at early stages, still remains mostly elusive. Here, we report whole-genome long and short read sequencing analysis of 76 lung cancers, focusing on very early-stage lung adenocarcinomas such as adenocarcinoma in situ (AIS) and minimally invasive adenocarcinoma. The obtained data is further integrated with bulk and spatial transcriptomic data and epigenomic data. These analyses reveal key events in lung carcinogenesis. Minimal somatic mutations in pivotal driver mutations and essential proliferative factors are the only detectable somatic mutations in the very early-stage of AIS. These initial events are followed by copy number changes and global DNA hypomethylation. Particularly, drastic changes are initiated at the later AIS stage, i.e., in Noguchi type B tumors, wherein cancer cells are exposed to the surrounding microenvironment. This study sheds light on the pathogenesis of lung adenocarcinoma from integrated pathological and molecular viewpoints.

RNA-binding motif protein 10 inactivates c-Myc by partnering with ribosomal proteins uL18 and uL5

RNA-binding motif protein 10 (RBM10) is a frequently mutated tumor suppressor in lung adenocarcinoma (LUAD). Yet, it remains unknown whether cancer-derived mutant RBM10 compromises its tumor suppression function and, if so, the molecular insight of the underlying mechanisms. Here, we show that wild-type RBM10 suppresses lung cancer cell growth and proliferation by inactivating c-Myc that is essential for cancer cell survival. RBM10 directly binds to c-Myc and promotes c-Myc's ubiquitin-dependent degradation, while RBM10 knockdown leads to the induction of c-Myc level and activity. This negative action on c-Myc is further boosted by ribosomal proteins (RPs) uL18 (RPL5) and uL5 (RPL11) via their direct binding to RBM10. Cancer-derived mutant RBM10-I316F fails to bind to uL18 and uL5 and to inactivate c-Myc, thus incapable of suppressing tumorigenesis. Our findings uncover RBM10 as a pivotal c-Myc repressor by cooperating with uL18 and uL5 in lung cancer cells, as its failure to do so upon mutation favors tumorigenesis.

Transcriptomic landscape based on annotated clinical features reveals PLPP2 involvement in lipid raft-mediated proliferation signature of early-stage lung adenocarcinoma

BACKGROUND

Image-based screening improves the detection of early-stage lung adenocarcinoma (LUAD)but also highlights the issue of high false-positive diagnoses, which puts patients at a risk of unnecessary over-treatment. Therefore, more precise discrimination criteria are required to ensure that patients with early-stage LUAD receive appropriate treatments.

METHODS

We integrated 158 early-stage LUAD cases from 2 independent cohorts, including 30 matched resected specimens with complete radiological and pathological information, and 128 retrospective pathological pair-samples with partial follow-up data. This integration allowed us to conduct a correlation analysis between clinical phenotype and transcriptome landscape. Immunohistochemistry was performed using tissue microarrays to examine the expression of phospholipid phosphatase 2 (PLPP2) and lipid-raft markers. Lipidomics analysis was used to determine the changes of lipid components in PLPP2-overexpressed cells. To assess the effects of PLPP2 on the malignant phenotypes of LUAD cells, we conducted mice tumor-bearing experiments and in vitro cellular experiments by knocking down PLPP2 and inhibiting lipid raft synthesis with MβCD, respectively.

RESULTS

Bioinformatics analysis indicated that the co-occurrence of lipid raft formation and rapid cell proliferation might exhibit synergistic effects in driving oncogenesis from lung preneoplasia to adenocarcinoma. The enhanced activation of the cell cycle promoted the transition from non-invasive to invasive status in early-stage LUAD, which was related to an increase in lipid rafts within LUAD cells. PLPP2 participated in lipid raft formation by altering the component contents of lipid rafts, such as esters, sphingomyelin, and sphingosine. Furthermore, elevated PLPP2 levels were identified as an independent prognostic risk factor for LUAD patients. Further results from in vivo and in vitro experiments confirmed that PLPP2 could induce excessive cell proliferation by enhancing lipid raft formation in LUAD cells.

CONCLUSIONS

Our study has revealed the characteristics of gene expression profiles in early-stage LUAD patients with the different radiological and pathological subtypes, as well as deciphered transcriptomic evolution trajectory from preneoplasia to invasive LUAD. Furthermore, it suggests that PLPP2-mediated lipid raft synthesis may be a significant biological event in the initiation of early-stage LUAD, offering a potential target for more precise diagnosis and therapy in clinical settings.

Comparison of gene mutation profile in different lung adenocarcinoma subtypes by targeted next-generation sequencing

BACKGROUND

Disease prognosis after resection of lung cancer could be affected by pathological subtypes. In this study, we investigated the difference of gene variation and significantly altered pathways between adenocarcinoma in situ (AIS)/microinvasive adenocarcinoma (MIA) and invasive adenocarcinoma (IAC) subtypes to reveal the molecular mechanism of prognosis differences.

METHODS

Sixty one tumor tissues were subjected to DNA extraction and customized 136 gene targeted next-generation sequencing. Comparisons between groups were performed with two-sided Fisher's exact test for categorical variables and two-tailed unpaired t test for numerical variables.

RESULTS

A total of 402 somatic mutations involved in 70 genes were detected in all these samples, and 74.29% of these genes were mutated in at least two samples. PMS2, ARID1A, EGFR, and POLE were the most frequently mutated genes. ALK_EML4 fusion was observed in one IAC patient and RET_ KIF5B fusion in one AIS patient. A significant higher proportion of patients with TP53 gene mutation was observed in the IAC group (P = 0.0057). The average onset age in IAC group is 62.48 years, which is greater than other subtypes (P = 0.0166). It revealed that mutations in genes involved in the mTOR signaling pathway (56.52% vs 26.32%, P = 0.0288) and Hippo signaling pathway (34.78% vs 10.53%, P = 0.0427) were significantly enriched in IAC subtypes, suggesting the key involvement of mTOR and Hippo signaling pathways in lung tumor development and malignant progression.

CONCLUSIONS

This study revealed the heterogeneity of gene mutations and significantly altered pathways between different lung cancer subtypes, suggesting the potential mechanism of different prognosis.