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Single-cell technologies have revealed the complexity of the tumour immune microenvironment with unparalleled resolution 1 – 9 . Most clinical strategies rely on histopathological stratification of tumour subtypes, yet the spatial context of single-cell phenotypes within these stratified subgroups is poorly understood. Here we apply imaging mass cytometry to characterize the tumour and immunological landscape of samples from 416 patients with lung adenocarcinoma across five histological patterns. We resolve more than 1.6 million cells, enabling spatial analysis of immune lineages and activation states with distinct clinical correlates, including survival. Using deep learning, we can predict with high accuracy those patients who will progress after surgery using a single 1-mm 2 tumour core, which could be informative for clinical management following surgical resection. Our dataset represents a valuable resource for the non-small cell lung cancer research community and exemplifies the utility of spatial resolution within single-cell analyses. This study also highlights how artificial intelligence can improve our understanding of microenvironmental features that underlie cancer progression and may influence future clinical practice. Using imaging mass cytometry, the tumour and immunological spatial landscapes of 416 lung adenocarcinomas are characterized, which, when combined with deep learning, can predict clinical outcomes with high accuracy.

Advanced metastatic cancer poses utmost clinical challenges and may present molecular and cellular features distinct from an early-stage cancer. Herein, we present single-cell transcriptome profiling of metastatic lung adenocarcinoma, the most prevalent histological lung cancer type diagnosed at stage IV in over 40% of all cases. From 208,506 cells populating the normal tissues or early to metastatic stage cancer in 44 patients, we identify a cancer cell subtype deviating from the normal differentiation trajectory and dominating the metastatic stage. In all stages, the stromal and immune cell dynamics reveal ontological and functional changes that create a pro-tumoral and immunosuppressive microenvironment. Normal resident myeloid cell populations are gradually replaced with monocyte-derived macrophages and dendritic cells, along with T-cell exhaustion. This extensive single-cell analysis enhances our understanding of molecular and cellular dynamics in metastatic lung cancer and reveals potential diagnostic and therapeutic targets in cancer-microenvironment interactions. Understanding the mechanisms that lead to lung adenocarcinoma metastasis is important for identifying new therapeutics. Here, the authors document the changes in the transcriptome of human lung adenocarcinoma using single-cell sequencing and link cancer cell signatures to immune cell dynamics.

BackgroundLung adenocarcinoma (LUAD) is a common pulmonary malignant disease with a poor prognosis. There were limited studies investigating the influences of the tumor immune microenvironment on LUAD patients’ survival and response to immune checkpoint inhibitors (ICIs). MethodsBased on TCGA-LUAD dataset, we constructed a prognostic immune signature and validated its predictive capability in the internal as well as total datasets. Then, we explored the differences of tumor-infiltrating lymphocytes, tumor mutation burden, and patients’ response to ICI treatment between the high-risk score group and low-risk score group.ResultsThis immune signature consisted of 17 immune-related genes, which was an independent prognostic factor for LUAD patients. In the low-risk score group, patients had better overall survival. Although the differences were non-significant, patients with low-risk scores had more tumor-infiltrating follicular helper T cells and fewer macrophages (M0), which were closely related to clinical outcomes. Additionally, the total TMB was markedly decreased in the low-risk score group. Using immunophenoscore as a surrogate of ICI response, we found that patients with low-risk scores had significantly higher immunophenoscore.ConclusionThe 17-immune-related genes signature may have prognostic and predictive relevance with ICI therapy but needs prospective validation.

Lung cancer is the world’s leading cause of cancer death and shows strong ancestry disparities. By sequencing and assembling a large genomic and transcriptomic dataset of lung adenocarcinoma (LUAD) in individuals of East Asian ancestry (EAS; n  = 305), we found that East Asian LUADs had more stable genomes characterized by fewer mutations and fewer copy number alterations than LUADs from individuals of European ancestry. This difference is much stronger in smokers as compared to nonsmokers. Transcriptomic clustering identified a new EAS-specific LUAD subgroup with a less complex genomic profile and upregulated immune-related genes, allowing the possibility of immunotherapy-based approaches. Integrative analysis across clinical and molecular features showed the importance of molecular phenotypes in patient prognostic stratification. EAS LUADs had better prediction accuracy than those of European ancestry, potentially due to their less complex genomic architecture. This study elucidated a comprehensive genomic landscape of EAS LUADs and highlighted important ancestry differences between the two cohorts. Genomic and transcriptomic analysis of lung adenocarcinoma (LUAD) in Asia indicates that Asian LUADs have fewer mutations, lower driver prevalence and fewer copy number alterations than European LUADs.

Metastasis frequently develops from disseminated cancer cells that remain dormant after the apparently successful treatment of a primary tumour. These cells fluctuate between an immune-evasive quiescent state and a proliferative state liable to immune-mediated elimination 1 – 6 . Little is known about the clearing of reawakened metastatic cells and how this process could be therapeutically activated to eliminate residual disease in patients. Here we use models of indolent lung adenocarcinoma metastasis to identify cancer cell-intrinsic determinants of immune reactivity during exit from dormancy. Genetic screens of tumour-intrinsic immune regulators identified the stimulator of interferon genes (STING) pathway as a suppressor of metastatic outbreak. STING activity increases in metastatic progenitors that re-enter the cell cycle and is dampened by hypermethylation of the STING promoter and enhancer in breakthrough metastases or by chromatin repression in cells re-entering dormancy in response to TGFβ. STING expression in cancer cells derived from spontaneous metastases suppresses their outgrowth. Systemic treatment of mice with STING agonists eliminates dormant metastasis and prevents spontaneous outbreaks in a T cell- and natural killer cell-dependent manner—these effects require cancer cell STING function. Thus, STING provides a checkpoint against the progression of dormant metastasis and a therapeutically actionable strategy for the prevention of disease relapse. STING signalling is activated in metastatic cancer cells that exit from an immune-evasive dormant state, blocking their progression and cancer relapse.

Background There is a growing interest in utilizing a combination of brain radiotherapy (RT) and tyrosine kinase inhibitors (TKIs) for patients diagnosed with brain metastases (BM) in epidermal growth factor receptor (EGFR) mutation-positive lung adenocarcinoma (LAC). The current status of this treatment strategy remains a subject of debate. Methods We initiated our study by conducting a comprehensive literature search using the SCI-expanded database of Web of Science Core Collection (WoSCC). We utilized the VOSPviewer software to analyze various aspects of the research, including the year of publication, authorship, keywords, and country.Subsequently, we performed an extensive and systematic literature search on popular online databases. Our primary outcome measures were overall survival (OS) and intracranial progression-free survival (iPFS), both quantified by hazard ratios (HRs). Additionally, for data verification, we included data from patients in non-small cell lung cancer with brain metastasis who underwent therapeutic intervention at the Cancer Prevention and Treatment Center of Sun Yat-sen University and the Radiotherapy Department of Hanzhong Central Hospital between August 2012 and November 2021. Results The bibliometric analysis revealed an increasing trend in research focused on the combination of RT and TKIs for the management of lung cancer brain metastases over the previous decade. Then, nine studies consistent with the research direction were included for meta-analysis. The meta-analysis showed that the OS (HR = 0.81, 95% confidence interval: 0.69–0.94; P  = 0.007) and iPFS (HR = 0.71, 95% confidence interval: 0.61–0.82; P  < 0.001) of the combination therapy were significantly prolonged. Finally, 168 EGFR-mutated BM advanced LAC patients in the real world were verified, and the median iPFS of the combination therapy ( n  = 88 and EGFR-TKIs alone ( n  = 80) were 16.0 and 9.0 months, respectively, ( P  < 0.001). The median OS was 29.0 and 27.0 months, respectively, with no dramatic difference ( P  = 0.188). Conclusions Research on EGFR-mutant LAC brain metastasis has turned towards exploring optimal treatment strategies for this condition. Our meta-analysis and real-world data analysis consistently demonstrate that combination therapy offers a substantial improvement in patient survival compared to EGFR-TKI monotherapy. Notably, among patients undergoing salvage radiotherapy (RT), our subgroup analysis reveals that those initially treated with third-generation TKIs experience more significant benefits than those treated with first- or second-generation TKIs.

Oncogenic KRAS is a major driver in lung adenocarcinoma (LUAD) that has yet to be therapeutically conquered. Here we report that the SLC7A11/glutathione axis displays metabolic synthetic lethality with oncogenic KRAS. Through metabolomics approaches, we found that mutationally activated KRAS strikingly increased intracellular cystine levels and glutathione biosynthesis. SLC7A11, a cystine/glutamate antiporter conferring specificity for cystine uptake, was overexpressed in patients with KRAS-mutant LUAD and showed positive association with tumor progression. Furthermore, SLC7A11 inhibition by either genetic depletion or pharmacological inhibition with sulfasalazine resulted in selective killing across a panel of KRAS-mutant cancer cells in vitro and tumor growth inhibition in vivo, suggesting the functionality and specificity of SLC7A11 as a therapeutic target. Importantly, we further identified a potent SLC7A11 inhibitor, HG106, that markedly decreased cystine uptake and intracellular glutathione biosynthesis. Furthermore, HG106 exhibited selective cytotoxicity toward KRAS-mutant cells by increasing oxidative stress- and ER stress-mediated cell apoptosis. Of note, treatment of KRAS-mutant LUAD with HG106 in several preclinical lung cancer mouse models led to marked tumor suppression and prolonged survival. Overall, our findings reveal that KRAS-mutant LUAD cells are vulnerable to SLC7A11 inhibition, offering potential therapeutic approaches for this currently incurable disease.

Purpose Recent studies have increasingly linked Ephrin receptor B2 (EPHB2) to cancer progression. However, comprehensive investigations into the immunological roles and prognostic significance of EPHB2 across various cancers remain lacking. Methods We employed various databases and bioinformatics tools to investigate the impact of EPHB2 on prognosis, immune infiltration, genome instability, and response to immunotherapy. Validation of the correlation between EPHB2 expression and M2 macrophages included analyses using bulk and single-cell transcriptomic datasets, spatial transcriptomics, and multi-fluorescence staining. Moreover, we performed cMap web tool to screen for EPHB2-targeted compounds and assessed their potential through molecular docking and dynamics simulations. Additionally, in vitro validation using lung adenocarcinoma (LUAD) cell lines was conducted to confirm the bioinformatics predictions about EPHB2. Results EPHB2 dysregulation was observed across multiple cancer types, where it demonstrated significant diagnostic and prognostic value. Gene Set Enrichment Analysis (GSEA) indicated that EPHB2 is involved in enhancing cellular proliferation, invasiveness of cancer cells, and modulation of the anti-cancer immune response. Furthermore, it is emerged as a pan-cancer marker for M2 macrophage infiltration, supported by integrated analyses of transcriptomics and multiple fluorescence staining. In LUAD cells, knockdown of EPHB2 expression led to a decrease in both cell proliferation and migratory activity. Conclusion EPHB2 expression may serve as a pivotal indicator of M2 macrophage infiltration, offering vital insights into tumor dynamics and progression across various cancers, including lung adenocarcinoma, highlighting its significant prognostic and therapeutic potential for further exploration.

Tumor extracellular matrix has been associated with drug resistance and immune suppression. Here, proteomic and RNA profiling reveal increased collagen levels in lung tumors resistant to PD-1/PD-L1 blockade. Additionally, elevated collagen correlates with decreased total CD8 + T cells and increased exhausted CD8 + T cell subpopulations in murine and human lung tumors. Collagen-induced T cell exhaustion occurs through the receptor LAIR1, which is upregulated following CD18 interaction with collagen, and induces T cell exhaustion through SHP-1. Reduction in tumor collagen deposition through LOXL2 suppression increases T cell infiltration, diminishes exhausted T cells, and abrogates resistance to anti-PD-L1. Abrogating LAIR1 immunosuppression through LAIR2 overexpression or SHP-1 inhibition sensitizes resistant lung tumors to anti-PD-1. Clinically, increased collagen, LAIR1, and TIM-3 expression in melanoma patients treated with PD-1 blockade predict poorer survival and response. Our study identifies collagen and LAIR1 as potential markers for immunotherapy resistance and validates multiple promising therapeutic combinations. Tumor extracellular matrix has been associated with cancer progression, therapy resistance and immune suppression. Here, the authors show that collagen generates resistance to PD-1/PD-L1 immunotherapy by upregulating LAIR1 expression and downstream signaling, leading to increased CD8+ T cell exhaustion.

Tumor microenvironment (TME) has been reported to exhibit a crucial effect in lung cancer. Therefore, this study was aimed to investigate the genes associated with TME and develop a risk score to predict the overall survival (OS) of patients with lung adenocarcinoma (LUAD) based on these genes. The immune and stromal scores were generated by the ESTIMATE algorithm for LUAD patients in The Cancer Genome Atlas (TCGA) database. Differentially expressed gene and weighted gene co-expression network analyses were used to derive immune- and stromal-related genes. The Least Absolute Shrinkage and Selection Operator (LASSO)-Cox regression was applied for further selection and the selected genes were inputted into stepwise regression to develop TME-related risk score (TMErisk) which was further validated in Gene Expression Omnibus (GEO) datasets. TMErisk-related biological phenotypes were analyzed in function enrichment, tumor immune signature, and tumor mutation signature. The patient’s response to immunotherapy was inferred by the tumor immune dysfunction and exclusion (TIDE) score and immunophenoscore (IPS). According to our results, TMErisk was developed based on SERPINE1, CX3CR1, CD200R1, GBP1, IRF1, STAP1, LOX, and OR7E47P. Furthermore, high TMErisk was identified as a poor factor for OS in TCGA and GEO datasets, as well as in subgroup analysis with different gender, smoking status, age, race, anatomic site, therapies, and tumor-node-metastasis (TNM) stages. Higher TMErisk is also associated negatively with the abundance of B cells, CD4+ T cells, CD8+ T cells, neutrophils, macrophages, and other stromal or immune cells. Several genes of the human leukocyte antigen (HLA) family and immune checkpoints were less expressed in the high-TMErisk group. Mutations of 19 genes occurred more frequently in the high-TMErisk group. These mutations may be associated with TME change and indicate patients’ response to immunotherapy. According to our analyses, a lower TMErisk score may indicate better response and OS outcome of immunotherapy.