In Situ-Grown 2D Perovskite Based on π-Conjugated Aggregation-Induced Emission Organic Spacer Boosting the Efficiency and Stability of 2D-3D Heterostructured Perovskite Solar Cells.

The two-dimensional-three-dimensional (2D-3D) heterostructured perovskite solar cells (PSCs) have drawn widespread interest, wherein the organic spacer plays a significant role in the photovoltaic performance. Herein, a novel π-conjugated organic spacer with the aggregation-induced emission (AIE) property, (Z)-2-([1,1'-biphenyl]-4-yl)-3-(5-(4-(3-aminopropoxy)phenyl)thiophen-2-yl)acrylonitrile (BPCSA-S), is designed and synthesized, which is successfully applied for the in situ construction of 2D-3D heterostructured PSCs via the two-step solution method. By virtue of the functional groups (i.e., cyano, thiophene, and amino) in BPCSA-S, the BPCSA-S organic spacer can trigger the in situ growth of 2D perovskites, which will serve as the template for the heteroepitaxial growth of 3D perovskites, thus obtaining a 2D-3D heterostructured film with high-quality and few defects. More pleasingly, benefiting from the AIE property and delocalized π-electrons in the π-conjugated BPCSA-S organic spacer, excellent photosensitization process and carrier transport can be achieved. Consequently, the resultant 2D-3D heterostructured PSCs yield a pleasing PCE of 22.07%, accompanied by mitigatory hysteresis, as well as enhanced stability. Our research shows a hopeful multifunctional organic spacer approach using the novel π-conjugated AIE organic spacer for high-performance PSCs.

Infiltrating characteristics and prognostic value of tertiary lymphoid structures in resected gastric neuroendocrine neoplasm patients.

Objectives: Tertiary lymphoid structures (TLSs) are lymphocyte aggregates that play an anti-tumor role in most solid tumors. However, the functions of TLS in gastric neuroendocrine neoplasms (GNENs) remain unknown. This study aimed to determine the characteristics and prognostic values of TLS in resected GNEN patients. Methods: Haematoxylin-eosin, immunohistochemistry (IHC) and multiple fluorescent IHC staining were used to assess TLS to investigate the correlation between TLSs and clinicopathological characteristics and its prognostic value. Results: Tertiary lymphoid structures were identified in 84.3% of patients with GNEN. They were located in the stromal area or outside the tumor tissue and mainly composed of B and T cells. A high density of TLSs promoted an anti-tumor immune response in GNEN. CD15+ TANs and FOXP3+ Tregs in TLSs inhibited the formation of TLSs. High TLS density was significantly associated with prolonged recurrence-free survival (RFS) and overall survival (OS) of GNENs. Univariate and multivariate Cox regression analyses revealed that TLS density, tumor size, tumor-node-metastasis (TNM) stage and World Health Organisation (WHO) classification were independent prognostic factors for OS, whereas TLS density, tumor size and TNM stage were independent prognostic factors for RFS. Finally, OS and RFS nomograms were developed and validated, which were superior to the WHO classification and the TNM stage. Conclusion: Tertiary lymphoid structures were mainly located in the stromal area or outside the tumor area, and high TLS density was significantly associated with the good prognosis of patients with GNEN. Incorporating TLS density into a nomogram may improve survival prediction in patients with resected GNEN.

Genomic and transcriptomic profiling of combined small-cell lung cancer through microdissection: unveiling the transformational pathway of mixed subtype.

BACKGROUND: Combined small-cell lung carcinoma (cSCLC) represents a rare subtype of SCLC, the mechanisms governing the evolution of cancer genomes and their impact on the tumor immune microenvironment (TIME) within distinct components of cSCLC remain elusive. METHODS: Here, we conducted whole-exome and RNA sequencing on 32 samples from 16 cSCLC cases. RESULTS: We found striking similarities between two components of cSCLC-LCC/LCNEC (SCLC combined with large-cell carcinoma/neuroendocrine) in terms of tumor mutation burden (TMB), tumor neoantigen burden (TNB), clonality structure, chromosomal instability (CIN), and low levels of immune cell infiltration. In contrast, the two components of cSCLC-ADC/SCC (SCLC combined with adenocarcinoma/squamous-cell carcinoma) exhibited a high level of tumor heterogeneity. Our investigation revealed that cSCLC originated from a monoclonal source, with two potential transformation modes: from SCLC to SCC (mode 1) and from ADC to SCLC (mode 2). Therefore, cSCLC might represent an intermediate state, potentially evolving into another histological tumor morphology through interactions between tumor and TIME surrounding it. Intriguingly, RB1 inactivation emerged as a factor influencing TIME heterogeneity in cSCLC, possibly through neoantigen depletion. CONCLUSIONS: Together, these findings delved into the clonal origin and TIME heterogeneity of different components in cSCLC, shedding new light on the evolutionary processes underlying this enigmatic subtype.

Assessment of human leukocyte antigen-based neoantigen presentation to determine pan-cancer response to immunotherapy.

Despite the central role of human leukocyte antigen class I (HLA-I) in tumor neoantigen presentation, quantitative determination of presentation capacity remains elusive. Based on a pooled pan-cancer genomic dataset of 885 patients treated with immune checkpoint inhibitors (ICIs), we developed a score integrating the binding affinity of neoantigens to HLA-I, as well as HLA-I allele divergence, termed the HLA tumor-Antigen Presentation Score (HAPS). Patients with a high HAPS were more likely to experience survival benefit following ICI treatment. Analysis of the tumor microenvironment indicated that the antigen presentation pathway was enriched in patients with a high HAPS. Finally, we built a neural network incorporating factors associated with neoantigen production, presentation, and recognition, which exhibited potential for differentiating cancer patients likely to benefit from ICIs. Our findings highlight the clinical utility of evaluating HLA-I tumor antigen presentation capacity and describe how ICI response may depend on HLA-mediated immunity.

ARID1A deficiency promotes progression and potentiates therapeutic antitumour immunity in hepatitis B virus-related hepatocellular carcinoma.

BACKGROUND: Exploring predictive biomarkers and therapeutic strategies of ICBs has become an urgent need in clinical practice. Increasing evidence has shown that ARID1A deficiency might play a critical role in sculpting tumor environments in various tumors and might be used as pan-cancer biomarkers for immunotherapy outcomes. The current study aims to explored the immune-modulating role of ARID1A deficiency in Hepatitis B virus (HBV) related hepatocellular carcinoma (HBV-HCC) and its potential immunotherapeutic implications. METHODS: In the current study, we performed a comprehensive analysis using bioinformatics approaches and pre-clinical experiments to evaluate the ARID1A regulatory role on the biological behavior, and immune landscape of Hepatitis B virus (HBV) related hepatocellular carcinoma (HBV-HCC). A total of 425 HBV-related hepatocellular carcinoma patients from TCGA-LIHC, AMC and CHCC-HBV cohort were enrolled in bioinformatics analysis. Immunohistochemical staining of HBV-HCC specimens and ARID1A deficiency cellular models were used to validate the results of the analysis. RESULTS: Our results have shown that ARID1A deficiency promoted tumor proliferation and metastasis. More importantly, ARID1A deficiency in HBV-HCC was associated with the higher TMB, elevated immune activity, and up-regulated expression of immune checkpoint proteins, especially TIM-3 in HBV-HCC. Further, the expression of Galectin-9, which is the ligand of TIM-3, was elevated in the ARID1A knockout HBV positive cell line. CONCLUSION: To conclude, we have shown that the ARID1A deficiency was correlated with more active immune signatures and higher expression of immune checkpoints in HBV-HCC. Additionally, the present study provides insights to explore the possibility of the predictive role of ARID1A in HBV-HCC patients responsive to immunotherapy.

A transcriptome based molecular classification scheme for cholangiocarcinoma and subtype-derived prognostic biomarker.

Previous studies on the molecular classification of cholangiocarcinoma (CCA) focused on certain anatomical sites, and disregarded tissue contamination biases in transcriptomic profiles. We aim to provide universal molecular classification scheme and prognostic biomarker of CCAs across anatomical locations. Comprehensive bioinformatics analysis is performed on transcriptomic data from 438 CCA cases across various anatomical locations. After excluding CCA tumors showing normal tissue expression patterns, we identify two universal molecular subtypes across anatomical subtypes, explore the molecular, clinical, and microenvironmental features of each class. Subsequently, a 30-gene classifier and a biomarker (called "CORE-37") are developed to predict the molecular subtype of CCA and prognosis, respectively. Two subtypes display distinct molecular characteristics and survival outcomes. Key findings are validated in external cohorts regardless of the stage and anatomical location. Our study provides a CCA classification scheme that complements the conventional anatomy-based classification and presents a promising prognostic biomarker for clinical application.

Cross-talk between gastric cancer and hepatic stellate cells promotes invadopodia formation during liver metastasis.

In gastric cancer (GC), the liver is a common organ for distant metastasis, and patients with gastric cancer with liver metastasis (GCLM) generally have poor prognosis. The mechanism of GCLM is unclear. Invadopodia are special membrane protrusions formed by tumor cells that can degrade the basement membrane and ECM. Herein, we investigated the role of invadopodia in GCLM. We found that the levels of invadopodia-associated proteins were significantly higher in liver metastasis than in the primary tumors of patients with GCLM. Furthermore, GC cells could activate hepatic stellate cells (HSCs) within the tumor microenvironment of liver metastases through the secretion of platelet-derived growth factor subunit B (PDGFB). Activated HSCs secreted hepatocyte growth factor (HGF), which activated the MET proto-oncogene, MET receptor of GC cells, thereby promoting invadopodia formation through the PI3K/AKT pathway and subsequently enhancing the invasion and metastasis of GC cells. Therefore, cross-talk between GC cells and HSCs by PDGFB/platelet derived growth factor receptor beta (PDGFRß) and the HGF/MET axis might represent potential therapeutic targets to treat GCLM.

Metabolic reprogramming involves in transition of activated/resting CD4+ memory T cells and prognosis of gastric cancer.

Background: Little is known on how metabolic reprogramming potentially prompts transition of activated and resting CD4+ memory T cells infiltration in tumor microenvironment of gastric cancer (GC). The study aimed to evaluate their interactions and develop a risk model for predicting prognosis in GC. Methods: Expression profiles were obtained from TCGA and GEO databases. An immunotherapeutic IMvigor210 cohort was also enrolled. CIBERSORT algorithm was used to evaluate the infiltration of immune cells. The ssGSEA method was performed to assess levels of 114 metabolism pathways. Prognosis and correlation analysis were conducted to identify metabolism pathways and genes correlated with activated CD4+ memory T cells ratio (AR) and prognosis. An AR-related metabolism gene (ARMG) risk model was constructed and validated in different cohorts. Flow cytometry was applied to validate the effect of all-trans retinoic acid (ATRA) on CD4+ memory T cells. Results: Since significantly inverse prognostic value and negative correlation of resting and activated CD4+ memory T cells, high AR level was associated with favorable overall survival (OS) in GC. Meanwhile, 15 metabolism pathways including retinoic acid metabolism pathway were significantly correlated with AR and prognosis. The ARMG risk model could classify GC patients with different outcomes, treatment responses, genomic and immune landscape. The prognostic value of the model was also confirmed in the additional validation, immunotherapy and pan-cancer cohorts. Functional analyses revealed that the ARMG model was positively correlated with pro-tumorigenic pathways. In vitro experiments showed that ATRA could inhibit levels of activated CD4+ memory T cells and AR. Conclusion: Our study showed that metabolic reprogramming including retinoic acid metabolism could contribute to transition of activated and resting CD4+ memory T cells, and affect prognosis of GC patients. The ARMG risk model could serve as a new tool for GC patients by accurately predicting prognosis and response to treatment.

Spatial heterogeneity of T cell repertoire across NSCLC tumors, tumor edges, adjacent and distant lung tissues.

Background: A better understanding of T cells in lung cancer and their distribution across tumor-adjacent lungs and peripheral blood is needed to improve efficacy and minimize toxicity from immunotherapy to lung cancer patients. Methods: Here, we performed CDR3ß TCR sequencing of 136 samples from 20 patients with early-stage NSCLC including peripheral blood mononuclear cells, tumors, tumor edges (<1 cm from tumor), as well as adjacent lungs 1 cm, 2 cm, 5 cm, and 10 cm away from the tumor to gain insight into the spatial heterogeneity of T cells across the lungs in patients with NSCLC. PD-L1, CD4, and CD8 expression was assessed using immunohistochemical staining, and genomic features were derived by targeted sequencing of 1,021 cancer-related genes. Multiplex immunohistochemistry against PD-1, CTLA4, LAG3, and TIM3 was performed on four patients to assess T cell exhaustion. Results: Our study reveals a decreasing gradient in TIL Tumor Infiltrating Lymphocytes homology with tumor edge, adjacent lungs, and peripheral blood but no discernible distance-associated patterns of T cell trafficking within the adjacent lung itself. Furthermore, we show a decrease in pathogen-specific TCRs in regions with high T cell clonality and PD-L1 expression. Conclusions: Exclusion in T exhaustion cells at play across the lungs of patients with NSCLC may potentially be the mechanism for lung cancer occurrence.

Dynamic circulating tumor DNA during chemoradiotherapy predicts clinical outcomes for locally advanced non-small cell lung cancer patients.

The value of circulating tumor DNA (ctDNA) during chemoradiotherapy (CRT) remains unclear but is critical for detecting molecular residual disease (MRD). In this prospective study, we sequenced 761 blood samples from 139 patients with locally advanced non-small cell lung cancer treated with definitive radiation therapy (RT). ctDNA concentrations showed a significantly declining trend as CRT progressed at on-RT and after-RT time points versus baseline. Thirty-eight (27.3%) patients with early undetectable ctDNA at both on-RT (RT reached 40 Gy) and after-RT time points, indicating early response to CRT, had better survival outcomes for both with or without consolidation immune checkpoint inhibitors. Longitudinal undetectable MRD was found in 20.1% patients. The 2-year cancer-specific progression-free survival of these patients was 88.4%, corresponding to a potentially cured population. Further analysis revealed that pretreatment ctDNA variants serve as an essential MRD informed source. These data provide clinical insights for ctDNA-MRD detection.

Dynamic cytokines signature predicts survival outcome from severe Immune-related hepatitis with PD-1/PD-L1 blockade in lung cancer.

BACKGROUND: Immune-related adverse events (irAEs), particularly immune-related hepatitis (IRH) is a potentially serious complication of immune checkpoint inhibitor (ICI) therapy. This retrospective cohort study investigated potential prognostic and predictive biomarkers for IRH. METHOD: This study included 37 patients with advanced lung cancer who received ICIs and were divided into two groups: ≥Grade 3 (G3)-IRH group (n = 17) and without irAE (no-irAE) group (n = 20). Blood samples collected at three different time points and pre-treatment tumor biopsy samples were analyzed using multi-omics assays. RESULTS: The IL-1B RNA expression was significantly increased (limma, fold = 1.94) in the ≥ G3-IRH group than the no-irAE group. Compared with no-irAE group, ≥G3-IRH group had higher monocyte and eosinophil infiltration and lower macrophage infiltration, particularly macrophage M2. Transcriptomics analyses of pre-treatment tumor samples revealed significant upregulation of various inflammation-related genes in the ≥ G3-IRH group (False discovery rate < 0.05). Moreover, various proinflammatory cytokines and chemokines were significantly lower in the plasma of the ≥ G3-IRH group than in the no-irAE group. Subgroup analyses of the ≥ G3-IRH group revealed that plasma IL-1A was significantly higher among those whose IRH resolved than those who had IRH-related death. Patients who died had a greater increase in immune score and Euclidean distance from the baseline to the seventh day of IRH onset, with a dramatic increase in Euclidean distance after immunosuppression, suggesting overstimulated immune status. CONCLUSION: Our study demonstrated the association between IL-1B overexpression and IRH susceptibility. Immune score and Euclidean distance of inflammatory cytokines may provide predictive value on the survival outcome from ≥ G3 IRH.

Prognostic utility of TME-associated genes in pancreatic cancer.

Background: Pancreatic cancer (PC) is a deadly disease. The tumor microenvironment (TME) participates in PC oncogenesis. This study focuses on the assessment of the prognostic and treatment utility of TME-associated genes in PC. Methods: After obtaining the differentially expressed TME-related genes, univariate and multivariate Cox analyses and least absolute shrinkage and selection operator (LASSO) were performed to identify genes related to prognosis, and a risk model was established to evaluate risk scores, based on The Cancer Genome Atlas (TCGA) data set, and it was validated by external data sets from the Gene Expression Omnibus (GEO) and Clinical Proteomic Tumor Analysis Consortium (CPTAC). Multiomics analyses were adopted to explore the potential mechanisms, discover novel treatment targets, and assess the sensitivities of immunotherapy and chemotherapy. Results: Five TME-associated genes, namely, FERMT1, CARD9, IL20RB, MET, and MMP3, were identified and a risk score formula constructed. Next, their mRNA expressions were verified in cancer and normal pancreatic cells. Multiple algorithms confirmed that the risk model displayed a reliable ability of prognosis prediction and was an independent prognostic factor, indicating that high-risk patients had poor outcomes. Immunocyte infiltration, gene set enrichment analysis (GSEA), and single-cell analysis all showed a strong relationship between immune mechanism and low-risk samples. The risk score could predict the sensitivity of immunotherapy and some chemotherapy regimens, which included oxaliplatin and irinotecan. Various latent treatment targets (LAG3, TIGIT, and ARID1A) were addressed by mutation landscape based on the risk model. Conclusion: The risk model based on TME-related genes can reflect the prognosis of PC patients and functions as a novel set of biomarkers for PC therapy.

Immune characteristics associated with lymph node metastasis in early-stage NSCLC.

PURPOSE: Tumor metastasis significantly impacts the prognosis of non-small cell lung cancer (NSCLC) patients, with lymph node (LN) metastasis being the most common and early form of spread. With the development of adjuvant immunotherapy, increasing attention has been paid to the tumor-draining lymph nodes（TDLN) in early-stage NSCLC, especially tumor-metastatic lymph nodes, which provides poor prognostic information but has potential benefits in adjuvant treatment. METHODS: We showed the remodeled immune environment in TDLNs through using TCR-seq to analyse 24 primary lung cancer tissues and 134 LNs from 24 lung cancer patients with or without LN metastasis. Additionally, we characterized the spatial profiling of immunocytes and tumor cells in TDLNs and primary tumor sites through using multi-IHC. RESULTS: We found the remodeled immune environment in TDLNs through analyzing primary lung cancer tissues and LNs from NSCLC patients with or without LN metastasis. Considering the intricate communication between tumor and immunocytes, we further subdivided TDLNs, revealing that metastasis-negative LNs from LN-metastatic patients (MNLN) exhibited greater immune activation, exhaustion, and memory in comparison to both metastasis-positive LNs (MPLN) and TDLNs from non-LN-metastatic patients (NMLN). CONCLUSIONS: Our data indicate that LN metastasis facilitated tumor-specific antigen presentation in TDLNs and induces T cell priming, while existing tumor cells generate an immune-suppressive environment in MPLNs through multiple mechanisms. These findings contribute to a comprehensive understanding of the immunological mechanisms through which LN metastasis influences tumor progression and plays a role in immunotherapy for NSCLC patients.

Prognostic and predictive impact of molecular tumor burden index in non-small cell lung cancer patients.

BACKGROUND: The biomarkers of immune checkpoint inhibitors in the treatment of non-small cell lung cancer (NSCLC) patients have limited predictive performance. In this study we aimed to investigate the feasibility of molecular tumor burden index (mTBI) in circulating tumor DNA (ctDNA) as a predictor for immunotherapy in patients with NSCLC. METHODS: From February 2017 to November 2020, pretreatment and on-treatment (3~6 weeks after first cycle of immunotherapy) dynamic plasma ctDNA samples from NSCLC patients receiving immune monotherapy or combination therapy were analyzed by targeted capture sequencing of 1021 genes. PyClone was used to infer the mTBI. The impact of pretreatment mTBI on survival outcomes was verified in the POPLAR/OAK trials. RESULTS: We found that patients without detectable baseline ctDNA had better survival outcomes (median overall survival [OS]: not reached vs. 12.8 months; hazard ratio [HR], 0.15; p = 0.035]). RB1 and SMARCA4 mutations were remarkably associated with worse survival outcomes. Furthermore, lower pretreatment mTBI was associated with superior OS (median: not reached vs. 8.1 months; HR, 0.22; p = 0.024) and PFS (median: 32.9 vs. 5.4 months; HR, 0.35; p = 0.045), but not objective response, which was validated in the POPLAR/OAK cohort, suggesting that baseline mTBI was a prognostic factor for NSCLC immunotherapy. Early dynamic changes of mTBI (ΔmTBI) significantly distinguished responsive patients, and patients with mTBI decrease to more than 68% at the final tumor evaluation had longer OS (median: 38.2 vs. 4.0 months; HR, 0.18; p = 0.017) and PFS (median: not reached vs. 2.3 months; HR, 0.24; p = 0.030). CONCLUSION: ΔmTBI had a good sensitivity to identify potential beneficial patients based on the best effect CT scans, demonstrating that mTBI dynamics were predictive of benefit from immune checkpoint blockade.

DELFMUT: duplex sequencing-oriented depth estimation model for stable detection of low-frequency mutations.

Duplex sequencing technology has been widely used in the detection of low-frequency mutations in circulating tumor deoxyribonucleic acid (DNA), but how to determine the sequencing depth and other experimental parameters to ensure the stable detection of low-frequency mutations is still an urgent problem to be solved. The mutation detection rules of duplex sequencing constrain not only the number of mutated templates but also the number of mutation-supportive reads corresponding to each forward and reverse strand of the mutated templates. To tackle this problem, we proposed a Depth Estimation model for stable detection of Low-Frequency MUTations in duplex sequencing (DELFMUT), which models the identity correspondence and quantitative relationships between templates and reads using the zero-truncated negative binomial distribution without considering the sequences composed of bases. The results of DELFMUT were verified by real duplex sequencing data. In the case of known mutation frequency and mutation detection rule, DELFMUT can recommend the combinations of DNA input and sequencing depth to guarantee the stable detection of mutations, and it has a great application value in guiding the experimental parameter setting of duplex sequencing technology.

Collagen-related gene expression level predicts the prognosis and immune therapy response.

BACKGROUND: Gastric cancer patients responded differently to the same treatment strategy and had various prognoses for the lack of biomarkers to guide the therapy choice. METHODS: RNA data of a local gastric cancer cohort with 103 patients were processed and used to explore potential treatment guiding factors. Cluster analysis was performed by non-negative matrix factorization. The expression level of collagen-related genes was evaluated by ssGSEA named collagen score (CS). Data from TCGA, ACRG, and an immune therapy cohort were utilized to explore prognosis and efficacy. Prognostic predictive power of CS was assessed using the nomogram. RESULTS: In our study, local RNA data were processed by cluster analysis, and it was found that cluster 2 contained a worse tumor infiltration status. The GSEA result showed that collagen-related pathways were differentially activated in two clusters. In TCGA and ACRG cohorts, the CS can be used as an independent prognostic factor (TCGA OS: p = 0.018, HR = 3.5; ACRG OS: p = 0.014, HR = 4.88). An immunotherapy cohort showed that the patients with higher CS had a significantly worse ORR (p = 0.0025). The high CS group contained several cell death pathways down-regulated and contained the worse tumor microenvironment. The nomogram demonstrated the survival prediction capability of collagen score. CONCLUSION: CS was verified as an independent prognostic factor and potentially reflected the therapeutic effect of immunotherapy. The CS could provide a new way to evaluate the clinical prognosis and response information helping develop the collagen-targeted treatment.

Stratification of non-small cell lung adenocarcinoma patients with EGFR actionable mutations based on drug-resistant stem cell genes.

EGFR-TKIs were used in NSCLC patients with actionable EGFR mutations and prolong prognosis. However, most patients treated with EGFR-TKIs developed resistance within around one year. This suggests that residual EGFR-TKIs resistant cells may eventually lead to relapse. Predicting resistance risk in patients will facilitate individualized management. Herein, we built an EGFR-TKIs resistance prediction (R-index) model and validate in cell line, mice, and cohort. We found significantly higher R-index value in resistant cell lines, mice models and relapsed patients. Patients with an elevated R-index had significantly shorter relapse time. We also found that the glycolysis pathway and the KRAS upregulation pathway were related to EGFR-TKIs resistance. MDSC is a significant immunosuppression factor in the resistant microenvironment. Our model provides an executable method for assessing patient resistance status based on transcriptional reprogramming and may contribute to the clinical translation of patient individual management and the study of unclear resistance mechanisms.

Heterogeneity of tumor immune microenvironment of EGFR/ALK-positive tumors versus EGFR/ALK-negative tumors in resected brain metastases from lung adenocarcinoma.

BACKGROUND: Previous studies found that lung adenocarcinomas (LUAD) with EGFR-positive and ALK-positive were less responsive to immunotherapy, which may be associated with a suppressive tumor immune microenvironment (TIME). Given the discordance in the TIME between primary lung cancer and brain metastasis, it is urgent to explore the TIME in patients with EGFR/ALK-positive LUAD with brain metastases (BMs). METHODS: The transcriptome feature of formalin-fixed and paraffin-embedded samples of BMs and paired primary LUAD from 70 patients with LUAD BMs was illustrated by RNA-sequencing. Six of them were available for paired sample analysis. Then, after excluding 3 co-occurring patients, we divided 67 BMs patients into 41 EGFR/ALK-positive and 26 EGFR/ALK-negative patients. The differences in immune profiling between the two groups were analyzed from three dimensions: TIME, T-cell receptor repertoire, and immunohistochemistry. Finally, the survival data of 55 patients were collected. RESULTS: Compared with primary LUAD, BMs present an immunosuppressed TIME, manifested as: inhibition of immune-related pathways; low expression of immune checkpoint; decreased infiltration of CD8+T cells and cytotoxic lymphocyte; increased proportion of suppressive M2 macrophages. In different subgroups based on EGFR/ALK gene variation status, both EGFR-positive and ALK-positive tumors present a relatively immunosuppressive microenvironment, but the heterogeneity of tumor microenvironment may undergo different mechanisms. EGFR-positive BMs showed decreased CD8+T cells and increased regulatory T cells (Treg) cells, while ALK-positive BMs showed decreased CD8+T cells and increased M2 macrophages. Moreover, in the TCGA-LUAD cohort, EGFR-positive tumors showed reduced CD8+T cell infiltrations (p<0.001) and borderline significantly higher Tregs than EGFR/ALK-negative (p=0.072). In parallel, ALK-positive tumors had higher median M2 macrophages infiltrations than EGFR/ALK-negative (p=0.175), although there was no statistical significance. Collectively, there was a similar immunosuppressive milieu between EGFR/ALK-positive primary LUAD and BMs. Moreover, survival analysis uncovered higher CD8A expression, cytotoxic lymphocyte infiltration, and immune scores were significantly associated with better prognosis in both EGFR/ALK-positive and EGFR/ALK-negative groups. CONCLUSION: This study found that LUAD-derived BMs exhibited an immunosuppressive TIME and revealed that EGFR-positive and ALK-positive BMs exhibited different immunosuppressive characteristics. Meanwhile, EGFR-negative BMs showed a potential benefit to immunotherapy. These findings boost molecular and clinical understanding of LUAD BMs.