Joint DNA-RNA-based NGS for diagnosis and treatment of a rare CD47-MET fusion lung adenocarcinoma which was immunoresistant and savoltinib-sensitive: a case report.

Targeted therapy and immunotherapy are both important in the treatment of non-small-cell lung cancer (NSCLC). Accurate diagnose and precise treatment are key in achieving long survival of patients. MET fusion is a rare oncogenic factor, whose optimal detection and treatment are not well established. Here, we report on a 32-year-old female lung adenocarcinoma patient with positive PD-L1 and negative driver gene detected by DNA-based next-generation sequencing (NGS). A radical resection of the primary lesion after chemotherapy combined with PD-1 checkpoint inhibitor administration indicated primary immuno-resistance according to her pathological response and rapid relapse. A rare CD47-MET was detected by RNA-based NGS, which was confirmed by fluorescence in situ hybridization. Multiplex immunofluorescence revealed a PD-L1 related heterogeneous immunosuppressive microenvironment with little distribution of CD4+ T cells and CD8+ T cells. Savolitinib therapy resulted in a progression-free survival (PFS) of >12 months, until a new secondary resistance mutation in MET p.D1228H was detected by re-biopsy and joint DNA-RNA-based NGS after disease progression. In this case, CD47-MET fusion NSCLC was primarily resistant to immunotherapy, sensitive to savolitinib, and developed secondary MET p.D1228H mutation after targeted treatment. DNA-RNA-based NGS is useful in the detection of such molecular events and tracking of secondary mutations in drug resistance. To this end, DNA-RNA-based NGS may be of better value in guiding precise diagnosis and individualized treatment in this patient population.

Advancing lung adenocarcinoma prognosis and immunotherapy prediction with a multi-omics consensus machine learning approach.

Lung adenocarcinoma (LUAD) is a tumour characterized by high tumour heterogeneity. Although there are numerous prognostic and immunotherapeutic options available for LUAD, there is a dearth of precise, individualized treatment plans. We integrated mRNA, lncRNA, microRNA, methylation and mutation data from the TCGA database for LUAD. Utilizing ten clustering algorithms, we identified stable multi-omics consensus clusters (MOCs). These data were then amalgamated with ten machine learning approaches to develop a robust model capable of reliably identifying patient prognosis and predicting immunotherapy outcomes. Through ten clustering algorithms, two prognostically relevant MOCs were identified, with MOC2 showing more favourable outcomes. We subsequently constructed a MOCs-associated machine learning model (MOCM) based on eight MOCs-specific hub genes. Patients characterized by a lower MOCM score exhibited better overall survival and responses to immunotherapy. These findings were consistent across multiple datasets, and compared to many previously published LUAD biomarkers, our MOCM score demonstrated superior predictive performance. Notably, the low MOCM group was more inclined towards 'hot' tumours, characterized by higher levels of immune cell infiltration. Intriguingly, a significant positive correlation between GJB3 and the MOCM score (R = 0.77, p < 0.01) was discovered. Further experiments confirmed that GJB3 significantly enhances LUAD proliferation, invasion and migration, indicating its potential as a key target for LUAD treatment. Our developed MOCM score accurately predicts the prognosis of LUAD patients and identifies potential beneficiaries of immunotherapy, offering broad clinical applicability.

Comprehensive analysis and identification of subtypes and hub genes of high immune response in lung adenocarcinoma.

BACKGROUND: The advent of immunotherapy targeting immune checkpoints has conferred significant clinical advantages to patients with lung adenocarcinoma (LUAD); However, only a limited subset of patients exhibit responsiveness to this treatment. Consequently, there is an imperative need to stratify LUAD patients based on their response to immunotherapy and enhance the therapeutic efficacy of these treatments. METHODS: The differentially co-expressed genes associated with CD8 + T cells were identified through weighted gene co-expression network analysis (WGCNA) and the Search Tool for the Retrieval of Interacting Genes (STRING) database. These gene signatures facilitated consensus clustering for TCGA-LUAD and GEO cohorts, categorizing them into distinct immune subtypes (C1, C2, C3, and C4). The Tumor Immune Dysfunction and Exclusion (TIDE) model and Immunophenoscore (IPS) analysis were employed to assess the immunotherapy response of these subtypes. Additionally, the impact of inhibitors targeting five hub genes on the interaction between CD8 + T cells and LUAD cells was evaluated using CCK8 and EDU assays. To ascertain the effects of these inhibitors on immune checkpoint genes and the cytotoxicity mediated by CD8 + T cells, flow cytometry, qPCR, and ELISA methods were utilized. RESULTS: Among the identified immune subtypes, subtypes C1 and C3 were characterized by an abundance of immune components and enhanced immunogenicity. Notably, both C1 and C3 exhibited higher T cell dysfunction scores and elevated expression of immune checkpoint genes. Multi-cohort analysis of Lung Adenocarcinoma (LUAD) suggested that these subtypes might elicit superior responses to immunotherapy and chemotherapy. In vitro experiments involved co-culturing LUAD cells with CD8 + T cells and implementing the inhibition of five pivotal genes to assess their function. The inhibition of these genes mitigated the immunosuppression on CD8 + T cells, reduced the levels of PD1 and PD-L1, and promoted the secretion of IFN-γ and IL-2. CONCLUSIONS: Collectively, this study delineated LUAD into four distinct subtypes and identified five hub genes correlated with CD8 + T cell activity. It lays the groundwork for refining personalized therapy and immunotherapy strategies for patients with LUAD.

[Intraperitoneal injection of human-derived anti-c-Met single-chain antibody inhibits the growth of transplanted tumours in A549 lung adenocarcinoma-loaded mice].

Objective To verify the anti-tumor effect of the mesenchymal-epithelial transition single-chain antibody (Met scFv) on subcutaneously transplanted tumors in nude mice. Methods A tumor model was established in nude mice by subcutaneous injection of A549 lung adenocarcinoma cells. Once the tumors were formed, IRDye680 LT N-hydroxysuccinimide (NHS) ester-labeled Met scFv was administered intraperitoneally. Real-time monitoring was conducted using a small animal imager to observe the dynamic distribution of the antibody in tumor-bearing mice. The affinity between c-Met and the antibody in tumor cells was detected. Tumor volume changes were observed and the tumor growth curve were plotted following regular tail vein injections of Met scFv. Immunohistochemical staining was employed to determine whether Met scFv could effectively bind to the c-Met antigen in tumor tissues. Results The distribution of Met scFv in nude mice showed that it was primarily located in the peritoneal cavity within the first 3 hours. After approximately 48 hours, fluorescent signals began to accumulate in the tumor tissue. Immunohistochemical staining of the tumors revealed high expression of c-Met in the tumor tissues; regular tail vein injections of Met scFv significantly slowed down the growth of tumors in mice. Conclusion Met scFv specifically recognizes tumor cells in vivo and exhibites significant anti-tumor activity.

FKBP3, a poor prognostic indicator, promotes the progression of LUAD via regulating ferroptosis and immune infiltration.

BACKGROUND: Ferroptosis was reported to possess the therapeutic potentials in various human cancers. In the present study, we explored the expression, clinical significance and the molecular mechanism of FK506 binding protein 3 (FKBP3) in the progression of lung adenocarcinoma (LUAD). MATERIAL AND METHOD: Cox regression was performed to obtain the prognosis related to differentially expressed genes (DEGs) in LUAD datasets from TCGA. We also downloaded the ferroptosis-related gene datasets from GeneCards. Venn diagram was performed to find the intersecting genes and FKBP3 was selected as the targeted gene by analyzing the diagnostic and prognostic values of Top10 intersecting genes. Moreover, univariate and multivariate analyses were performed to evaluate the association between clinicopathological factors and survival rates. GO/KEGG and GSEA analysis was performed to explore the function of FKBP3 in LUAD progression. Protein-protein interaction (PPI) network was performed via STRING database and the top10 hub genes were selected. Finally, the relationship between FKBP3 and immune infiltration was explored by ssGSEA analysis. RESULTS: Firstly, 184 genes associated with the prognosis of LUAD and ferroptosis were obtained. FKBP3 was found to be significantly associated with a poor overall survival rate of LUAD patients. Immunohistochemical staining results showed that FKBP3 was highly located in cytoplasm and membrane of cells in LUAD tissues. PPI network analysis results showed that HDAC1, YY1, HDAC2, MTOR, PSMA3, PIN1, NCL, C14orf166, PIN4, and LARP6 were the top10 hub genes. Furthermore, spearman analysis results showed that the expression of FKBP3 was positively correlated with the abundance of Th2 cells and T helper cells. CONCLUSION: High level of FKBP3 was associated with poor prognostic outcomes of LUAD patients, which also inhibited immune infiltration in LUAD tissues. Additionally, FKBP3 was involved in regulating the ferroptosis process in LUAD patients. Thus, FKBP3 possessed the tumor promotion role might be involving in regulating ferroptosis and immune infiltration in LUAD progression.

The deubiquitinase USP2a promotes tumor immunosuppression by stabilizing immune checkpoint B7-H4 in lung adenocarcinoma harboring EGFR-activating mutants.

B7-H4 is an immune checkpoint crucial for inhibiting CD8+ T-cell activity. A clinical trial is underway to investigate B7-H4 as a potential immunotherapeutic agent. However, the regulatory mechanism of B7-H4 degradation via the ubiquitin-proteasome pathway (UPP) remains poorly understood. In this study, we discovered that proteasome inhibitors effectively increased B7-H4 expression, while EGFR-activating mutants promoted B7-H4 expression through the UPP. We screened B7-H4 binding proteins by co-immunoprecipitation and mass spectrometry and found that USP2a acted as a deubiquitinase of B7-H4 by removing K48- and K63-linked ubiquitin chains from B7-H4, leading to a reduction in B7-H4 degradation. EGFR mutants enhanced B7-H4 stability by upregulating USP2a expression. We further investigated the role of USP2a in tumor growth in vivo. Depletion of USP2a in L858R/LLC cells inhibited tumor cell proliferation, consequently suppressing tumor growth in immune-deficient nude mice by destabilizing downstream molecules such as Cyclin D1. In an immune-competent C57BL/6 mouse tumor model, USP2a abrogation facilitated infiltration of CD95+CD8+ effector T cells and hindered infiltration of Tim-3+CD8+ and LAG-3+CD8+ exhausted T cells by destabilizing B7-H4. Clinical lung adenocarcinoma samples showed a significant correlation between B7-H4 abundance and USP2a expression, indicating the contribution of the EGFR/USP2a/B7-H4 axis to tumor immunosuppression. In summary, this study elucidates the dual effects of USP2a in tumor growth by stabilizing Cyclin D1, promoting tumor cell proliferation, and stabilizing B7-H4, contributing to tumor immunosuppression. Therefore, USP2a represents a potential target for tumor therapy.

Pan-cancer analysis of PSCA that is associated with immune infiltration and affects patient prognosis.

Prostate stem cell antigen (PSCA) is associated with disease progression, promotion of angiogenesis, invasion, metastasis and immune evasion in cancer. However, its expression pattern and diagnostic and prognostic potential have not been thoroughly analysed from a pan-cancer perspective. This study aimed to examine the effects of PSCA on the prognosis and inflammatory cell infiltration patterns of various cancer types. We analysed the relationship between PSCA expression and immunological subtypes in tumor microenvironment (TME) and the role of molecular subtypes, potentially promising immune biomarkers and tumour-infiltrating lymphocytes (TILs) in various cancer types, especially lung adenocarcinoma (LUAD). In addition, we investigated the prognostic significance of PSCA expression in LUAD. The co-expression network of PSCA was found to be mainly involved in the regulation of immune responses and antigen processing and expression and was significantly enriched in pathological and substance metabolism-related pathways in cancer. Altogether, this study reveals that PSCA is a promising target for immunotherapy in patients with cancer.

Ultrasensitive PD-L1-Expressing Exosome Immunosensors Based on a Chemiluminescent Nickel-Cobalt Hydroxide Nanoflower for Diagnosis and Classification of Lung Adenocarcinoma.

Programmed death ligand-1 (PD-L1)-expressing exosomes are considered a potential marker for diagnosis and classification of lung adenocarcinoma (LUAD). There is an urgent need to develop highly sensitive and accurate chemiluminescence (CL) immunosensors for the detection of PD-L1-expressing exosomes. Herein, N-(4-aminobutyl)-N-ethylisopropanol-functionalized nickel-cobalt hydroxide (NiCo-DH-AA) with a hollow nanoflower structure as a highly efficient CL nanoprobe was synthesized using gold nanoparticles as a "bridge". The resulting NiCo-DH-AA exhibited a strong and stable CL emission, which was ascribed to the exceptional catalytic capability and large specific surface area of NiCo-DH, along with the capacity of AuNPs to facilitate free radical generation. On this basis, an ultrasensitive sandwich CL immunosensor for the detection of PD-L1-expressing exosomes was constructed by using PD-L1 antibody-modified NiCo-DH-AA as an effective signal probe and rabbit anti-CD63 protein polyclonal antibody-modified carboxylated magnetic bead as a capture platform. The immunosensor demonstrated outstanding analytical performance with a wide detection range of 4.75 × 103-4.75 × 108 particles/mL and a low detection limit of 7.76 × 102 particles/mL, which was over 2 orders of magnitude lower than the reported CL method for detecting PD-L1-expressing exosomes. Importantly, it was able to differentiate well not only between healthy persons and LUAD patients (100% specificity and 87.5% sensitivity) but also between patients with minimally invasive adenocarcinoma and invasive adenocarcinoma (92.3% specificity and 52.6% sensitivity). Therefore, this study not only presents an ultrasensitive and accurate diagnostic method for LUAD but also offers a novel, simple, and noninvasive approach for the classification of LUAD.

Overexpression of Malat1 drives metastasis through inflammatory reprogramming of the tumor microenvironment.

Expression of the long noncoding RNA (lncRNA) metastasis-associated lung adenocarcinoma transcript 1 (MALAT1) correlates with tumor progression and metastasis in many tumor types. However, the impact and mechanism of action by which MALAT1 promotes metastatic disease remain elusive. Here, we used CRISPR activation (CRISPRa) to overexpress MALAT1/Malat1 in patient-derived lung adenocarcinoma (LUAD) cell lines and in the autochthonous K-ras/p53 LUAD mouse model. Malat1 overexpression was sufficient to promote the progression of LUAD to metastatic disease in mice. Overexpression of MALAT1/Malat1 enhanced cell mobility and promoted the recruitment of protumorigenic macrophages to the tumor microenvironment through paracrine secretion of CCL2/Ccl2. Ccl2 up-regulation was the result of increased global chromatin accessibility upon Malat1 overexpression. Macrophage depletion and Ccl2 blockade counteracted the effects of Malat1 overexpression. These data demonstrate that a single lncRNA can drive LUAD metastasis through reprogramming of the tumor microenvironment.

Disulfidptosis-related lncRNAs signature predicting prognosis and immunotherapy effect in lung adenocarcinoma.

PURPOSE: Lung adenocarcinoma (LUAD) is a prevalent malignant tumor worldwide, with high incidence and mortality rates. However, there is still a lack of specific and sensitive biomarkers for its early diagnosis and targeted treatment. Disulfidptosis is a newly identified mode of cell death that is characteristic of disulfide stress. Therefore, exploring the correlation between disulfidptosis-related long non-coding RNAs (DRGs-lncRNAs) and patient prognosis can provide new molecular targets for LUAD patients. METHODS: The study analysed the transcriptome data and clinical data of LUAD patients in The Cancer Genome Atlas (TCGA) database, gene co-expression, and univariate Cox regression methods were used to screen for DRGs-lncRNAs related to prognosis. The risk score model of lncRNA was established by univariate and multivariate Cox regression models. TIMER, CIBERSORT, CIBERSORT-ABS, and other methods were used to analyze immune infiltration and further evaluate immune function analysis, immune checkpoints, and drug sensitivity. Real-time polymerase chain reaction (RT-PCR) was performed to detect the expression of DRGs-lncRNAs in LUAD cell lines. RESULTS: A total of 108 lncRNAs significantly associated with disulfidptosis were identified. A prognostic model was constructed by screening 10 lncRNAs with independent prognostic significance through single-factor Cox regression analysis, LASSO regression analysis, and multiple-factor Cox regression analysis. Survival analysis of patients through the prognostic model showed that there were obvious survival differences between the high- and low-risk groups. The risk score of the prognostic model can be used as an independent prognostic factor independent of other clinical traits, and the risk score increases with stage. Further analysis showed that the prognostic model was also different from tumor immune cell infiltration, immune function, and immune checkpoint genes in the high- and low-risk groups. Chemotherapy drug susceptibility analysis showed that high-risk patients were more sensitive to Paclitaxel, 5-Fluorouracil, Gefitinib, Docetaxel, Cytarabine, and Cisplatin. Additionally, RT-PCR analysis demonstrated differential expression of DRGs-lncRNAs between LUAD cell lines and the human bronchial epithelial cell line. CONCLUSIONS: The prognostic model of DRGs-lncRNAs constructed in this study has certain accuracy and reliability in predicting the survival prognosis of LUAD patients, and provides clues for the interaction between disulfidptosis and LUAD immunotherapy.

Identification of JUN gene and cellular microenvironment in response to PD-1 blockade treatment in lung cancer patients via single-cell RNA sequencing.

Exploring the molecular mechanisms of PD-1/PDL-1 blockade for non-small cell lung cancer (NSCLC) would facilitate understanding for tumor microenvironment (TME) and development of individualized medicine. To date, biomarkers of response to PD-1 blockade therapy were still limited. In this study, we hypothesize that cell type in the tumor microenvironment can influence the effect of PD-1 blockade immunotherapy through specific genes. Therefore, we re-analyze the single-cell RNA sequencing data and validation in tissue from lung adenocarcinoma patients. Dynamic changes of cellular subpopulation were observed after anti-PD-1 immunotherapy among TMEs between primary/metastasis or good/poor response patients. Non-exhausted CD8 T cells and dysregulated genes were observed in responsing patients from PD-1 blockade therapy. Among all changed genes, JUN, involved in PD-1 blockade immunotherapy pathway, and could be considered as a PD-1 responsing biomarker.

The immune microenvironment of lung adenocarcinoma featured with ground-glass nodules.

Early-stage lung cancer is now more commonly identified in the form of ground-glass nodules (GGNs). Presently, the treatment of lung cancer with GGNs mainly depends on surgery; however, issues still exist such as overtreatment and delayed treatment due to the nonuniform standard of follow-up. Therefore, the discovery of a noninvasive treatment could expand the treatment repertoire of ground-glass nodular lung cancer and benefit the prognosis of patients. Immunotherapy has recently emerged as a new promising approach in the field of lung cancer treatment. Thus, this study presents a comprehensive review of the immune microenvironment of lung cancer with GGNs and describes the functions and characteristics of various immune cells involved, aiming to provide guidance for the clinical identification of novel immunotherapeutic targets.

Identifying and assessing a prognostic model based on disulfidptosis-related genes: implications for immune microenvironment and tumor biology in lung adenocarcinoma.

Introduction: Lung cancer, with the highest global mortality rate among cancers, presents a grim prognosis, often diagnosed at an advanced stage in nearly 70% of cases. Recent research has unveiled a novel mechanism of cell death termed disulfidptosis, which is facilitated by glucose scarcity and the protein SLC7A11. Methods: Utilizing the least absolute shrinkage and selection operator (LASSO) regression analysis combined with Cox regression analysis, we constructed a prognostic model focusing on disulfidptosis-related genes. Nomograms, correlation analyses, and enrichment analyses were employed to assess the significance of this model. Among the genes incorporated into the model, CHRNA5 was selected for further investigation regarding its role in LUAD cells. Biological functions of CHRNA5 were assessed using EdU, transwell, and CCK-8 assays. Results: The efficacy of the model was validated through internal testing and an external validation set, with further evaluation of its robustness and clinical applicability using a nomogram. Subsequent correlation analyses revealed associations between the risk score and infiltration of various cancer types, as well as oncogene expression. Enrichment analysis also identified associations between the risk score and pivotal biological processes and KEGG pathways. Our findings underscore the significant impact of CHRNA5 on LUAD cell proliferation, migration, and disulfidptosis. Conclusion: This study successfully developed and validated a robust prognostic model centered on disulfidptosis-related genes, providing a foundation for predicting prognosis in LUAD patients.

Insights into the heterogeneity of the tumor microenvironment in lung adenocarcinoma and squamous carcinoma through single-cell transcriptomic analysis: Implications for distinct immunotherapy outcomes.

BACKGROUND: Immune checkpoint blockade has emerged as a key strategy to the therapy landscape of non-small cell lung cancer (NSCLC). However, notable differences in immunotherapeutic outcomes exist between the two primary NSCLC subtypes: lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC). This disparity may stem from the tumor immune microenvironment's heterogeneity at the transcriptome level. METHODS: By integrative analysis of transcriptomic characterization of 38 NSCLC patients by single-cell RNA sequencing, the present study revealed a distinct tumor microenvironment (TME) between LUAD and LUSC, with relevant results further confirmed in bulk transcriptomic and multiplex immunofluorescence (mIF) validation cohort of neoadjuvant immunotherapy patients. RESULTS: LUAD exhibited a more active immune microenvironment compared to LUSC. This included highly expression of HLA I/II in cancer cells, reinforced antigen presentation potential of dendritic cells and enhanced cytotoxic activity observed in T/NK cells. In LUSC, cancer cells highly expressed genes belonging to the aldo-keto reductases, glutathione S-transferases and aldehyde dehydrogenase family, negatively correlating with immunotherapy outcomes in the validation cohort of our center. Further analysis revealed elevated infiltrated cancer-associated fibroblasts (CAFs) in LUSC, which was corroborated in The Cancer Genome Atlas cohort. Corresponding increased infiltration of ADH1B+ CAFs in major pathologic response (MPR) patients and the higher presence of FAP+ CAFs in non-MPR patients were demonstrated by multiplex mIF. Moreover, upregulating immunosuppressive extracellular matrix remodeling was identified in LUSC. CONCLUSIONS: These comprehensive analyses advance the understanding of the differences in TME between LUAD and LUSC, offering insights for patient selection and developing subtype-specific treatment strategies.

The predictive value of E2F7 in immunotherapy efficacy for lung adenocarcinoma: An observational study.

Lung adenocarcinoma (LUAD) is the most common pathological type of lung cancer. In recent years, immunotherapy has greatly changed the treatment pattern of advanced LUAD. However, only a small proportion of LUAD patients benefitted from immune checkpoint inhibitor therapy. There is an urgent need to develop a biomarker to predict immune therapy response. E2F7 has been shown to be closely related to immune cell infiltration and immune checkpoint expression in tumors. However, it is unclear whether the E2F7 expression is related to the immunotherapy efficacy in LUAD. Therefore, we conducted this study to investigate the clinical characteristics, function, and immunotherapy responsiveness of E2F7 expression, and to explore the potential of E2F7 as an immunotherapy response biomarker in LUAD. We analyzed the clinical characteristics and biological function of E2F7 expression based on data from the Cancer Genome Atlas and Gene Expression Omnibus database. In addition, we used single-cell sequencing data to analyze the immune regulatory effects of E2F7 in LUAD. Furthermore, we analyzed the immunotherapy response prediction ability of E2F7 expression based on the immunotherapy database. Compared to normal lung tissue, E2F7 was specifically overexpressed in LUAD, and its expression was associated with higher malignancy and poor efficacy. E2F7 high expression was an independent risk factor affecting the prognosis of LUAD. E2F7 was enriched in cell division and cell cycle functions. In addition, the expressions of immune checkpoints were correlated with the E2F7 expression. E2F7 was highly expressed in myeloid cells, and E2F7 highly expressed myeloid cells were associated with immune and inflammatory responses. Moreover, the expression level of E2F7 can effectively distinguish different immune therapy responses in LUAD patients. E2F7 was upregulated in LUAD, and high expression of E2F7 was associated with higher malignancy and poor efficacy. E2F7 high expression was an independent risk factor affecting the prognosis of LUAD. Moreover, E2F7 may exert its immunosuppressive effect by affecting the function of myeloid cells. These results indicated the potential role of E2F7 as a biomarker for predicting LUAD immunotherapy responses.

Identification of PSMD11 as a novel cuproptosis- and immune-related prognostic biomarker promoting lung adenocarcinoma progression.

BACKGROUND: Due to the unfavorable prognosis associated with lung adenocarcinoma (LUAD), the development of targeted therapies and immunotherapies is essential. Cuproptosis, an emerging form of regulated cell death, is implicated in mitochondrial metabolism and is induced by copper ions. This study aimed to explore the prognostic value of cuproptosis- and immune-related genes (CIRGs) in LUAD. METHODS: We used The Cancer Genome Atlas database to develop a prognostic prediction model for LUAD patients based on eight CIRGs. Using Cox regression analysis, we determined that the CIRG signature is a reliable, independent prognostic factor. We further identified PSMD11 as a critical CIRG and performed immunohistochemistry to study the protein expression levels of PSMD11 in LUAD tissues. We also investigated the impact of PSMD11 on the biological behavior of lung cancer cell lines. RESULTS: We found that patients with low PSMD11 expression levels displayed an improved prognosis compared with those with high PSMD11 expression levels. Overexpression of PSMD11 enhanced proliferation, migration, invasion, and tumor growth of lung carcinoma cell line A549, while PSMD11 knockdown diminished proliferation, migration, invasion, and tumor growth of lung carcinoma cell line PC9. Additionally, we discovered that PSMD11 expression was positively correlated with the infiltration of myeloid-derived suppressor cells and the increased expression of immunosuppressive molecules. CONCLUSION: These findings suggest that PSMD11 may serve as a valuable prognostic biomarker and therapeutic target for LUAD.

TMPRSS2 is a tumor suppressor and its downregulation promotes antitumor immunity and immunotherapy response in lung adenocarcinoma.

BACKGROUND: TMPRSS2, a key molecule for SARS-CoV-2 invading human host cells, has an association with cancer. However, its association with lung cancer remains insufficiently unexplored. METHODS: In five bulk transcriptomics datasets, one single-cell RNA sequencing (scRNA-seq) dataset and one proteomics dataset for lung adenocarcinoma (LUAD), we explored associations between TMPRSS2 expression and immune signatures, tumor progression phenotypes, genomic features, and clinical prognosis in LUAD by the bioinformatics approach. Furthermore, we performed experimental validation of the bioinformatics findings. RESULTS: TMPRSS2 expression levels correlated negatively with the enrichment levels of both immune-stimulatory and immune-inhibitory signatures, while they correlated positively with the ratios of immune-stimulatory/immune-inhibitory signatures. It indicated that TMPRSS2 levels had a stronger negative correlation with immune-inhibitory than with immune-stimulatory signatures. TMPRSS2 downregulation correlated with increased proliferation, stemness, genomic instability, tumor progression, and worse survival in LUAD. We further validated that TMPRSS2 was downregulated with tumor progression in the LUAD cohort we collected from Jiangsu Cancer Hospital, China. In vitro and in vivo experiments verified the association of TMPRSS2 deficiency with increased tumor cell proliferation and invasion and antitumor immunity in LUAD. Moreover, in vivo experiments demonstrated that TMPRSS2-knockdown tumors were more sensitive to BMS-1, an inhibitor of PD-1/PD-L1. CONCLUSIONS: TMPRSS2 is a tumor suppressor, while its downregulation is a positive biomarker of immunotherapy in LUAD. Our data provide a potential link between lung cancer and pneumonia caused by SARS-CoV-2 infection.

Integrated multi-omics analysis and machine learning to refine molecular subtypes, prognosis, and immunotherapy in lung adenocarcinoma.

Lung adenocarcinoma (LUAD) has a malignant characteristic that is highly aggressive and prone to metastasis. There is still a lack of suitable biomarkers to facilitate the refinement of precision-based therapeutic regimens. We used a combination of 10 known clustering algorithms and the omics data from 4 dimensions to identify high-resolution molecular subtypes of LUAD. Subsequently, consensus machine learning-related prognostic signature (CMRS) was developed based on subtypes related genes and an integrated program framework containing 10 machine learning algorithms. The efficiency of CMRS was analyzed from the perspectives of tumor microenvironment, genomic landscape, immunotherapy, drug sensitivity, and single-cell analysis. In terms of results, through multi-omics clustering, we identified 2 comprehensive omics subtypes (CSs) in which CS1 patients had worse survival outcomes, higher aggressiveness, mRNAsi and mutation frequency. Subsequently, we developed CMRS based on 13 key genes up-regulated in CS1. The prognostic predictive efficiency of CMRS was superior to most established LUAD prognostic signatures. CMRS demonstrated a strong correlation with tumor microenvironmental feature variants and genomic instability generation. Regarding clinical performance, patients in the high CMRS group were more likely to benefit from immunotherapy, whereas low CMRS were more likely to benefit from chemotherapy and targeted drug therapy. In addition, we evaluated that drugs such as neratinib, oligomycin A, and others may be candidates for patients in the high CMRS group. Single-cell analysis revealed that CMRS-related genes were mainly expressed in epithelial cells. The novel molecular subtypes identified in this study based on multi-omics data could provide new insights into the stratified treatment of LUAD, while the development of CMRS could serve as a candidate indicator of the degree of benefit of precision therapy and immunotherapy for LUAD.

A risk score based on polyamine metabolism and chemotherapy-related genes predicts prognosis and immune cells infiltration of lung adenocarcinoma.

We aimed to explore whether the genes associated with both platinum-based therapy and polyamine metabolism could predict the prognosis of LUAD. We searched for the differential expression genes (DEGs) associated with platinum-based therapy, then we interacted them with polyamine metabolism-related genes to obtain hub genes. Subsequently, we analysed the main immune cell populations in LUAD using the scRNA-seq data, and evaluated the activity of polyamine metabolism of different cell subpopulations. The DEGs between high and low activity groups were screened to identify key DEGs to establish prognostic risk score model. We further elucidated the landscape of immune cells, mutation and drug sensitivity analysis in different risk groups. Finally, we got 10 hub genes associated with both platinum-based chemotherapy and polyamine metabolism, and found that these hub genes mainly affected signalling transduction pathways. B cells and mast cells with highest polyamine metabolism activity, while NK cells were found with lowest polyamine metabolism activity based on scRNA-seq data. DEGs between high and low polyamine metabolism activity groups were identified, then 6 key genes were screened out to build risk score, which showed a good predictive power. The risk score showed a universal negative correlation with immunotherapy checkpoint genes and the cytotoxic T cells infiltration. The mutation rates of EGFR in low-risk group was significantly higher than that of high-risk group. In conclusion, we developed a risk score based on key genes associated with platinum-based therapy and polyamine metabolism, which provide a new perspective for prognosis prediction of LUAD.

Integrated bulk and single-cell RNA sequencing identifies an aneuploidy-based gene signature to predict sensitivity of lung adenocarcinoma to traditional chemotherapy drugs and patients' prognosis.

Background: Patients with lung adenocarcinoma (LUAD) often develop a poor prognosis. Currently, researches on prognostic and immunotherapeutic capacity of aneuploidy-related genes in LUAD are limited. Methods: Genes related to aneuploidy were screened based on bulk RNA sequencing data from public databases using Spearman method. Next, univariate Cox and Lasso regression analyses were performed to establish an aneuploidy-related riskscore (ARS) model. Results derived from bioinformatics analysis were further validated using cellular experiments. In addition, typical LUAD cells were identified by subtype clustering, followed by SCENIC and intercellular communication analyses. Finally, ESTIMATE, ssGSEA and CIBERSORT algorithms were employed to analyze the potential relationship between ARS and tumor immune environment. Results: A five-gene ARS signature was developed. These genes were abnormally high-expressed in LUAD cell lines, and in particular the high expression of CKS1B promoted the proliferative, migratory and invasive phenotypes of LUAD cell lines. Low ARS group had longer overall survival time, higher degrees of inflammatory infiltration, and could benefit more from receiving immunotherapy. Patients in low ASR group responded more actively to traditional chemotherapy drugs (Erlotinib and Roscovitine). The scRNA-seq analysis annotated 17 cell subpopulations into seven cell clusters. Core transcription factors (TFs) such as CREB3L1 and CEBPD were enriched in high ARS cell group, while TFs such as BCLAF1 and UQCRB were enriched in low ARS cell group. CellChat analysis revealed that high ARS cell groups communicated with immune cells via SPP1 (ITGA4-ITGB1) and MK (MDK-NCl) signaling pathways. Conclusion: In this research, integrative analysis based on the ARS model provided a potential direction for improving the diagnosis and treatment of LUAD.