CD161+CD127+CD8+ T cell subsets can predict the efficacy of anti-PD-1 immunotherapy in non-small cell lung cancer with diabetes mellitus.

The role of CD161+CD127+CD8+ T cells in non-small cell lung cancer (NSCLC) patients with diabetes remains unexplored. This study determined the prevalence, phenotype, and function of CD8+ T cell subsets in NSCLC with diabetes. We recruited NSCLC patients (n = 436) treated with anti-PD-1 immunotherapy as first-line treatment. The progression-free survival (PFS), overall survival (OS), T cells infiltration, and peripheral blood immunological characteristics were analyzed in NSCLC patients with or without diabetes. NSCLC patients with diabetes exhibited shorter PFS and OS (p = 0.0069 and p = 0.012, respectively) and significantly lower CD8+ T cells infiltration. Mass cytometry by time-of-flight (CyTOF) showed a higher percentage of CD161+CD127+CD8+ T cells among CD8+T cells in NSCLC with diabetes before anti-PD-1 treatment (p = 0.0071) than that in NSCLC without diabetes and this trend continued after anti-PD-1 treatment (p = 0.0393). Flow cytometry and multiple-immunofluorescence confirmed that NSCLC with diabetes had significantly higher CD161+CD127+CD8+ T cells to CD8+T cells ratios than NSCLC patients without diabetes. The RNA-sequencing analysis revealed immune-cytotoxic genes were reduced in the CD161+CD127+CD8+ T cell subset compared to CD161+CD127-CD8+ T cells in NSCLC with diabetes. CD161+CD127+CD8+ T cells exhibited more T cell-exhausted phenotypes in NSCLC with diabetes. NSCLC patients with diabetes with ≥ 6.3% CD161+CD127+CD8+ T cells to CD8+T cells ratios showed worse PFS. These findings indicate that diabetes is a risk factor for NSCLC patients who undergo anti-PD-1 immunotherapy.CD161+CD127+CD8+ T cells could be a key indicator of a poor prognosis in NSCLC with diabetes. Our findings would help in advancing anti-PD-1 therapy in NSCLC patients with diabetes.

Candidate tumor-specific CD8+ T cell subsets identified in the malignant pleural effusion of advanced lung cancer patients by single-cell analysis.

Isolation of tumor-specific T cells and their antigen receptors (TCRs) from malignant pleural effusions (MPE) may facilitate the development of TCR-transduced adoptive cellular immunotherapy products for advanced lung cancer patients. However, the characteristics and markers of tumor-specific T-cells in MPE are largely undefined. To this end, to establish the phenotypes and antigen specificities of CD8+ T cells, we performed single-cell RNA and TCR sequencing of samples from three advanced lung cancer patients. Dimensionality reduction on a total of 4,983 CD8+ T cells revealed 10 clusters including naïve, memory, and exhausted phenotypes. We focused particularly on exhausted T cell clusters and tested their TCR reactivity against neoantigens predicted from autologous cancer cell lines. Four different TCRs specific for the same neoantigen and one orphan TCR specific for the autologous cell line were identified from one of the patients. Differential gene expression analysis in tumor-specific T cells relative to the other T cells identified CXCL13, as a candidate gene expressed by tumor-specific T cells. In addition to expressing CXCL13, tumor-specific T cells were present in a higher proportion of T cells co-expressing PDCD1(PD-1)/TNFRSF9(4-1BB). Furthermore, flow cytometric analyses in advanced lung cancer patients with MPE documented that those with high PD-1/4-1BB expression have a better prognosis in the subset of 57 adenocarcinoma patients (p = .039). These data suggest that PD-1/4-1BB co-expression might identify tumor-specific CD8+ T cells in MPE, which are associated with patients' prognosis. (233 words).

Faecalibaterium prausnitzii strain EXL01 boosts efficacy of immune checkpoint inhibitors.

Gut microbiota impacts responses to immune checkpoint inhibitors (ICI). A high level of Faecalibacterium prausnitzii have been associated with a positive response to ICI in multiple cancer types. Here, based on fecal shotgun metagenomics data, we show in two independent cohorts of patients with non-small cell lung cancer and advanced melanoma that a high level of F. prausnitzii at baseline is positively associated with a better clinical response to ICI. In MCA205 tumor-bearing mice, administration of F. prausnitzii strain EXL01, already in clinical development for Inflammatory Bowel Disease, restores the anti-tumor response to ICI in the context of antibiotic-induced microbiota perturbation at clinical and tumor transcriptomics level. In vitro, EXL01 strain enhances T cell activation in the presence of ICI. Interestingly, oral administration of EXL01 strain did not induce any change in fecal microbiota diversity or composition, suggesting a direct effect on immune cells in the small intestine. F. prausnitzii strain EXL01 will be evaluated as an adjuvant to ICI in multiple cancers in the near future.

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.

Causal association between immune cells and lung cancer risk: a two-sample bidirectional Mendelian randomization analysis.

Background: Previous studies have highlighted the crucial role of immune cells in lung cancer development; however, the direct link between immunophenotypes and lung cancer remains underexplored. Methods: We applied two-sample Mendelian randomization (MR) analysis, using genetic variants as instruments to determine the causal influence of exposures on outcomes. This method, unlike traditional randomized controlled trials (RCTs), leverages genetic variants inherited randomly at conception, thus reducing confounding and preventing reverse causation. Our analysis involved three genome-wide association studies to assess the causal impact of 731 immune cell signatures on lung cancer using genetic instrumental variables (IVs). We initially used the standard inverse variance weighted (IVW) method and further validated our findings with three supplementary MR techniques (MR-Egger, weighted median, and MR-PRESSO) to ensure robustness. We also conducted MR-Egger intercept and Cochran's Q tests to assess heterogeneity and pleiotropy. Additionally, reverse MR analysis was performed to explore potential causality between lung cancer subtypes and identified immunophenotypes, using R software for all statistical calculations. Results: Our MR analysis identified 106 immune signatures significantly associated with lung cancer. Notably, we found five suggestive associations across all sensitivity tests (P<0.05): CD25 on IgD- CD24- cells in small cell lung carcinoma (ORIVW =0.885; 95% CI: 0.798-0.983; P IVW =0.022); CD27 on IgD+ CD24+ cells in lung squamous cell carcinoma (ORIVW =1.054; 95% CI: 1.010-1.100; P IVW =0.015); CCR2 on monocyte cells in lung squamous cell carcinoma (ORIVW =0.941; 95% CI: 0.898-0.987; P IVW =0.012); CD123 on CD62L+ plasmacytoid dendritic cells (ORIVW =0.958; 95% CI: 0.924-0.992; P IVW =0.017) as well as on plasmacytoid dendritic cells (ORIVW =0.958; 95% CI: 0.924-0.992; P IVW =0.017) in lung squamous cell carcinoma. Conclusion: This study establishes a significant genomic link between immune cells and lung cancer, providing a robust basis for future clinical research aimed at lung cancer management.

Prognostic value of lung immune prognostic index in non-small cell lung cancer patients receiving immune checkpoint inhibitors: a meta-analysis.

Background and Purpose: Until now, it has been difficult to accurately predict the efficacy of immunotherapy in patients with non-small cell lung cancer (NSCLC). A novel indicator, the lung immune prognostic index (LIPI), has shown relatively high prognostic value in patients with solid cancer. Therefore, this study aimed to further identify the association between LIPI and the survival of patients with NSCLC who receive immune checkpoint inhibitors (ICIs). Methods: Several electronic databases were searched for available publications up to April 23, 2023. Immunotherapy outcomes included overall survival (OS), progression-free survival (PFS), and hazard ratios (HRs) with 95% confidence intervals (CIs). Subgroup analysis based on the study design and comparison of the LIPI was conducted. Results: In this meta-analysis, 21 studies with 9,010 patients were included in this meta-analysis. The pooled results demonstrated that elevated LIPI was significantly associated with poor OS (HR = 2.50, 95% CI:2.09-2.99, p < 0.001) and PFS (HR = 1.77, 95% CI:1.64-1.91, p < 0.001). Subgroup analyses stratified by study design (retrospective vs. prospective) and comparison of LIPI (1 vs. 0, 2 vs. 0, 1-2 vs. 0, 2 vs. 1 vs. 0, 2 vs. 0-1 and 2 vs. 1) showed similar results. Conclusion: LIPI could serve as a novel and reliable prognostic factor in NSCLC treated with ICIs, and elevated LIPI predicts worse prognosis.

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.

Non B Cell-Derived Immunoglobulins in Lung Epithelial Cells and Lung Cancer.

As the locus for air exchange, lung tissue is perpetually exposed to a significant quantity of foreign pathogens. Consequently, lung has developed a refined and intricate immune system. Beyond their physical and chemical barrier roles, lung epithelial cells can contribute to immune defence through the expression of Toll-like receptors (TLRs) and other pattern recognition receptors, along with the secretion of cytokines. Emerging evidence demonstrates that lung epithelial cells can generate and secrete immunoglobulins (Igs), including IgM, IgA, or IgG, thus performing antibody function. Moreover, malignantly transformed lung epithelial cells have been discovered to produce high levels of Ig, predominantly IgG, which do not fulfill the role of antibodies, but instead carries out tumour-promoting activity. Structural analysis has indicated that the biological activity of IgG produced by lung cancer cells differs from that of Igs produced by normal lung epithelial cells due to the unique glycosylation modification. Specifically, the sialylated IgG (SIA-IgG), characterised by a non-traditional N-glycosylation modification at the Asn162 site of Igγ CH1, is highly expressed in tumour stem cells. It has been demonstrated that SIA-IgG relies on this unique sialylation modification to promote tumorigenesis, metastasis, and immune evasion. Current results have proven that the Ig produced by lung epithelial cells has multifaceted biological activities, including immune defence functions under physiological conditions, while acquiring tumour-promoting activity during malignant transformation. These insights possess potential for the diagnosis and treatment of lung cancer as novel biomarkers and targets.

Deciphering the role of cuproptosis-related lncRNAs in shaping the lung cancer immune microenvironment: A comprehensive prognostic model.

Cuproptosis plays an important role in cancer, but its role in lung cancer remains unknown. Transcriptional profiles, clinical details and mutation data were acquired from the Cancer Genome Atlas database through a variety of methods. The analysis of this publicly available data was comprehensively performed using R software along with its relevant packages, ensuring a thorough examination of the information. In this study, we conducted a detailed analysis of cuproptosis-related genes and lncRNA co-expression, identifying 129 relevant lncRNAs and establishing a prognostic model with four key lncRNAs (LINC00996, RPARP-AS1, SND1-IT1, TMPO-AS1). Utilizing data from TCGA and GEO databases, the model effectively categorized patients into high- and low-risk groups, showing significant survival differences. Correlation analysis highlighted specific relationships between individual lncRNAs and cuproptosis genes. Our survival analysis indicated a higher survival rate in the low-risk group across various cohorts. Additionally, the model's predictive accuracy was confirmed through independent prognostic analysis and ROC curve evaluations. Functional enrichment analysis revealed distinct biological pathways and immune functions between risk groups. Tumour mutation load analysis differentiated high- and low-risk groups by their mutation profiles. Drug sensitivity analysis and immune infiltration studies using the CIBERSORT algorithm further elucidated the potential treatment responses in different risk groups. This comprehensive evaluation underscores the significance of lncRNAs in cuproptosis and their potential as biomarkers for lung cancer prognosis and immune microenvironment.

Real-world comprehensive genomic and immune profiling reveals distinct age- and sex-based genomic and immune landscapes in tumors of patients with non-small cell lung cancer.

Introduction: Younger patients with non-small cell lung cancer (NSCLC) (<50 years) represent a significant patient population with distinct clinicopathological features and enriched targetable genomic alterations compared to older patients. However, previous studies of younger NSCLC suffer from inconsistent findings, few studies have incorporated sex into their analyses, and studies targeting age-related differences in the tumor immune microenvironment are lacking. Methods: We performed a retrospective analysis of 8,230 patients with NSCLC, comparing genomic alterations and immunogenic markers of younger and older patients while also considering differences between male and female patients. We defined older patients as those ≥65 years and used a 5-year sliding threshold from <45 to <65 years to define various groups of younger patients. Additionally, in an independent cohort of patients with NSCLC, we use our observations to inform testing of the combinatorial effect of age and sex on survival of patients given immunotherapy with or without chemotherapy. Results: We observed distinct genomic and immune microenvironment profiles for tumors of younger patients compared to tumors of older patients. Younger patient tumors were enriched in clinically relevant genomic alterations and had gene expression patterns indicative of reduced immune system activation, which was most evident when analyzing male patients. Further, we found younger male patients treated with immunotherapy alone had significantly worse survival compared to male patients ≥65 years, while the addition of chemotherapy reduced this disparity. Contrarily, we found younger female patients had significantly better survival compared to female patients ≥65 years when treated with immunotherapy plus chemotherapy, while treatment with immunotherapy alone resulted in similar outcomes. Discussion: These results show the value of comprehensive genomic and immune profiling (CGIP) for informing clinical treatment of younger patients with NSCLC and provides support for broader coverage of CGIP for younger patients with advanced NSCLC.

[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.

Using random forests to uncover the predictive power of distance-varying cell interactions in tumor microenvironments.

Tumor microenvironments (TMEs) contain vast amounts of information on patient's cancer through their cellular composition and the spatial distribution of tumor cells and immune cell populations. Exploring variations in TMEs between patient groups, as well as determining the extent to which this information can predict outcomes such as patient survival or treatment success with emerging immunotherapies, is of great interest. Moreover, in the face of a large number of cell interactions to consider, we often wish to identify specific interactions that are useful in making such predictions. We present an approach to achieve these goals based on summarizing spatial relationships in the TME using spatial K functions, and then applying functional data analysis and random forest models to both predict outcomes of interest and identify important spatial relationships. This approach is shown to be effective in simulation experiments at both identifying important spatial interactions while also controlling the false discovery rate. We further used the proposed approach to interrogate two real data sets of Multiplexed Ion Beam Images of TMEs in triple negative breast cancer and lung cancer patients. The methods proposed are publicly available in a companion R package funkycells.

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.

Frequency-dependent selection of neoantigens fosters tumor immune escape and predicts immunotherapy response.

Cancer is an evolutionary process shaped by selective pressure from the microenvironments. However, recent studies reveal that certain tumors undergo neutral evolution where there is no detectable fitness difference amongst the cells following malignant transformation. Here, through computational modeling, we demonstrate that negative frequency-dependent selection (or NFDS), where the immune response against cancer cells depends on the clonality of neoantigens, can lead to an immunogenic landscape that is highly similar to neutral evolution. Crucially, NFDS promotes high antigenic heterogeneity and early immune evasion in hypermutable tumors, leading to poor responses to immune checkpoint blockade (ICB) therapy. Our model also reveals that NFDS is characterized by a negative association between average clonality and total burden of neoantigens. Indeed, this unique feature of NFDS is common in the whole-exome sequencing (WES) datasets (357 tumor samples from 275 patients) from four melanoma cohorts with ICB therapy and a non-small cell lung cancer (NSCLC) WES dataset (327 tumor samples from 100 patients). Altogether, our study provides quantitative evidence supporting the theory of NFDS in cancer, explaining the high prevalence of neutral-looking tumors. These findings also highlight the critical role of frequency-dependent selection in devising more efficient and predictive immunotherapies.

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.

PDL1 targeting by miR-138-5p amplifies anti-tumor immunity and Jurkat cells survival in non-small cell lung cancer.

Non-small cell lung cancer (NSCLC) has constituted over 80% of the lung cancer population with a poor prognosis. Over the past decade, immunotherapy has been constructed in the enlargement of immune checkpoint inhibitors as a promising approach for NSCLC treatment. Evading the immune system using the PD-1/PD-L1 axis is an intelligent way for cancers, and T cells cannot respond fully and confront cancer. Recently, the miR-138 was reported as a PD-L1 regulator in NSCLC. However, its inhibitory impact on T-cell exhaustion has not been characterized. The present study aims to impair PD-L1 (B7-H1) expression in Adenocarcinoma cell lines using miR-138-5p and determines how it prevents Jurak cell exhaustion. To gain the purpose, first, 18 highly significant dysregulated miRNAs containing hsa-miR-138 and CD274-mRNA network were detected in NSCLC based on bioinformatics analysis. Moreover, our study revealed a high level of miR-138-5p could make significant changes like PDL1 downregulation, proliferation, and mortality rate in A549/Calu6 cells. We also simulate cancer environmental conditions by culturing Jurak cells and NSCLC cell lines under the influence of stimulator cytokines to show how miR-138-5p survives Jurak cells by targeting PD-L1/PD-1pathway.

Designable Nanoadaptor for Enhanced Recognition of Natural Killer Cell to Tumor via Bio-orthogonal Click Reaction.

Highly efficient recognition of cancer cells by immune cells is important for successful therapeutic-cell-based cancer immunotherapy. Herein, we present a facile NIR-II nanoadaptor [hyaluronic acid (HA)/dibenzocyclooctyne (DBCO)-Au:Ag2Te quantum dots (QDs)] for enhancing the tumor recognition and binding ability of natural killer (NK) cells via a bio-orthogonal click reaction in vivo. The Nanoadaptor possesses superior tumor-targeting capacity, facilitating the accumulation of the chemical receptor DBCO at the tumor sites. Subsequently, the enrichment of DBCO on tumor cell surfaces provides multivalent recognition sites for capturing pretreated azide engineered NK92 cells (NK92-N3) through an efficient click reaction, thereby significantly enhancing the therapeutical efficiency. The dynamic process of nanoadaptor-mediated recognition of NK cells to tumor cells could be vividly observed using multiplexed NIR-II fluorescence imaging in a mouse model of lung cancer. Such a nanoadaptor strategy can be extended to other therapeutic cellular systems and holds promise for future clinical applications.

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.

Serum albumin and derived neutrophil-to-lymphocyte ratio are potential predictive biomarkers for immune checkpoint inhibitors in small cell lung cancer.

Background: Immune checkpoint inhibitors (ICIs) have reshaped the treatment landscape of small cell lung cancer (SCLC), but only a minority of patients benefit from this therapy. Therefore, it is critical to identify potential risk factors that could predict the efficacy of ICI treatment in SCLC patients and identify patient subgroups who may benefit the most from ICI therapy. Methods: Our study included a total of 183 SCLC patients who had received at least one dose of ICI treatment. We utilized both logistic regression and Cox proportional hazard regression to evaluate whether various patient clinical factors and serum biomarkers could serve as predictors of patient response to treatment and overall survival (OS) during ICI therapy. Results: Logistic regression showed that patients with a history of surgery (p=0.003, OR 9.06, 95% CI: (2.17, 37.9)) and no metastasis (p=0.008, OR 7.82, 95% CI: (1.73, 35.4)) exhibited a higher odds of response to ICI treatment. Cox regression analyses demonstrated that pretreatment blood albumin (p=0.003, HR 1.72, 95% CI: (1.21, 2.45)) and derived neutrophil to lymphocyte ratio (dNLR) (p=0.003, HR 1.71, 95% CI: (1.20-2.44)) were independent predictors for OS in SCLC patients. By establishing a pre-treatment prognostic scoring system based on baseline albumin and dNLR, we found that patients with high albumin and low dNLR exhibited a significantly better prognosis than those with low albumin and high dNLR in both the full (P<.0001, HR 0.33, 95% CI: 0.20-0.55) and the metastatic cohort (P<.0001, HR 0.28, 95% CI: 0.15-0.51). The better prognostic group also had younger age, higher BMI and lower systemic inflammatory biomarker values than the unfavorable group (P<.0001). Conclusion: Our data reveals the significant role of metastasis status and treatment history in predicting the initial response of SCLC patients to ICI treatment. However, baseline serum albumin and dNLR provide a more precise prognostic prediction for patient OS. The scoring system based on albumin and dNLR enhances the ability to stratify patient prognosis and holds the potential to guide clinical decision-making for SCLC patients undergoing ICI therapy.