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Background Lung cancer is among the major diseases threatening human health. Although the immune response plays an important role in tumor development, its exact mechanisms are unclear. Materials and methods Here, we used CIBERSORT and ESTIMATE algorithms to determine the proportion of tumor-infiltrating immune cells (TICs) as well as the number of immune and mesenchymal components from the data of 474 lung cancer patients from the Gene Expression Omnibus database. And we used data from The Cancer Genome Atlas database (TCGA) for validation. Results We observed that immune, stromal, and assessment scores were only somewhat related to survival with no statistically significant differences. Further investigations revealed these scores to be associated with different pathology types. GO and KEGG analyses of differentially expressed genes revealed that they were strongly associated with immunity in lung cancer. In order to determine whether the signaling pathways identified by GO and KEGG signaling pathway enrichment analyses were up- or down-regulated, we performed a gene set enrichment analysis using the entire matrix of differentially expressed genes. We found that signaling pathways involved in hallmark allograft rejection, hallmark apical junction, hallmark interferon gamma response, the hallmark P53 pathway, and the hallmark TNF-α signaling via NF-ĸB were up-regulated in the high-ESTIMATE-score group. CIBERSORT analysis for the proportion of TICs revealed that different immune cells were positively correlated with the ESTIMATE score. Cox regression analysis of the differentially expressed genes revealed that CPA3 , C15orf48 , FCGR1B , and GNG4 were associated with patient prognosis. A prognostic model was constructed wherein patients with high-risk scores had a worse prognosis ( p  < 0.001 using the log-rank test). The Area Under Curve (AUC)value for the risk model in predicting the survival was 0.666. The validation set C index was 0.631 (95% CI: 0.580–0.652). The AUC for the risk formula in the validation set was 0.560 that confirmed predictivity of the signature. Conclusion We found that immune-related gene expression models could predict patient prognosis. Moreover, high- and low-ESTIMATE-score groups had different types of immune cell infiltration.

BackgroundPD-1 inhibitors have been routinely used in the treatment of advanced non-small cell lung cancer (NSCLC), and have demonstrated to significantly improve survivorship when combining with other conventional therapies, such as chemotherapy and anti-angiogenesis therapy. PD-L1 is the most commonly used biomarker to select benefiting groups, while not all patients with high PD-L1 expression benefit from immunotherapy. Therefore, identifying other prognostic and predictive biomarkers, including peripheral blood indexes, is essential.MethodsWe retrospectively collected medical records and hematological data of 151 patients with advanced NSCLC treated with PD-1 inhibitor-based combination therapy in our hospital. The peripheral blood indexes of interest were NLR, PLR, PAR, Hb, LDH, CEA, and NSE. The association between peripheral blood indexes and treatment responses or survival outcomes was examined by multivariable logistic regression and Cox regression, respectively.ResultsThe decreased CEA at week 6 (OR = 4.209, 95%CI: 1.287-13.758) or 12 (OR = 7.267, 95%CI: 1.508-35.006) post-treatment was related to a higher disease control rate. The decrease or NLR at week 6 (OR = 3.081, 95%CI: 1.464-6.483) or 12 (OR = 3.304, 95%CI: 1.560-7.001) post-treatment, or CEA at week 12 post-treatment (OR = 2.469, 95%CI: 1.134-5.375), was associated with a higher objective response rate. Patients whose NLR (HR = 0.610, 95%CI: 0.411-0.907) or CEA (HR = 0.477, 95%CI: 0.320-0.710) decreased at week 6 post-treatment tended to have longer progression-free survival, and similar results were found in those with decreased NLR (HR = 0.587, 95%CI: 0.388-0.886) or CEA (HR = 0.406, 95%CI: 0.270-0.609) at week 12 post-treatment. Patients whose CEA (HR = 0.543, 95%CI: 0.339-0.871) or NSE (HR = 0.619, 95%CI: 0.386-0.994) decreased after 6 weeks post-treatment appeared to have longer overall survival, and the same was found for those whoseCEA (HR = 0.620, 95%CI: 0.390-0.986) or NSE (HR = 0.578, 95%CI: 0.353-0.947) was decreased at 12 weeks after treatment.ConclusionPost-treatment NLR, CEA and NSE changes are suggestive indicators for the prognosis of NSCLC patients after immunotherapy.

Hepatocellular carcinoma (HCC) is the most common pathological type of primary liver cancer. The lack of prognosis indicators is one of the challenges in HCC. In this study, we investigated the combination of tertiary lymphoid structure (TLS) and several systemic inflammation parameters as a prognosis indicator for HCC. We retrospectively recruited 126 postoperative patients with primary HCC. The paraffin section was collected for TLS density assessment. In addition, we collected the systemic inflammation parameters from peripheral blood samples. We evaluated the prognostic values of those parameters on overall survival (OS) using Kaplan-Meier curves, univariate and multivariate Cox regression. Last, we plotted a nomogram to predict the survival of HCC patients. We first found TLS density was positively correlated with HCC patients' survival (HR=0.16, 95% CI: 0.06 - 0.39, < 0.0001), but the power of TLS density for survival prediction was found to be limited (AUC=0.776, 95% CI:0.772 - 0.806). Thus, we further introduced several systemic inflammation parameters for survival analysis, we found neutrophil-to-lymphocyte ratio (NLR) was positively associated with OS in univariate Cox regression analysis. However, the combination of TLS density and NLR better predicts patient's survival (AUC=0.800, 95% CI: 0.698-0.902, < 0.001) compared with using any single indicator alone. Last, we incorporated TLS density, NLR, and other parameters into the nomogram to provide a reproducible approach for survival prediction in HCC clinical practice. The combination of TLS density and NLR was shown to be a good predictor of HCC patient survival. It also provides a novel direction for the evaluation of immunotherapies in HCC.

Abstract Interpreting genes of interest is essential for identifying molecular mechanisms, but acquiring such information typically involves tedious manual retrieval. To streamline this process, the fanyi package offers tools to retrieve gene information from sources like National Center for Biotechnology Information (NCBI), significantly enhancing accessibility. Additionally, understanding the latest research advancements and sharing achievements are crucial for junior researchers. However, language barriers often restrict knowledge absorption and career development. To address these challenges, we developed the fanyi package, which leverages artificial intelligence (AI)-driven online translation services to accurately translate among multiple languages. This dual functionality allows researchers to quickly capture and comprehend information, promotes a multilingual environment, and fosters innovation in academic community. Meanwhile, the translation functions are versatile and applicable beyond biomedicine research to other domains as well. The fanyi package is freely available at https://github.com/YuLab-SMU/fanyi.

Objectives Programmed Cell Death-1/ Programmed Death-ligand 1 (PD-1 / PD-L1) inhibitor therapies targeting immunocytes induce persistent tumor remission in various cancers. However, the appropriate biomarkers for the therapeutic efficacy of PD-L1 and PD-1 blockade remain elusive. Materials and methods For a comprehensive analysis of peri-treatment lymphocyte differentiation, in the current study, we enrolled 146 non-small cell lung cancer patients who received α-PD-1 therapies for exploring the peripheral blood lymphocyte differentiation pattern at baseline and post-treatment (dynamic changes) by flow cytometry. Results At baseline, CD4 + / CD8 + T cell ratio predicts good responses and outcomes, but activated T cell and cytotoxic T cell counts predict poor responses and outcomes. And for dynamic changes, after 6 weeks of immune checkpoint blockade (ICB) treatment, compared with baseline level, the elevation of total T and B cell counts indicate poor responses, and total T and T H cell counts indicate poor prognosis while activated T cell predicts good prognosis. And after 12 weeks, elevated total lymphocyte, cytotoxic T cell counts, and decreased total T cell counts and CD4 + / CD8 + T cell ratio predict good responses / outcomes. Our clinical predicting model shows good performance in predicting ICB treatment responses / outcomes. Conclusion Patients with favorable clinical responses / outcomes have distinctive peripheral blood immunocyte differentiation characteristics, indicating the potential of utilizing the peripheral immunocyte differentiation patterns for predicting ICB responses / outcomes.

Cancer stem cells (CSCs) are believed to be crucial in the initiation, progression, and recurrence of cancer. CSCs are also known to be more resistant to cancer treatments. However, the interaction between CSCs and the immune microenvironment is complex and not fully understood. In current study we used single cell RNA sequence (scRNA-Seq, public dataset) technology to identify the characteristic of CSCs. We found that the lung adenocarcinoma cancer stem population is highly inflammatory and remodels the tumor microenvironment by secreting inflammatory factors, specifically the acute phase protein serum amyloid A (SAA). Next, we developed an ex-vivo autologous patient-derived organoids (PDOs) and peripheral blood mononuclear cells (PBMCs) co-culture model to evaluate the immune biological impact of SAA. We found that SAA not only promotes chemoresistance by inducing cancer stem transformation, but also restricts anti-tumor immunity and promotes tumor fibrosis by driving type 2 immunity, and α-SAA neutralization antibody could restrict treatment resistant and tumor fibrosis. Mechanically, we found that the malignant phenotype induced by SAA is dependent on P2X7 receptor. Our data indicate that cancer stem cells secreted SAA have significant biological impact to promote treatment resistant and tumor fibrosis by driving cancer stemness transformation and type 2 immunity polarization via P2X7 receptor. Notably, α-SAA neutralization antibody shows therapeutic potential by restricting these malignant phenotypes.

BackgroundMetastatic recurrence poses a significant challenge in cancer treatment, impacting patient survival and prognosis. Understanding the biological mechanisms behind it is essential for improving treatment strategies and patient outcomes. Lung cancer, the leading cause of cancer-related deaths, is a focus of research for treatment and prognosis. This study specifically targets stage III non-small cell lung cancer (NSCLC) patients following surgery due to their high recurrence variability.MethodsTo delve into the mechanisms of metastatic recurrence in stage III NSCLC patients, we used a comprehensive experimental approach. Long-term follow-up of postoperative patients was combined with single-cell sequencing to uncover tumor microenvironment changes. In vivo and in vitro experiments, including tissue cytometry analysis, real-time PCR, western blotting, gene silencing, cell co-culture, flow cytometry, and chromatin immunoprecipitation-quantitative PCR, were conducted to investigate ALCAM-related gene regulation. Tissue samples and clinical data were collected from stage III NSCLC patients who underwent lung cancer resection between August 2018 and July 2021.ResultsAnalysis revealed distinct epithelial gene expression patterns between recurrence and non-recurrence groups, highlighting the reduced interaction between ALCAM ligand on epithelial cells and CD6 receptor on T cells. Lower ALCAM levels intensified an immunosuppressive state, halting cell cycle progression and promoting tumor proliferation and migration, linked to metastatic recurrence. The transcription factor MYB was identified as a key ALCAM regulator, shedding light on its impact on tumor advancement. Reduced ALCAM expression correlated with poorer prognosis, offering insights into NSCLC recurrence mechanisms.ConclusionsOur study underscores the pivotal role of the ALCAM-CD6 axis in metastatic recurrence of stage III NSCLC. ALCAM regulation not only influences immune-tumor cell interactions but also drives tumor cell proliferation and migration by affecting the cell cycle. This finding presents a promising target for NSCLC treatment and aids in assessing patient prognosis effectively.

Serum amyloid A (SAA), an acute-phase pro-inflammatory protein, is overexpressed in several cancers and is involved in shaping pro-tumor responses. We have previously reported that lung cancer stem cells secrete SAA, which contributes to tumor progression by inhibition of T 1 immunity. Here, we extended our studies to examine the mechanism of SAA mediated immunosuppression in both antigen-presenting cells (APCs) and the subsequent activation of T cells. Using co-culture systems and mice models, we found that SAA impaired dendritic cell and macrophage activation and drove macrophages toward an M2 phenotype with reduced antigen presentation. Lung cancer cells overexpressing SAA also consistently showed impaired CD8 T cell infiltration and cytotoxicity, while SAA neutralization were efficient at enhancing CD8 T cell activation and response to anti-tumor immunity. Mechanistically, we found that the immunosuppressive phenotype induced by SAA on APCs is mediated in part by CD36. Critically, inhibiting SAA by neutralization antibody recovered APC activity and enhanced T cell-dependent tumor control. our results identify SAA as an important immunosuppressive mediator in the tumor microenvironment, implying that the SAA neutralizing antibody may be a potential target for the improvement of lung cancer immunotherapy.

Gastric cancer (GC) is the third leading cause of cancer-associated deaths worldwide. Stromal cells, especially mesenchymal stem cells (MSCs), play significant roles in the development of therapy resistance depending on their paracrine function. The PD-1/PD-L1 crosstalk between cancer and immune cells has been well studied. Emerging evidence suggests that PD-L1 also contributes to tumor resistance to therapy. Cell survival and apoptosis were assessed using CCK-8, colony formation, and flow cytometry assays. Protein alterations were analyzed Western blot. Gene knockdown and overexpression were achieved with siRNA/shRNA and lentiviral infection, respectively. Drug effects on tumors were assessed with xenografts in nude mice. In addition, GC patient samples after chemotherapy treatment were collected to observe the relationship between chemotherapy effect and CTCF or PD-L1. In response to 5-fluorouracil or paclitaxel treatment, GCMSC-CM enhanced the cell viability and decreased the apoptosis rate. Furthermore, blocking PD-L1 or CTCF in GC cells prevented GCMSC-induced drug resistance accompanied by a decline in cell stemness. Consistent with these observations, mice treated with GCMSC-CM showed a lower sensitivity to 5-fluorouracil. In addition, high expression of CTCF and PD-L1 was associated with poor chemotherapy progression in the clinic. Study results demonstrate a mechanism where GCMSC-CM promotes GC chemoresistance by upregulating CTCF-PD-L1 and provide strong evidence in support of targeting CTCF-PD-L1 signaling as a strategy to prevent resistance in the clinic.

The dysfunction of natural killer (NK) cells has been increasingly reported in malignancies, especially in solid tumours. Mesenchymal stem cells (MSCs) exhibit pleiotropic functions that include mediating immune cell exhaustion which is implicated in cancer progression. However, the association of MSCs derived from gastric cancer (gastric cancer mesenchymal stem cells: GCMSCs) with the dysfunction of NK cells remains poorly understood. In this study, we demonstrated that GCMSCs effectively contributed to the exhaustion of NK cells through the release of soluble factors. Furthermore, passivation of the antitumour effect in NK cells was closely associated with their dysfunctional state. The GCMSC-conditioned medium prevented the frequency and effector function of infiltrating NK cells in tumour-bearing mouse models, thus promoting tumour growth. Mechanistically, mammalian target of rapamycin (mTOR) signalling, a critical regulator of cellular metabolism that mediates the function of immune cells, was inhibited in NK cells treated with GCMSCs. However, the checkpoint receptor PD-1 was still present at minimal levels with or without GCMSCs. The study results revealed that GCMSCs contributed to dysfunctional NK cells involved at least partially in the inhibition of mTOR signalling, suggesting potential directions for NK cell-based cancer immunotherapy.