Selective Cleavage of α-Olefins to Produce Acetylene and Hydrogen.

Acetylene production from mixed α-olefins emerges as a potentially green and energy-efficient approach with significant scientific value in the selective cleavage of C-C bonds. On the Pd(100) surface, it is experimentally revealed that C2 to C4 α-olefins undergo selective thermal cleavage to form surface acetylene and hydrogen. The high selectivity toward acetylene is attributed to the 4-fold hollow sites which are adept at severing the terminal double bonds in α-olefins to produce acetylene. A challenge arises, however, because acetylene tends to stay at the Pd(100) surface. By using the surface alloying methodology with alien Au, the surface Pd d-band center has been successfully shifted away from the Fermi level to release surface-generated acetylene from α-olefins as a gaseous product. Our study actually provides a technological strategy to economically produce acetylene and hydrogen from α-olefins.

Inhibition of PKA/CREB1 pathway confers sensitivity to ferroptosis in non-small cell lung cancer.

Ferroptosis is a type of regulated cell death characterized by iron accumulation and lipid peroxidation. The molecular mechanisms underlying ferroptosis regulation in non-small cell lung cancer (NSCLC) are poorly understood. In this study, we found that protein kinase A (PKA) inhibition enhanced ferroptosis susceptibility in NSCLC cells, as evidenced by reduced cell viability and increased lipid peroxidation. We further identified cAMP-responsive element protein 1 (CREB1), a transcription factor and a substrate of PKA, as a key regulator of ferroptosis. Knockdown of CREB1 sensitized NSCLC cells to ferroptosis inducers (FINs) and abolished the effects of PKA inhibitor and agonist, revealing the pivotal role of CREB1 in ferroptosis regulation. Using a high-throughput screening approach and subsequent validation by chromatin immunoprecipitation (ChIP) and dual-luciferase assays, we discovered that CREB1 transcriptionally activated stearoyl-CoA desaturase (SCD), an enzyme that catalyzes the conversion of saturated fatty acids to monounsaturated fatty acids. SCD conferred ferroptosis resistance by decreasing the availability of polyunsaturated fatty acids for lipid peroxidation, and its overexpression rescued the effect of CREB1 knockdown on ferroptosis in vitro. Besides, CREB1 knockdown suppressed xenograft tumor growth in the presence of Imidazole Ketone Erastin (IKE), a potent FIN, and this effect was reversed by SCD. Finally, we showed that high expression of CREB1 was associated with poor prognosis in NSCLC patients from public datasets and our institution. Collectively, this study illustrates the effect of PKA/CREB1/SCD axis in regulating ferroptosis of NSCLC, targeting this pathway may provide new strategies for treating NSCLC patients.

Cisplatin resistance-related multi-omics differences and the establishment of machine learning models.

OBJECTIVES: Platinum-based chemotherapies are currently the first-line treatment of non-small cell lung cancer. This study will improve our understanding of the causes of resistance to cisplatin, especially in lung adenocarcinoma (LUAD) and provide a reference for therapeutic decisions in clinical practice. METHODS: Cancer Cell Line Encyclopedia (CCLE), The Cancer Genome Atlas (TCGA) and Zhongshan hospital affiliated to Fudan University (zs-cohort) were used to identify the multi-omics differences related to platinum chemotherapy. Cisplatin-resistant mRNA and miRNA models were constructed by Logistic regression, classification and regression tree and C4.5 decision tree classification algorithm with previous feature selection performed via least absolute shrinkage and selection operator (LASSO). qRT-PCR and western-blotting of A549 and H358 cells, as well as single-cell Seq data of tumor samples were applied to verify the tendency of certain genes. RESULTS: 661 cell lines were divided into three groups according to the IC50 value of cisplatin, and the top 1/3 (220) with a small IC50 value were defined as the sensitive group while the last 1/3 (220) were enrolled in the insensitive group. TP53 was the most common mutation in the insensitive group, in contrast to TTN in the sensitive group. 1348 mRNA, 80 miRNA, and 15 metabolites were differentially expressed between 2 groups (P < 0.05). According to the LASSO penalized logistic modeling, 6 of the 1348 mRNAs, FOXA2, BATF3, SIX1, HOXA1, ZBTB38, IRF5, were selected as the associated features with cisplatin resistance and for the contribution of predictive mRNA model (all of adjusted P-values < 0.001). Three of 6 (BATF3, IRF5, ZBTB38) genes were finally verified in cell level and patients in zs-cohort. CONCLUSIONS: Somatic mutations, mRNA expressions, miRNA expressions, metabolites and methylation were related to the resistance of cisplatin. The models we created could help in the prediction of the reaction and prognosis of patients given platinum-based chemotherapies.

Differences in genetics and microenvironment of lung adenocarcinoma patients with or without TP53 mutation.

BACKGROUND: Differences in genetics and microenvironment of LUAD patients with or without TP53 mutation were analyzed to illustrate the role of TP53 mutation within the carcinogenesis of LUAD, which will provide new concepts for the treatment of LUAD. METHODS: In this study, we used genetics and clinical info from the TCGA database, including somatic mutations data, RNA-seq, miRNA-seq, and clinical data. More than one bioinformatics tools were used to analyze the unique genomic pattern of TP53-related LUAD. RESULTS: According to TP53 gene mutation status, we divided the LUAD patients into two groups, including 265 in the mutant group (MU) and 295 in the wild-type group (WT). 787 significant somatic mutations were detected between the groups, including mutations in titin (TTN), type 2 ryanodine receptor (RYR2) and CUB and Sushi multiple domains 3(CSMD3), which were up-regulated in the MU. However, no significant survival difference was observed. At the RNA level, we obtained 923 significantly differentially expressed genes; in the MU, α-defensin 5(DEFA5), pregnancy-specific glycoprotein 5(PSG5) and neuropeptide Y(NPY) were the most up-regulated genes, glucose-6-phosphatase (G6PC), alpha-fetoprotein (AFP) and carry gametocidal (GC) were the most down-regulated genes. GSVA analysis revealed 30 significant pathways. Compared with the WT, the expression of 12 pathways in the mutant group was up-regulated, most of which pointed to cell division. There were significant differences in tumor immune infiltrating cells, such as Macrophages M1, T cells CD4 memory activated, Mast cells resting, and Dendritic cells resting. In terms of immune genes, a total of 35 immune-related genes were screened, of which VGF (VGF nerve growth factor inducible) and PGC (peroxisome proliferator-activated receptor gamma coactivator) were the most significant up-regulated and down-regulated genes, respectively. Research on the expression pattern of immunomodulators found that 9 immune checkpoint molecules and 6 immune costimulatory molecules were considerably wholly different between the two groups. CONCLUSIONS: Taking the mutant group as a reference, LUAD patients in the mutant group had significant differences in somatic mutations, mRNA-seq, miRNA-seq, immune infiltration, and immunomodulators, indicating that TP53 mutation plays a crucial role in the occurrence and development of LUAD.

Identification of differentially expressed genes in lung adenocarcinoma cells using single-cell RNA sequencing not detected using traditional RNA sequencing and microarray.

Lung adenocarcinoma (LUAD) is the leading cause of cancer-related deaths worldwide. Traditional RNA sequencing data fails to detect the exact cellular and molecular changes in tumor cells as they make up only a small proportion of tumor tissue. 10× genomics single-cell RNA sequencing (10× scRNA-seq) and gene expression data of LUAD patients was obtained from the Department of Thoracic Surgery, Zhongshan Hospital, Fudan University, ArrayExpress, TCGA, and GEO databases. Differentially expressed genes (DEGs) were identified in LUAD and alveolar cells (DEGs-scRNA-cancer_cell), tumor- and normal tissue-derived cells (DEGs-scRNA-sample), and normal and LUAD patients (DEGs-Bulk). Flow cytometry and qRT-PCR were performed to validate the significantly differentially expressed ligand-receptor pairs. We selected 159,219 cells and 594 samples in the scRNA-seq data and traditional RNA sequencing, respectively. A total of 1042 DEGs-scRNA-cancer_cell, 788 DEGs-scRNA-sample, and 2510 DEGs-Bulk were identified in this study. We also identified 57 DEGs that were only detected in DEGs-scRNA-cancer_cell (only-DEGs-scRNA-cancer_cell). To explore the relationship between only-DEGs-scRNA-cancer_cell and survival in LUAD, 14 and 22 only-DEGs-scRNA-cancer_cell, which were closely related with survival in TCGA and GEO cohorts were identified. Functional enrichment analyses showed these DEGs-scRNA-cancer_cells were mainly related to cell proliferation and immunoregulation. Our study detected and compared DEGs at different levels and revealed genes that may regulate tumor development. Our results provide a potential new protocol to determine the contribution of DEGs to cancer progression and to help identify potential therapeutic targets.

Identification of immune-related gene signature predicting survival in the tumor microenvironment of lung adenocarcinoma.

The tumor microenvironment (TME) plays an essential role in the occurrence and progression of malignancy. The potential prognostic TME-related biomarkers of lung adenocarcinoma (LUAD) remained unclear, which were investigated in this research. The RNA-sequencing profiles and corresponding clinical parameters were extracted from TCGA and GEO databases, based on which the stromal and immune scores were calculated through the ESTIMATE algorithm. Overlapping differentially expressed genes between stromal and immune score group were analyzed by the LASSO and Random Forrest algorithms and validated in cases from our center. And a prognostic 8-gene signature was constructed using Cox regression. The infiltration of 22 hematopoietic cell phenotypes was assessed by the CIBERSORT algorithms. We found that female, elder patients, and solid predominant subtype had obviously higher stromal and immune scores. And patients with early stage LUAD received a prominently higher immune score. A high stromal or immune score meant a good prognosis. Subsequently, eight TME-related prognostic genes (ATAD5, CYP4F3, CYP4F12, ESPNL, FXYD2, GPX2, NLGN4Y, and SERPINC1) were identified by both LASSO regression and Radom Forest algorithms. High 8-gene signature group exhibited worse overall survival. Furthermore, B cell naïve, plasma cells, T cell follicular helper, and macrophages M1 were prominently more in high signature group. Nevertheless, fewer T cells CD4 memory resting, monocytes, and dendritic cell resting were identified in the high signature group. The composition of the tumor microenvironment significantly affected the prognosis of LUAD patients. We provided a new strategy for the exploration of prognostic TME-related biomarkers and immunotherapy.

Identification and validation of tumor environment phenotypes in lung adenocarcinoma by integrative genome-scale analysis.

PURPOSE: To comprehensively elucidate the landscape of the tumor environment (TME) of lung adenocarcinoma (LUAD), which has a profound impact on prognosis and response to immunotherapy. METHODS AND MATERIALS: Using a large dataset of LUAD patients from The Cancer Genome Atlas, Gene Expression Omnibus database (GEO), and our institution (n = 1411), we estimated the infiltration pattern of 24 immune cell populations in each sample and systematically correlated the TME phenotypes with genomic traits and clinicopathologic characteristics. RESULTS: The LUAD microenvironment was classified into two distinct TME clusters (A and B), and a random forest classifier model was constructed. TMEcluster A was characterized by sparse distribution of immune cell infiltration, relatively low levels of immunomodulators and slightly higher mutation load. By contrast, enrichment of both cytotoxic T cells and immunosuppressor cells was observed in TMEcluster B. Moreover, several immune-related cytokines or markers including IFN-γ, TNF-ß, and several immune checkpoint molecules such as PD-L1 were also upregulated in TMEcluster B. Multivariable Cox analysis revealed that the TMEcluster was an independent prognostic factor (TMEcluster B vs. A, hazard ratio = 0.68, 95% confidence interval = 0.50-0.91, p = 0.010). These findings were all externally validated in the data from the GEO database and our institution. CONCLUSIONS: Our findings describe a comprehensive landscape of LUAD immune infiltration pattern and integrate several previously proposed biomarkers associated with distinct immunophenotypes, thus shedding light on how tumors interact with immune microenvironment. Our results may guide a more precise immune therapeutic strategy for LUAD patients.

Log odds of positive lymph nodes predicts survival in patients treated with neoadjuvant therapy followed by esophagectomy.

BACKGROUND AND OBJECTIVES: We aimed to evaluate the efficacy of the log odds of positive lymph nodes (LODDS) in survival prediction of patients with esophageal carcinoma receiving neoadjuvant therapy, compared with N descriptor and positive lymph node ratio (LNR). METHODS: Patients with esophageal carcinoma receiving neoadjuvant therapy from 2004 to 2015 were reviewed in Surveillance, Epidemiology, and End Results database. The receiver operating characteristics curve and area under the curve (AUC) were used to compare discriminatory power among N descriptor, LNR, and LODDS. The goodness of fit was measured using the -2 log-likelihood ratio (-2LLR). RESULTS: About 2239 patients with a 22 months median follow-up and a 37.8% 5-year overall survival rate were included. LODDS had the best discriminatory power and goodness of fit (LODDS vs N descriptor, AUC 0.666 vs 0.626, -2LLR 15 680.402 vs 15 746.162; LODDS vs LNR, AUC 0.666 vs 0.635, -2LLR 15 680.402 vs 15 712.379; all P < .001). LODDS was the best for fewer than 15 lymph nodes retrieved (LODDS vs N descriptor, AUC 0.652 vs 0.618, P < .001; LODDS vs LNR, AUC 0.652 vs 0.625, P = .005). The prognosis of patients without metastatic nodes could be discriminated by LODDS. CONCLUSIONS: LODDS could better predict survival of patients with esophageal carcinoma receiving neoadjuvant therapy.

Retinoic acid receptor alpha inhibits ferroptosis by promoting thioredoxin and protein phosphatase 1F in lung adenocarcinoma.

Ferroptosis is a recently discovered form of cell death that plays an important role in tumor growth and holds promise as a target for antitumor therapy. However, evidence in the regulation of ferroptosis in lung adenocarcinoma (LUAD) remains elusive. Here, we show that retinoic acid receptor alpha (RARA) is upregulated with the treatment of ferroptosis inducers (FINs). Pharmacological activation of RARA increases the resistance of LUAD to ferroptosis according to cell viability and lipid peroxidation assays, while RARA inhibitor or knockdown (KD) does the opposite. Through transcriptome sequencing in RARA-KD cells and chromatin immunoprecipitation (CHIP)-Seq data, we identify thioredoxin (TXN) and protein phosphatase 1 F (PPM1F) as downstream targets of RARA, both of which inhibit ferroptosis. We confirm that RARA binds to the promotor region of TXN and PPM1F and promotes their transcription by CHIP-qPCR and dual-luciferase assays. Overexpression of TXN and PPM1F reverses the effects of RARA knockdown on ferroptosis in vitro and vivo. Clinically, RARA knockdown or inhibitor increases cells' sensitivity to pemetrexed and cisplatin (CDDP). Immunohistochemistry (IHC) of LUAD from our cohort shows the same expression tendency of RARA and the downstream targets. Our study uncovers that RARA inhibits ferroptosis in LUAD by promoting TXN and PPM1F, and inhibiting RARA-TXN/PPM1F axis represents a promising strategy for improving the efficacy of FINs or chemotherapy in the treatment of LUAD patients.

IL6-STAT3-C/EBPß-IL6 positive feedback loop in tumor-associated macrophages promotes the EMT and metastasis of lung adenocarcinoma.

BACKGROUND: Lung cancer is one of the most common tumors in the world, and metastasis is one of the major causes of tumor-related death in lung cancer patients. Tumor-associated macrophages (TAMs) are a major component of the tumor microenvironment (TME) and are frequently associated with tumor metastasis in human cancers. However, the regulatory mechanisms of TAMs in lung cancer metastasis remain unclear. METHODS: Single-cell sequencing analysis of lung cancer and normal tissues from public databases and from 14 patients who underwent surgery at Zhongshan Hospital was performed. In vitro co-culture experiments were performed to evaluate the effects of TAMs on lung cancer migration and invasion. Changes in the expression of IL-6, STAT3, C/EBPΒ, and EMT pathway were verified using RT-qPCR, western blotting, and immunofluorescence. Dual luciferase reporter assays and ChIP were used to reveal potential regulatory sites on the transcription factor sets. In addition, the effects of TAMs on lung cancer progression and metastasis were confirmed by in vivo models. RESULTS: TAM infiltration is associated with tumor progression and poor prognosis. IL-6 secreted by TAMs can activate the JAK2/STAT3 pathway through autocrine secretion, and STAT3 acts as a transcription factor to activate the expression of C/EBPß, which further promotes the transcription and expression of IL-6, forming positive feedback loops for IL6-STAT3-C/EBPß-IL6 in TAMs. IL-6 secreted by TAMs promotes lung cancer progression and metastasis in vivo and in vitro by activating the EMT pathway, which can be attenuated by the use of JAK2/STAT3 pathway inhibitors or IL-6 monoclonal antibodies. CONCLUSIONS: Our data suggest that TAMs promote IL-6 expression by forming an IL6-STAT3-C/EBPß-IL6 positive feedback loop. Released IL-6 can induce the EMT pathway in lung cancer to enhance migration, invasion, and metastasis. The use of IL-6-neutralizing antibody can partially counteract the promotion of LUAD by TAMs. A novel mechanism of macrophage-promoted tumor progression was revealed, and the IL6-STAT3-C/EBPß-IL6 signaling cascade may be a potential therapeutic target against lung cancer.

Targeting TAM-secreted S100A9 effectively enhances the tumor-suppressive effect of metformin in treating lung adenocarcinoma.

Metformin's effect on tumor treatment was complex, because it significantly reduced cancer cell proliferation in vitro, but made no difference in prognosis in several clinical cohorts. Our transcriptome sequencing results revealed that tumor-associated macrophage (TAM) infiltration significantly increased in active lung adenocarcinoma (LUAD) patients with long-term metformin use. We further identified that the tumor suppressive effect of metformin was more significant in mice after the depletion of macrophages, suggesting that TAMs might play an important role in metformin's effects in LUAD. Combining 10X Genomics single-cell sequencing of tumor samples, transcriptome sequencing of metformin-treated TAMs, and the ChIP-Seq data of the Encode database, we identified and validated that metformin significantly increased the expression and secretion of S100A9 of TAMs through AMPK-CEBP/ß pathway. For the downstream, S100A9 binds to RAGE receptors on the surface of LUAD cells, and then activates the NF-κB pathway to promote EMT and progression of LUAD, counteracting the inhibitory effect of metformin on LUAD cells. In cell-derived xenograft models (CDX) and patient-derived xenograft models (PDX) models, our results showed that neutralizing antibodies targeting TAM-secreted S100A9 effectively enhanced the tumor suppressive effect of metformin in treating LUAD. Our results will enable us to better comprehend the complex role of metformin in LUAD, and advance its clinical application in cancer treatment.

PLK1 regulating chemoradiotherapy sensitivity of esophageal squamous cell carcinoma through pentose phosphate pathway/ferroptosis.

BACKGROUND: Esophageal squamous cell carcinoma (ESCC) is the most common pathological type of esophageal cancer in China, accounting for more than 90 %. Most patients were diagnosed with advanced-stage ESCC, for whom new adjuvant therapy is recommended. Therefore, it is urgent to explore new therapeutic targets for ESCC. Ferroptosis, a newly discovered iron-dependent programmed cell death, has been shown to play an important role in carcinogenesis by many studies. This study explored the effect of Polo like kinase 1 (PLK1) on chemoradiotherapy sensitivity of ESCC through ferroptosis METHODS: In this study, we knocked out the expression of PLK1 (PLK1-KO) in ESCC cell lines (KYSE150 and ECA109) with CRISPR/CAS9. The effects of PLK1-knock out on G6PD, the rate-limiting enzyme of pentose phosphate pathway (PPP), and downstream NADPH and GSH were explored. The lipid peroxidation was observed by flow cytometry, and the changes in mitochondria were observed by transmission electron microscopy. Next, through the CCK-8 assay and clone formation assay, the sensitivity to cobalt 60 rays, paclitaxel, and cisplatin were assessed after PLK1-knock out, and the nude mouse tumorigenesis experiment further verified it. The regulation of transcription factor YY1 on PLK1 was evaluated by dual luciferase reporter assay. The expression and correlation of PLK1 and YY1, and their impact on prognosis were analyzed in more than 300 ESCC cases from the GEO database and our center. Finally, the above results were further proved by single-cell sequencing. RESULTS: After PLK1 knockout, the expression of G6PD dimer and the level of NADPH and GSH in KYSE150 and ECA109 cells significantly decreased. Accordingly, lipid peroxidation increased, mitochondria became smaller, membrane density increased, and ferroptosis was more likely to occur. However, with the stimulation of exogenous GSH (10 mM), there was no significant difference in lipid peroxidation and ferroptosis between the PLK1-KO group and the control group. After ionizing radiation, the PLK1-KO group had higher lipid peroxidation ratio, more cell death, and was more sensitive to radiation, while exogenous GSH (10 mM) could eliminate this difference. Similar results could also be observed when receiving paclitaxel combined with cisplatin and chemoradiotherapy. The expression of PLK1, G6PD dimer, and the level of NADPH and GSH in KYSE150, ECA109, and 293 T cells stably transfected with YY1-shRNAs significantly decreased, and the cells were more sensitive to radiotherapy and chemotherapy. ESCC patients from the GEO database and our center, YY1 and PLK1 expression were significantly positively-correlated, and the survival of patients with high expression of PLK1 was significantly shorter. Further analysis of single-cell sequencing specimens of ESCC in our center confirmed the above results. CONCLUSION: In ESCC, down-regulation of PLK1 can inhibit PPP, and reduce the level of NADPH and GSH, thereby promoting ferroptosis and improving their sensitivity to radiotherapy and chemotherapy. Transcription factor YY1 has a positive regulatory effect on PLK1, and their expressions were positively correlated. PLK1 may be a target for predicting and enhancing the chemoradiotherapy sensitivity of ESCC.

Generic User Behavior: A User Behavior Similarity-Based Recommendation Method.

Recommender system (RS) plays an important role in Big Data research. Its main idea is to handle huge amounts of data to accurately recommend items to users. The recommendation method is the core research content of the whole RS. However, the existing recommendation methods still have the following two shortcomings: (1) Most recommendation methods use only one kind of information about the user's interaction with items (such as Browse or Purchase), which makes it difficult to model complete user preference. (2) Most mainstream recommendation methods only consider the final consistency of recommendation (e.g., user preferences) but ignore the process consistency (e.g., user behavior), which leads to the biased final result. In this article, we propose a recommendation method based on the Entity Interaction Knowledge Graph (EIKG), which draws on the idea of collaborative filtering and innovatively uses the similarity of user behaviors to recommend items. The method first extracts fact triples containing interaction relations from relevant data sets to generate the EIKG; then embeds the entities and relations in the EIKG; finally, uses link prediction techniques to recommend items for users. The proposed method is compared with other recommendation methods on two publicly available data sets, Scholat and Lizhi, and the experimental result shows that it exceeds the state of the art in most metrics, verifying the effectiveness of the proposed method.

Characterization of Infiltrating Immune Cells and Secretory or Membrane-Associated Proteins in KRAS Lung Adenocarcinoma.

Background: This study identified the expression and prognosis significance of secretory or membrane-associated proteins in KRAS lung adenocarcinoma (LUAD) and depicted the characteristics between the immune cell infiltration and the expression of these genes. Methods: Gene expression data of LUAD samples (n = 563) were accessed from The Cancer Genome Atlas (TCGA). The expression of secretory or membrane-associated proteins was compared among the KRAS-mutant, wild-type, and normal groups, as well as the subgroup of the KRAS-mutant group. We identified the survival-related differentially expressed secretory or membrane-associated proteins and conducted the functional enrichment analysis. Then, the characterization and association between their expression and the 24 immune cell subsets were investigated. We also constructed a scoring model to predict KRAS mutation by LASSO and logistic regression analysis. Results: Secretory or membrane-associated genes with differential expression (n = 74) across three groups (137 KRAS LUAD, 368 wild-type LUAD, and 58 normal groups) were identified, and the results of GO and KEGG indicated that they were strongly associated with immune cell infiltrations. Among them, ten genes were significantly related to the survival of patients with KRAS LUAD. The expression of IL37, KIF2, INSR, and AQP3 had the most significant correlations with immune cell infiltration. In addition, eight DEGs from the KRAS subgroups were highly correlated with immune infiltrations, especially TNFSF13B. Using LASSO-logistic regression, a KRAS mutation prediction model based on the 74 differentially expressed secretory or membrane-associated genes was built, and the accuracy was 0.79. Conclusion: The research investigated the relationship between the expression of KRAS-related secretory or membrane-associated proteins in LUAD patients with prognostic prediction and immune infiltration characterization. Our study demonstrated that secretory or membrane-associated genes were closely associated with the survival of KRAS LUAD patients and were strongly correlated to immune cell infiltration.

Zhen Wu decoction represses renal fibrosis by invigorating tubular NRF2 and TFAM to fuel mitochondrial bioenergetics.

BACKGROUND: Zhen Wu Decoction (ZWD) is a prescription from the classical text "Treatise on Exogenous Febrile Disease" and has been extensively used to control kidney diseases since the time of the Eastern Han Dynasty. HYPOTHESIS: We hypothesized that ZWD limits tubular fibrogenesis by reinvigorating tubular bio-energetic capacity. STUDY DESIGN / METHODS: A mouse model of chronic kidney disease (CKD) was established using unilateral ureteral obstruction (UUO). Three concentrations of ZWD, namely 25.2 g/kg (high dosage), 12.6 g/kg (middle dosage), and 6.3 g/kg (low dosage), were included to study the dose-effect relationship. Real-time qPCR was used to observe gene transcription in blood samples from patients with CKD. Different siRNAs were designed to study the role of mitochondrial transcription factor A (TFAM) and nuclear factor (erythroid-derived 2)-related factor 2 (NRF2) in transforming growth factor (TGF)-ß1 induced fibrogenesis and mitochondrial damage. RESULTS: We showed that ZWD efficiently attenuates renal function impairment and reduces renal interstitial fibrosis. TFAM and NRF2 were repressed, and the stimulator of interferon genes (STING) was activated in CKD patient blood sample. We further confirmed that ZWD activated TFAM depended on NRF2 as an important negative regulator of STING in mouse kidneys. Treatment with ZWD significantly reduced oxidative stress and inflammation by regulating the levels of oxidative phosphorylation (OXPHOS) and pro-inflammatory factors, such as interleukin-6, interleukin-1ß, tumor necrosis factor receptor 1, and mitochondrial respiratory chain subunits. NRF2 inhibitors can weaken the ability of ZWD to increase TFAM expression and heal injured mitochondria, playing a similar role to that of STING inhibitors. Our study showed that ZWD elevates the expression of TFAM and mitochondrial respiratory chain subunits by promoting NRF2 activation, after suppressing mitochondrial membrane damage and cristae breakdown and restricting mitochondrial DNA (mtDNA) leakage into the cytoplasm to reduce STING activation. CONCLUSION: ZWD maintains mitochondrial integrity and improves OXPHOS which represents an innovative insight into "strengthening Yang-Qi" theory. ZWD limits tubular fibrogenesis by reinvigorating tubular bioenergetic capacity.

Dissecting the single-cell transcriptome network of macrophage and identifies a signature to predict prognosis in lung adenocarcinoma.

PURPOSE: The tumor immune microenvironment (TME) plays a vital role in tumorigenesis, progression, and treatment. Macrophages, as an important component of the tumor microenvironment, play an essential role in antitumor immunity and TME remodeling. In this study, we aimed to explore the different functions of different origins macrophages in TME and their value as potential predictive markers of prognosis and treatment. METHODS: We performed single-cell analysis using 21 lung adenocarcinoma (LUAD), 12 normal, and four peripheral blood samples from our data and public databases. A prognostic prediction model was then constructed using 502 TCGA patients and explored the potential factors affecting prognosis. The model was validated using data from 4 different GEO datasets with 544 patients after integration. RESULTS: According to the source of macrophages, we classified macrophages into alveolar macrophages (AMs) and interstitial macrophages (IMs). AMs mainly infiltrated in normal lung tissue and expressed proliferative, antigen-presenting, scavenger receptors genes, while IMs occupied the majority in TME and expressed anti-inflammatory, lipid metabolism-related genes. Trajectory analysis revealed that AMs rely on self-renew, whereas IMs originated from monocytes in the blood. Cell-to-cell communication showed that AMs interacted mainly with T cells through the MHC I/II signaling pathway, while IMs mostly interacted with tumor-associated fibrocytes and tumor cells. We then constructed a risk model based on macrophage infiltration and showed an excellent predictive power. We further revealed the possible reasons for its potential prognosis prediction by differential genes, immune cell infiltration, and mutational differences. CONCLUSION: In conclusion, we investigated the composition, expression differences, and phenotypic changes of macrophages from different origins in lung adenocarcinoma. In addition, we developed a prognostic prediction model based on different macrophage subtype infiltration, which can be used as a valid prognostic biomarker. New insights were provided into the role of macrophages in the prognosis and potential treatment of LUAD patients.

Identification of the relationship between single-cell N6-methyladenosine regulators and the infiltrating immune cells in esophageal carcinoma.

Background: N6-methyladenosine (m6A) RNA methylation plays a crucial role in important genomic processes in a variety of malignancies. However, the characterization of m6A with infiltrating immune cells in the tumor microenvironment (TME) in esophageal squamous carcinoma (ESCC) remains unknown. Methods: The single-cell transcriptome data from five ESCC patients in our hospital were analyzed, and TME clusters associated with prognosis and immune checkpoint genes were investigated. Cell isolation and qPCR were conducted to validate the gene characterization in different cells. Results: According to distinct biological processes and marker genes, macrophages, T cells, and B cells clustered into three to four different subgroups. In addition, we demonstrated that m6A RNA methylation regulators were strongly related to the clinical and biological features of ESCC. Analysis of transcriptome data revealed that m6A-mediated TME cell subsets had high predictive value and showed a close relationship with immune checkpoint genes. The validation results from qPCR demonstrated the characteristics of essential genes. CellChat analysis revealed that RNA from TME cells m6A methylation-associated cell subtypes had substantial and diversified interactions with cancer cells. Further investigation revealed that MIF- (CD74+CXCR4) and MIF- (CD74+CD44) ligand-receptor pairings facilitated communication between m6A-associated subtypes of TME cells and cancer cells. Conclusion: Overall, our study demonstrated for the first time the function of m6A methylation-mediated intercellular communication in the microenvironment of tumors in controlling tumor development and anti-tumor immune regulation in ESCC.

The genomic signature of resistance to platinum-containing neoadjuvant therapy based on single-cell data.

BACKGROUND: Neoadjuvant chemotherapy (NACT) becomes the first-line option for advanced tumors, while patients who are not sensitive to it may not benefit. Therefore, it is important to screen patients suitable for NACT. METHODS: Single-cell data of lung adenocarcinoma (LUAD) and esophageal squamous carcinoma (ESCC) before and after cisplatin-containing (CDDP) NACT and cisplatin IC50 data of tumor cell lines were analyzed to establish a CDDP neoadjuvant chemotherapy score (NCS). Differential analysis, GO, KEGG, GSVA and logistic regression models were performed by R. Survival analysis were applied to public databases. siRNA knockdown in A549, PC9, TE1 cell lines, qRT-PCR, western-blot, cck8 and EdU experiments were used for further verification in vitro. RESULTS: 485 genes were expressed differentially in tumor cells before and after neoadjuvant treatment for LUAD and ESCC. After combining the CDDP-associated genes, 12 genes, CAV2, PHLDA1, DUSP23, VDAC3, DSG2, SPINT2, SPATS2L, IGFBP3, CD9, ALCAM, PRSS23, PERP, were obtained and formed the NCS score. The higher the score, the more sensitive the patients were to CDDP-NACT. The NCS divided LUAD and ESCC into two groups. Based on differentially expressed genes, a model was constructed to predict the high and low NCS. CAV2, PHLDA1, ALCAM, CD9, IGBP3 and VDAC3 were significantly associated with prognosis. Finally, we demonstrated that the knockdown of CAV2, PHLDA1 and VDAC3 in A549, PC9 and TE1 significantly increased the sensitivity to cisplatin. CONCLUSIONS: NCS scores and related predictive models for CDDP-NACT were developed and validated to assist in selecting patients who might benefit from it.

Expression Analysis of Ligand-Receptor Pairs Identifies Cell-to-Cell Crosstalk between Macrophages and Tumor Cells in Lung Adenocarcinoma.

Background: Lung adenocarcinoma is one of the most commonly diagnosed malignancies worldwide. Macrophage plays crucial roles in the tumor microenvironment, but its autocrine network and communications with tumor cell are still unclear. Methods: We acquired single-cell RNA sequencing (scRNA-seq) (n = 30) and bulk RNA sequencing (n = 1480) samples of lung adenocarcinoma patients from previous literatures and publicly available databases. Various cell subtypes were identified, including macrophages. Differentially expressed ligand-receptor gene pairs were obtained to explore cell-to-cell communications between macrophages and tumor cells. Furthermore, a machine-learning predictive model based on ligand-receptor interactions was built and validated. Results: A total of 159,219 single cells (18,248 tumor cells and 29,520 macrophages) were selected in this study. We identified significantly correlated autocrine ligand-receptor gene pairs in tumor cells and macrophages, respectively. Furthermore, we explored the cell-to-cell communications between macrophages and tumor cells and detected significantly correlated ligand-receptor signaling pairs. We determined that some of the hub gene pairs were associated with patient prognosis and constructed a machine-learning model based on the intercellular interaction network. Conclusion: We revealed significant cell-to-cell communications (both autocrine and paracrine network) within macrophages and tumor cells in lung adenocarcinoma. Hub genes with prognostic significance in the network were also identified.

A Novel Prognostic Signature Revealed the Interaction of Immune Cells in Tumor Microenvironment Based on Single-Cell RNA Sequencing for Lung Adenocarcinoma.

Background: The tumor immune microenvironment (TIME) played an important role in immunotherapy prognosis and treatment response. Immune cells constitute a large part of the tumor microenvironment and regulate tumor progression. Our research is dedicated to studying the infiltrating immune cell in lung adenocarcinoma (LUAD) and seeking potential targets. Methods: The scRNA-seq data were collected from our FDZSH and two public datasets. The code for cell-type mapping algorithms was downloaded from the CIBERSORTx portal. The bioinformatics data of LUAD patients could be approached from The Cancer Genome Atlas (TCGA) portal. Weighted gene coexpression network analysis (WGCNA) and least absolute shrinkage and selection operator (LASSO) analyses were performed to construct a risk model. TIMER2 and TIDE helped with the immune infiltration estimation, while PROGENy helped the cancer-related pathways' enrichment analysis. GSE31210 dataset and IMVigor ICB therapy cohort validated our findings as the external validation datasets. Results: We clustered the scRNA-seq dataset (integrating our FDZSH datasets and other public datasets) into 23 subpopulations. After curated cell annotation, we implemented Cibersort and WGCNA analysis to anchor the brown module and natural killer cell cluster1 due to the most relationship with tumor trait. The overlap of the brown module gene, natural killer cell signature, and DEGs of tumor and adjacent normal samples was screened by LASSO Cox regression. The obtained 5-gene risk model showed an excellent prognostic performance in the validation dataset. Furthermore, there was a correlation between risk score and tumor-infiltrating immune cells and tumor genomics abnormity. Patients with higher risk scores had a significantly lower immunotherapy response rate. Conclusion: Our observations implied that immune cells played a pivotal role in TIME and established a 5-gene signature (including IDH2, ADRB2, SFTPC, CCDC69, and CCND2) on the basement of nature killer markers targeted by WGCNA analysis. The significance of clinical outcome and immunotherapy response prediction was validated robustly.