Integrated Proteogenomic Characterization of Clear Cell Renal Cell Carcinoma.

To elucidate the deregulated functional modules that drive clear cell renal cell carcinoma (ccRCC), we performed comprehensive genomic, epigenomic, transcriptomic, proteomic, and phosphoproteomic characterization of treatment-naive ccRCC and paired normal adjacent tissue samples. Genomic analyses identified a distinct molecular subgroup associated with genomic instability. Integration of proteogenomic measurements uniquely identified protein dysregulation of cellular mechanisms impacted by genomic alterations, including oxidative phosphorylation-related metabolism, protein translation processes, and phospho-signaling modules. To assess the degree of immune infiltration in individual tumors, we identified microenvironment cell signatures that delineated four immune-based ccRCC subtypes characterized by distinct cellular pathways. This study reports a large-scale proteogenomic analysis of ccRCC to discern the functional impact of genomic alterations and provides evidence for rational treatment selection stemming from ccRCC pathobiology.

Systematic Immunotherapy Target Discovery Using Genome-Scale In Vivo CRISPR Screens in CD8 T Cells.

CD8 T cells play essential roles in anti-tumor immune responses. Here, we performed genome-scale CRISPR screens in CD8 T cells directly under cancer immunotherapy settings and identified regulators of tumor infiltration and degranulation. The in vivo screen robustly re-identified canonical immunotherapy targets such as PD-1 and Tim-3, along with genes that have not been characterized in T cells. The infiltration and degranulation screens converged on an RNA helicase Dhx37. Dhx37 knockout enhanced the efficacy of antigen-specific CD8 T cells against triple-negative breast cancer in vivo. Immunological characterization in mouse and human CD8 T cells revealed that DHX37 suppresses effector functions, cytokine production, and T cell activation. Transcriptomic profiling and biochemical interrogation revealed a role for DHX37 in modulating NF-κB. These data demonstrate high-throughput in vivo genetic screens for immunotherapy target discovery and establishes DHX37 as a functional regulator of CD8 T cells.

Expression of the membrane tetraspanin claudin 18 on cancer cells promotes T lymphocyte infiltration and antitumor immunity in pancreatic cancer.

Tumors weakly infiltrated by T lymphocytes poorly respond to immunotherapy. We aimed to unveil malignancy-associated programs regulating T cell entrance, arrest, and activation in the tumor environment. Differential expression of cell adhesion and tissue architecture programs, particularly the presence of the membrane tetraspanin claudin (CLDN)18 as a signature gene, demarcated immune-infiltrated from immune-depleted mouse pancreatic tumors. In human pancreatic ductal adenocarcinoma (PDAC) and non-small cell lung cancer, CLDN18 expression positively correlated with more differentiated histology and favorable prognosis. CLDN18 on the cell surface promoted accrual of cytotoxic T lymphocytes (CTLs), facilitating direct CTL contacts with tumor cells by driving the mobilization of the adhesion protein ALCAM to the lipid rafts of the tumor cell membrane through actin. This process favored the formation of robust immunological synapses (ISs) between CTLs and CLDN18-positive cancer cells, resulting in increased T cell activation. Our data reveal an immune role for CLDN18 in orchestrating T cell infiltration and shaping the tumor immune contexture.

LSD1 Ablation Stimulates Anti-tumor Immunity and Enables Checkpoint Blockade.

Chromatin regulators play a broad role in regulating gene expression and, when gone awry, can lead to cancer. Here, we demonstrate that ablation of the histone demethylase LSD1 in cancer cells increases repetitive element expression, including endogenous retroviral elements (ERVs), and decreases expression of RNA-induced silencing complex (RISC) components. Significantly, this leads to double-stranded RNA (dsRNA) stress and activation of type 1 interferon, which stimulates anti-tumor T cell immunity and restrains tumor growth. Furthermore, LSD1 depletion enhances tumor immunogenicity and T cell infiltration in poorly immunogenic tumors and elicits significant responses of checkpoint blockade-refractory mouse melanoma to anti-PD-1 therapy. Consistently, TCGA data analysis shows an inverse correlation between LSD1 expression and CD8+ T cell infiltration in various human cancers. Our study identifies LSD1 as a potent inhibitor of anti-tumor immunity and responsiveness to immunotherapy and suggests LSD1 inhibition combined with PD-(L)1 blockade as a novel cancer treatment strategy.

Comprehensive and Integrated Genomic Characterization of Adult Soft Tissue Sarcomas.

Sarcomas are a broad family of mesenchymal malignancies exhibiting remarkable histologic diversity. We describe the multi-platform molecular landscape of 206 adult soft tissue sarcomas representing 6 major types. Along with novel insights into the biology of individual sarcoma types, we report three overarching findings: (1) unlike most epithelial malignancies, these sarcomas (excepting synovial sarcoma) are characterized predominantly by copy-number changes, with low mutational loads and only a few genes (TP53, ATRX, RB1) highly recurrently mutated across sarcoma types; (2) within sarcoma types, genomic and regulomic diversity of driver pathways defines molecular subtypes associated with patient outcome; and (3) the immune microenvironment, inferred from DNA methylation and mRNA profiles, associates with outcome and may inform clinical trials of immune checkpoint inhibitors. Overall, this large-scale analysis reveals previously unappreciated sarcoma-type-specific changes in copy number, methylation, RNA, and protein, providing insights into refining sarcoma therapy and relationships to other cancer types.

Macrophage mitochondrial bioenergetics and tissue invasion are boosted by an Atossa-Porthos axis in Drosophila.

Cellular metabolism must adapt to changing demands to enable homeostasis. During immune responses or cancer metastasis, cells leading migration into challenging environments require an energy boost, but what controls this capacity is unclear. Here, we study a previously uncharacterized nuclear protein, Atossa (encoded by CG9005), which supports macrophage invasion into the germband of Drosophila by controlling cellular metabolism. First, nuclear Atossa increases mRNA levels of Porthos, a DEAD-box protein, and of two metabolic enzymes, lysine-α-ketoglutarate reductase (LKR/SDH) and NADPH glyoxylate reductase (GR/HPR), thus enhancing mitochondrial bioenergetics. Then Porthos supports ribosome assembly and thereby raises the translational efficiency of a subset of mRNAs, including those affecting mitochondrial functions, the electron transport chain, and metabolism. Mitochondrial respiration measurements, metabolomics, and live imaging indicate that Atossa and Porthos power up OxPhos and energy production to promote the forging of a path into tissues by leading macrophages. Since many crucial physiological responses require increases in mitochondrial energy output, this previously undescribed genetic program may modulate a wide range of cellular behaviors.

SpatialCells: automated profiling of tumor microenvironments with spatially resolved multiplexed single-cell data.

Cancer is a complex cellular ecosystem where malignant cells coexist and interact with immune, stromal and other cells within the tumor microenvironment (TME). Recent technological advancements in spatially resolved multiplexed imaging at single-cell resolution have led to the generation of large-scale and high-dimensional datasets from biological specimens. This underscores the necessity for automated methodologies that can effectively characterize molecular, cellular and spatial properties of TMEs for various malignancies. This study introduces SpatialCells, an open-source software package designed for region-based exploratory analysis and comprehensive characterization of TMEs using multiplexed single-cell data. The source code and tutorials are available at https://semenovlab.github.io/SpatialCells. SpatialCells efficiently streamlines the automated extraction of features from multiplexed single-cell data and can process samples containing millions of cells. Thus, SpatialCells facilitates subsequent association analyses and machine learning predictions, making it an essential tool in advancing our understanding of tumor growth, invasion and metastasis.

Assessing residential PM2.5 concentrations and infiltration factors with high spatiotemporal resolution using crowdsourced sensors.

Building conditions, outdoor climate, and human behavior influence residential concentrations of fine particulate matter (PM2.5). To study PM2.5 spatiotemporal variability in residences, we acquired paired indoor and outdoor PM2.5 measurements at 3,977 residences across the United States totaling >10,000 monitor-years of time-resolved data (10-min resolution) from the PurpleAir network. Time-series analysis and statistical modeling apportioned residential PM2.5 concentrations to outdoor sources (median residential contribution = 52% of total, coefficient of variation = 69%), episodic indoor emission events such as cooking (28%, CV = 210%) and persistent indoor sources (20%, CV = 112%). Residences in the temperate marine climate zone experienced higher infiltration factors, consistent with expectations for more time with open windows in milder climates. Likewise, for all climate zones, infiltration factors were highest in summer and lowest in winter, decreasing by approximately half in most climate zones. Large outdoor-indoor temperature differences were associated with lower infiltration factors, suggesting particle losses from active filtration occurred during heating and cooling. Absolute contributions from both outdoor and indoor sources increased during wildfire events. Infiltration factors decreased during periods of high outdoor PM2.5, such as during wildfires, reducing potential exposures from outdoor-origin particles but increasing potential exposures to indoor-origin particles. Time-of-day analysis reveals that episodic emission events are most frequent during mealtimes as well as on holidays (Thanksgiving and Christmas), indicating that cooking-related activities are a strong episodic emission source of indoor PM2.5 in monitored residences.

Development of a TMErisk model based on immune infiltration in tumour microenvironment to predict prognosis of immune checkpoint inhibitor treatment in hepatocellular carcinoma.

Immune checkpoint inhibitor (ICI) treatment has created the opportunity of improved outcome for patients with hepatocellular carcinoma (HCC). However, only a minority of HCC patients benefit from ICI treatment owing to poor treatment efficacy and safety concerns. There are few predictive factors that precisely stratify HCC responders to immunotherapy. In this study, we developed a tumour microenvironment risk (TMErisk) model to divide HCC patients into different immune subtypes and evaluated their prognosis. Our results indicated that virally mediated HCC patients who had more common tumour protein P53 (TP53) alterations with lower TMErisk scores were appropriate for ICI treatment. HCC patients with alcoholic hepatitis who more commonly harboured catenin beta 1 (CTNNB1) alterations with higher TMErisk scores could benefit from treatment with multi-tyrosine kinase inhibitors. The developed TMErisk model represents the first attempt to anticipate tumour tolerance of ICIs in the TME through the degree of immune infiltration in HCCs.

MrGPS: an m6A-related gene pair signature to predict the prognosis and immunological impact of glioma patients.

N6-methyladenosine (m6A) RNA methylation is the predominant epigenetic modification for mRNAs that regulates various cancer-related pathways. However, the prognostic significance of m6A modification regulators remains unclear in glioma. By integrating the TCGA lower-grade glioma (LGG) and glioblastoma multiforme (GBM) gene expression data, we demonstrated that both the m6A regulators and m6A-target genes were associated with glioma prognosis and activated various cancer-related pathways. Then, we paired m6A regulators and their target genes as m6A-related gene pairs (MGPs) using the iPAGE algorithm, among which 122 MGPs were significantly reversed in expression between LGG and GBM. Subsequently, we employed LASSO Cox regression analysis to construct an MGP signature (MrGPS) to evaluate glioma prognosis. MrGPS was independently validated in CGGA and GEO glioma cohorts with high accuracy in predicting overall survival. The average area under the receiver operating characteristic curve (AUC) at 1-, 3- and 5-year intervals were 0.752, 0.853 and 0.831, respectively. Combining clinical factors of age and radiotherapy, the AUC of MrGPS was much improved to around 0.90. Furthermore, CIBERSORT and TIDE algorithms revealed that MrGPS is indicative for the immune infiltration level and the response to immune checkpoint inhibitor therapy in glioma patients. In conclusion, our study demonstrated that m6A methylation is a prognostic factor for glioma and the developed prognostic model MrGPS holds potential as a valuable tool for enhancing patient management and facilitating accurate prognosis assessment in cases of glioma.

Identification of immune-related gene signatures for chronic obstructive pulmonary disease with metabolic syndrome: evidence from integrated bulk and single-cell RNA sequencing data.

Chronic obstructive pulmonary disease (COPD) is closely related to innate and adaptive inflammatory immune responses. It is increasingly becoming evident that metabolic syndrome (MetS) affects a significant portion of COPD patients. Through this investigation, we identify shared immune-related candidate biological markers. The Weighted Gene Co-Expression Network Analysis (WGCNA) was utilized to reveal the co-expression modules linked to COPD and MetS. The commonly expressed genes in the COPD and MetS were utilized to conduct an enrichment analysis. We adopted machine-learning to screen and validate hub genes. We also assessed the relationship between hub genes and immune cell infiltration in COPD and MetS, respectively. Moreover, associations across hub genes and metabolic pathways were also explored. Finally, we chose a single-cell RNA sequencing (scRNA-seq) dataset to investigate the hub genes and shared mechanisms at the level of the cells. We also applied cell trajectory analysis and cell-cell communication analysis to focus on the vital immune cell we were interested in. As a result, we selected and validated 13 shared hub genes for COPD and MetS. The enrichment analysis and immune infiltration analysis illustrated strong associations between hub genes and immunology. Additionally, we applied metabolic pathway enrichment analysis, indicating the significant role of reactive oxygen species (ROS) in COPD with MetS. Through scRNA-seq analysis, we found that ROS might accumulate the most in the alveolar macrophages. In conclusion, the 13 hub genes related to the immune response and metabolism may serve as diagnostic biomarkers and treatment targets of COPD with MetS.

Comprehensive bioinformatics analysis of human cytomegalovirus pathway genes in pan-cancer.

BACKGROUND: Human cytomegalovirus (HCMV) is a herpesvirus that can infect various cell types and modulate host gene expression and immune response. It has been associated with the pathogenesis of various cancers, but its molecular mechanisms remain elusive. METHODS: We comprehensively analyzed the expression of HCMV pathway genes across 26 cancer types using the Cancer Genome Atlas (TCGA) and The Genotype-Tissue Expression (GTEx) databases. We also used bioinformatics tools to study immune invasion and tumor microenvironment in pan-cancer. Cox regression and machine learning were used to analyze prognostic genes and their relationship with drug sensitivity. RESULTS: We found that HCMV pathway genes are widely expressed in various cancers. Immune infiltration and the tumor microenvironment revealed that HCMV is involved in complex immune processes. We obtained prognostic genes for 25 cancers and significantly found 23 key genes in the HCMV pathway, which are significantly enriched in cellular chemotaxis and synaptic function and may be involved in disease progression. Notably, CaM family genes were up-regulated and AC family genes were down-regulated in most tumors. These hub genes correlate with sensitivity or resistance to various drugs, suggesting their potential as therapeutic targets. CONCLUSIONS: Our study has revealed the role of the HCMV pathway in various cancers and provided insights into its molecular mechanism and therapeutic significance. It is worth noting that the key genes of the HCMV pathway may open up new doors for cancer prevention and treatment.

Comprehensive analysis of zinc and ring finger 3 in prognostic value and pan-cancer immunity.

Zinc and ring finger 3 (ZNRF3) is a negative suppressor of Wnt signal and newly identified as an important regulator in tumorigenesis and development. However, the pan-cancer analysis of ZNRF3 has not been reported. We found that ZNRF3 was significantly decreased in six tumors including CESC, KIRP, KIRC, SKCM, OV, and ACC, but increased in twelve tumors, namely LGG, ESCA, STES, COAD, STAD, LUSC, LIHC, THCA, READ, PAAD, TGCT, and LAML. Clinical outcomes of cancer patients were closely related to ZNRF3 expression in ESCA, GBM, KIRC, LUAD, STAD, UCEC, LGG, and SARC. The highest genetic alteration frequency of ZNRF3 occurred in ACC. Abnormal expression of ZNRF3 could be attributed to the differences of copy number variation (CNV) and DNA methylation as well as ZNRF3-interacting proteins. Besides, ZNRF3 were strongly associated with tumor heterogeneity, tumor stemness, immune score, stromal score and ESTIMATE score in certain cancers. In terms of immune cell infiltration, ZNRF3 was positively correlated to infiltration of cancer-associated fibroblasts in CESC, HNSC, OV, PAAD, PRAD, and THYM, but negatively associated with infiltration of CD8 T cells in HNSC, KIRC, KIRP and THYM. Moreover, ZNRF3 expression was correlated with most immune checkpoint genes in SARC, LUSC, LUAD, PRAD, THCA, UVM, TGCT, and OV, and associated with overwhelming majority of immunoregulatory genes in almost all cancers. Most RNA modification genes were also remarkably related to ZNRF3 level in KIRP, LUAD, LUSC, THYM, UVM, PRAD, and UCEC, indicating that ZNRF3 might have an important effect on cancer epigenetic regulation. Finally, we verified the expression and role of ZNRF3 in clinical specimens and cell lines of renal cancer and liver cancer. This study provides a comprehensive pan-cancer analysis of ZNRF3 and reveals the complexity of its carcinogenic effect.

Novel ferroptosis gene biomarkers and immune infiltration profiles in diabetic kidney disease via bioinformatics.

Diabetic kidney disease (DKD) is the primary cause of end-stage renal disease, exhibiting high disability and mortality rates. Ferroptosis is vital for the progression of DKD, but the exact mechanism remains unclear. This study aimed to explore the potential mechanism of ferroptosis-related genes in DKD and their relationship with the immune and to identify new diagnostic biomarkers to help treat and diagnose DKD. GSE30122 and GSE47185 were obtained from the Gene Expression Omnibus database and were integrated into a merged dataset, followed by functional enrichment analysis. Then potential differentially expressed genes were screened. Ferroptosis-related differentially-expressed genes were identified, followed by gene ontology analysis. Protein-protein interaction networks were constructed and hub genes were screened. The immune cell-infiltrating state in the dataset was assessed using appropriate algorithms. Immune signature subtypes were constructed using the consensus clustering analysis. Hub gene expression was validated using qRT-PCR and immunohistochemistry. A total of Eleven screened ferroptosis-related differentially expressed genes were screened. Six potentially diagnostically favorable ferroptosis-related hub genes were identified. Significantly increased expression of γδT cells, resting mast cells, and macrophages infiltration was observed in the DKD group. Additionally, two distinct immune signature subgroups were identified. Ferroptosis-related hub genes were significantly correlated with differentially infiltrated immune cells. Six hub genes were significantly upregulated in HK-2 cells following high glucose treatment and in human kidney tissues of patients with DKD. Six ferroptosis-related hub genes were identified as potential biomarkers of diabetic kidney disease, but further validation is needed.

Cytotoxic T lymphocytes require transcription for infiltration but not target cell lysis.

Effector cytotoxic T lymphocytes (CTLs) are critical for ridding the body of infected or cancerous cells. CTL T cell receptor (TCR) ligation not only drives the delivery and release of cytolytic granules but also initiates a new wave of transcription. In order to address whether TCR-induced transcriptomic changes impact the ability of CTLs to kill, we asked which genes are expressed immediately after CTLs encounter targets and how CTL responses change when inhibiting transcription. Our data demonstrate that while expression of cytokines/chemokines and transcriptional machinery depend on transcription, cytotoxic protein expression and cytolytic activity are relatively robust to transcription blockade, with CTLs lysing nearby target cells for several hours after actinomycin D treatment. Monitoring CTL movement among target cells after inhibiting transcription demonstrates an infiltration defect that is not rectified by provision of exogenous cytokine/chemokine gradients, indicating a cell-intrinsic transcriptional requirement for infiltration. Together, our results reveal differential molecular control of CTL functions, separating recruitment and infiltration from cytolysis.

Endoplasmic Reticulum Protein 72 Regulates Integrin Mac-1 Activity to Influence Neutrophil Recruitment.

BACKGROUND: Integrins mediate the adhesion, crawling, and migration of neutrophils during vascular inflammation. Thiol exchange is important in the regulation of integrin functions. ERp72 (endoplasmic reticulum-resident protein 72) is a member of the thiol isomerase family responsible for the catalysis of disulfide rearrangement. However, the role of ERp72 in the regulation of Mac-1 (integrin αMß2) on neutrophils remains elusive. METHODS: Intravital microscopy of the cremaster microcirculation was performed to determine in vivo neutrophil movement. Static adhesion, flow chamber, and flow cytometry were used to evaluate in vitro integrin functions. Confocal fluorescent microscopy and coimmunoprecipitation were utilized to characterize the interactions between ERp72 and Mac-1 on neutrophil surface. Cell-impermeable probes and mass spectrometry were used to label reactive thiols and identify target disulfide bonds during redox exchange. Biomembrane force probe was performed to quantitatively measure the binding affinity of Mac-1. A murine model of acute lung injury induced by lipopolysaccharide was utilized to evaluate neutrophil-associated vasculopathy. RESULTS: ERp72-deficient neutrophils exhibited increased rolling but decreased adhesion/crawling on inflamed venules in vivo and defective static adhesion in vitro. The defect was due to defective activation of integrin Mac-1 but not LFA-1 (lymphocyte function-associated antigen-1) using blocking or epitope-specific antibodies. ERp72 interacted with Mac-1 in lipid rafts on neutrophil surface leading to the reduction of the C654-C711 disulfide bond in the αM subunit that is critical for Mac-1 activation. Recombinant ERp72, via its catalytic motifs, increased the binding affinity of Mac-1 with ICAM-1 (intercellular adhesion molecule-1) and rescued the defective adhesion of ERp72-deficient neutrophils both in vitro and in vivo. Deletion of ERp72 in the bone marrow inhibited neutrophil infiltration, ameliorated tissue damage, and increased survival during murine acute lung injury. CONCLUSIONS: Extracellular ERp72 regulates integrin Mac-1 activity by catalyzing disulfide rearrangement on the αM subunit and may be a novel target for the treatment of neutrophil-associated vasculopathy.

Identification of necroptosis-associated miRNA signature for predicting prognosis and immune landscape in stomach adenocarcinoma.

PURPOSE: This study aims to identify the potential necroptosis related genes (NRGs)-associated miRNAs signature and explore the impact on the prognosis of stomach adenocarcinoma (STAD). METHODS: Employing rigorous methodologies, we utilized univariate Cox, Lasso and multivariate Cox regression analyses to develop a prognostic signature. Kaplan-Meier (K-M) and ROC curves were applied to assess the prognostic value of signature in a training group and an independent test group. Furthermore, we conducted Gene Set Enrichment Analysis (GSEA) for enrichment of tumor-related pathways. The risk score was calculated for each patient based on the expression of miRNAs which were enrolled in the signature. Patients were stratified into high- and low-risk groups. The immune cell infiltration and immunotherapy were compared between the two groups. Finally, the diagnostic potential of the miRNA was explored by RT-qPCR. RESULTS: We constructed a prognostic model based on 6 NRGs-associated miRNAs. K-M plots underscored superior survival outcomes in the low-risk group. GSEA results revealed the enrichment of several tumor-related pathways in the high-risk group. Notably, CD8+ T cells, Tregs and activated memory CD4+ T cells exhibited negative correlations with the risk score. Additionally, a few immune checkpoint genes, such as CTLA4, PD1 and PD-L1, were significantly upregulated in the low-risk group. Furthermore, the serum expression levels of all these 6 miRNAs were significantly elevated in STAD patients. CONCLUSIONS: Our study identified a robust risk score derived from a signature of 6 NRGs-associated miRNAs, demonstrating high efficacy for prognosis of STAD. These results not only contributed to our understanding of STAD pathogenesis, but also held promise for potential clinical applications, particularly in the realm of personalized immunotherapy for STAD patients.

Integrative Proteomics and N-Glycoproteomics Analyses of Rheumatoid Arthritis Synovium Reveal Immune-Associated Glycopeptides.

Rheumatoid arthritis (RA) is a typical autoimmune disease characterized by synovial inflammation, synovial tissue hyperplasia, and destruction of bone and cartilage. Protein glycosylation plays key roles in the pathogenesis of RA but in-depth glycoproteomics analysis of synovial tissues is still lacking. Here, by using a strategy to quantify intact N-glycopeptides, we identified 1260 intact N-glycopeptides from 481 N-glycosites on 334 glycoproteins in RA synovium. Bioinformatics analysis revealed that the hyper-glycosylated proteins in RA were closely linked to immune responses. By using DNASTAR software, we identified 20 N-glycopeptides whose prototype peptides were highly immunogenic. We next calculated the enrichment scores of nine types of immune cells using specific gene sets from public single-cell transcriptomics data of RA and revealed that the N-glycosylation levels at some sites, such as IGSF10_N2147, MOXD2P_N404, and PTCH2_N812, were significantly correlated with the enrichment scores of certain immune cell types. Furthermore, we showed that aberrant N-glycosylation in the RA synovium was related to increased expression of glycosylation enzymes. Collectively, this work presents, for the first time, the N-glycoproteome of RA synovium and describes immune-associated glycosylation, providing novel insights into RA pathogenesis.

Microfluidics guided by deep learning for cancer immunotherapy screening.

Immunocyte infiltration and cytotoxicity play critical roles in both inflammation and immunotherapy. However, current cancer immunotherapy screening methods overlook the capacity of the T cells to penetrate the tumor stroma, thereby significantly limiting the development of effective treatments for solid tumors. Here, we present an automated high-throughput microfluidic platform for simultaneous tracking of the dynamics of T cell infiltration and cytotoxicity within the 3D tumor cultures with a tunable stromal makeup. By recourse to a clinical tumor-infiltrating lymphocyte (TIL) score analyzer, which is based on a clinical data-driven deep learning method, our platform can evaluate the efficacy of each treatment based on the scoring of T cell infiltration patterns. By screening a drug library using this technology, we identified an epigenetic drug (lysine-specific histone demethylase 1 inhibitor, LSD1i) that effectively promoted T cell tumor infiltration and enhanced treatment efficacy in combination with an immune checkpoint inhibitor (anti-PD1) in vivo. We demonstrated an automated system and strategy for screening immunocyte-solid tumor interactions, enabling the discovery of immuno- and combination therapies.

Identification and validation of CRLF1 and NRG1 as immune-related signatures in hypertrophic scar.

BACKGROUND: Hypertrophic scar (HTS) is a prevalent chronic inflammatory skin disorder characterized by abnormal proliferation and extracellular matrix deposition and the precise mechanisms underlying HTS remain elusive. This study aimed to identify and validate potential immune-related genes associated with hypertrophic scar formation. METHODS: Skin samples from normal (n = 12) and hypertrophic scar tissues (n = 12) were subjected to RNA-seq analysis. Differentially expressed genes (DEGs) and significant modular genes in Weighted gene Co-expression Network Analysis (WGCNA) were identified. Subsequently, functional enrichment analysis was performed on the intersecting genes. Additionally, eight immune-related genes were matched from the ImmPort database. Validation of NRG1 and CRLF1 was carried out using an external cohort (GSE136906). Furthermore, the association between these two genes and immune cells was assessed by Spearman correlation analysis. Finally, RNA was extracted from normal and hypertrophic scar samples, and RT-qPCR, Immunohistochemistry staining and Western Blot were employed to validate the expression of characteristic genes. RESULTS: A total of 940 DEGs were identified between HTS and normal samples, and 288 key module genes were uncovered via WGCNA. Enrichment analysis in key module revealed involvement in many immune-related pathways, such as Th17 cell differentiation, antigen processing and presentation and B cell receptor signaling pathway. The eight immune-related genes (IFI30, NR2F2, NRG1, ESM1, NFATC2, CRLF1, COLEC12 and IL6) were identified by matching from the ImmPort database. Notably, we observed that activated mast cell positively correlated with CRLF1 expression, while CD8 T cells exhibited a positive correlation with NRG1. The expression of NRG1 and CRLF1 was further validated in clinical samples. CONCLUSION: In this study, two key immune-related genes (CRLF1 and NRG1) were identified as characteristic genes associated with HTS. These findings provide valuable insights into the immune-related mechanisms underlying hypertrophic scar formation.