Dynamic immunoediting by macrophages in homologous recombination deficiency-stratified pancreatic ductal adenocarcinoma.

Pancreatic ductal adenocarcinoma (PDAC) is a lethal disease, notably resistant to existing therapies. Current research indicates that PDAC patients deficient in homologous recombination (HR) benefit from platinum-based treatments and poly-ADP-ribose polymerase inhibitors (PARPi). However, the effectiveness of PARPi in HR-deficient (HRD) PDAC is suboptimal, and significant challenges remain in fully understanding the distinct characteristics and implications of HRD-associated PDAC. We analyzed 16 PDAC patient-derived tissues, categorized by their homologous recombination deficiency (HRD) scores, and performed high-plex immunofluorescence analysis to define 20 cell phenotypes, thereby generating an in-situ PDAC tumor-immune landscape. Spatial phenotypic-transcriptomic profiling guided by regions-of-interest (ROIs) identified a crucial regulatory mechanism through localized tumor-adjacent macrophages, potentially in an HRD-dependent manner. Cellular neighborhood (CN) analysis further demonstrated the existence of macrophage-associated high-ordered cellular functional units in spatial contexts. Using our multi-omics spatial profiling strategy, we uncovered a dynamic macrophage-mediated regulatory axis linking HRD status with SIGLEC10 and CD52. These findings demonstrate the potential of targeting CD52 in combination with PARPi as a therapeutic intervention for PDAC.

Mechanism of immune activation mediated by genomic instability and its implication in radiotherapy combined with immune checkpoint inhibitors.

Various genetic and epigenetic changes associated with genomic instability (GI), including DNA damage repair defects, chromosomal instability, and mitochondrial GI, contribute to development and progression of cancer. These alterations not only result in DNA leakage into the cytoplasm, either directly or through micronuclei, but also trigger downstream inflammatory signals, such as the cyclic GMP-AMP synthase (cGAS)-stimulator of interferon genes (STING) signaling pathway. Apart from directly inducing DNA damage to eliminate cancer cells, radiotherapy (RT) exerts its antitumor effects through intracellular DNA damage sensing mechanisms, leading to the activation of downstream inflammatory signaling pathways. This not only enables local tumor control but also reshapes the immune microenvironment, triggering systemic immune responses. The combination of RT and immunotherapy has emerged as a promising approach to increase the probability of abscopal effects, where distant tumors respond to treatment due to the systemic immunomodulatory effects. This review emphasizes the importance of GI in cancer biology and elucidates the mechanisms by which RT induces GI remodeling of the immune microenvironment. By elucidating the mechanisms of GI and RT-induced immune responses, we aim to emphasize the crucial importance of this approach in modern oncology. Understanding the impact of GI on tumor biological behavior and therapeutic response, as well as the possibility of activating systemic anti-tumor immunity through RT, will pave the way for the development of new treatment strategies and improve prognosis for patients.

A single-cell pan-cancer analysis to show the variability of tumor-infiltrating myeloid cells in immune checkpoint blockade.

Myeloid cells are vital components of the immune system and have pivotal functions in orchestrating immune responses. Understanding their functions within the tumor microenvironment and their interactions with tumor-infiltrating lymphocytes presents formidable challenges across diverse cancer types, particularly with regards to cancer immunotherapies. Here, we explore tumor-infiltrating myeloid cells (TIMs) by conducting a pan-cancer analysis using single-cell transcriptomics across eight distinct cancer types, encompassing a total of 192 tumor samples from 129 patients. By examining gene expression patterns and transcriptional activities of TIMs in different cancer types, we discern notable alterations in abundance of TIMs and kinetic behaviors prior to and following immunotherapy. We also identify specific cell-cell interaction targets in immunotherapy; unique and shared regulatory profiles critical for treatment response; and TIMs associated with survival outcomes. Overall, our study illuminates the heterogeneity of TIMs and improves our understanding of tissue-specific and cancer-specific myeloid subsets within the context of tumor immunotherapies.

A dynamic online nomogram predicting prostate cancer short-term prognosis based on 18F-PSMA-1007 PET/CT of periprostatic adipose tissue: a multicenter study.

BACKGROUND: Rising prostate-specific antigen (PSA) levels following radical prostatectomy are indicative of a poor prognosis, which may associate with periprostatic adipose tissue (PPAT). Accordingly, we aimed to construct a dynamic online nomogram to predict tumor short-term prognosis based on 18F-PSMA-1007 PET/CT of PPAT. METHODS: Data from 268 prostate cancer (PCa) patients who underwent 18F-PSMA-1007 PET/CT before prostatectomy were analyzed retrospectively for model construction and validation (training cohort: n = 156; internal validation cohort: n = 65; external validation cohort: n = 47). Radiomics features (RFs) from PET and CT were extracted. Then, the Rad-score was constructed using logistic regression analysis based on the 25 optimal RFs selected through maximal relevance and minimal redundancy, as well as the least absolute shrinkage and selection operator. A nomogram was constructed to predict short-term prognosis which determined by persistent PSA. RESULTS: The Rad-score consisting of 25 RFs showed good discrimination for classifying persistent PSA in all cohorts (all P < 0.05). Based on the logistic analysis, the radiomics-clinical combined model, which contained the optimal RFs and the predictive clinical variables, demonstrated optimal performance at an AUC of 0.85 (95% CI: 0.78-0.91), 0.77 (95% CI: 0.62-0.91) and 0.84 (95% CI: 0.70-0.93) in the training, internal validation and external validation cohorts. In all cohorts, the calibration curve was well-calibrated. Analysis of decision curves revealed greater clinical utility for the radiomics-clinical combined nomogram. CONCLUSION: The radiomics-clinical combined nomogram serves as a novel tool for preoperative individualized prediction of short-term prognosis among PCa patients.

Radiotherapy enhances efficacy of PD-1 inhibitors in advanced hepatocellular carcinoma: A propensity-matched real-world study.

BACKGROUND: To address the need for immunotherapy in patients with advanced primary hepatocellular carcinoma (HCC), combination with radiotherapy (RT) has emerged as a promising strategy. In preclinical studies, irradiated tumors released tumor antigens to synergistically increase the antitumor effect of immunotherapy. Hence, we investigated whether RT enhances the efficacy of anti-programmed death receptor-1 (PD-1) inhibitors in advanced HCC in real-world practice. METHODS: Between August 2018 and June 2021, 172 patients with advanced primary HCC were enrolled in the tertiary center (Zhongshan Hospital of Fudan University); 95 were treated with a combination of RT and the inhibitor of PD-1 (RT-PD1 cohort), and 77 were administered anti-PD-1 therapy (PD1 cohort). The first cycle of PD-1 inhibitors was administered within 60 days or concurrently with RT. Propensity score matching for bias reduction was used to evaluate the clinical outcomes. RESULTS: Among 71 propensity-matched pairs, median progression-free survival was 5.7 months in the RT-PD1 cohort vs. 2.9 months in the PD1 cohort ( P  <0.001). Median overall survival was 20.9 months in the RT-PD1 cohort vs. 11.2 months in the PD1 cohort ( P  = 0.018). Compared with patients in the PD1 cohort, patients in the RT-PD1 cohort had significantly higher objective response rates (40.8%, 29/71 vs. 19.7%, 14/71, P  = 0.006) and disease control rates (62.0%, 44/71 vs. 31.0%, 22/71, P  <0.001). The incidences of toxic effects were not significantly different between the two cohorts. CONCLUSIONS: RT plus anti-PD-1 therapy is well tolerated. RT enhances the efficacy of anti-PD-1 therapy in patients with advanced primary HCC by improving survival outcomes without increased toxic effects.

RECQL4 Inhibits Radiation-Induced Tumor Immune Awakening via Suppressing the cGAS-STING Pathway in Hepatocellular Carcinoma.

Many patients with hepatocellular carcinoma (HCC) respond poorly to radiotherapy despite remarkable advances in treatment. A deeper insight into the mechanism of sensitivity of HCC to this therapy is urgently required. It is demonstrated that RECQL4 is upregulated in the malignant cells of patients with HCC. Elevated RECQL4 levels reduce the sensitivity of HCC to radiotherapy by repairing radiation-induced double-stranded DNA (dsDNA) fragments. Mechanistically, the inhibitory effect of RECQL4 on radiotherapy is due to the reduced recruitment of dendritic cells and CD8+ T cells in the tumor microenvironment (TME). RECQL4 disrupts the radiation-induced transformation of the TME into a tumoricidal niche by inhibiting the cGAS-STING pathway in dendritic cells. Knocking out STING in dendritic cells can block the impact of RECQL4 on HCC radiosensitivity. Notably, high RECQL4 expressions in HCC is significantly associated with poor prognosis in multiple independent cohorts. In conclusion, this study highlights how HCC-derived RECQL4 disrupts cGAS-STING pathway activation in dendritic cells through DNA repair, thus reducing the radiosensitivity of HCC. These findings provide new perspectives on the clinical treatment of HCC.

Multimodal radiomics based on 18F-Prostate-specific membrane antigen-1007 PET/CT and multiparametric MRI for prostate cancer extracapsular extension prediction.

OBJECTIVES: To compare the performance of the multiparametric magnetic resonance imaging (mpMRI) radiomics and 18F-Prostate-specific membrane antigen (PSMA)-1007 PET/CT radiomics model in diagnosing extracapsular extension (EPE) in prostate cancer (PCa), and to evaluate the performance of a multimodal radiomics model combining mpMRI and PET/CT in predicting EPE. METHODS: We included 197 patients with PCa who underwent preoperative mpMRI and PET/CT before surgery. mpMRI and PET/CT images were segmented to delineate the regions of interest and extract radiomics features. PET/CT, mpMRI, and multimodal radiomics models were constructed based on maximum correlation, minimum redundancy, and logistic regression analyses. Model performance was evaluated using the area under the receiver operating characteristic curve (AUC) and indices derived from the confusion matrix. RESULTS: AUC values for the mpMRI, PET/CT, and multimodal radiomics models were 0.85 (95% CI, 0.78-0.90), 0.73 (0.64-0.80), and 0.83 (0.75-0.89), respectively, in the training cohort and 0.74 (0.61-0.85), 0.62 (0.48-0.74), and 0.77 (0.64-0.87), respectively, in the testing cohort. The net reclassification improvement demonstrated that the mpMRI radiomics model outperformed the PET/CT one in predicting EPE, with better clinical benefits. The multimodal radiomics model performed better than the single PET/CT radiomics model (P < .05). CONCLUSION: The mpMRI and 18F-PSMA-PET/CT combination enhanced the predictive power of EPE in patients with PCa. The multimodal radiomics model will become a reliable and robust tool to assist urologists and radiologists in making preoperative decisions. ADVANCES IN KNOWLEDGE: This study presents the first application of multimodal radiomics based on PET/CT and MRI for predicting EPE.

CENPL accelerates cell proliferation, cell cycle, apoptosis, and glycolysis via the MEK1/2-ERK1/2 pathway in hepatocellular carcinoma.

Centromere protein L (CENPL) is involved in the mitotic process of eukaryotic cells and the development of various types of cancer. However, its role in hepatocellular carcinoma (HCC) remains unclear. This study aimed to investigate the expression and clinical significance of CENPL in HCC, and explore its involvement in regulating HCC cell proliferation, apoptosis, cell cycle, and glycolysis both in vivo and in vitro. CENPL expression was analyzed in HCC and normal liver tissues using The Cancer Genome Atlas, Gene Expression Omnibus mining, real-time quantitative polymerase chain reaction, and immunohistochemistry. Functional assays were used to assess the role of CENPL in HCC cell proliferation, apoptosis, cell cycle, and glycolysis. The potential pathways underlying the regulatory effects of CENPL, as well as the expression of mitogen-activated protein kinase (MAPK) signaling pathway-related molecules and markers of proliferation and glycolysis were investigated. CENPL was significantly upregulated in HCC tissue and associated with multiple clinicopathological features and poor patient prognosis. Univariate and multivariate analyses demonstrated that CENPL may serve as an independent prognostic factor for HCC. Upregulation of CENPL in HCC regulated tumor proliferation and glycolytic processes. Mechanistic studies revealed that differentially expressed genes between the CENPL-overexpressing and control groups were mainly concentrated in the MAPK signaling pathway. Pathway inhibition analysis indicated that CENPL activated the MEK1/2-ERK1/2 signaling pathway to promote proliferation and glycolysis in HCC cells. This study elucidated the role of CENPL in regulating cell proliferation, apoptosis, cell cycle, and glycolysis in HCC. CENPL may represent a therapeutic target and prognostic biomarker for HCC.

Deciphering the immune modulation through deep transcriptomic profiling and therapeutic implications of DNA damage repair pattern in hepatocellular carcinoma.

AIMS: DNA damage repair (DDR) plays a pivotal role in hepatocellular carcinoma (HCC), driving oncogenesis, progression, and therapeutic response. However, the mechanisms of DDR mediated immune cells and immuno-modulatory pathways in HCC are yet ill-defined. METHODS: Our study introduces an innovative deep machine learning framework for precise DDR assessment, utilizing single-cell RNA sequencing (scRNA-seq) and bulk RNA-seq data. Single-cell RNA sequencing data were obtained and in total 85,628 cells of primary or post-immunotherapy cases were analyzed. Large-scale HCC datasets, including 1027 patients in house together with public datasets, were used for 101 machine-learning models and a novel DDR feature was derived at single-cell resolution (DDRscore). Druggable targets were predicted using the reverse phase protein array (RPPA) proteomic profiling of 169 HCC patients and RNA-seq data from 22 liver cancer cell lines. RESULTS: Our investigation reveals a dynamic interplay of DDR with natural killer cells and B cells in the primary HCC microenvironment, shaping a tumor-promoting immune milieu through metabolic programming. Analysis of HCC post-immunotherapy demonstrates elevated DDR levels that induces epithelial-mesenchymal transition and fibroblast-like transformation, reshaping the fibrotic tumor microenvironment. Conversely, attenuated DDR promotes antigen cross-presentation by dendritic cells and CD8+ T cells, modulating the inflammatory tumor microenvironment. Regulatory network analysis identifies the CXCL10-CXCR3 axis as a key determinant of immunotherapeutic response in low DDR HCC, potentially regulated by transcription factors GATA3, REL, and TBX21. Using machine learning techniques by combining bulk RNA-seq data in house together with public datasets, we introduce DDRscore, a robust consensus DDR scoring system to predict overall survival and resistance to PD-1 therapy in HCC patients. Finally, we identify BRAF as a potential therapeutic target for high DDRscore patients. CONCLUSION: Our comprehensive findings advance our understanding of DDR and the tumor microenvironment in HCC, providing insights into immune regulatory mechanisms mediated via DDR pathways.

Ursa: A Comprehensive Multiomics Toolbox for High-Throughput Single-Cell Analysis.

The burgeoning amount of single-cell data has been accompanied by revolutionary changes to computational methods to map, quantify, and analyze the outputs of these cutting-edge technologies. Many are still unable to reap the benefits of these advancements due to the lack of bioinformatics expertise. To address this issue, we present Ursa, an automated single-cell multiomics R package containing 6 automated single-cell omics and spatial transcriptomics workflows. Ursa allows scientists to carry out post-quantification single or multiomics analyses in genomics, transcriptomics, epigenetics, proteomics, and immunomics at the single-cell level. It serves as a 1-stop analytic solution by providing users with outcomes to quality control assessments, multidimensional analyses such as dimension reduction and clustering, and extended analyses such as pseudotime trajectory and gene-set enrichment analyses. Ursa aims bridge the gap between those with bioinformatics expertise and those without by providing an easy-to-use bioinformatics package for scientists in hoping to accelerate their research potential. Ursa is freely available at https://github.com/singlecellomics/ursa.

Coiled-coil domain-containing 154 promotes colorectal cancer proliferation and metastasis via interacting with minichromosome maintenance complex component 2.

Coiled-Coil Domain-Containing (CCDC) is a large class of structural proteins containing left-handed supercoiled structure. The clinical value and the functional implication of CCDC in colorectal cancer (CRC) remain unknown. Based on the genetic, transcriptional, and clinical data from The Cancer Genome Atlas, five of thirty-six CCDC proteins were differentially expressed in the CRC and associated with the survival of patients with CRC. A CCDC-score model was established to evaluate the prognosis of patients. The potential function of Coiled-Coil Domain-Containing 154 (CCDC154) was investigated using bioinformatical methods, which unveiled that high expression of CCDC154 indicates poor survival for patients with CRC and correlates with low infiltration of CD8+ T cells and high infiltration of neutrophils, indicating that CCDC154 enhances tumor growth and metastasis. CCDC154 interacts with Minichromosome Maintenance Complex Component 2 (MCM2) protein and promotes malignant phenotype via MCM2. We validated the expression level and survival prediction value of CCDC154 in clinical samples, and analyzed its co-expression of MCM2, Ki-67 and p53. This work discloses the role of CCDC in clinical setting and CCDC154 functions in CRC.

Deep dissection of stemness-related hierarchies in hepatocellular carcinoma.

BACKGROUND: Increasing evidence suggests that hepatocellular carcinoma (HCC) stem cells (LCSCs) play an essential part in HCC recurrence, metastasis, and chemotherapy and radiotherapy resistance. Multiple studies have demonstrated that stemness-related genes facilitate the progression of tumors. However, the mechanism by which stemness-related genes contribute to HCC is not well understood. Here, we aim to construct a stemness-related score (SRscores) model for deeper analysis of stemness-related genes, assisting with the prognosis and individualized treatment of HCC patients.Further, we found that the gene LPCAT1 was highly expressed in tumor tissues by immunohistochemistry, and sphere-forming assay revealed that knockdown of LPCAT1 inhibited the sphere-forming ability of hepatocellular carcinoma cells. METHODS: We used the TCGA-LIHC dataset to screen stemness-related genes of HCC from the MSigDB database. Prognosis, tumor microenvironment, immunological checkpoints, tumor immune dysfunction, rejection, treatment sensitivity, and putative biological pathways were examined. Random forest created the SRscores model. The anti-PD-1/anti-CTLA4 immunotherapy, tumor mutational burden, medication sensitivity, and cancer stem cell index were compared between the high- and low-risk score groups. We also examined risk scores for different cell types using single-cell RNA sequencing data and correlated transcription factor activity in cancer stem cells with SRscores genes. Finally, we tested core marker expression and biological functions. RESULTS: Patients can be divided into two subtypes (Cluster1 and Cluster2) based on the TCGA-LIHC dataset's identification of 11 stemness-related genes. Additionally, a SRscores was developed based on subtypes. Cluster2 and the group with the lowest SRscores had superior survival and immunotherapy response than Cluster1 and the group with the highest SRscores. The group with a high SRscores was significantly more enriched in classical tumor pathways than the group with a low SRscores. Multiple transcription factors and SRscores genes are correlated. The core gene LPCAT1 is highly expressed in rat liver cancer tissues and promotes tumor cell sphere formation. CONCLUSION: A SRscores model can be utilized to predict the prognosis of HCC patients as well as their response to immunotherapy.

STING-Dependent Sensing of Self-DNA Driving Pyroptosis Contributes to Radiation-Induced Lung Injury.

PURPOSE: Radiation therapy (RT) is indispensable for managing thoracic carcinomas. However, its application is limited by radiation-induced lung injury (RILI), one of the most common and fatal complications of thoracic RT. Nonetheless, the exact molecular mechanisms of RILI remain poorly understood. METHODS AND MATERIALS: To elucidate the underlying mechanisms, various knockout mouse strains were subjected to 16 Gy whole-thoracic RT. RILI was assessed by quantitative real-time polymerase chain reaction, enzyme-linked immunosorbent assay, histology, western blot, immunohistochemistry, and computed tomography examination. To perform further mechanistic studies on the signaling cascade during the RILI process, pulldown, chromatin immunoprecipitation assay, and rescue assays were conducted. RESULTS: We found that the cGAS-STING pathway was significantly upregulated after irradiation exposure in both the mouse models and clinical lung tissues. Knocking down either cGAS or STING led to attenuated inflammation and fibrosis in mouse lung tissues. NLRP3 is hardwired to the upstream DNA-sensing cGAS-STING pathway to trigger of the inflammasome and amplification of the inflammatory response. STING deficiency suppressed the expressions of the NLRP3 inflammasome and pyroptosis-pertinent components containing IL-1ß, IL-18, GSDMD-N, and cleaved caspase-1. Mechanistically, interferon regulatory factor 3, the essential transcription factor downstream of cGAS-STING, promoted the pyroptosis by transcriptionally activating NLRP3. Moreover, we found that RT triggered the release of self-dsDNA in the bronchoalveolar space, which is essential for the activation of cGAS-STING and the downstream NLRP3-mediated pyroptosis. Of note, Pulmozyme, an old drug for the management of cystic fibrosis, was revealed to have the potential to mitigate RILI by degrading extracellular dsDNA and then inhibiting the cGAS-STING-NLRP3 signaling pathway. CONCLUSIONS: These results delineated the crucial function of cGAS-STING as a key mediator of RILI and described a mechanism of pyroptosis linking cGAS-STING activation with the amplification of initial RILI. These findings indicate that the dsDNA-cGAS-STING-NLRP3 axis might be potentially amenable to therapeutic targeting for RILI.

Anoikis resistance of small airway epithelium is involved in the progression of chronic obstructive pulmonary disease.

Background: Anoikis resistance is recognized as a crucial step in the metastasis of cancer cells. Most epithelial tumors are distinguished by the ability of epithelial cells to abscond anoikis when detached from the extracellular matrix. However, no study has investigated the involvement of anoikis in the small airway epithelium (SAE) of chronic obstructive pulmonary disease (COPD). Methods: Anoikis-related genes (ANRGs) exhibiting differential expression in COPD were identified using microarray datasets obtained from the Gene Expression Omnibus (GEO) database. Unsupervised clustering was performed to classify COPD patients into anoikis-related subtypes. Gene Ontology (GO) analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis, gene set enrichment analysis (GSEA), and gene set variation analysis (GSVA) were used to annotate the functions between different subtypes. Differential expression analysis and weighted gene co-expression network analysis (WGCNA) were leveraged to identify key molecules. The relative proportion of infiltrating immune cells in the SAE was quantified using the CIBERSORT and ssGSEA computational algorithms, and the correlation between key molecules and immune cell abundance was analyzed. The expression of key molecules in BEAS-2B cells exposed to cigarette smoke extract (CSE) was validated using qRT-PCR. Results: A total of 25 ANRGs exhibited differential expression in the SAE of COPD patients, based on which two subtypes of COPD patients with distinct anoikis patterns were identified. COPD patients with anoikis resistance had more advanced GOLD stages and cigarette consumption. Functional annotations revealed a different immune status between COPD patients with pro-anoikis and anoikis resistance. Tenomodulin (TNMD) and long intergenic non-protein coding RNA 656 (LINC00656) were subsequently identified as key molecules involved in this process, and a close correlation between TNMD and the infiltrating immune cells was observed, such as activated CD4+ memory T cells, M1 macrophages, and activated NK cells. Further enrichment analyses clarified the relationship between TNMD and the inflammatory and apoptotic signaling pathway as the potential mechanism for regulating anoikis. In vitro experiments showed a dramatic upregulation of TNMD and LINC00656 in BEAS-2B cells when exposed to 3% CSE for 48 hours. Conclusion: TNMD contributes to the progression of COPD by inducing anoikis resistance in SAE, which is intimately associated with the immune microenvironment.

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.

Antinuclear antibody (ANA) status predicts immune-related adverse events in liver cancer patients undergoing anti-PD-1 therapy.

Immune-related adverse events (irAEs) clinically resemble autoimmune diseases, indicating autoantibodies could be potential biomarkers for the prediction of irAEs. This study aimed to assess the predictive value of peripheral blood antinuclear antibody (ANA) status for irAEs, considering the time and severity of irAEs, as well as treatment outcome in liver cancer patients administered anti-PD-1 therapy. Ninety-three patients with advanced primary liver cancer administered anti-PD-1 treatment were analyzed retrospectively. They were divided into the ANA positive (ANA+, titer ≥ 1:100) and negative (ANA-, titer < 1:100) groups. Development of irAEs, progression-free survival (PFS), and overall survival (OS) were assessed. Compared with ANA- patients, ANA+ cases were more prone to develop irAEs (43.3% vs. 19.2%, P = 0.031). With the increase of ANA titers, the frequency of irAEs increased. The time interval between anti-PD-1 therapy and the onset of irAEs was significantly shorter in ANA+ patients compared with the ANA- group (median, 1.7 months vs. 5.0 months, P = 0.022). Moreover, the time between anti-PD-1 therapy and irAE occurrence decreased with increasing ANA titer. In addition, PFS and OS were decreased in ANA+ patients compared with the ANA- group (median PFS, 2.8 months vs. 4.2 months, P = 0.043; median OS, 21.1 months vs. not reached, P = 0.041). IrAEs occur at higher frequency in ANA+ liver cancer patients undergoing anti-PD-1 therapy. ANA titer could help predict irAE development and treatment outcome in these patients.

[Comparison between macroscopic identification and DNA barcoding identification of Amomi Fructus].

This study aims to explore the consistency between macroscopic identification and DNA barcoding identification of Amomi Fructus. With the DNA barcoding identification results, we evaluated the reliability of identifying Amomi Fructus quality by combining macroscopic traits with main volatile chemical components. Thirteen batches of Amomi Fructus samples were collected for identification. Firstly, the morphological and sensory characteristics of each sample were observed and recorded according to the standard in Chinese Pharmacopoeia(2020 edition). The 100-fruit weight, longitudinal diameter, transverse diameter, and longitudinal diameter-to-transverse diameter ratio were measured, which correspond to large, solid, and full kernel representing good quality in the sensory evaluation. The odor value detected by electronic nose and major volatile components(borneol, camphor, limonene, and borneol acetate) correspond to the sensory evaluation of strong odor representing good quality. Secondly, DNA barcoding was employed to identify the 13 batches of samples. Finally, clustering analysis was performed for the main volatile components and macroscopic traits, and the identification results were compared with those of DNA barcoding. Except two batches of samples(No.6 and No.10), the macroscopic identification showed the results consistent with those of DNA barcoding, with an identification rate of 84.62%. The clustering results of the content of four volatile chemical components and macroscopic traits were also consistent with the DNA barcoding identification results. DNA barcoding can verify the results of macroscopic identification and provide a scientific basis for the inheritance and development of macroscopic identification. Moreover, the combination of macroscopic traits and chemical components demonstrates higher accuracy in the quality evaluation of Chinese medicinal materials.

Gut microbiota modulate radiotherapy-associated antitumor immune responses against hepatocellular carcinoma Via STING signaling.

Studies of the gut-liver axis have enhanced our understanding of the pathophysiology of various liver diseases and the mechanisms underlying the regulation of the effectiveness of therapies. Radiotherapy (RT) is an important therapeutic option for patients with unresectable hepatocellular carcinoma (HCC). However, the role of the microbiome in regulating the response to RT remains unclear. The present study characterizes the gut microbiome of patients responsive or non-responsive to RT and investigates the molecular mechanisms underlying the differences in patient response. We collected fecal samples for 16S rRNA sequencing from a prospective longitudinal trial of 24 HCC patients receiving RT. We used fecal microbiota transplantation (FMT), flow cytometry, and transcriptome sequencing to explore the effects of dysbiosis on RT. We also examined the role of stimulator of interferon genes (STING) in RT-associated antitumor immune responses mediated by gut microbiota in STING- (Tmem173-/-) and cGAS-knockout (Mb21d1-/-) mouse models. We propose that primary resistance to RT could be attributed to the disruption of the gut microbiome. Mechanistically, gut microbiome dysbiosis impairs antitumor immune responses by suppressing antigen presentation and inhibiting effector T cell functions through the cGAS-STING-IFN-I pathway. Cyclic-di-AMP - an emerging second messenger of bacteria - may act as a STING agonist and is thus a potential target for the prediction and modulation of responses to RT in HCC patients. Our study highlights the therapeutic potential of modulating the gut microbiome in HCC patients receiving RT and provides a new strategy for the radiosensitization of liver cancer.

Molecular Characteristics of T Cell-Mediated Tumor Killing in Hepatocellular Carcinoma.

Background: Although checkpoint blockade is a promising approach for the treatment of hepatocellular carcinoma (HCC), subsets of patients expected to show a response have not been established. As T cell-mediated tumor killing (TTK) is the fundamental principle of immune checkpoint inhibitor therapy, we established subtypes based on genes related to the sensitivity to TKK and evaluated their prognostic value for HCC immunotherapies. Methods: Genes regulating the sensitivity of tumor cells to T cell-mediated killing (referred to as GSTTKs) showing differential expression in HCC and correlations with prognosis were identified by high-throughput screening assays. Unsupervised clustering was applied to classify patients with HCC into subtypes based on the GSTTKs. The tumor microenvironment, metabolic properties, and genetic variation were compared among the subgroups. A scoring algorithm based on the prognostic GSTTKs, referred to as the TCscore, was developed, and its clinical and predictive value for the response to immunotherapy were evaluated. Results: In total, 18 out of 641 GSTTKs simultaneously showed differential expression in HCC and were correlated with prognosis. Based on the 18 GSTTKs, patients were clustered into two subgroups, which reflected distinct TTK patterns in HCC. Tumor-infiltrating immune cells, immune-related gene expression, glycolipid metabolism, somatic mutations, and signaling pathways differed between the two subgroups. The TCscore effectively distinguished between populations with different responses to chemotherapeutics or immunotherapy and overall survival. Conclusions: TTK patterns played a nonnegligible role in formation of TME diversity and metabolic complexity. Evaluating the TTK patterns of individual tumor will contribute to enhancing our cognition of TME characterization, reflects differences in the functionality of T cells in HCC and guiding more effective therapy strategies.

Exploration on Varying Patterns of Morphological Features and Quality of Armeniacae Semen Amarum in Rancid Process Based on Colorimeter, Electronic Nose, and GC/MS Coupled With Human Panel.

In recent years, the domestic and international trade volumes of Chinese medicinal materials (CMMs) keep increasing. By the end of 2019, the total amount of exported CMMs reached as high as US $1.137 billion, while imported was US $2.155 billion. A stable and controllable quality system of CMMs apparently becomes the most important issue, which needs multifaceted collaboration from harvesting CMMs at a proper season to storing CMMs at a proper temperature. However, due to imperfect storage conditions, different kinds of deteriorations are prone to occur, for instance, get moldy or rancid, which not only causes a huge waste of CMM resources but also poses a great threat to clinical medication safety and public health. The key issue is to quickly and accurately distinguish deteriorated CMM samples so as to avoid consuming low-quality or even harmful CMMs. However, some attention has been paid to study the changing quality of deteriorated CMMs and a suitable method for identifying them. In this study, as a medicine and food material which easily becomes rancid, armeniacae semen amarum (ASA) was chosen as a research objective, and experimental ASA samples of different rancidness degrees were collected. Then, various kinds of analytical methods and technologies were applied to explore the changing rules of ASA quality and figure out the key indicators for the quality evaluation of ASA in the rancid process, including the human panel, colorimeter, electronic nose, and GC/MS. This study aims to analyze the correlation between the external morphological features and the inner chemical compounds, to find out the specific components from "quantitative change" to "qualitative change" in the process of "getting rancid," and to discover the dynamic changes in the aforementioned key indicators at different stages of rancidness. The results showed since ASA samples began to get rancid with the extension of storage time, morphological features, namely, surface color and smell, changed significantly, and the degree of rancidness further deepened at the same time. Based on macroscopic identification accomplished via the human panel, ASA samples with varying degrees of rancidness were divided into four groups. The result of colorimeter analysis was in agreement with that of the human panel, as well as the determination of the amygdalin content and peroxide value. Moreover, there were obvious differences in the amygdalin content and peroxide value among ASA samples with different rancidness degrees. With a higher degree of rancidness, the content of amygdalin decreased, while the peroxide value increased significantly. The rancidness degree of ASA has a negative correlation with the amygdalin content and a positive correlation with the peroxide value. The newly discovered nonanal and 2-bromopropiophenone in rancid ASA samples may be the key components of "rancidity smell," and these two components would be the exclusive components that trigger "quantitative change" to "qualitative change" in the process of rancidness of ASA. This study sheds light on studying the internal mechanism of "rancidness" of CMMs and provides an important basis for the effective storage and safe medication of easy-to-get rancid herbs, and it also plays an important foundation for the establishment of a stable and controllable quality system for CMMs.