Joint DNA-RNA-based NGS for diagnosis and treatment of a rare CD47-MET fusion lung adenocarcinoma which was immunoresistant and savoltinib-sensitive: a case report.

Targeted therapy and immunotherapy are both important in the treatment of non-small-cell lung cancer (NSCLC). Accurate diagnose and precise treatment are key in achieving long survival of patients. MET fusion is a rare oncogenic factor, whose optimal detection and treatment are not well established. Here, we report on a 32-year-old female lung adenocarcinoma patient with positive PD-L1 and negative driver gene detected by DNA-based next-generation sequencing (NGS). A radical resection of the primary lesion after chemotherapy combined with PD-1 checkpoint inhibitor administration indicated primary immuno-resistance according to her pathological response and rapid relapse. A rare CD47-MET was detected by RNA-based NGS, which was confirmed by fluorescence in situ hybridization. Multiplex immunofluorescence revealed a PD-L1 related heterogeneous immunosuppressive microenvironment with little distribution of CD4+ T cells and CD8+ T cells. Savolitinib therapy resulted in a progression-free survival (PFS) of >12 months, until a new secondary resistance mutation in MET p.D1228H was detected by re-biopsy and joint DNA-RNA-based NGS after disease progression. In this case, CD47-MET fusion NSCLC was primarily resistant to immunotherapy, sensitive to savolitinib, and developed secondary MET p.D1228H mutation after targeted treatment. DNA-RNA-based NGS is useful in the detection of such molecular events and tracking of secondary mutations in drug resistance. To this end, DNA-RNA-based NGS may be of better value in guiding precise diagnosis and individualized treatment in this patient population.

Research progress on roles of iron metabolism in the occurrence and development of periodontitis. / é“ä»£è°¢åœ¨æ ¢æ€§ç‰™å‘¨ç‚Žå‘ç”Ÿå‘å±•ä¸­çš„ä½œç”¨ç ”ç©¶è¿›å±•.

Iron metabolism refers to the process of absorption, transport, excretion and storage of iron in organisms, including the biological activities of iron ions and iron-binding proteins in cells. Clinical research and animal experiments have shown that iron metabolism is associated with the progress of periodontitis. Iron metabolism can not only enhance the proliferation and toxicity of periodontal pathogens, but also activate host immune- inflammatory response mediated by macrophages, neutrophils and lymphocytes. In addition, iron metabolism is also involved in regulating the cellular death sensitivity of gingival fibroblasts and osteoblasts and promoting the differentiation of osteoclasts to play a regulatory role in the regeneration and repair of periodontal tissue. This article reviews the research progress on the pathogenesis of periodontitis from the perspective of iron metabolism, aiming to provide new ideas for the treatment of periodontitis.

Bioinspired soft-hard combined system with mild photothermal therapeutic activity promotes diabetic bone defect healing via synergetic effects of immune activation and angiogenesis.

Background: The comprehensive management of diabetic bone defects remains a substantial clinical challenge due to the hostile regenerative microenvironment characterized by aggravated inflammation, excessive reactive oxygen species (ROS), bacterial infection, impaired angiogenesis, and unbalanced bone homeostasis. Thus, an advanced multifunctional therapeutic platform capable of simultaneously achieving immune regulation, bacterial elimination, and tissue regeneration is urgently designed for augmented bone regeneration under diabetic pathological milieu. Methods and Results: Herein, a photoactivated soft-hard combined scaffold system (PGCZ) was engineered by introducing polydopamine-modified zeolitic imidazolate framework-8-loaded double-network hydrogel (soft matrix component) into 3D-printed poly(ε-caprolactone) (PCL) scaffold (hard matrix component). The versatile PGCZ scaffold based on double-network hydrogel and 3D-printed PCL was thus prepared and features highly extracellular matrix-mimicking microstructure, suitable biodegradability and mechanical properties, and excellent photothermal performance, allowing long-term structural stability and mechanical support for bone regeneration. Under periodic near-infrared (NIR) irradiation, the localized photothermal effect of PGCZ triggers the on-demand release of Zn2+, which, together with repeated mild hyperthermia, collectively accelerates the proliferation and osteogenic differentiation of preosteoblasts and potently inhibits bacterial growth and biofilm formation. Additionally, the photoactivated PGCZ system also presents outstanding immunomodulatory and ROS scavenging capacities, which regulate M2 polarization of macrophages and drive functional cytokine secretion, thus leading to a pro-regenerative microenvironment in situ with enhanced vascularization. In vivo experiments further demonstrated that the PGCZ platform in conjunction with mild photothermal therapeutic activity remarkably attenuated the local inflammatory cascade, initiated endogenous stem cell recruitment and neovascularization, and orchestrated the osteoblast/osteoclast balance, ultimately accelerating diabetic bone regeneration. Conclusions: This work highlights the potential application of a photoactivated soft-hard combined system that provides long-term biophysical (mild photothermal stimulation) and biochemical (on-demand ion delivery) cues for accelerated healing of diabetic bone defects.

Action of circulating and infiltrating B cells in the immune microenvironment of colorectal cancer by single-cell sequencing analysis.

BACKGROUND: The complexity of the immune microenvironment has an impact on the treatment of colorectal cancer (CRC), one of the most prevalent malignancies worldwide. In this study, multi-omics and single-cell sequencing techniques were used to investigate the mechanism of action of circulating and infiltrating B cells in CRC. By revealing the heterogeneity and functional differences of B cells in cancer immunity, we aim to deepen our understanding of immune regulation and provide a scientific basis for the development of more effective cancer treatment strategies. AIM: To explore the role of circulating and infiltrating B cell subsets in the immune microenvironment of CRC, explore the potential driving mechanism of B cell development, analyze the interaction between B cells and other immune cells in the immune microenvironment and the functions of communication molecules, and search for possible regulatory pathways to promote the anti-tumor effects of B cells. METHODS: A total of 69 paracancer (normal), tumor and peripheral blood samples were collected from 23 patients with CRC from The Cancer Genome Atlas database (https://portal.gdc.cancer.gov/). After the immune cells were sorted by multicolor flow cytometry, the single cell transcriptome and B cell receptor group library were sequenced using the 10X Genomics platform, and the data were analyzed using bioinformatics tools such as Seurat. The differences in the number and function of B cell infiltration between tumor and normal tissue, the interaction between B cell subsets and T cells and myeloid cell subsets, and the transcription factor regulatory network of B cell subsets were explored and analyzed. RESULTS: Compared with normal tissue, the infiltrating number of CD20+B cell subsets in tumor tissue increased significantly. Among them, germinal center B cells (GCB) played the most prominent role, with positive clone expansion and heavy chain mutation level increasing, and the trend of differentiation into memory B cells increased. However, the number of plasma cells in the tumor microenvironment decreased significantly, and the plasma cells secreting IgA antibodies decreased most obviously. In addition, compared with the immune microenvironment of normal tissues, GCB cells in tumor tissues became more closely connected with other immune cells such as T cells, and communication molecules that positively regulate immune function were significantly enriched. CONCLUSION: The role of GCB in CRC tumor microenvironment is greatly enhanced, and its affinity to tumor antigen is enhanced by its significantly increased heavy chain mutation level. Meanwhile, GCB has enhanced its association with immune cells in the microenvironment, which plays a positive anti-tumor effect.

New perspectives in prognostication of hepatocellular carcinoma: The role and clinical implications of transient receptor potential family genes.

The study titled "Transient receptor potential-related risk model predicts prognosis of hepatocellular carcinoma patients" is a significant contribution to hepatocellular carcinoma (HCC) research, highlighting the role of transient receptor potential (TRP) family genes in the disease's progression and prognosis. Utilizing data from The Cancer Genome Atlas database, it establishes a new risk assessment model, emphasizing the interaction of TRP genes with tumor proliferation pathways, key metabolic reactions like retinol metabolism, and the tumor immune microenvironment. Notably, the overexpression of the TRPC1 gene in HCC correlates with poorer patient survival outcomes, suggesting its potential as a prognostic biomarker and a target for personalized therapy, particularly in strategies combining immunotherapy and anti-TRP agents.

Spatial distribution of tumour immune infiltrate predicts outcomes of patients with high-risk soft tissue sarcomas after neoadjuvant chemotherapy.

BACKGROUND: Anthracycline-based neoadjuvant chemotherapy (NAC) may modify tumour immune infiltrate. This study characterized immune infiltrate spatial distribution after NAC in primary high-risk soft tissue sarcomas (STS) and investigate association with prognosis. METHODS: The ISG-STS 1001 trial randomized STS patients to anthracycline plus ifosfamide (AI) or a histology-tailored (HT) NAC. Four areas of tumour specimens were sampled: the area showing the highest lymphocyte infiltrate (HI) at H&E; the area with lack of post-treatment changes (highest grade, HG); the area with post-treatment changes (lowest grade, LG); and the tumour edge (TE). CD3, CD8, PD-1, CD20, FOXP3, and CD163 were analyzed at immunohistochemistry and digital pathology. A machine learning method was used to generate sarcoma immune index scores (SIS) that predict patient disease-free and overall survival (DFS and OS). FINDINGS: Tumour infiltrating lymphocytes and PD-1+ cells together with CD163+ cells were more represented in STS histologies with complex compared to simple karyotype, while CD20+ B-cells were detected in both these histology groups. PD-1+ cells exerted a negative prognostic value irrespectively of their spatial distribution. Enrichment in CD20+ B-cells at HI and TE areas was associated with better patient outcomes. We generated a prognostic SIS for each tumour area, having the HI-SIS the best performance. Such prognostic value was driven by treatment with AI. INTERPRETATION: The different spatial distribution of immune populations and their different association with prognosis support NAC as a modifier of tumour immune infiltrate in STS. FUNDING: Pharmamar; Italian Ministry of Health [RF-2019-12370923; GR-2016-02362609]; 5 × 1000 Funds-2016, Italian Ministry of Health; AIRC Grant [ID#28546].

Deciphering the roles of the HMGB family in cancer: Insights from subcellular localization dynamics.

The high-mobility group box (HMGB) family consists of four DNA-binding proteins that regulate chromatin structure and function. In addition to their intracellular functions, recent studies have revealed their involvement as extracellular damage-associated molecular patterns (DAMPs), contributing to immune responses and tumor development. The HMGB family promotes tumorigenesis by modulating multiple processes including proliferation, metabolic reprogramming, metastasis, immune evasion, and drug resistance. Due to the predominant focus on HMGB1 in the literature, little is known about the remaining members of this family. This review summarizes the structural, distributional, as well as functional similarities and distinctions among members of the HMGB family, followed by a comprehensive exploration of their roles in tumor development. We emphasize the distributional and functional hierarchy of the HMGB family at both the organizational and subcellular levels, with a focus on their relationship with the tumor immune microenvironment (TIME), aiming to prospect potential strategies for anticancer therapy.

The tumor-stroma ratio in giant cell tumor of bone: associations with the immune microenvironment and responsiveness to denosumab treatment.

BACKGROUND: Currently, there is limited understanding regarding the clinical significance of the tumor-stroma ratio (TSR) in giant cell tumor of bone (GCTB). Hence, we aimed to investigate the distribution of TSR in GCTB and explore its correlation with various clinicopathologic factors, immune microenvironment, survival prognosis, and denosumab treatment responsiveness. METHODS: We conducted a multicenter cohort study comprising 426 GCTB patients treated at four centers. TSR was evaluated on hematoxylin and eosin-stained and immunofluorescent sections of tumor specimens. Immunohistochemistry was performed to assess CD3+, CD4+, CD8+, CD20+, PD-1+, PD-L1+, and FoxP3+ TIL subtypes as well as Ki-67 expression levels in 426 tissue specimens. These parameters were then analyzed for their correlations with patient outcomes [local recurrence-free survival (LRFS) and overall survival (OS)], clinicopathological features, and denosumab treatment responsiveness. RESULTS: Low TSR was significantly associated with poor LRFS and OS in both cohorts. Furthermore, TSR was also correlated with multiple clinicopathological features, TIL subtype expression, and denosumab treatment responsiveness. TSR demonstrated similar predictive capabilities as the conventional Campanacci staging system for predicting patients' LRFS and OS. CONCLUSION: The results of this study provide evidence supporting the use of TSR as a reliable prognostic tool in GCTB and as a predictor of denosumab treatment responsiveness. These findings may aid in developing individualized treatment strategies for GCTB patients in the future.

A Novel Cellular Senescence-related lncRNA Signature for Predicting the Prognosis of Breast Cancer Patients.

Background: Long non-coding RNA (lncRNA), a crucial regulator in breast cancer (BC) development, is intricately linked with cellular senescence. However, there is a lack of cellular senescence-related lncRNAs (CSRLs) signature to evaluate the prognosis of BC patients. Methods: Correlation analysis was conducted to identify lncRNAs associated with cellular senescence. Subsequently, a CSRL signature was crafted in the training cohort. The model's accuracy was evaluated through survival analysis and receiver operating characteristic curves. Furthermore, prognostic nomograms amalgamating cellular senescence and clinical characteristics were devised. Tumor microenvironment and checkpoint disparities were compared between low-risk and high-risk groups. The correlation between these signatures and treatment response in BC patients was also investigated. Finally, functional experiments were conducted for validation. Results: A signature comprising nine CSRLs was devised, which demonstrated adept prognostic capability in BC patients. Functional enrichment analysis revealed that tumor and immune-related pathways were predominantly enriched. Compared to the low-risk group, the high-risk group could benefit more from immunotherapy and certain chemotherapeutic agents. The expression of the 9 CSRLs was validated through in vitro experiments in different subtypes of BC cell lines and tissues. AC098484.1 was specifically verified for its association with senescence-associated secretory phenotypes. Conclusion: The CSRLs signature emerges as a promising prognostic biomarker for BC, with implications for immunological studies and treatment strategies. AC098484.1 has potential relevance in the treatment of BC cell senescence, and these findings improve the clinical treatment levels for BC patients.

Synergistic Anti-Tumor Efficacy Achieved by Reversing Drug Resistance through the Regulation of the Tumor Immune Microenvironment with IL-12 and Osimertinib Combination Therapy.

The objective of this study was to investigate the role of IL-12 in enhancing the anti-tumor efficacy of the small molecule targeted drug osimertinib in resistant tumor models and reversing resistance mechanisms. We utilized paired non-small cell lung cancer H1975 tumor tissues, establishing mouse tumor models with diverse tumor immune microenvironments. Analytical methods including immunohistochemistry and immunofluorescence were employed to compare immune cell infiltration, cytokines, effector molecules, and protein changes in resistant signaling pathways in tumor tissues, shedding light on IL-12's mechanism of action in enhancing osimertinib efficacy and reversing resistance. Results showed that osimertinib monotherapy had limited tumor suppression, whereas IL-12 exhibited more significant anti-tumor effects. Combination therapy groups demonstrated even greater tumor suppression with increased immune cell infiltration, elevated immune-related factor secretion, reduced immunosuppressive MDSCs, and decreased resistance-related signaling pathway markers. In conclusion, IL-12 enhances anti-tumor efficacy and reverses osimertinib resistance through various mechanisms, including increased immune cell infiltration, reduced immunosuppressive MDSCs, enhanced immune cell granzyme and IFN-γ release, decreased PDL-1 expression, improved tumor microenvironment, restored immune surveillance, and heightened cancer cell sensitivity to osimertinib.

Integrating machine learning algorithms and multiple immunohistochemistry validation to unveil novel diagnostic markers based on costimulatory molecules for predicting immune microenvironment status in triple-negative breast cancer.

Introduction: Costimulatory molecules are putative novel targets or potential additions to current available immunotherapy, but their expression patterns and clinical value in triple-negative breast cancer (TNBC) are to be clarified. Methods: The gene expression profiles datasets of TNBC patients were obtained from The Cancer Genome Atlas and the Gene Expression Omnibus databases. Diagnostic biomarkers for stratifying individualized tumor immune microenvironment (TIME) were identified using the Least Absolute Shrinkage and Selection Operator (LASSO) and Support Vector Machine-Recursive Feature Elimination (SVM-RFE) algorithms. Additionally, we explored their associations with response to immunotherapy via the multiplex immunohistochemistry (mIHC). Results: A total of 60 costimulatory molecule genes (CMGs) were obtained, and we determined two different TIME subclasses ("hot" and "cold") through the K-means clustering method. The "hot" tumors presented a higher infiltration of activated immune cells, i.e., CD4 memory-activated T cells, resting NK cells, M1 macrophages, and CD8 T cells, thereby enriched in the B cell and T cell receptor signaling pathways. LASSO and SVM-RFE algorithms identified three CMGs (CD86, TNFRSF17 and TNFRSF1B) as diagnostic biomarkers. Following, a novel diagnostic nomogram was constructed for predicting individualized TIME status and was validated with good predictive accuracy in TCGA, GSE76250 and GSE58812 databases. Further mIHC conformed that TNBC patients with high CD86, TNFRSF17 and TNFRSF1B levels tended to respond to immunotherapy. Conclusion: This study supplemented evidence about the value of CMGs in TNBC. In addition, CD86, TNFRSF17 and TNFRSF1B were found as potential biomarkers, significantly promoting TNBC patient selection for immunotherapeutic guidance.

Quantification and Profiling of Early and Late Differentiation Stage T Cells in Mantle Cell Lymphoma Reveals Immunotherapeutic Targets in Subsets of Patients.

With the aim to advance the understanding of immune regulation in MCL and to identify targetable T-cell subsets, we set out to combine image analysis and spatial omic technology focused on both early and late differentiation stages of T cells. MCL patient tissue (n = 102) was explored using image analysis and GeoMx spatial omics profiling of 69 proteins and 1812 mRNAs. Tumor cells, T helper (TH) cells and cytotoxic (TC) cells of early (CD57-) and late (CD57+) differentiation stage were analyzed. An image analysis workflow was developed based on fine-tuned Cellpose models for cell segmentation and classification. TC and CD57+ subsets of T cells were enriched in tumor-rich compared to tumor-sparse regions. Tumor-sparse regions had a higher expression of several key immune suppressive proteins, tentatively controlling T-cell expansion in regions close to the tumor. We revealed that T cells in late differentiation stages (CD57+) are enriched among MCL infiltrating T cells and are predictive of an increased expression of immune suppressive markers. CD47, IDO1 and CTLA-4 were identified as potential targets for patients with T-cell-rich MCL TIME, while GITR might be a feasible target for MCL patients with sparse T-cell infiltration. In subgroups of patients with a high degree of CD57+ TC-cell infiltration, several immune checkpoint inhibitors, including TIGIT, PD-L1 and LAG3 were increased, emphasizing the immune-suppressive features of this highly differentiated T-cell subset not previously described in MCL.

TimiGP-Response: the pan-cancer immune landscape associated with response to immunotherapy.

Accumulating evidence suggests that the tumor immune microenvironment (TIME) significantly influences the response to immunotherapy, yet this complex relationship remains elusive. To address this issue, we developed TimiGP-Response (TIME Illustration based on Gene Pairing designed for immunotherapy Response), a computational framework leveraging single-cell and bulk transcriptomic data, along with response information, to construct cell-cell interaction networks associated with responders and estimate the role of immune cells in treatment response. This framework was showcased in triple-negative breast cancer treated with immune checkpoint inhibitors targeting the PD-1:PD-L1 interaction, and orthogonally validated with imaging mass cytometry. As a result, we identified CD8+ GZMB+ T cells associated with responders and its interaction with regulatory T cells emerged as a potential feature for selecting patients who may benefit from these therapies. Subsequently, we analyzed 3,410 patients with seven cancer types (melanoma, non-small cell lung cancer, renal cell carcinoma, metastatic urothelial carcinoma, hepatocellular carcinoma, breast cancer, and esophageal cancer) treated with various immunotherapies and combination therapies, as well as several chemo- and targeted therapies as controls. Using TimiGP-Response, we depicted the pan-cancer immune landscape associated with immunotherapy response at different resolutions. At the TIME level, CD8 T cells and CD4 memory T cells were associated with responders, while anti-inflammatory (M2) macrophages and mast cells were linked to non-responders across most cancer types and datasets. Given that T cells are the primary targets of these immunotherapies and our TIME analysis highlights their importance in response to treatment, we portrayed the pan-caner landscape on 40 T cell subtypes. Notably, CD8+ and CD4+ GZMK+ effector memory T cells emerged as crucial across all cancer types and treatments, while IL-17-producing CD8+ T cells were top candidates associated with immunotherapy non-responders. In summary, this study provides a computational method to study the association between TIME and response across the pan-cancer immune landscape, offering resources and insights into immune cell interactions and their impact on treatment efficacy.

MICAL1 promotes the proliferation in acute myeloid leukemia and is associated with clinical prognosis and immune infiltration.

Acute myeloid leukemia (AML) is one of the most common hematopoietic malignancies that has a poor prognosis and a high rate of relapse. Dysregulated metabolism plays an important role in AML progression. This study aimed to conduct a comprehensive analysis of MRGs using TCGA and GEO datasets and further explore the potential function of critical MRGs in AML progression. In this study, we identified 17 survival-related differentially expressed MRGs in AML using TCGA and GEO datasets. The 150 AML samples were divided into three molecular subtypes using 17 MRGs, and we found that three molecular subtypes exhibited a different association with ferroptosis, cuproptosis and m6A related genes. Moreover, a prognostic signature that comprised nine MRGs and had good predictive capacity was established by LASSO-Cox stepwise regression analysis. Among the 17 MRGs, our attention focused on MICAL1 which was highly expressed in many types of tumors, including AML and its overexpression was also confirmed in several AML cell lines. We also found that the expression of MICAL1 was associated with several immune cells. Moreover, functional experiments revealed that knockdown of MICAL1 distinctly suppressed the proliferation of AML cells. Overall, this study not only contributes to a deeper understanding of the molecular mechanisms underlying AML but also provides potential targets and prognostic markers for AML treatment. These findings offer robust support for further research into therapeutic strategies and mechanisms related to AML, with the potential to improve the prognosis and quality of life for AML patients. Nevertheless, further research is needed to validate these findings and explore more in-depth molecular mechanisms.

The crosstalk between immune cells and tumor pyroptosis: advancing cancer immunotherapy strategies.

Pyroptosis is a cell death process characterized by cell swelling until membrane rupture and release of intracellular contents. As an effective tumor treatment strategy, inducing tumor cell pyroptosis has received widespread attention. In this process, the immune components within the tumor microenvironment play a key regulatory role. By regulating and altering the functions of immune cells such as cytotoxic T lymphocytes, natural killer cells, tumor-associated macrophages, and neutrophils, tumor cell pyroptosis can be induced. This article provides a comprehensive review of the molecular mechanisms of cell pyroptosis, the impact of the tumor immune microenvironment on tumor cell pyroptosis, and its mechanisms. It aims to gain an in-depth understanding of the communication between the tumor immune microenvironment and tumor cells, and to provide theoretical support for the development of new tumor immunotherapies.

Correlation of PD-L1 expression with CD8+ T cells and oxidative stress-related molecules NRF2 and NQO1 in esophageal squamous cell carcinoma.

Oxidative stress and the immune microenvironment both contribute to the pathogenesis of esophageal squamous cell carcinoma (ESCC). However, their interrelationships remain poorly understood. We aimed to examine the status of key molecules involved in oxidative stress and the immune microenvironment, as well as their relationships with each other and with clinicopathological features and prognosis in ESCC. The expression of programmed death-ligand 1 (PD-L1), CD8, nuclear factor erythroid-2 related factor-2 (NRF2), and NAD(P)H quinone oxidoreductase 1 (NQO1) was detected using immunohistochemistry in tissue samples from 176 patients with ESCC. We employed both combined positive score (CPS) and tumor proportion score (TPS) to evaluate PD-L1 expression and found a positive correlation between CPS and TPS. Notably, PD-L1 expression, as assessed by either CPS or TPS, was positively correlated with both NRF2 nuclear score and NQO1 score in stage II-IV ESCC. We also observed a positive correlation between the density of CD8+ T cells and PD-L1 expression. Furthermore, high levels of PD-L1 CPS, but not TPS, were associated with advanced TNM stage and lymph node metastases. Moreover, both PD-L1 CPS and the nuclear expression of NRF2 were found to be predictive of shorter overall survival in stage II-IV ESCC. By using the Mandard-tumor regression grading (TRG) system to evaluate the pathological response of tumors to neoadjuvant chemotherapy (NACT), we found that the TRG-5 group had higher NRF2 nuclear score, PD-L1 CPS, and TPS in pre-NACT biopsy samples compared with the TRG-3 + 4 group. The NQO1 scores of post-NACT surgical specimens were significantly higher in the TRG-5 group than in the TRG 3 + 4 group. In conclusion, the expression of PD-L1 is associated with aberrant NRF2 signaling pathway, advanced TNM stage, lymph node metastases, and unfavorable prognosis. The dysregulation of PD-L1 and aberrant activation of the NRF2 signaling pathway are implicated in resistance to NACT. Our findings shed light on the complex interrelationships between oxidative stress and the immune microenvironment in ESCC, which may have implications for personalized therapies and improved patient outcomes.

NAD metabolism-related genes provide prognostic value and potential therapeutic insights for acute myeloid leukemia.

Introduction: Acute myeloid leukemia (AML) is an aggressive blood cancer with high heterogeneity and poor prognosis. Although the metabolic reprogramming of nicotinamide adenine dinucleotide (NAD) has been reported to play a pivotal role in the pathogenesis of acute myeloid leukemia (AML), the prognostic value of NAD metabolism and its correlation with the immune microenvironment in AML remains unclear. Methods: We utilized our large-scale RNA-seq data on 655 patients with AML and the NAD metabolism-related genes to establish a prognostic NAD metabolism score based on the sparse regression analysis. The signature was validated across three independent datasets including a total of 1,215 AML patients. ssGSEA and ESTIMATE algorithms were employed to dissect the tumor immune microenvironment. Ex vivo drug screening and in vitro experimental validation were performed to identify potential therapeutic approaches for the high-risk patients. In vitro knockdown and functional experiments were employed to investigate the role of SLC25A51, a mitochondrial NAD+ transporter gene implicated in the signature. Results: An 8-gene NAD metabolism signature (NADM8) was generated and demonstrated a robust prognostic value in more than 1,800 patients with AML. High NADM8 score could efficiently discriminate AML patients with adverse clinical characteristics and genetic lesions and serve as an independent factor predicting a poor prognosis. Immune microenvironment analysis revealed significant enrichment of distinct tumor-infiltrating immune cells and activation of immune checkpoints in patients with high NADM8 scores, acting as a potential biomarker for immune response evaluation in AML. Furthermore, ex vivo drug screening and in vitro experimental validation in a panel of 9 AML cell lines demonstrated that the patients with high NADM8 scores were more sensitive to the PI3K inhibitor, GDC-0914. Finally, functional experiments also substantiated the critical pathogenic role of the SLC25A51 in AML, which could be a promising therapeutic target. Conclusion: Our study demonstrated that NAD metabolism-related signature can facilitate risk stratification and prognosis prediction in AML and guide therapeutic decisions including both immunotherapy and targeted therapies.

Understanding gut dysbiosis for hepatocellular carcinoma diagnosis and treatment.

The gut microbiome can play a crucial role in hepatocellular carcinoma (HCC) progression through the enterohepatic circulation, primarily acting via metabolic reprogramming and alterations in the hepatic immune microenvironment triggered by microbe-associated molecular patterns (MAMPs), metabolites, and fungi. In addition, the gut microbiome shows potential as a biomarker for early HCC diagnosis and for assessing the efficacy of immunotherapy in unresectable HCC. This review examines how gut microbiota dysbiosis, with varied functional profiles, contributes to HCCs of different etiologies. We discuss therapeutic strategies to modulate the gut microbiome including diets, antibiotics, probiotics, fecal microbiota transplantation, and nano-delivery systems, and underscore their potential as an adjunctive treatment modality for HCC.

Unraveling dynamic immunological landscapes in intracerebral hemorrhage: insights from single-cell and spatial transcriptomic profiling.

Intracerebral hemorrhage (ICH) poses a formidable challenge in stroke management, with limited therapeutic options, particularly in the realm of immune-targeted interventions. Clinical trials targeting immune responses post-ICH have encountered setbacks, potentially attributable to the substantial cellular heterogeneity and intricate intercellular networks within the brain. Here, we present a pioneering investigation utilizing single-cell RNA sequencing and spatial transcriptome profiling at hyperacute (1 h), acute (24 h), and subacute (7 days) intervals post-ICH, aimed at unraveling the dynamic immunological landscape and spatial distributions within the cerebral tissue. Our comprehensive analysis revealed distinct cell differentiation patterns among myeloid and lymphocyte populations, along with delineated spatial distributions across various brain regions. Notably, we identified a subset of lymphocytes characterized by the expression of Spp1 and Lyz2, termed macrophage-associated lymphocytes, which exhibited close interactions with myeloid cells. Specifically, we observed prominent interactions between Lgmn+Macro-T cells and microglia through the spp1-cd44 pathway during the acute phase post-ICH in the choroid plexus. These findings represent a significant advancement in our understanding of immune cell dynamics at single-cell resolution across distinct post-ICH time points, thereby laying the groundwork for exploring critical temporal windows and informing the development of targeted therapeutic strategies.

Elucidating prognosis in cervical squamous cell carcinoma and endocervical adenocarcinoma: a novel anoikis-related gene signature model.

Background: Cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC) are among the most prevalent gynecologic malignancies globally. The prognosis is abysmal once cervical cancer progresses to lymphatic metastasis. Anoikis, a specialized form of apoptosis induced by loss of cell adhesion to the extracellular matrix, plays a critical role. The prediction model based on anoikis-related genes (ARGs) expression and clinical data could greatly aid clinical decision-making. However, the relationship between ARGs and CESC remains unclear. Methods: ARGs curated from the GeneCards and Harmonizome portals were instrumental in delineating CESC subtypes and in developing a prognostic framework for patients afflicted with this condition. We further delved into the intricacies of the immune microenvironment and pathway enrichment across the identified subtypes. Finally, our efforts culminated in the creation of an innovative nomogram that integrates ARGs. The utility of this prognostic tool was underscored by Decision Curve Analysis (DCA), which illuminate its prospective benefits in guiding clinical interventions. Results: In our study, We discerned a set of 17 survival-pertinent, anoikis-related differentially expressed genes (DEGs) in CESC, from which nine were meticulously selected for the construction of prognostic models. The derived prognostic risk score was subsequently validated as an autonomous prognostic determinant. Through comprehensive functional analyses, we observed distinct immune profiles and drug response patterns among divergent prognostic stratifications. Further, we integrated the risk scores with the clinicopathological characteristics of CESC to develop a robust nomogram. DCA corroborated the utility of our model, demonstrating its potential to enhance patient outcomes through tailored clinical treatment strategies. Conclusion: The predictive signature, encompassing nine pivotal genes, alongside the meticulously constructed nomogram developed in this research, furnishes clinicians with a sophisticated tool for tailoring treatment strategies to individual patients diagnosed with CESC.