Machine learning based on biological context facilitates the identification of microvascular invasion in intrahepatic cholangiocarcinoma.

Intrahepatic cholangiocarcinoma (ICC) is a rare disease associated with a poor prognosis, primarily due to early recurrence and metastasis. An important feature of this condition is microvascular invasion (MVI). However, current predictive models based on imaging have limited efficacy in this regard. This study employed a random forest model to construct a predictive model for MVI identification and uncover its biological basis. Single-cell transcriptome sequencing, whole exome sequencing, and proteome sequencing were performed. The area under the curve of the prediction model in the validation set was 0.93. Further analysis indicated that MVI-associated tumor cells exhibited functional changes related to epithelial-mesenchymal transition and lipid metabolism due to alterations in the NF-kappa B and MAPK signaling pathways. Tumor cells were also differentially enriched for the IL-17 signaling pathway. There was less infiltration of SLC30A1+ CD8+ T cells expressing cytotoxic genes in MVI-associated ICC, whereas there was more infiltration of myeloid cells with attenuated expression of the MHC II pathway. Additionally, MVI-associated intercellular communication was closely related to the SPP1-CD44 and ANXA1-FPR1 pathways. These findings resulted in a brilliant predictive model and fresh insights into MVI.

TRP channel-related LncRNAs, AC092535.4 and LINC01637, as novel prognostic biomarkers for uveal melanoma.

Introduction: Transient receptor potential (TRP) channels function as cellular sensors with a broad impact, and their dysregulation is linked to numerous cancers. The influence of TRP channel-related long noncoding RNAs (TCRLs) on uveal melanoma (UM) remains poorly understood. Methods: We employed bioinformatics to examine the RNA-seq data and relevant clinical information of UM in the TCGA databases. By implementing coexpression analysis, we identified differentially expressed TCRLs. Using univariate Cox regression analysis, selection operator (LASSO) algorithm and stepwise regression, five key prognostic biomarkers were chosen. The high- and low-risk groups were divided based on the risk scores. Afterwards, the prediction performance of the signature was evaluated by receiver operating characteristic (ROC) curve and Kaplan-Meier (K-M) survival analysis. The functional enrichment analysis of TCRLs was also investigated. Following that, we examined immune cell infiltration, immune checkpoint expression, and tumor immune microenvironment between patients in high and low risk groups. TCRLs were validated using Random forests and multifactor Cox analysis. Candidate biomarkers were identified and screened. Finally, the effects of the candidate biomarkers on the proliferation, migration and invasion of UM cells were detected by CCK-8 assay, migration assay and perforation invasion assay. Results: The risk score generated by five TCRLs demonstrated robust predictive power. The high-risk group exhibited a poorer prognosis, increased immune cell infiltration, and an active tumor immune microenvironment compared to the low-risk group. Furthermore, two TCRLs of risk score, AC092535.4 and LINC01637, were screened to multiplex modelling. The in vitro experiments demonstrated that UM cells were suppressed following AC092535.4 or LINC01637 knockdown. Discussion: Two TCRLs, AC092535.4 and LINC01637, serve as novel prognostic biomarkers for uveal melanoma and may present potential therapeutic targets.

Illuminating immunotherapy response via precision T cell-targeted PET imaging.

Traditionally, immunotherapy agent selection and treatment strategies are guided by biopsy-based histological information. However, biopsies are limited in that they are invasive, provide static information regarding the tumor immune microenvironment, and only sample a small part of one tumor site. The tumor microenvironment is dynamic and heterogenous. As a result, the immune milieu at one site may be distinct from other metastatic sites. These factors make identifying which patients are likely to respond to different immunotherapies and which harbor intrinsic resistance mechanisms difficult to identify based on a biopsy alone. As such, there is significant interest in alternative methodologies that better characterize the tumor immune microenvironment and monitor immunotherapy response. PET imaging potentially offers a non-invasive way to characterize the tumor immune microenvironment at the primary tumor and metastases and allow for longitudinal characterization. Herein, we review pre-clinically and clinically tested T cell-targeted PET radiopharmaceuticals, as T cells have been the dominant immunotherapy target, and their utility in both evaluating response to immunotherapy and in understanding the systemic immune response to treatment with immunotherapeutics.

Mismatch repair-proficient tumor footprints in the sands of immune desert: mechanistic constraints and precision platforms.

Mismatch repair proficient (MMRp) tumors of colorectal origin are one of the prevalent yet unpredictable clinical challenges. Despite earnest efforts, optimal treatment modalities have yet to emerge for this class. The poor prognosis and limited actionability of MMRp are ascribed to a low neoantigen burden and a desert-like microenvironment. This review focuses on the critical roadblocks orchestrated by an immune evasive mechanistic milieu in the context of MMRp. The low density of effector immune cells, their weak spatiotemporal underpinnings, and the high-handedness of the IL-17-TGF-ß signaling are intertwined and present formidable challenges for the existing therapies. Microbiome niche decorated by Fusobacterium nucleatum alters the metabolic program to maintain an immunosuppressive state. We also highlight the evolving strategies to repolarize and reinvigorate this microenvironment. Reconstruction of anti-tumor chemokine signaling, rational drug combinations eliciting T cell activation, and reprograming the maladapted microbiome are exciting developments in this direction. Alternative vulnerability of other DNA damage repair pathways is gaining momentum. Integration of liquid biopsy and ex vivo functional platforms provide precision oncology insights. We illustrated the perspectives and changing landscape of MMRp-CRC. The emerging opportunities discussed in this review can turn the tide in favor of fighting the treatment dilemma for this elusive cancer.

RAB42 overexpression correlates with poor prognosis, immune cell infiltration and chemoresistance.

Background: RAB42 (Ras-related protein 42) is a new small GTPase that controls the vesicular trafficking from endosomes to trans-Golgi network in mammalian cells. However, the role of RAB42 in multiple cancers, especially in liver hepatocellular carcinoma (LIHC), has not been well investigated. Methods: A variety of cancer-related databases and online tools, including TCGA, GTEx, TARGET, QUANTISEQ, EPIC, RNAactDrug, CTR-DB, TIMER algorithms and Sangerbox, were applied to explore the correlation of RAB42 expression with prognosis, immune microenvironment, immune regulatory network, RNA modification, pathway activation and drug sensitivity in pan-cancer. The prognostic, immunomodulatory and tumor-promoting effects of RAB42 were verified in various malignancies and determined by a series of in vitro cellular experiments. Results: RAB42 is significantly overexpressed in most cancers with advanced pathological stages. Its overexpression is correlated with poor survival in pan-cancer. RAB42 overexpression has a high diagnostic accuracy of various cancers (AUC > 0.80). RAB42 overexpression not only correlates with distinct stromal immune infiltration and level of immune checkpoint molecules, but also associates with weak immune cell infiltration, immunomodulatory genes expression, and immunotherapeutic response to immune checkpoint inhibitors (ICIs). Additionally, RAB42 overexpression correlates with enhanced expression of m6A RNA methylation-related genes (MRGs) and its interactors. Moreover, overexpression of RAB42 serves as a drug-resistant marker to certain chemotherapies and acts as a potential biomarker for LIHC. Notably, RAB42 overexpression or activation promotes the cellular proliferation, migration and invasion of LIHC. Conclusion: Overexpressed RAB42 serves as a potential prognostic biomarker and therapeutic target in pan-cancer, especially in LIHC.

Transarterial Embolization Enhances Programmed Cell Death Ligand 1 Expression and Influences CD8+T Lymphocytes Cytotoxicity in an Orthotopic Hepatocellular Carcinoma Rat Model.

PURPOSE: To investigate the influence of transarterial embolization (TAE) on programmed cell death-ligand 1(PD-L1) expression and CD8+T tumour infiltrative lymphocyte cytotoxicity in the Sprague-Dawley (SD) rat model of hepatocellular carcinoma (HCC). MATERIALS AND METHODS: An orthotopic HCC model was established in twenty SD rats treated with TAE (lipiodol, n = 10) or sham (normal saline, n = 10) using homologous N1S1 hepatoma cells. Rats were euthanized 1 week after embolization. Flow cytometry was used to assess the proportion of CD4+T, CD8+T and programmed cell death-1+(PD-1+) CD8+T lymphocytes in the spleens and tumours. Distribution of CD8+T, granzyme-B+CD8+T lymphocytes and PD-L1+ cells was assessed by immunohistochemistry (IHC) or multiplex IHC. p value < 0.05 was considered statistically significant. RESULTS: The CD4/CD8 ratio and PD-1+CD8+ T lymphocytes exhibited higher values in TAE-treated tumours compared to sham-treated tumours (p = 0.021 and p = 0.071, respectively). Conversely, the number of CD8+T lymphocytes was decreased in TAE-treated tumours (p = 0.043), especially in the central region (p = 0.045). However, more CD8+T lymphocytes were found infiltrating the marginal region than central region in TAE-treated tumours (p = 0.046). The proportion of granzyme-B+CD8+T lymphocytes and the PD-L1 positive areas was elevated in tumours that treated with TAE (p all < 0.05). There was a negative correlation between PD-L1 expression and the number of infiltration of CD8+ T lymphocytes (p = 0.036). CONCLUSIONS: Immune cells are distributed unevenly in the tumours after TAE. The intrinsic induction state of the tumour after embolization may be insufficient to elicit a maximal response to PD-1/PD-L1 inhibitors.

UBTD1 is a potential prognostic biomarker in colorectal cancer.

Colorectal cancer (CRC) is a complex malignancy with poorly understood molecular mechanisms, necessitating the identification of genetic markers. Although Ubiquitin domain-containing protein 1 (UBTD1) has received significant attention in the study of human cancers, its specific role in CRC is yet to be fully clarified. This study sought to examine how UBTD1 expression was associated with various clinical and pathological characteristics of CRC, and to determine its prognostic significance and biological function, utilizing data from clinical samples and large-scale databases. Notably, UBTD1 expression was found to be upregulated in CRC, resulting in decreased survival rates and unfavorable clinical characteristics such as advanced T, N, and pathological stages. The findings of the multivariate Cox regression analysis illustrated that UBTD1 expression upregulation is a significant independent marker of unfavorable outcomes in CRC patients. An examination of the functional enrichment of UBTD1 and the genes it co-expresses indicated that it could serve as an oncogene by modulating the expression of genes implicated in crucial tumorigenesis pathways and functions. Additionally, immune cell infiltration analysis suggested a link between UBTD1 levels and various immune cells, particularly macrophages. In conclusion, the use of UBTD1 as a biomarker for both the prognosis and diagnosis of CRC has promising prospects for further investigation and therapeutic approaches.

Integrating single-cell transcriptomics and machine learning to predict breast cancer prognosis: A study based on natural killer cell-related genes.

Breast cancer (BC) is the most commonly diagnosed cancer in women globally. Natural killer (NK) cells play a vital role in tumour immunosurveillance. This study aimed to establish a prognostic model using NK cell-related genes (NKRGs) by integrating single-cell transcriptomic data with machine learning. We identified 44 significantly expressed NKRGs involved in cytokine and T cell-related functions. Using 101 machine learning algorithms, the Lasso + RSF model showed the highest predictive accuracy with nine key NKRGs. We explored cell-to-cell communication using CellChat, assessed immune-related pathways and tumour microenvironment with gene set variation analysis and ssGSEA, and observed immune components by HE staining. Additionally, drug activity predictions identified potential therapies, and gene expression validation through immunohistochemistry and RNA-seq confirmed the clinical applicability of NKRGs. The nomogram showed high concordance between predicted and actual survival, linking higher tumour purity and risk scores to a reduced immune score. This NKRG-based model offers a novel approach for risk assessment and personalized treatment in BC, enhancing the potential of precision medicine.

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.

SEC61 translocon gamma subunit is correlated with glycolytic activity, epithelial mesenchymal transition and the immune suppressive phenotype of lung adenocarcinoma.

Lung adenocarcinoma (LUAD) remains a predominant cause of cancer-related mortality globally, underscoring the urgency for targeted therapeutic strategies. The specific role and impact of the SEC61 translocon gamma subunit (SEC61G) in LUAD progression and metastasis remain largely unexplored. In this study, we use a multifaceted approach, combining bioinformatics analysis with experimental validation, to elucidate the pivotal role of SEC61G and its associated molecular mechanisms in LUAD. Our integrated analyses reveal a significant positive correlation between SEC61G expression and the glycolytic activity of LUAD, as evidenced by increased fluorodeoxyglucose (FDG) uptake on positron emission tomography (PET)/CT scans. Further investigations show the potential influence of SEC61G on metabolic reprogramming, which contributes to the immunosuppressive tumor microenvironment (TME). Remarkably, we identify a negative association between SEC61G expression levels and the infiltration of critical immune cell populations within the TME, along with correlations with immune checkpoint gene expression and tumor heterogeneity scores in LUAD. Functional studies demonstrate that SEC61G knockdown markedly inhibits the migration of A549 and H2030 LUAD cells. This inhibitory effect is accompanied by a significant downregulation of key regulators of tumor progression, including hypoxia-inducible factor-1 alpha (HIF-1α), lactate dehydrogenase A, and genes involved in the epithelial-mesenchymal transition pathway. In conclusion, our comprehensive analyses position SEC61G as a potential prognostic biomarker intricately linked to glycolytic metabolism, the EMT pathway, and the establishment of an immune-suppressive phenotype in LUAD. These findings underscore the potential of SEC61G as a therapeutic target and predictive marker for immunotherapeutic responses in LUAD patients.

Single cell analyses reveal the PD-1 blockade response-related immune features in hepatocellular carcinoma.

Background: Immunotherapy has demonstrated its potential to improve the prognosis of patients with hepatocellular carcinoma (HCC); however, patients' responses to immunotherapy vary a lot. A comparative analysis of the tumor microenvironment (TME) in responders and non-responders is expected to unveil the mechanisms responsible for the immunotherapy resistance and provide potential treatment targets. Methods: We performed sequencing analyses using 10x Genomics technology on six HCC patients who responded to anti-PD-1 therapy and one HCC patient who did not respond. Additionally, we obtained single cell data from untreated, responsive, and nonresponsive HCC patients from public databases, and used part of the datasets as a validation cohort. These data were integrated using algorithms such as Harmony. An independent validation cohort was established. Furthermore, we performed spatial transcriptomic sequencing on the tumor adjacent tissues of three HCC responsive patients using 10x Genomics spatial transcriptomic technology. Additionally, we analyzed data about three HCC patients obtained from public databases. Finally, we validated our conclusions using immunofluorescence, flow cytometry, and in vivo experiments. Results: Our findings confirmed the presence of "immune barrier" partially accounting for the limited efficacy of immunotherapy. Our analysis revealed a significant increase in TREM2+ Macrophages among non-responsive patients expressing multiple immunosuppressive signals. anti-Csf1r monoclonal antibodies effectively eliminated these macrophages and augmented the therapeutic effects of anti-PD-1 therapy. TCR+ Macrophages possessed direct tumor-killing capabilities. IL1B+ cDC2 was the primary functional subtype of cDC2 cells. Absence of THEMIShi CD8+ T subtypes might diminish immunotherapeutic effects. Furthermore, CD8+ T cells entered a state of stress after anti-PD-1 treatment, which might be associated with CD8+ T cell exhaustion and senescence. Conclusions: The profiles of immune TMEs showed differences in HCC patients responsive, non-responsive and untreated. These differences might explain the discounted efficacy of immunotherapy in some HCC patients. The cells and molecules, which we found to carry unique capabilities, may be targeted to enhance immunotherapeutic outcomes in patients with HCC.

Clinical significance, molecular characterization, and immune microenvironment analysis of coagulation-related genes in clear cell renal cell carcinoma.

Background: Numerous studies have revealed a tight connection between tumor development and the coagulation system. However, the effects of coagulation on the prognosis and tumor microenvironment (TME) of clear cell renal cell carcinoma (ccRCC) remain poorly understood. Methods: We employed the consensus clustering method to characterize distinct molecular subtypes associated with coagulation patterns. Subsequently, we examined variations in the overall survival (OS), genomic profiles, and TME characteristics between these subtypes. To develop a prognostic coagulation-related risk score (CRRS) model, we utilized the least absolute shrinkage and selection operator Cox regression and stepwise multivariate Cox regression analyses. We also created a nomogram to aid in the clinical application of the risk score, evaluating the relationships between the CRRS and the immune microenvironment, responsiveness to immunotherapy, and targeted treatment. The clinical significance of PLAUR and its biological function in ccRCC were also further analyzed. Results: There were significant differences in clinical features, prognostic stratification, genomic variation, and TME characteristics between the two coagulation-related subtypes. We established and validated a CRRS using six coagulation-related genes that can be employed as an effective indicator of risk stratification and prognosis estimation for ccRCC patients. Significant variations in survival outcomes were observed between the high- and low-risk groups. The nomogram was proficient in predicting the 1-, 3-, and 5-year OS. Additionally, the CRRS emerged as a novel tool for evaluating the clinical effectiveness of immunotherapy and targeted treatments in ccRCC. Moreover, we confirmed upregulated PLAUR expression in ccRCC samples that was significantly correlated with poor patient prognosis. PLAUR knockdown notably inhibited ccRCC cell proliferation and migration. Conclusion: Our data suggested that CRRS may be employed as a reliable predictive biomarker that can provide therapeutic benefits for immunotherapy and targeted therapy in ccRCC.

Prognostic insights, immune infiltration, and therapeutic response: Cytoplasmic poly(A) tail regulators in hepatocellular carcinoma.

The presence of a poly(A) tail is indispensable for the post-transcriptional regulation of gene expression in cancer. This dynamic and modifiable feature of transcripts is under the control of various nuclear and cytoplasmic proteins. This study aimed to develop a novel cytoplasmic poly(A)-related signature for predicting prognosis, clinical attributes, tumor immune microenvironment (TIME), and treatment response in hepatocellular carcinoma (HCC). Utilizing RNA sequencing (RNA-seq) data from The Cancer Genome Atlas (TCGA), non-negative matrix factorization (NMF), and principal-component analysis (PCA) were employed to categorize HCC patients into three clusters, thus demonstrating the pivotal prognostic role of cytoplasmic poly(A) tail regulators. Furthermore, machine learning algorithms such as least absolute shrinkage and selection operator (LASSO), survival analysis, and Cox proportional hazards modeling were able to distinguish distinct cytoplasmic poly(A) subtypes. As a result, a 5-gene signature derived from TCGA was developed and validated using International Cancer Genome Consortium (ICGC) HCC datasets. This novel classification based on cytoplasmic poly(A) regulators has the potential to improve prognostic predictions and provide guidance for chemotherapy, immunotherapy, and transarterial chemoembolization (TACE) in HCC.

Multicenter integration analysis of TRP channels revealed potential mechanisms of immunosuppressive microenvironment activation and identified a machine learning-derived signature for improving outcomes in gliomas.

AIM: This study aimed to explore the mechanisms of transient receptor potential (TRP) channels on the immune microenvironment and develop a TRP-related signature for predicting prognosis, immunotherapy response, and drug sensitivity in gliomas. METHODS: Based on the unsupervised clustering algorithm, we identified novel TRP channel clusters and investigated their biological function, immune microenvironment, and genomic heterogeneity. In vitro and in vivo experiments revealed the association between TRPV2 and macrophages. Subsequently, based on 96 machine learning algorithms and six independent glioma cohorts, we constructed a machine learning-based TRP channel signature (MLTS). The performance of the MLTS in predicting prognosis, immunotherapy response, and drug sensitivity was evaluated. RESULTS: Patients with high expression levels of TRP channel genes had worse prognoses, higher tumor mutation burden, and more activated immunosuppressive microenvironment. Meanwhile, TRPV2 was identified as the most essential regulator in TRP channels. TRPV2 activation could promote macrophages migration toward malignant cells and alleviate glioma prognosis. Furthermore, MLTS could work independently of common clinical features and present stable and superior prediction performance. CONCLUSION: This study investigated the comprehensive effect of TRP channel genes in gliomas and provided a promising tool for designing effective, precise treatment strategies.

Downregulation of DIP2B as a prognostic marker inhibited cancer proliferation and migration and was associated with immune infiltration in lung adenocarcinoma via CCND1 and MMP2.

Background: DIP2B is related to cancer progression. This study investigated the roles and pathways of DIP2B in lung adenocarcinoma (LUAD). Methods: DIP2B expression and the relationship between survival time of cancer patients and DIP2B expression were analyzed. The relationship between DIP2B expression and survival time in LUAD patients was evaluated by a meta-analysis. Cox and survival analyses were used to evaluate the prognostic factors and construct a prognostic nomogram. The mechanisms and effects of DIP2B and the relationship between DIP2B expression and the immune microenvironment were investigated using bioinformatics, CCK-8, western blotting, and transwell experiments. Results: DIP2B was overexpressed in LUAD tissues. DIP2B overexpression was associated with shorter prognosis and was an unfavorable risk factor for prognosis in LUAD patients. DIP2B co-expressed genes were involved in cell division, DNA repair, cell cycle, and others. Inhibition of DIP2B expression could downregulate the proliferation, migration, and invasion of LUAD A549 and H1299 cells, which was related to the decrease in CCND1 and MMP2 protein expression. BRCA1 overexpression was associated with short prognosis, and the nomogram formed by DIP2B and BRCA1 was associated with a poor prognosis in LUAD patients. DIP2B expression correlated with immune cells (such as CD8 T cells, Tcm, and iDCs) and cell markers. Conclusion: DIP2B is a potential biomarker of poor prognosis and the immune microenvironment in LUAD. Inhibition of DIP2B expression downregulated cancer cell proliferation, migration, and invasion, which might be related to the decrease in CCND1 and MMP2 protein expression. DIP2B-related nomograms might be useful tools for predicting the prognosis of LUAD patients.

Anoikis resistance regulates immune infiltration and drug sensitivity in clear-cell renal cell carcinoma: insights from multi omics, single cell analysis and in vitro experiment.

Background: Anoikis is a form of programmed cell death essential for preventing cancer metastasis. In some solid cancer, anoikis resistance can facilitate tumor progression. However, this phenomenon is underexplored in clear-cell renal cell carcinoma (ccRCC). Methods: Using SVM machine learning, we identified core anoikis-related genes (ARGs) from ccRCC patient transcriptomic data. A LASSO Cox regression model stratified patients into risk groups, informing a prognostic model. GSVA and ssGSEA assessed immune infiltration, and single-cell analysis examined ARG expression across immune cells. Quantitative PCR and immunohistochemistry validated ARG expression differences between immune therapy responders and non-responders in ccRCC. Results: ARGs such as CCND1, CDKN3, PLK1, and BID were key in predicting ccRCC outcomes, linking higher risk with increased Treg infiltration and reduced M1 macrophage presence, indicating an immunosuppressive environment facilitated by anoikis resistance. Single-cell insights showed ARG enrichment in Tregs and dendritic cells, affecting immune checkpoints. Immunohistochemical analysis reveals that ARGs protein expression is markedly elevated in ccRCC tissues responsive to immunotherapy. Conclusion: This study establishes a novel anoikis resistance gene signature that predicts survival and immunotherapy response in ccRCC, suggesting that manipulating the immune environment through these ARGs could improve therapeutic strategies and prognostication in ccRCC.

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.

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.

Histopathological growth pattern and vessel co-option in intrahepatic cholangiocarcinoma.

Intrahepatic cholangiocarcinoma (iCCA) exhibits different blood imaging features and prognosis depending on histology. To clarity histopathological growth patterns (HGPs) and vascularization processes of iCCA, we collected 145 surgical specimens and histologically classified them into large bile duct (LBD) (20 cases), small bile duct (SBD) (54), cholangiolocarcinoma (CLC) (35), combined SBD-CLC (cSBD-CLC) (26), and ductal plate malformation (DPM) (10) (sub)types. According to the invasive pattern at the interface between tumor and adjacent background liver, HGPs were classified into desmoplastic, pushing, and replacing HGPs. Desmoplastic HGP predominated in LBD type (55.5%), while replacing HGP was common in CLC (82.9%) and cSBD-CLC (84.6%) subtypes. Desmoplastic HGP reflected angiogenesis, while replacing HGP showed vessel co-option in addition to angiogenesis. By evaluating microvessel density (MVD) using vascular markers, ELTD1 identified vessel co-option and angiogenesis, and ELTD1-positive MVD at invasive margin in replacing HGP was significantly higher than those in desmoplastic and pushing HGPs. REDD1, an angiogenesis-related marker, demonstrated preferably higher MVD in the tumor center than in other areas. iCCA (sub)types and HGPs were closely related to vessel co-option and immune-related factors (lymphatic vessels, lymphocytes, and neutrophils). In conclusion, HGPs and vascular mechanisms characterize iCCA (sub)types and vessel co-option linked to the immune microenvironment.