Jianpi-Tiaoqi decoction inhibits tumour proliferation and lung metastasis in tumour-bearing mice with triple-negative breast cancer.

Traditional Chinese medicine, specifically the Jianpi Tiaoqi (JPTQ) decoction, has been explored for its role in treating breast cancer, particularly in inhibiting lung metastasis in affected mice. Our study evaluated the effects of JPTQ on several factors, including tumour growth, apoptosis, angiogenesis, epithelial-to-mesenchymal transition (EMT) and immune microenvironment regulation. We used bioluminescence imaging to observe in situ tumour growth and potential lung metastasis. Transcriptomic analysis provided insights into gene expression, whereas flow cytometry was used to examine changes in specific immune cells, such as CD4+ T cells and myeloid-derived suppressor cells. Several essential proteins and genes, including vascular endothelial growth factor (VEGF), matrix metalloprotein-9 (MMP-9) and B-cell lymphoma 2 (Bcl-2), were assessed through quantitative real-time polymerase chain reaction, western blotting and immunohistochemistry. Our findings showed that JPTQ treatment inhibited tumour proliferation in cancer-bearing mice. Bioluminescence imaging and pathological analysis indicated a reduction in lung metastasis. Transcriptome analysis of lung and tumour tissues indicated that the genes associated with EMT, angiogenesis, proliferation and apoptosis were regulated in the JPTQ-treated group. Kyoto Encyclopedia of Genes and Genomes analysis suggested enrichment of immune-related pathways. Flow cytometry indicated that JPTQ treatment reduced the proportion of monocyte-myeloid-derived suppressor cells in the lung and increased the number of CD4+ T cells in the peripheral blood and the number of T helper 1 (Th1) cells in the spleen (P < 0.05). E-cadherin and cleaved caspase 3 were upregulated, whereas Snail, Bcl-2, Ki67 and VEGF were downregulated in the lung and tumour tissues; moreover, the expression of MMP-9 was downregulated in the lung tissue (P < 0.05). In essence, JPTQ not only inhibits tumour growth in affected mice, but also promotes positive immune responses, reduces angiogenesis, boosts tumour cell apoptosis, reverses EMT and decreases breast cancer lung metastasis.

Identification and validation of a platelet-related signature for predicting survival and drug sensitivity in multiple myeloma.

Background: Significant progress has been achieved in the management of multiple myeloma (MM) by implementing high-dose therapy and stem cell transplantation. Moreover, the prognosis of patients has been enhanced due to the introduction of novel immunomodulatory drugs and the emergence of new targeted therapies. However, predicting the survival rates of patients with multiple myeloma is still tricky. According to recent researches, platelets have a significant impact in affecting the biological activity of tumors and are essential parts of the tumor microenvironment. Nonetheless, it is still unclear how platelet-related genes (PRGs) connect to the prognosis of multiple myeloma. Methods: We analyzed the expression of platelet-related genes and their prognostic value in multiple myeloma patients in this study. We also created a nomogram combining clinical metrics. Furthermore, we investigated disparities in the biological characteristics, immunological microenvironment, and reaction to immunotherapy, along with analyzing the drug susceptibility within diverse risk groups. Results: By using the platelet-related risk model, we were able to predict patients' prognosis more accurately. Subjects in the high-risk cohort exhibited inferior survival outcomes, both in the training and validation datasets, as compared to those in the low-risk cohort (p < 0.05). Moreover, there were differences in the immunological microenvironments, biological processes, clinical features, and chemotherapeutic drug sensitivity between the groups at high and low risk. Using multivariable Cox regression analyses, platelet-related risk score was shown to be an independent prognostic influence in MM (p < 0.001, hazard ratio (HR) = 2.001%, 95% confidence interval (CI): 1.467-2.730). Furthermore, the capacity to predict survival was further improved when a combined nomogram was utilized. In training cohort, this outperformed the predictive value of International staging system (ISS) alone from a 5-years area under curve (AUC) = 0.668 (95% CI: 0.611-0.725) to an AUC = 0.721 (95% CI: 0.665-0.778). Conclusion: Our study revealed the potential benefits of PRGs in terms of survival prognosis of MM patients. Furthermore, we verified its potential as a drug target for MM patients. These findings open up novel possibilities for prognostic evaluation and treatment choices for MM.

Construction of an Immunogenic Cell Death-Related Gene Signature and Genetic Subtypes for Predicting Prognosis, Immune Microenvironments, and Drug Sensitivity in Hepatocellular Carcinoma.

Purpose: Immunogenic cell death (ICD) is a type of regulated cell death that modifies the immune response by releasing DAMPs or danger signals. Herein, we aimed to develop an ICD-related predictive model for patients with hepatocellular carcinoma (HCC) and investigate its applicability for predicting prognostic outcomes and immunotherapeutic responses. Methods: Differentially expressed genes of ICD were identified in the HCC and normal liver samples. A prognostic risk model and a nomogram containing clinicopathological features were created. To validate the effectiveness of the model, an external dataset was used. Clinical characteristics, prognosis, tumor mutation burden, immune microenvironments, biological function and chemotherapeutic drug sensitivity were evaluated for different genetic subtypes and risk groups. Results: A total of 35 ICD-related genes (ICDRGs) were identified between HCC and normal samples, 11 of which were significantly associated with overall survival (OS) in HCC patients. Four different genetic subtypes were formed and eight ICDRGs were selected to develop a risk prognostic model. The risk scores were shown to be an independent prognostic factor for HCC and positively correlated with pathological severity. Patients in the high-risk group had a higher frequency of TP53 mutations, increased expression of immune checkpoints and human leukocyte antigen genes. The inhibitory concentrations of chemotherapeutic drugs differed in different populations. Conclusion: In this study, we developed an ICDRG risk model and demonstrated its applicability in predicting survival outcomes, immune and chemotherapeutic responses in HCC patients. ICDRGs are expected to be used as novel biomarkers in the medical decision-making of HCC.

A review of natural products targeting tumor immune microenvironments for the treatment of lung cancer.

Lung cancer (LC) produces some of the most malignant tumors in the world, with high morbidity and mortality. Tumor immune microenvironment (TIME), a component of the tumor microenvironment (TME), are critical in tumor development, immune escape, and drug resistance. The TIME is composed of various immune cells, immune cytokines, etc, which are important biological characteristics and determinants of tumor progression and outcomes. In this paper, we reviewed the recently published literature and discussed the potential uses of natural products in regulating TIME. We observed that a total of 37 natural compounds have been reported to exert anti-cancer effects by targeting the TIME. In different classes of natural products, terpenoids are the most frequently mentioned compounds. TAMs are one of the most investigated immune cells about therapies with natural products in TIME, with 9 natural products acting through it. 17 natural products exhibit anti-cancer properties in LC by modulating PD-1 and PD-L1 protein activity. These natural products have been extensively evaluated in animal and cellular LC models, but their clinical trials in LC patients are lacking. Based on the current review, we have revealed that the mechanisms of LC can be treated with natural products through TIME intervention, resulting in a new perspective and potential therapeutic drugs.

N6-Methyladenosine (m6A) Methylation Is Associated with the Immune Microenvironments in Acute Intracerebral Hemorrhage (ICH).

Researchers have recently found that N6-methyladenosine (m6A) is a type of internal posttranscriptional modification that is essential in mammalian mRNA. However, the features of m6A RNA methylation in acute intracerebral hemorrhage (ICH) remain unknown. To explore differential methylations and to discover their functions in acute ICH patients, we recruited three acute ICH patients, three healthy controls, and an additional three patients and healthy controls for validation. The m6A methylation levels in blood samples from the two groups were determined by ultrahigh-performance liquid chromatography coupled with triple quadruple mass spectrometry (UPLC-QQQ-MS). Methylated RNA immunoprecipitation sequencing (MeRIP-seq) was employed to identify differences in m6A modification, and the differentially expressed m6A-modified genes were confirmed by MeRIP-qPCR. We found no significant differences in the total m6A levels between the two groups but observed differential methylation peaks. Compared with the control group, the coding genes showing increased methylation following acute ICH were mostly involved in processes connected with osteoclast differentiation, the neurotrophin signaling pathway, and the spliceosome, whereas genes with reduced m6A modification levels after acute ICH were found to be involved in the B-cell and T-cell receptor signaling pathways. These results reveal that differentially m6A-modified genes may influence the immune microenvironments in acute ICH.

Identification of subclusters and prognostic genes based on glycolysis/gluconeogenesis in hepatocellular carcinoma.

Background: This study aimed to examine glycolysis/gluconeogenesis-related genes in hepatocellular carcinoma (HCC) and evaluate their potential roles in HCC progression and immunotherapy response. Methods: Data analyzed in this study were collected from GSE14520, GSE76427, GSE174570, The Cancer Genome Atlas (TCGA), PXD006512, and GSE149614 datasets, metabolic pathways were collected from MSigDB database. Differentially expressed genes (DEGs) were identified between HCC and controls. Differentially expressed glycolysis/gluconeogenesis-related genes (candidate genes) were obtained and consensus clustering was performed based on the expression of candidate genes. Bioinformatics analysis was used to evaluate candidate genes and screen prognostic genes. Finally, the key results were tested in HCC patients. Results: Thirteen differentially expressed glycolysis/gluconeogenesis-related genes were validated in additional datasets. Consensus clustering analysis identified two distinct patient clusters (C1 and C2) with different prognoses and immune microenvironments. Immune score and tumor purity were significantly higher in C1 than in C2, and CD4+ memory activated T cell, Tfh, Tregs, and macrophage M0 were higher infiltrated in HCC and C1 group. The study also identified five intersecting DEGs from candidate genes in TCGA, GSE14520, and GSE141198 as prognostic genes, which had a protective role in HCC patient prognosis. Compared with the control group, the prognostic genes all showed decreased expression in HCC patients in RT-qPCR and Western blot analyses. Flow cytometry verified the abnormal infiltration level of immune cells in HCC patients. Conclusion: Results showed that glycolysis/gluconeogenesis-related genes were associated with patient prognosis, immune microenvironment, and response to immunotherapy in HCC. It suggests that the model based on five prognostic genes may valuable for predicting the prognosis and immunotherapy response of HCC patients.

Extreme environments and human health: From the immune microenvironments to immune cells.

Exposure to extreme environments causes specific acute and chronic physiological responses in humans. The adaptation and the physiological processes under extreme environments predominantly affect multiple functional systems of the organism, in particular, the immune system. Dysfunction of the immune system affected by several extreme environments (including hyperbaric environment, hypoxia, blast shock, microgravity, hypergravity, radiation exposure, and magnetic environment) has been observed from clinical macroscopic symptoms to intracorporal immune microenvironments. Therefore, simulated extreme conditions are engineered for verifying the main influenced characteristics and factors in the immune microenvironments. This review summarizes the responses of immune microenvironments to these extreme environments during in vivo or in vitro exposure, and the approaches of engineering simulated extreme environments in recent decades. The related microenvironment engineering, signaling pathways, molecular mechanisms, clinical therapy, and prevention strategies are also discussed.

Single-cell transcriptome analysis reveals T population heterogeneity and functions in tumor microenvironment of colorectal cancer metastases.

Cell mediated immune escape, a microenvironment factor, induces tumorigenesis and metastasis. The purpose of this study was to display the characteristics of T cell populations in immune microenvironments for colorectal cancer (CRC) metastasis. Unsupervised cluster analysis was conducted to identify functionally distinct T cell clusters from 3,003 cells in peripheral blood and 4,656 cells in tissues. Subsequently, a total of 8 and 4 distinct T cell population clusters were identified from tumor tissue and peripheral blood, respectively. High levels of CD8+TEX, CD4+TRM, TH1-like T cells, CD8+TEM, tumor-Treg from tissues, and CD4+TN from peripheral blood are essential components of immune microenvironment for the prediction of CRC metastasis. Moreover, exhausted T cells are characterized by higher expression of multiple inhibitory receptors, including PDCD1 and LAG3. Some genes such as PFKFB3, GNLY, circDCUN1D4, TXNIP and NR4A2 in T cells of cluster were statistically different between CRC metastasis and non-metastasis. The ligand-receptor interactions identified between different cluster cells and metastases-related DEGs identified from each cluster revealed that the communications of cells, alterations of functions, and numbers of T subsets may contribute to the metastasis of CRC. The mutation frequency of KiAA1551, ATP8B4 and LNPEP in T cells from tissues and SOR1 from peripheral blood were higher in metastatic CRC than that in non-metastatic CRC. In conclusion, the discovery of differential genes in T cells may provide potential targets for immunotherapy of CRC metastasis and relevant insights into the clinical prediction and prognosis of CRC metastasis.

Regulation of the tumor immune microenvironment by the Hippo Pathway: Implications for cancer immunotherapy.

The tumor immune microenvironment (TIME) is a dynamic and complex ecosystem consisting of immune cells, stromal cells, and tumor cells. It plays a crucial role in shaping cancer progression and treatment outcomes. Notably, tumor-associated immune cells are key regulators within the TIME, influencing immune responses and therapeutic efficacy. The Hippo pathway is a critical signaling pathway involved in the TIME and cancer progression. In this review, we provide an overview of the Hippo pathway's role in the TIME, focusing on its interactions with immune cells and their implications in cancer biology and therapy. Specifically, we discuss the involvement of the Hippo pathway in regulating T-cell function, macrophage polarization, B-cell differentiation, MDSC activity, and dendritic cell-mediated immune responses. Furthermore, we explore its influence on PD-L1 expression in lymphocytes and its potential as a therapeutic target. While recent progress has been made in understanding the Hippo pathway's molecular mechanisms, challenges remain in deciphering its context-dependent effects in different cancers and identifying predictive biomarkers for targeted therapies. By elucidating the intricate crosstalk between the Hippo pathway and the TME, we aim to contribute to the development of innovative strategies for cancer treatment.

SPARTIN: a Bayesian method for the quantification and characterization of cell type interactions in spatial pathology data.

Introduction: The acquisition of high-resolution digital pathology imaging data has sparked the development of methods to extract context-specific features from such complex data. In the context of cancer, this has led to increased exploration of the tumor microenvironment with respect to the presence and spatial composition of immune cells. Spatial statistical modeling of the immune microenvironment may yield insights into the role played by the immune system in the natural development of cancer as well as downstream therapeutic interventions. Methods: In this paper, we present SPatial Analysis of paRtitioned Tumor-Immune imagiNg (SPARTIN), a Bayesian method for the spatial quantification of immune cell infiltration from pathology images. SPARTIN uses Bayesian point processes to characterize a novel measure of local tumor-immune cell interaction, Cell Type Interaction Probability (CTIP). CTIP allows rigorous incorporation of uncertainty and is highly interpretable, both within and across biopsies, and can be used to assess associations with genomic and clinical features. Results: Through simulations, we show SPARTIN can accurately distinguish various patterns of cellular interactions as compared to existing methods. Using SPARTIN, we characterized the local spatial immune cell infiltration within and across 335 melanoma biopsies and evaluated their association with genomic, phenotypic, and clinical outcomes. We found that CTIP was significantly (negatively) associated with deconvolved immune cell prevalence scores including CD8+ T-Cells and Natural Killer cells. Furthermore, average CTIP scores differed significantly across previously established transcriptomic classes and significantly associated with survival outcomes. Discussion: SPARTIN provides a general framework for investigating spatial cellular interactions in high-resolution digital histopathology imaging data and its associations with patient level characteristics. The results of our analysis have potential implications relevant to both treatment and prognosis in the context of Skin Cutaneous Melanoma. The R-package for SPARTIN is available at https://github.com/bayesrx/SPARTIN along with a visualization tool for the images and results at: https://nateosher.github.io/SPARTIN.

External cold atmospheric plasma-responsive on-site hydrogel for remodeling tumor immune microenvironment.

Although immunotherapy has recently emerged as a promising anti-tumor approach, it remains limited by the immunosuppressive tumor microenvironment. Cold atmospheric plasma irradiation can generate reactive oxygen species and trigger the presentation of tumor-associated antigens. Here, we exploited cold atmospheric plasma for on-site hydrogel application in the tumor environment, aiming to facilitate the sustainable uptake of tumor-associated antigens and nanoadjuvants by dendritic cells. Hyaluronic acid-tyramine conjugate was intratumorally injected as a liquid and formed an on-site hydrogel under irradiation with cold atmospheric plasma. Intratumoral delivery of hyaluronic acid-tyramine conjugate with transforming growth factor ß-blocking nanoadjuvant (TLN) followed by cold atmospheric plasma irradiation yielded a micro-network of TLN-loaded hydrogel (TLN@CHG). In vivo intratumoral injection of TLN@CHG promoted the activation of dendritic cells and more effectively increased the proportion of CD4 T cells and CD8 T cells in the tumor microenvironment, compared to the groups receiving TLN or hydrogel alone. Moreover, in CT26 tumor model mice, cold atmospheric plasma-induced TLN@CHG therapy ablated the primary tumor and provided 100% survival among mice rechallenged with CT26 cells. Taken together, our findings suggest that an on-site hydrogel-based micro-network of TLN has the potential to remodel the tumor immune microenvironment. Although we used TLN in this study, the concept could be extended to support the sustained action of other nanoadjuvants in a hydrogel micro-network.

[Infiltration and significance of M1 macrophage in breast cancer: an analysis of METABRIC database and clinical validation].

Objective: To investigate the differences of immune microenvironment between stage T1N3 and stage T3N0 breast cancer patients and explore the relationship between M1 macrophage infiltration and lymph node metastasis in breast cancer. Methods: Clinical information and RNA-sequencing (RNA-Seq) expression data of stage T1N3 (n=9) and stage T3N0 (n=11) breast cancer patients were extracted from Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) databases. Using CIBERSORT, the proportions of 22 types of immune cells were calculated, and then the differences of immune cell infiltration between stage T1N3 and T3N0 patients were compared. From 2011 to 2022, pathologic specimens were collected from breast cancer patients who underwent curative resection at the Cancer Hospital, Chinese Academy of Medical Sciences, including 77 at stage T1N3 and 58 at stage T3N0.The METABRIC database analysis results were verified by examining the density of M1 macrophages in tissues using dual-staining immunohistochemistry. Results: METABRIC data analysis showed M1 macrophage was the highest proportion, 15.85% in stage T1N3 breast cancer; M2 macrophage was the highest proportion, 13.07% in stage T3N0 breast cancer.M1 macrophage proportions were statistically different between patients with stage T1N3 and stage T3N0 (P=0.010). The dual-staining immunohistochemistry analysis of breast cancer tissues showed M1 macrophage density (median) of 62.0 and 38.0 cells/mm(2) for stage T1N3 and T3N0, respectively. The difference was statistically significant (P=0.002). Conclusion: The density of M1 macrophages is notably higher in stage T1N3 patients and is associated with lymph node metastasis.

Harnessing Reconstructed Macrophage Modulation of Infiltration-Excluded Immune Microenvironments To Delineate Glioma Infiltrative Region.

High invasiveness of glioma produces residual glioma cells in the brain parenchyma after surgery and ultimately causes recurrence. Precise delineation of glioma infiltrative region is critical for an accurate complete resection, which is challenging. The glioma-infiltrating area constitutes infiltration-excluded immune microenvironments (I-E TIMEs), which recruits endogenous or adoptive macrophages to the invasive edge of glioma. Thus, combined with immune cell tracing technology, we provided a novel strategy for the preoperative precise definition of the glioma infiltration boundary, even satellite-like infiltration stoves. Herein, the biomimetic probe was constructed by internalizing fluorophore labeled PEGylated KMnF3 nanoparticles into bone-marrow-derived macrophages using magnetic resonance imaging (MRI)/fluorescence imaging (FI). The biomimetic probe was able to cross the blood-brain barrier and home to the orthotopic glioma infiltrates including satellite stove under MRI and FI tracing, which was validated using hematoxylin and eosin staining, indicating its excellent performance in distinguishing the margins between the glioma cell and normal tissues. This study guides the precise definition of glioma infiltration boundaries at the cellular level, including the observation of any residual glioma cells after surgery. Thus, it has the potential to guide surgery to maximize resection and predict recurrence in the clinic.

Architecture-Engineered Electrospinning Cascade Regulates Spinal Microenvironment to Promote Nerve Regeneration.

The inflammatory cascade after spinal cord injury (SCI) causes necrotizing apoptosis of local stem cells, which limits nerve regeneration. Therefore, coordinating the inflammatory immune response and neural stem cell (NSC) functions is key to promoting the recovery of central nervous system function. In this study, a hydrogel "perfusion" system and electrospinning technology are integrated, and a "concrete" composite support for the repair of nerve injuries is built. The hydrogel's hydrophilic properties activate macrophage integrin receptors to mediate polarization into anti-inflammatory subtypes and cause a 10% increase in polarized M2 macrophages, thus reprogramming the SCI immune microenvironment. Programmed stromal cell-derived factor-1α and brain-derived neurotrophic factor released from the composite increase recruitment and neuronal differentiation of NSCs by approximately four- and twofold, respectively. The fiber system regulates the SCI immune inflammatory microenvironment, recruits endogenous NSCs, promotes local blood vessel germination and maturation, and improves nerve function recovery in a rat SCI model. In conclusion, the engineering fiber composite improves the local inflammatory response. It promotes nerve regeneration through a hydrophilic programmed cytokine-delivery system, which further improves and supplements the immune response mechanism regulated by the inherent properties of the biomaterial. The new fiber composite may serve as a new treatment approach for SCI.

Infiltration and significance of M1 macrophage in breast cancer: an analysis of METABRIC database and clinical validation / 中华肿瘤杂志

Objective: To investigate the differences of immune microenvironment between stage T1N3 and stage T3N0 breast cancer patients and explore the relationship between M1 macrophage infiltration and lymph node metastasis in breast cancer. Methods: Clinical information and RNA-sequencing (RNA-Seq) expression data of stage T1N3 (n=9) and stage T3N0 (n=11) breast cancer patients were extracted from Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) databases. Using CIBERSORT, the proportions of 22 types of immune cells were calculated, and then the differences of immune cell infiltration between stage T1N3 and T3N0 patients were compared. From 2011 to 2022, pathologic specimens were collected from breast cancer patients who underwent curative resection at the Cancer Hospital, Chinese Academy of Medical Sciences, including 77 at stage T1N3 and 58 at stage T3N0.The METABRIC database analysis results were verified by examining the density of M1 macrophages in tissues using dual-staining immunohistochemistry. Results: METABRIC data analysis showed M1 macrophage was the highest proportion, 15.85% in stage T1N3 breast cancer; M2 macrophage was the highest proportion, 13.07% in stage T3N0 breast cancer.M1 macrophage proportions were statistically different between patients with stage T1N3 and stage T3N0 (P=0.010). The dual-staining immunohistochemistry analysis of breast cancer tissues showed M1 macrophage density (median) of 62.0 and 38.0 cells/mm(2) for stage T1N3 and T3N0, respectively. The difference was statistically significant (P=0.002). Conclusion: The density of M1 macrophages is notably higher in stage T1N3 patients and is associated with lymph node metastasis.

Construction of a co-expression network and prediction of metastasis markers in colorectal cancer patients with liver metastasis.

Background: Colorectal cancer (CRC) is a common global malignancy associated with high invasiveness, high metastasis, and poor prognosis. CRC commonly metastasizes to the liver, where the treatment of metastasis is both difficult and an important topic in current CRC management. Methods: Microarrays data of human CRC with liver metastasis (CRCLM) were downloaded from the National Center for Biotechnology Information (NCBI) Gene Expression Omnibus (GEO) database to identify potential key genes. Differentially expressed (DE) genes (DEGs) and DEmiRNAs of primary CRC tumor tissues and metastatic liver tissues were identified. Microenvironment Cell Populations (MCP)-counter was used to estimate the abundance of immune cells in the tumor micro-environment (TME), and weighted gene correlation network analysis (WGCNA) was used to construct the co-expression network analysis. Gene Ontology and Kyoto Encyclopaedia of Gene and Genome (KEGG) pathway enrichment analyses were conducted, and the protein-protein interaction (PPI) network for the DEGs were constructed and gene modules were screened. Results: Thirty-five pairs of matched colorectal primary cancer and liver metastatic gene expression profiles were screened, and 610 DEGs (265 up-regulated and 345 down-regulated) and 284 DEmiRNAs were identified. The DEGs were mainly enriched in the complement and coagulation cascade pathways and renin secretion. Immune infiltrating cells including neutrophils, monocytic lineage, and cancer-associated fibroblasts (CAFs) differed significantly between primary tumor tissues and metastatic liver tissues. WGCN analysis obtained 12 modules and identified 62 genes with significant interactions which were mainly related to complement and coagulation cascade and the focal adhesion pathway. The best subset regression analysis and backward stepwise regression analysis were performed, and eight genes were determined, including F10, FGG, KNG1, MBL2, PROC, SERPINA1, CAV1, and SPP1. Further analysis showed four genes, including FGG, KNG1, CAV1, and SPP1 were significantly associated with CRCLM. Conclusions: Our study implies complement and coagulation cascade and the focal adhesion pathway play a significant role in the development and progression of CRCLM, and FGG, KNG1, CAV1, and SPP1 may be metastatic markers for its early diagnosis.

A Novel Necroptosis-Related Prognostic Signature of Glioblastoma Based on Transcriptomics Analysis and Single Cell Sequencing Analysis.

Background: Glioblastoma (GBM) is the most common and deadly brain tumor. The clinical significance of necroptosis (NCPS) genes in GBM is unclear. The goal of this study is to reveal the potential prognostic NCPS genes associated with GBM, elucidate their functions, and establish an effective prognostic model for GBM patients. Methods: Firstly, the NCPS genes in GBM were identified by single-cell analysis of the GSE182109 dataset in the GEO database and weighted co-expression network analysis (WGCNA) of The Cancer Genome Atlas (TCGA) data. Three machine learning algorithms (Lasso, SVM-RFE, Boruta) combined with COX regression were used to build prognostic models. The subsequent analysis included survival, immune microenvironments, and mutations. Finally, the clinical significance of NCPS in GBM was explored by constructing nomograms. Results: We constructed a GBM prognostic model composed of NCPS-related genes, including CTSD, AP1S1, YWHAG, and IER3, which were validated to have good performance. According to the above prognostic model, GBM patients in the TCGA and CGGA groups could be divided into two groups according to NCPS, with significant differences in survival analysis between the two groups and a markedly worse prognostic status in the high NCPS group (p < 0.001). In addition, the high NCPS group had higher levels of immune checkpoint-related gene expression, suggesting that they may be more likely to benefit from immunotherapy. Conclusions: Four genes (CTSD, AP1S1, YWHAG, and IER3) were screened through three machine learning algorithms to construct a prognostic model for GBM. These key and novel diagnostic markers may become new targets for diagnosing and treating patients with GBM.

Multi-Scale Spatial Analysis of the Tumor Microenvironment Reveals Features of Cabozantinib and Nivolumab Efficacy in Hepatocellular Carcinoma.

Background: Concomitant inhibition of vascular endothelial growth factor (VEGF) and programmed cell death protein 1 (PD-1) or its ligand PD-L1 is a standard of care for patients with advanced hepatocellular carcinoma (HCC), but only a minority of patients respond, and responses are usually transient. Understanding the effects of therapies on the tumor microenvironment (TME) can provide insights into mechanisms of therapeutic resistance. Methods: 14 patients with HCC were treated with the combination of cabozantinib and nivolumab through the Johns Hopkins Sidney Kimmel Comprehensive Cancer Center. Among them, 12 patients (5 responders + 7 non-responders) underwent successful margin negative resection and are subjects to tissue microarray (TMA) construction containing 37 representative tumor region cores. Using the TMAs, we performed imaging mass cytometry (IMC) with a panel of 27-cell lineage and functional markers. All multiplexed images were then segmented to generate a single-cell dataset that enables (1) tumor-immune compartment analysis and (2) cell community analysis based on graph-embedding methodology. Results from these hierarchies are merged into response-associated biological process patterns. Results: Image processing on 37 multiplexed-images discriminated 59,453 cells and was then clustered into 17 cell types. Compartment analysis showed that at immune-tumor boundaries from NR, PD-L1 level on tumor cells is significantly higher than remote regions; however, Granzyme B expression shows the opposite pattern. We also identify that the close proximity of CD8+ T cells to arginase 1hi (Arg1hi) macrophages, rather than CD4+ T cells, is a salient feature of the TME in non-responders. Furthermore, cell community analysis extracted 8 types of cell-cell interaction networks termed cellular communities (CCs). We observed that in non-responders, macrophage-enriched CC (MCC) and lymphocyte-enriched CC (LCC) strongly communicate with tumor CC, whereas in responders, such communications were undermined by the engagement between MCC and LCC. Conclusion: These results demonstrate the feasibility of a novel application of multiplexed image analysis that is broadly applicable to quantitative analysis of pathology specimens in immuno-oncology and provides further evidence that CD163-Arg1hi macrophages may be a therapeutic target in HCC. The results also provide critical information for the development of mechanistic quantitative systems pharmacology models aimed at predicting outcomes of clinical trials.

Two immune-enhanced molecular subtypes differ in inflammation, immune checkpoints, mutations, and prognostic outcome in stage I-II colonic carcinoma.

The purpose of this paper is to investigate the immune function of the tumor microenvironment and its clinical correlation with colonic carcinoma. Immune genes were downloaded from the The Cancer Genome Atlas database. Five subtypes are obtained by cluster screening based on immune gene expression data. The C3 and C4 subtypes show stronger immune activity. In addition, the C4 subtype has the largest number of gene mutations and the worst prognosis. Most of the immune signatures are upregulated in the C4 subtype, while most of the immune infiltration-related cells are upregulated in the C3 and C4 subtypes. The different immune microenvironments between these subtypes may provide new ideas for immunotherapy strategies in colon carcinoma.

Heterogeneous Tumor-Immune Microenvironments between Primary and Metastatic Tumors in a Patient with ALK Rearrangement-Positive Large Cell Neuroendocrine Carcinoma.

Evolution of tumor-immune microenviroments (TIMEs) occurs during tumor growth and dissemination. Understanding inter-site tumor-immune heterogeneity is essential to harness the immune system for cancer therapy. While the development of immunotherapy against lung cancer with driver mutations and neuroendocrine tumors is ongoing, little is known about the TIME of large cell neuroendocrine carcinoma (LCNEC) or anaplastic lymphoma kinase (ALK) rearrangement-positive lung cancer. We present a case study of a 32-year-old female patient with ALK-rearrangement-positive LCNEC, who had multiple distant metastases including mediastinal lymph-node, bilateral breasts, multiple bones, liver and brain. Multiple biopsy samples obtained from primary lung and three metastatic tumors were analyzed by fluorescent multiplex immunohistochemistry. Tissue localizations of tumor-infiltrating lymphocytes in the tumor nest and surrounding stroma were evaluated. T cell and B cell infiltrations were decreased with distance from primary lung lesion. Although each tumor displayed a unique TIME, all tumors exhibited concomitant regression after treatment with an ALK-inhibitor. This study provides the first evidence of the coexistence of distinct TIME within a single individual with ALK-rearrangement-positive LCNEC. The present study contributes to our understanding of heterogeneous TIMEs between primary and metastatic lesions and provides new insights into the complex interplay between host-immunity and cancer cells in primary and metastatic lesions.