Memory Cells Research Articles

All-in-One Magneto-optical Memory Arrays Based on a Two-Dimensional Ferromagnetic Metal.

Two-dimensional (2D) van der Waals (vdW) magnetic materials with atomic-scale thickness and smooth interfaces promise the possibility of developing high-density, energy-efficient spintronic devices. However, it remains a challenge to effectively control the perpendicular magnetic anisotropy (PMA) of 2D vdW ferromagnetic materials, as well as the integration of multiple memory cells. Here, we report highly efficient magneto-optical memory arrays by utilizing the huge spin-orbit torques (SOT) induced by the in-plane current in Fe3GeTe2 (FGT) flake. The device is constructed from individual FGT flakes without heavy metal assistance and allows for a low current density. The magneto-optical memory arrays implement nonvolatile memories for three bits and can be repeatedly scrubbed for "writing" and "reading". Besides, we show that FGT nanoflakes possess current-controlled volatile switching behavior at zero magnetic field. These results provide a solution for the next generation of all-vdW-scalable, high-performance spintronic logic devices and SOT-Magnetic Random Access Memory (MRAM).

A Systematic Literature Review on The Role of LSTM Networks in Capturing Temporal Dependencies in Data Mining Algorithms

Data mining plays a crucial role in extracting meaningful insights from large and complex data sets, with broad applications in sectors like finance, health care, and market analysis. Traditional techniques—such as classification, clustering, association rule mining, regression, and anomaly detection—are effective for analyzing structured data but struggle with sequential data due to the challenges of modeling temporal dependencies. Long Short Term Memory (LSTM) networks, a specialized form of Recurrent Neural Networks (RNNs), provide a solution to these challenges. By incorporating memory cells and gating mechanisms, LSTM effectively manage long-term dependencies and address issues like vanishing and exploding gradients. This paper reviews the impact of LSTM networks on data mining, analyzing over 60 key publications. By synthesizing concepts and recent advancements, the review underscores how LSTMs enhance the ability of data mining algorithms to capture and predict temporal patterns, reflecting current research trends and innovations

An Overview of the Future of Memory Cells: Advances in SSD Technology

This paper explores the topic of Solid-State Drives (SSDs) and NAND flash memory. Information of this paper is mainly obtained from authoritative academic websites and papers related to SSDs and flash memory. Memory cells are fundamental components in various electronic devices. In the field of data storage, SSDs represent the latest generation of storage devices, offering significantly better performance and functionality than traditional hard disk drives (HDDs). NAND flash memory chips are crucial component of SSDs, particularly 3D NAND, which exhibits exceptional performance and holds significant potential for future advancements. This paper will commence by providing an overview of SSDs and HDDs, followed by a comparison between NAND flash and NOR flash, and ultimately analysing the future of NAND flash memory technology employed in SSDs, with a focus on elucidating the advantages of 2D NAND over 3D NAND. Additionally, this paper explains a few challenges that NAND technology faces currently, as well as some possible solutions.

OMIP-109: 45-color full spectrum flow cytometry panel for deep immunophenotyping of the major lineages present in human peripheral blood mononuclear cells with emphasis on the T cell memory compartment.

The need for more in-depth exploration of the human immune system has moved the flow cytometry field forward with advances in instrumentation, reagent development and availability, and user-friendly implementation of data analysis methods. We developed a high-quality human 45-color panel, for comprehensive characterization of major cell lineages present in circulation including T cells, γδ T cells, NKT-like cells, B cells, NK cells, monocytes, basophils, dendritic cells, and ILCs. Assay optimization steps are described in detail to ensure that each marker in the panel was optimally resolved. In addition, we highlight the outstanding discernment of cell activation, exhaustion, memory, and differentiation states of CD4+ and CD8+ T cells using this 45-color panel. The panel enabled an in-depth description of very distinct phenotypes associated with the complexity of the T cell memory response. Furthermore, we present how this panel can be effectively used for cell sorting on instruments with a similar optical layout to achieve the same level of resolution. Functional evaluation of sorted specific rare cell subsets demonstrated significantly different patterns of immunological responses to stimulation, supporting functional and phenotypic differences within the T cell memory subsets. In summary, the combination of full spectrum profiling technology and careful assay design and optimization results in a high resolution multiparametric 45-color assay. This panel offers the opportunity to fully characterize immunological profiles present in peripheral blood in the context of infectious diseases, autoimmunity, neurodegeneration, immunotherapy, and biomarker discovery.

Self-Adjuvanting Adenoviral Nanovaccine for Effective T-Cell-Mediated Immunity and Long-Lasting Memory Cell Activation against Tuberculosis.

An enhanced vaccine is immediately required to swap the more than 100 year-old bacillus Calmette-Guerin (BCG) vaccine against tuberculosis. Here, trimethyl chitosan-loaded inactivated Mycobacterium smegmatis (MST), along with potent adenovirus hexon protein (AdHP), and toll-like receptor (TLR)-1/2 as a nanovaccine, was developed against tuberculosis (TB). The nanoformulation increased the bioavailability of MST and elicited the targeting ability. Nanovaccines have a size range of 183.5 ± 9.5 nm with a spherical morphology and uniform distribution. The nanovaccine exhibited a higher release of antigen in acidic pH, and this is mainly due to protonation of ionizable groups in polymeric materials. The nanovaccine facilitated the effective cellular uptake of bone-marrow-derived dendritic cells and progressive endosomal escape in a shorter period. In vitro analyses indicated that the nanovaccine activated cytokine and T-cell production and also assisted in humoral immunity by producing antibodies. The nanovaccine was able to induce more cellular and humoral memory cells and a better protective immune response. Nanomaterials effectively delivered the MST, AdHP, and TLR1/2 antigens to the major histocompatibility complex class I and II pathways to generate protective cytotoxic CD8+ and CD4+ T-cells. In vivo experiments, compared with free MST and BCG, showed that mice immunized with the nanovaccine induced more specific CD4+, CD8+, and memory T-cell activations. Overall, the fabricated nanovaccine was able to control the release of antigens and adjuvants and enhance memory cell activation and humoral immunity against TB.

Central Memory CD4 T Cells from Persons with HIV Accumulate DNA Content Defects During Proliferative Response.

Central memory (TCM) cells are a subpopulation of CD4 T cells that sustain overall CD4 T cell counts in HIV infection. The mechanisms underlying their eventual demise, which leads to loss of CD4 T cell counts, are not known. To understand their proneness to death despite their increased movement to proliferation, we examined cell division together with possible cell accumulation in different phases of the cell cycle. Purified circulating TCM cells from untreated people living with HIV (PLWH) (n = 9) and healthy controls (n = 10) were stimulated in vitro using anti-CD3/CD28 agonistic antibodies plus IL-2 and cultured for 4 days. Cell viability, DNA content, proliferation, and cyclin A and cyclin B expression were measured. We found that PLWH TCM cells more frequently had a DNA content lower than G0/G1, compared with controls (p = .043). These cells accumulated with each division. The proportion of cells with sub-G0/G1 DNA content that were cycling (expressing cyclin A) was greater in the PLWH group (p = .003). The percentage of TCM cells expressing cyclin A+ among those in G0/G1 and was also greater in the PLWH group (p = .043), suggesting arrest before G2/M. While TCM cells from PLWH can proliferate, during this process some of them accumulate defects in DNA content that are incompatible with viability, suggesting that they could be intrinsically prone to cell cycle-dependent death. This provides a possible mechanism underlying the increased TCM cell turnover in HIV infection.

Water-to-air unmanned aerial vehicle (UAV) based rolling shutter optical camera communication (OCC) system with gated recurrent unit neural network (GRU-NN)

Underwater sensors and autonomous underwater vehicles (AUVs) are widely adopted in oceanic research activities. As the number of underwater sensors and AUVs is growing quickly, the bandwidth requirements are increasing accordingly. In this work, we put forward and demonstrate a large field-of-view (FOV) water-to-air unmanned aerial vehicle (UAV) based optical camera communication (OCC) system with gated recurrent unit neural network (GRU-NN) for the first time to the best of our knowledge. As the UAVs are embedded with complementary-metal-oxide-semiconductor (CMOS) cameras, there is no need to install OCC receivers (Rxs), reducing the deployment cost. Moreover, the large photo-sensitive area of the CMOS camera can support a large FOV OCC transmission without the need for precise optical alignment. Here, by utilizing the column matrix identification during the rolling shutter pattern decoding in the CMOS image sensor, the scintillation caused by water turbulence can be reduced. Besides, in the outdoor and windy environment, the UAV will experience significant movement caused by the wind making it very difficult to capture stable OCC frames in the CMOS image sensor. Here, we propose and demonstrate utilizing GRU-NN, which is a special realization of the recurrent neural network (RNN) with memory cells capable of learning the time-domain dependent signals. It is shown that the GRU-NN can learn effectively from successive image frames in time-domain and produce correct prediction even under the windy and unstable UAV flying environment. Experimental results reveal that the proposed GRU-NN can outperform the previous pixel-per-symbol labeling neural network (PPS-NN), and also can significantly reduce the computation time when compared with long-short-term-memory-neural-network (LSTM-NN). The proposed system can decode 4-level pulse-amplitude-modulation (PAM4) rolling shutter OCC patterns at data rates of 5.4 kbit/s and 3.0 kbit/s under clear and cloudy water, respectively, fulfilling the pre-forward error correction bit-error rate (pre-FEC BER = 3.8 × 10−3). We also demonstrate that the UAV based OCC system can support data rates of 5.4 kbit/s, 4.2 kbit/s, and 3.0 kbit/s at distances of 2.2 m, 3.2 m, and 4.2 m, respectively, at outdoor and windy environments.

Néel Vector Auto-Oscillations and Reorientations Induced by Spin-Polarized Electric Currents in Antiferromagnetic Mn2Au Nanolayer

The electrical excitation of spin dynamics in antiferromagnets is important for the development of high-speed spintronic devices with a low power consumption. Here, we present a theoretical study of the spin dynamics generated in the Ni/Cu/Mn2Au/Cu/Ni nanostructure by a perpendicular-to-plane electric current. Our investigation includes atomistic simulations of spin reorientations in a few monolayer antiferromagnetic Mn2Au film and numerical calculations of nonequilibrium spin accumulation in the nanostructure comprising ferromagnetic Ni polarizers with antiparallel magnetizations. This combined approach enables us to quantify the dynamics of Mn magnetic moments induced by the spin-transfer torque created by the spin-polarized charge flow. The calculations show that the direct electric current with the density exceeding some temperature-dependent threshold value gives rise to steady-state auto-oscillations of the Néel vector in the [Formula: see text]-oriented Mn2Au nanolayer. As the precession of Mn magnetic moments occurs around an out-of-plane direction strongly deflected from their initial in-plane orientations, the emergence of auto-oscillations should be regarded as the realization of a dynamic spin reorientation transition in the antiferromagnetic crystal. Remarkably, the precession frequency rises with increasing current density J and exceeds 1[Formula: see text]THz at [Formula: see text][Formula: see text]A[Formula: see text]m[Formula: see text], which makes the described antiferromagnetic spin transfer nano-oscillator attractive for device applications. Furthermore, our simulations demonstrate that a picosecond current pulse injected into the Ni/Cu/Mn2Au/Cu/Ni nanostructure can induce a precessional switching of the Néel vector. Depending on the current density and pulse duration, the Néel vector rotates by either 90° or 180° and attains stable orientation along the corresponding [Formula: see text] easy axis in the plane of the Mn2Au nanolayer. This feature shows that the Ni/Cu/Mn2Au/Cu/Ni nanostructure could be used as a nonvolatile memory cell with the electrical writing and readout.

The structure and formation of non-volatile memory cells of Superflash

Split-gate embedded Flash memory technology has been around for decades and has become the standard for a wide range of devices, such as microcontrollers and smart cards. Among the, due to a number of advantages, Silicon Storage Technology Super Flash non-volatile memory technology has become the most widespread. This article presents the results of a study of the memory cells structure, examines in detail the principle of their operation and the main technological stages of the production process of forming transistor structures.

Circadian rhythm genes contribute to the prognosis prediction and potential therapeutic target in gastric cancer

The role of circadian rhythm genes (CRGs) in gastric cancer (GC) is poorly understood. This study aimed to develop a CRG signature to improve understanding of prognosis and immunotherapy responses in GC patients. We integrated the The Cancer Genome Atlas-Stomach adenocarcinoma (TCGA-STAD) dataset with CRGs to develop a prognostic signature for GC. The signature’s predictive ability was validated using Kaplan-Meier and ROC curves. The CIBERSORT algorithm evaluated immune cell proportions, and tumor immune dysfunction and exclusion score, as well as immune phenotype score, determined the response to immunotherapy for STAD patients. Finally, we assessed signature genes expression using real-time quantitative polymerase chain reaction. We developed a 4-CRG signature for STAD, demonstrating accurate prognostic ability. The low-risk group showed increased B cell memory and CD8 + T cells, and decreased M2 Macrophages compared to the high-risk group. Patients in the low-risk group had a higher likelihood of benefiting from immunotherapy. Additionally, gastric cancer tissues exhibited elevated expression of OPN3 and decreased expression of TP53 compared to adjacent tissue. This study successfully established a prognostic signature for CRGs, accurately predicting prognosis and immunotherapeutic response among STAD patients, providing insights for the development of personalized therapeutic strategies for these patients.

Immunotherapy response induces divergent tertiary lymphoid structure morphologies in hepatocellular carcinoma.

Tertiary lymphoid structures (TLS) are associated with improved response in solid tumors treated with immune checkpoint blockade, but understanding of the prognostic and predictive value of TLS and the circumstances of their resolution is incomplete. Here we show that in hepatocellular carcinoma treated with neoadjuvant immunotherapy, high intratumoral TLS density at the time of surgery is associated with pathologic response and improved relapse-free survival. In areas of tumor regression, we identify a noncanonical involuted morphology of TLS marked by dispersion of the B cell follicle, persistence of a T cell zone enriched for T cell-mature dendritic cell interactions and increased expression of T cell memory markers. Collectively, these data suggest that TLS can serve as both a prognostic and predictive marker of response to immunotherapy in hepatocellular carcinoma and that late-stage TLS may support T cell memory formation after elimination of a viable tumor.

A FinFET-based static memory cell optimized for stability and low power consumption

A FinFET-based static memory cell optimized for stability and low power consumption

T Cell Responses to SARS-CoV-2 in Vaccinated Pregnant Women: A Comparative Study of Pre-Pregnancy and During-Pregnancy Infections

The COVID-19 pandemic has posed unprecedented challenges to global public health, particularly for vulnerable populations like pregnant women. This study delves into the T cell immune responses in pregnant women with confirmed SARS-CoV-2 infection, all of whom received three doses of a COVID-19 vaccine. Using the ELISpot assay, we measured T cell responses against SARS-CoV-2 spike S1 and nucleocapsid peptides in two groups: those infected before and during pregnancy. Our results showed weak to moderate correlations between T cell responses and neutralizing antibody levels, with no statistically significant differences between the two groups. T cell reactivity appeared to decrease over time post-diagnosis, regardless of infection timing. Intriguingly, over half of the participants maintained detectable T cell memory responses beyond one year post-infection, suggesting the long-term persistence of cellular immunity. These insights contribute to the understanding of COVID-19 immunology in pregnant women, highlighting the importance of considering both humoral and cellular immune responses in this high-risk population.

Integrated non-reciprocal magneto-optics with ultra-high endurance for photonic in-memory computing

AbstractProcessing information in the optical domain promises advantages in both speed and energy efficiency over existing digital hardware for a variety of emerging applications in artificial intelligence and machine learning. A typical approach to photonic processing is to multiply a rapidly changing optical input vector with a matrix of fixed optical weights. However, encoding these weights on-chip using an array of photonic memory cells is currently limited by a wide range of material- and device-level issues, such as the programming speed, extinction ratio and endurance, among others. Here we propose a new approach to encoding optical weights for in-memory photonic computing using magneto-optic memory cells comprising heterogeneously integrated cerium-substituted yttrium iron garnet (Ce:YIG) on silicon micro-ring resonators. We show that leveraging the non-reciprocal phase shift in such magneto-optic materials offers several key advantages over existing architectures, providing a fast (1 ns), efficient (143 fJ per bit) and robust (2.4 billion programming cycles) platform for on-chip optical processing.

LC-MS/MS analysis reveals plasma protein signatures associated with lymph node metastasis in colorectal cancer

ObjectivesColorectal cancer (CRC) is a major global health concern, ranking as the third most common cancer and the fourth leading cause of cancer-related deaths worldwide. Currently, the diagnostic accuracy of Lymph node metastasis (LNM) is currently unsatisfactory. Therefore, there is an urgent need to develop a reliable tool that can accurately predict lymph node metastasis (LNM) in patients diagnosed with CRC.MethodsWe conducted an extensive proteomics investigation aimed at examining lymph node metastasis (LNM) in individuals diagnosed with colorectal cancer (CRC). In the discovery stage, employing a mass spectrometry-based proteomic approach, we analyzed a cohort of 60 colorectal cancer patients (NM=30, LNM=30), identifying distinct molecular profiles that differentiate patients with and without lymph node metastasis (LNM). Subsequently, we validated the protein classifier associated with lymph node metastasis.ResultsWe elucidated a combinatorial predictive protein biomarker that can distinguish patients with and without lymph node metastasis by LC-MS/MS. The classifier achieved an area under the curve (AUC) of 0.892 (95% CI, 0.842-0.941), while in the testing cohort, it attained an AUC of 0.929 (95% CI, 0.824-1.000). Furthermore, the four protein markers demonstrated an AUC of 0.84 (95% CI, 0.783–0.890) in the validation cohort. Additionally, we categorized patients into three types based on immunophenotyping. Type 1 primarily consisted of patients with negative lymph node metastasis (NM), characterized by immune cells such as NK cells, CD4 T effector memory cells, and memory B cells. Type 2 mainly included patients with positive lymph node metastasis (LNM), characterized by immune cells such as mesangial cells, epithelial cells, and mononuclear cells. In Type 1, a prominent upregulation observed in immune inflammation, as well as in glucose and lipid metabolism. In Type 2, significant upregulation was evident in pathways such as pyrimidine metabolism and cell cycle regulation. The findings of this study suggest that immune mechanisms may exert a pivotal role in the process of lymph node metastasis in CRC.ConclusionsHere, we present plasma protein signatures associated with lymph node metastasis in colorectal cancer (CRC). However, further validation across multiple centers is necessary to generalize these findings.

Analysis of etched drain based Cylindrical agate‐all‐around tunnel field effect transistor based static random access memory cell design

AbstractThis paper aims to propose a novel method for designing an static random access memory (SRAM) cell using an etched drain based Cyl GAA TFET with a hetero‐substrate material and an elevated density strip. The aim is to reduce power dissipation and improve stability, as demonstrated through analysis utilizing static noise margin (SNM) as well as N‐curve methods. With respect to the 16 nm MOSFET based SRAM cell, the proposed device‐based SRAM cell shows significant improvements with a 68.305% reduction in leakage power, a 15.58% increase in static voltage noise margin (SVNM), an 8.623% increase in static current noise margin (SINM), an 8.152% increase in write trip voltage (WTV), a 12.86% increase in write trip current (WTI), a 27.62% increase in static power noise margin (SPNM), and a 19.95% increase in write trip power (WTP). The design is implemented and analyzed using Cadence Virtuoso software, and a novel approach of look up tables and Verilog A is utilized for the device to circuit application. These results indicate promising advancements in the design of SRAM cells, which could have significant implications for the development of advanced computer systems.

Integrating machine learning and bioinformatics approaches for identifying novel diagnostic gene biomarkers in colorectal cancer.

This study aimed to identify diagnostic gene biomarkers for colorectal cancer (CRC) by analyzing differentially expressed genes (DEGs) in tumor and adjacent normal samples across five colon cancer gene-expression profiles (GSE10950, GSE25070, GSE41328, GSE74602, GSE142279) from the Gene Expression Omnibus (GEO) database. Intersecting identified DEGs with the module with the highest correlation to gene expression patterns of tumor samples in the gene co-expression network analysis revealed 283 overlapped genes. Centrality measures were calculated for these genes in the reconstructed STRING protein-protein interaction network. Applying LASSO logistic regression, eleven genes were ultimately recognized as candidate diagnostic genes. Among these genes, the area under the receiver operating characteristic curve (AUROC) values for nine genes (CDC25B, CDK4, IQGAP3, MMP1, MMP7, SLC7A5, TEAD4, TRIB3, and UHRF1) surpassed the threshold of 0.92 in both the training and validation sets. We evaluated the diagnostic performance of these genes with four machine learning algorithms: random forest (RF), support vector machines (SVM), artificial neural network (ANN), and gradient boosting machine (GBM). In the testing dataset (GSE21815 and GSE106582), the AUROC scores were greater than 0.95 for all of the machine learning algorithms, indicating the high diagnostic performance of the nine genes. Besides, these nine genes are also significantly correlated to twelve immune cells, namely Mast cells activated, Macrophages M0, M1, and M2, Neutrophils, T cells CD4 memory activated, T cells follicular helper, T cells CD8, T cells CD4 memory resting, B cells memory, Plasma cells, and Mast cells resting (P < 0.05). These results strongly suggest that all of the nine genes have the potential to serve as reliable diagnostic biomarkers for CRC.

Landscape of the immune infiltration and identification of molecular diagnostic markers associated with immune cells in patients with kidney transplantation

Rejection seriously affects the success of kidney transplantations. However, the molecular mechanisms underlying this rejection remain unclear. The GSE21374 and GSE36059 datasets were downloaded from the Gene Expression Omnibus (GEO) database. Next, the Cell-type Identification by Estimating Relative Subsets of RNA Transcripts (CIBERSORT) algorithm was used to infer the proportions of 22 immune cells. Moreover, infiltrating immune cell-related genes were identified using weighted gene co-expression network analysis (WGCNA), and enrichment analysis was conducted to observe their biological functions. Extreme Gradient Boosting (XGBoost) and Least Absolute Shrinkage and Selection Operator (LASSO) logistic regression algorithms were used to screen hub genes. Quantitative real-time PCR was conducted to verify the number of immune cells and hub gene expression levels. The rejection and non-rejection groups showed significantly different distributions (P < 0.05) of eight immune cells (B cell memory, Plasma cells, mast cells, follicular helper T cells, T CD8 cells, Macrophages M1, T Cells CD4 memory activated, and gamma delta T cells). Subsequently, CD8A, CRTAM, GBP2, WARS, and VAMP5 were screened as hub genes using the XGBoost and LASSO algorithms and could be used as diagnostic biomarkers. Finally, differential analysis and quantitative real-time PCR suggested that CD8A, CRTAM, GBP2, WARS, and VAMP5 were upregulated in rejection samples compared to non-rejection samples. The present study identified five key infiltrating immune cell-related genes (CD8A, CRTAM, GBP2,WARS, and VAMP5) involved in kidney transplant rejection, which may explain the molecular mechanism of rejection in kidney transplantation development.

Humoral and cellular immune response to AZD1222 /Covishield and BV152/Covaxin COVID-19 vaccines among adults in India

ABSTRACT Several COVID-19 vaccines were developed using different approaches to prevent both symptomatic COVID-19 cases and fatalities. The adults were vaccinated with two doses of AZD1222/Covishield (n = 77) [manufactured by Serum Institute of India Pvt Ltd] vaccine and BV152/Covaxin (n = 99) [manufactured by Bharat Biotech] vaccine. They were assessed for immune response at pre-vaccination, 1 month post first and 6 months post second dose for anti-SARS-CoV-2 IgG antibody, surrogate neutralizing antibody (NAbs), immune phenotypes, antigen specific NK, B and T cell response, their effector functionality by ELISPOT and plasma cytokine profile. Both vaccines elicited enhanced IgG antibody and Nab levels compared to the baseline. BV152/Covaxin, the whole virus inactivated vaccine exhibited higher IgG (70% vs 100%), Nab (90% vs 100%), and robust T cell (31% vs 96%) responses at 6 months post second dose compared to 1 month post first dose justifying the utility of the second dose. Detection of SARS-CoV-2 WV and S1 specific CD4+ central T cell memory response in AZD1222/Covishield vaccinee at 6 months post second dose and higher CD4+ and CD8+ naïve and central memory T cell response in BV152/Covaxin vaccinee at 1 month post first dose indicated the involvement of memory T cells. Persistent IgG and NAb responses along with IgG+B and IgG+memory B cells in AZD1222/Covishield recipients at 6 months post second dose indicated sustained immune memory response. Continued heightened IFN-γ secreting T cell response (ELISPOT) displayed by both the vaccine platforms could serve as a co correlate of protection, further to evaluation in follow up studies. Overall, our data suggest that coordinated functions of humoral and cellular branches of adaptive immunity may pave ways toward protective immunity against COVID-19.

Integrative multi-omics analysis reveals the role of tumor-associated endothelial cells and their signature in prognosis of intrahepatic cholangiocarcinoma

This study aims to investigate the interplay between tumor-associated endothelial cells (TECs) and immune cells within the tumor microenvironment (TME) and its impact on tumor prognosis. We conducted single-cell RNA sequencing (scRNA-seq) of tumor, normal, and lymph node tissues obtained from intrahepatic cholangiocarcinoma (ICC) patients to reveal the role of TECs in tumor angiogenesis and their significant heterogeneity. Meanwhile, we identified genes highly expressed in TECs and constructed TEC signatures (TEC.Sig). Next, we calculated TEC scores of samples based on TEC.Sig. Patients with higher TEC scores exhibited a higher frequency of KRAS mutations, which was associated with increased infiltration of neutrophils and immature dendritic cells (iDCs), and decreased numbers of natural killer (NK), CD4 + T, and CD8 + T effector memory (Tem) cells, indicating an inflammation-dominated immunosuppressive phenotype. In contrast, BAP1 mutations and CXCL12 overexpression showed a contrasting trend. Spatial transcriptomics analysis and histological experiments further confirmed that TECs interacted with various tumor-killing immune cells through the CXCL12/CXCR4 axis. Multiple tumor immunotherapy datasets confirmed that the TEC.Sig could predict patient responses to immunotherapy. The TEC score is a promising and reliable biomarker for predicting genetic mutations and prognosis in ICC patients. Enhancing the regulation of the CXCL12/CXCR4 signaling pathway may represent a potential novel therapeutic target for ICC treatment.