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Natural killer (NK) cells comprise one subset of the innate lymphoid cell (ILC) family. Despite reported antitumor functions of NK cells, their tangible contribution to tumor control in humans remains controversial. This is due to incomplete understanding of the NK cell states within the tumor microenvironment (TME). Here, we demonstrate that peripheral circulating NK cells differentiate down two divergent pathways within the TME, resulting in different end states. One resembles intraepithelial ILC1s (ieILC1) and possesses potent in vivo antitumor activity. The other expresses genes associated with immune hyporesponsiveness and has poor antitumor functional capacity. Interleukin-15 (IL-15) and direct contact between the tumor cells and NK cells are required for the differentiation into CD49a⁺CD103⁺ cells, resembling ieILC1s. These data explain the similarity between ieILC1s and tissue-resident NK cells, provide insight into the origin of ieILC1s, and identify the ieILC1-like cell state within the TME to be the NK cell phenotype with the greatest antitumor activity. Because the proportions of the different ILC states vary between tumors, these findings provide a resource for the clinical study of innate immune responses against tumors and the design of novel therapy.

Natural killer (NK) cells are innate immune effectors with considerable heterogeneity and potent antitumor capabilities. Intraepithelial ILC1 (ieILC1)-like NK cells, a population of cytotoxic tissue-resident innate lymphoid cells, have recently been documented in the microenvironment of head and neck squamous cell carcinomas (HNSCC) and other solid tumors. These cells have antitumor cytolytic potential and are potent producers of type 1 cytokines, including IFNγ. Here, we identify a subpopulation of ex vivo differentiated ieILC1-like NK cells that produce IL-13 upon stimulation. Functional characterization revealed that these cells co-expressed IFNγ and IL-13 while maintaining an ILC1 transcriptional signature. IL-13 was induced either upon co-culture with tumor cell lines, or in response to TGF-β and IL-15. IL-13-expressing ieILC1-like NK cells were identified among tumor infiltrating lymphocytes expanded from patient HNSCC tumors, in support of their in vivo existence in primary tumors. These data demonstrate additional heterogeneity within the ieILC1-like NK cell population than previously appreciated and highlight a unique form of ILC plasticity in which cells with clear ILC1 transcriptional profiles express a type 2 cytokine. With the known roles of IL-13 in cancer cell growth dynamics and immunoregulation, the identification of this subset within tumor microenvironments presents a potential target for therapeutic manipulation.

BackgroundNatural killer (NK) cells are innate immune cells that generate inflammatory responses important for anti-tumor responses. NK cell therapies have been increasingly explored and tested as a novel approach to cancer immunotherapy in recent years. In contrast to currently approved CAR-T technologies, NK cell therapy can potentially be administered off-the-shelf with low risk of graft-versus-host disease compared to T cells.1 Recently, we identified intraepithelial ILC1-like (ieILC1-like) NK cells as the subset of NK cells within the tumor microenvironment (TME) of head and neck squamous cell carcinoma (HNSCC) with the highest cytotoxicity.2 Here, we explore how these cells may modulate the TME and interact with other immune cells in the anti-tumor response.MethodsWe used various methods to assess the range of cytokine production by ieILC1-like NK cells in the context of cancer. Co-culture of activated conventional NK (cNK) cells (CD56+CD49a+CD103-CD3-CD14-CD19-CD20-) or ieILC1-like NK cells (CD56+CD49a+CD103+CD3-CD14-CD19-CD20-) with K562 chronic myelogenous leukemia (CML) cells was performed and cytokines were analyzed via Luminex immunoassay of cultured supernatants, evaluating a panel of 80 cytokines and chemokines. Validation was performed by intracellular flow cytometry of the cells in this co-culture system.ResultsLuminex analysis revealed that the co-culture of ieILC1-like NK cells with K562 cells resulted in elevated levels of CXCL10 in cultured supernatants compared to that of K562 cells alone, ieILC1-like NK cells alone, or cNKs co-cultured with K562. Similarly, cultured supernatants of ieILC1-like NK cells with K562 had elevated levels of IL-13 compared to that of K562 alone, ieILC1-like NK cells alone, or cNKs co-cultured with K562. To determine the source of these cytokines, we performed intracellular flow cytometry. We found that the K562 cells were the primary source of CXCL10 when co-cultured with ieILC1-like NK cells. Unexpectedly, however, IL-13 was uniquely produced by a subset of IFN-gamma-producing ieILC1-like NK cells following stimulation by tumor cells.ConclusionsThe ieILC1-like NK cells induce CXCL10 production by K562, most likely via IFN-gamma. CXCL10 is a pro-inflammatory chemokine involved in immune cell recruitment to the TME.3 Unexpectedly, we identified a subset of ieILC1-like NK cells that produce IL-13, a Th2-type cytokine that has the potential to dampen anti-tumor immune responses and possibly promote tumor survival and proliferation.4 Thus, the CD49a+CD103+ ieILC1-like NK cell population is heterogeneous, and further studies to understand the functional differences of these distinct subsets are necessary.AcknowledgementsWe thank the Stanford Human Immune Monitoring Center for their assistance with the Luminex assays involved in this project.ReferencesWolf NK, Kissiov DU, Raulet DH. Roles of natural killer cells in immunity to cancer, and applications to immunotherapy. Nat Rev Immunol. 2022;23:90–105.Moreno-Nieves UY, Tay JK, Saumyaa S, et al. Landscape of innate lymphoid cells in human head and neck cancer reveals divergent NK cell states in the tumor microenvironment. Proc Natl Acad Sci U S A. 2021;118(28):e2101169118.Liu M, Guo S, Stiles JK. The emerging role of CXCL10 in cancer (Review). Oncol Lett. 2011 Jul;2(4):583–589Terabe M, Park JM, Berzofsky JA. Role of IL-13 in regulation of anti-tumor immunity and tumor growth. Cancer Immunol Immunother. 2004;53(2):79–85.

ACTL6a is an essential component of SWI/SNF and expressed on the chromosome 3q26 cytoband, which is amplified in head and neck squamous cell carcinomas (HNSCC). While ACTL6A is emerging as an oncogene, its role as a treatment target and mechanisms of transcription factor induction remain unknown. Here, we show that ACTL6A expression is a mediator of the Warburg effect, with ACTL6A knockdown inducing mitochondrial dependency and significantly decreasing levels of aerobic glycolysis. These effects lead to near complete attenuation of hypoxic cell growth by blunting induction of HIF1α and HIF2α protein expression. They also sensitize treatment resistant HNSCC cells to the tumor killing effects of the complex I inhibitor IACS-010759 . Using ATAC-seq, we identify ACTL6A as a mediator of chromatin accessibility of AP-1 transcription factor sites and find that it regulates upstream MAPK signaling through induction of Ras and Galectin-1. These effects sensitize ACTL6A over-expressing cells to inhibition of glycolysis by MEK inhibitors. Our results link SWI/SNF subunit amplification with potentiation of MAPK signaling in HNSCC and provide a novel mechanism by which cancer cells drive aerobic glycolysis and reduce mitochondrial dependency. We leverage these findings to propose treatment strategies for hypoxic tumors with SWI/SNF subunit amplifications.

Natural killer (NK) cell-based immunotherapies represent a promising avenue for cancer treatment due to their ability to eliminate cancer cells independently of antigen presentation and potential for \"off-the-shelf\" use. However, the molecular determinants governing tumor cell susceptibility to NK cell-mediated cytotoxicity remain incompletely understood. Here we employed CRISPR activation (CRISPRa) screening to systematically identify cancer cell surface regulators of NK cell killing across multiple cancer types. Using a comprehensive surfaceome-focused library, we screened human and murine cancer cell lines co-cultured with NK cells, identifying both known and novel ligands that modulate NK cell cytotoxicity. Our screens revealed established factors including CD43 (encoded by ), while uncovering previously uncharacterized regulators such as CD44, PDPN, and Siglec-1/CD169. Validation through complementary cDNA overexpression and genetic knockout approaches confirmed that disruption of CD43, CD44, PDPN, and Siglec-1 significantly altered cancer cell susceptibility to NK killing both and in humanized mouse models. Analysis of clinical datasets show that expression of identified factors correlates with patient survival outcomes in an NK-context dependent manner supporting their therapeutic relevance. Most notably, our mechanistic studies demonstrate that CD43-mediated NK cell resistance operates independently of its previously proposed interaction with Siglec-7 on NK cells. Furthermore, we find that targeting CD43 on either NK cells or engineered T cells substantially enhances their cytotoxic activity against leukemia cell lines. These results establish gain-of-function screening as a powerful approach for discovering immunoregulatory surface proteins and identify multiple promising targets for enhancing NK cell-based cancer immunotherapies.

Modern science advances fastest when thought meets action. LabOS represents the first AI co-scientist that unites computational reasoning with physical experimentation through multimodal perception, self-evolving agents, and Extended-Reality(XR)-enabled human-AI collaboration. By connecting multi-model AI agents, smart glasses, and robots, LabOS allows AI to see what scientists see, understand experimental context, and assist in real-time execution. Across applications -- from cancer immunotherapy target discovery to stem-cell engineering and material science -- LabOS shows that AI can move beyond computational design to participation, turning the laboratory into an intelligent, collaborative environment where human and machine discovery evolve together.

Modern science advances fastest when thought meets action. LabOS represents the first AI co-scientist that unites computational reasoning with physical experimentation through multimodal perception, self-evolving agents, and XR-enabled, embodied human-AI collaboration. To empower agentic AI with embodied intelligence, we built LabSuperVision, the first vision-language-model (VLM) benchmark spanning biomedical and materials science laboratories, designed to evaluate scientific perception and reasoning. This endowed LabOS with visual reasoning capabilities that surpass those of general-purpose models on laboratory-specific tasks. By connecting multi-model AI agents, smart glasses, and human-AI-robot collaboration, LabOS allows AI to see what scientists see, understand experimental context, and participate in real-time execution through immersive XR interaction and robotic autonomation. Across applications-from cancer immunotherapy target discovery to cell engineering-LabOS shows that AI can move beyond computational design to participation, turning the laboratory into an intelligent, collaborative environment where human and machine discovery evolve together.

The pathogenicity in Candida spp was attributed by several virulence factors such as production of tissue damaging extracellular enzymes, germ tube formation, hyphal morphogenesis and establishment of drug resistant biofilm. The objective of present study was to investigate the effects of silver nanoparticles (AgNPs) on growth, cell morphology and key virulence attributes of Candida species. AgNPs were synthesized by the using seed extract of (Sc), and were characterized by UV-Vis spectrophotometer, Fourier-transform infrared spectroscopy (FTIR), scanning electron microscopy (SEM), energy-dispersive X-ray (EDX), and transmission electron microscopy (TEM). ScAgNPs were used to evaluate their antifungal and antibacterial activity as well as their potent inhibitory effects on germ tube and biofilm formation and extracellular enzymes viz. phospholipases, proteinases, lipases and hemolysin secreted by spp. The MICs values of ScAgNPs were ranged from 0.125-0.250 mg/ml, whereas the MBCs and MFCs were 0.250 and 0.500 mg/ml, respectively. ScAgNPs significantly inhibit the production of phospholipases by 82.2, 75.7, 78.7, 62.5, and 65.8%; proteinases by 82.0, 72.0, 77.5, 67.0, and 83.7%; lipase by 69.4, 58.8, 60.0, 42.9, and 65.0%; and hemolysin by 62.8, 69.7, 67.2, 73.1, and 70.2% in , , , and , respectively, at 500 μg/ml. ScAgNPs inhibit germ tube formation in C. albicans up to 97.1% at 0.25 mg/ml. LIVE/DEAD staining results showed that ScAgNPs almost completely inhibit biofilm formation in C. albicans. TEM analysis shows that ScAgNPs not only anchored onto the cell surface but also penetrated and accumulated in the cytoplasm that causes severe damage to the cell wall and cytoplasmic membrane. To summarize, the biosynthesized ScAgNPs strongly suppressed the multiplication, germ tube and biofilm formation and most importantly secretion of hydrolytic enzymes (viz. phospholipases, proteinases, lipases and hemolysin) by Candia spp. The present research work open several avenues of further study, such as to explore the molecular mechanism of inhibition of germ tubes and biofilm formation and suppression of production of various hydrolytic enzymes by Candida spp.

A biomarker is any measurable biological moiety that can be assessed and measured as a potential index of either normal or abnormal pathophysiology or pharmacological responses to some treatment regimen. Every tissue in the body has a distinct biomolecular make-up, which is known as its biomarkers, which possess particular features, viz., the levels or activities (the ability of a gene or protein to carry out a particular body function) of a gene, protein, or other biomolecules. A biomarker refers to some feature that can be objectively quantified by various biochemical samples and evaluates the exposure of an organism to normal or pathological procedures or their response to some drug interventions. An in-depth and comprehensive realization of the significance of these biomarkers becomes quite important for the efficient diagnosis of diseases and for providing the appropriate directions in case of multiple drug choices being presently available, which can benefit any patient. Presently, advancements in omics technologies have opened up new possibilities to obtain novel biomarkers of different types, employing genomic strategies, epigenetics, metabolomics, transcriptomics, lipid-based analysis, protein studies, etc. Particular biomarkers for specific diseases, their prognostic capabilities, and responses to therapeutic paradigms have been applied for screening of various normal healthy, as well as diseased, tissue or serum samples, and act as appreciable tools in pharmacology and therapeutics, etc. In this review, we have summarized various biomarker types, their classification, and monitoring and detection methods and strategies. Various analytical techniques and approaches of biomarkers have also been described along with various clinically applicable biomarker sensing techniques which have been developed in the recent past. A section has also been dedicated to the latest trends in the formulation and designing of nanotechnology-based biomarker sensing and detection developments in this field.

There will be a dearth of electrical energy in the prospective world due to exponential increase in electrical energy demand of rapidly growing world population. With the development of internet-of-things (IoT), more smart devices will be integrated into residential buildings in smart cities that actively participate in electricity market via demand response (DR) programs to efficiently manage energy in order to meet this increasing energy demand. Thus, with this incitement, an energy management strategy using price-based DR program is developed for IoT-enabled residential buildings. We propose a wind-driven bacterial foraging algorithm (WBFA), which is a hybrid of wind-driven optimization (WDO) and bacterial foraging optimization (BFO) algorithms. Subsequently, we devised a strategy based on our proposed WBFA to systematically manage the power usage of IoT-enabled residential building smart appliances by scheduling to alleviate peak-to-average ratio (PAR), minimize cost of electricity, and maximize user comfort (UC). This increases effective energy utilization, which in turn increases the sustainability of IoT-enabled residential buildings in smart cities. The WBFA-based strategy automatically responds to price-based DR programs to combat the major problem of the DR programs, which is the limitation of consumer’s knowledge to respond upon receiving DR signals. To endorse productiveness and effectiveness of the proposed WBFA-based strategy, substantial simulations are carried out. Furthermore, the proposed WBFA-based strategy is compared with benchmark strategies including binary particle swarm optimization (BPSO) algorithm, genetic algorithm (GA), genetic wind driven optimization (GWDO) algorithm, and genetic binary particle swarm optimization (GBPSO) algorithm in terms of energy consumption, cost of electricity, PAR, and UC. Simulation results show that the proposed WBFA-based strategy outperforms the benchmark strategies in terms of performance metrics.