The Female-Biased General Odorant Binding Protein 2 of Semiothisa cinerearia Displays Binding Affinity for Biologically Active Host Plant Volatiles.

Herbivorous insects rely on volatile chemical cues from host plants to locate food sources and oviposition sites. General odorant binding proteins (GOBPs) are believed to be involved in the detection of host plant volatiles. In the present study, one GOBP gene, ScinGOBP2, was cloned from the antennae of adult Semiothisa cinerearia. Reverse-transcription PCR and real-time quantitative PCR analysis revealed that the expression of ScinGOBP2 was strongly biased towards the female antennae. Fluorescence-based competitive binding assays revealed that 8 of the 27 host plant volatiles, including geranyl acetone, decanal, cis-3-hexenyl n-valerate, cis-3-hexenyl butyrate, 1-nonene, dipentene, α-pinene and ß-pinene, bound to ScinGOBP2 (KD = 2.21-14.94 µM). The electrical activities of all eight ScinGOBP2 ligands were confirmed using electroantennography. Furthermore, oviposition preference experiments showed that eight host volatiles, such as decanal, cis-3-hexenyl n-valerate, cis-3-hexenyl butyrate, and α-pinene, had an attractive effect on female S. cinerearia, whereas geranyl acetone, 1-nonene, ß-pinene, and dipentene inhibited oviposition in females. Consequently, it can be postulated that ScinGOBP2 may be implicated in the perception of host plant volatiles and that ScinGOBP2 ligands represent significant semiochemicals mediating the interactions between plants and S. cinerearia. This insight could facilitate the development of a chemical ecology-based approach for the management of S. cinerearia.

Lanthanum-modified tobermorite synthesized from fly ash for efficient phosphate removal.

Phosphate removal from water by lanthanum-modified tobermorite synthesized from fly ash (LTFA) with different lanthanum concentrations was studied. LTFA samples were characterized by X-ray diffraction, Fourier transform infrared spectroscopy, scanning electron microscopy, and Brunauer‒Emmett‒Teller specific surface area analysis. The results showed that the LTFA samples were mainly composed of mesoporous tobermorite-11 Å, and LTFA1 with a lanthanum concentration of 0.15 M had a high specific surface area (83.82 m2/g) and pore volume (0.6778 cm3/g). The phosphate adsorption capacities of LTFA samples were highest at pH 3 and gradually decreased with increasing pH. The phosphate adsorption kinetics data on LTFA samples were most accurately described by the Elovich model. The adsorption isotherms were in the strongest agreement with the Temkin model, and LTFA1 showed the highest phosphate adsorption capacity (282.51 mg P/g), which was higher than that of most other lanthanum-modified adsorbents. LTFA1 presented highly selective adsorption of phosphate with other coexisting ions (HCO3-, Cl-, SO42-, and NO3-). In addition, phosphate was adsorbed onto LTFA samples by forming inner-sphere phosphate complexes and amorphous lanthanum phosphate. This study provides technical support for development of efficient fly ash-based phosphate adsorbents.

TIE1 promotes cervical cancer progression via Basigin-matrix metalloproteinase axis.

Background: Tyrosine kinase with immunoglobulin and EGF-like domains 1 (TIE1) is known as an orphan receptor prominently expressed in endothelial cells and participates in angiogenesis by regulating TIE2 activity. Our previous study demonstrated elevated TIE1 expression in cervical cancer cells. However, the role of TIE1 in cervical cancer progression, metastasis and treatment remains elusive. Methods: Immunohistochemistry staining for TIE1 and Basigin was performed in 135 human cervical cancer tissues. Overexpressing vectors and siRNAs were used to manipulate gene expression in tumor cells. Colony formation, wound healing, and transwell assays were used to assess cervical cancer cell proliferation and migration in vitro. Subcutaneous xenograft tumor and lung metastasis mouse models were established to examine tumor growth and metastasis. Co-Immunoprecipitation and Mass Spectrometry were applied to explore the proteins binding to TIE1. Immunoprecipitation and immunofluorescence staining were used to verify the interaction between TIE1 and Basigin. Cycloheximide chase assay and MG132 treatment were conducted to analyze protein stability. Results: High TIE1 expression was associated with poor survival in cervical cancer patients. TIE1 overexpression promoted the proliferation, migration and invasion of cervical cancer cells in vitro, as well as tumor growth and metastasis in vivo. In addition, Basigin, a transmembrane glycoprotein, was identified as a TIE1 binding protein, suggesting a pivotal role in matrix metalloproteinase regulation, angiogenesis, cell adhesion, and immune responses. Knockdown of Basigin or treatment with the Basigin inhibitor AC-73 reversed the tumor-promoting effect of TIE1 in vitro and in vivo. Furthermore, we found that TIE1 was able to interact with and stabilize the Basigin protein and stimulate the Basigin-matrix metalloproteinase axis. Conclusion: TIE1 expression in cervical cells exerts a tumor-promoting effect, which is at least in part dependent on its interaction with Basigin. These findings have revealed a TIE2-independent mechanism of TIE1, which may provide a new biomarker for cervical cancer progression, and a potential therapeutic target for the treatment of cervical cancer patients.

System-level time computation and representation in the suprachiasmatic nucleus revealed by large-scale calcium imaging and machine learning.

The suprachiasmatic nucleus (SCN) is the mammalian central circadian pacemaker with heterogeneous neurons acting in concert while each neuron harbors a self-sustained molecular clockwork. Nevertheless, how system-level SCN signals encode time of the day remains enigmatic. Here we show that population-level Ca2+ signals predict hourly time, via a group decision-making mechanism coupled with a spatially modular time feature representation in the SCN. Specifically, we developed a high-speed dual-view two-photon microscope for volumetric Ca2+ imaging of up to 9000 GABAergic neurons in adult SCN slices, and leveraged machine learning methods to capture emergent properties from multiscale Ca2+ signals as a whole. We achieved hourly time prediction by polling random cohorts of SCN neurons, reaching 99.0% accuracy at a cohort size of 900. Further, we revealed that functional neuron subtypes identified by contrastive learning tend to aggregate separately in the SCN space, giving rise to bilaterally symmetrical ripple-like modular patterns. Individual modules represent distinctive time features, such that a module-specifically learned time predictor can also accurately decode hourly time from random polling of the same module. These findings open a new paradigm in deciphering the design principle of the biological clock at the system level.

Dual-constrained physics-enhanced untrained neural network for lensless imaging.

An untrained neural network (UNN) paves a new way to realize lensless imaging from single-frame intensity data. Based on the physics engine, such methods utilize the smoothness property of a convolutional kernel and provide an iterative self-supervised learning framework to release the needs of an end-to-end training scheme with a large dataset. However, the intrinsic overfitting problem of UNN is a challenging issue for stable and robust reconstruction. To address it, we model the phase retrieval problem into a dual-constrained untrained network, in which a phase-amplitude alternating optimization framework is designed to split the intensity-to-phase problem into two tasks: phase and amplitude optimization. In the process of phase optimization, we combine a deep image prior with a total variation prior to retrain the loss function for the phase update. In the process of amplitude optimization, a total variation denoising-based Wirtinger gradient descent method is constructed to form an amplitude constraint. Alternative iterations of the two tasks result in high-performance wavefield reconstruction. Experimental results demonstrate the superiority of our method.

Interface-Targeting Carrier-Catalytic Integrated Design Contributing to Lithium Dihalide-Rich SEI toward High Interface Stability for Long-Life Solid-State Lithium-Metal Batteries.

The generation of solid electrolyte interphase (SEI) largely determines the comprehensive performance of all-solid-state batteries. Herein, a novel "carrier-catalytic" integrated design is strategically exploited to in situ construct a stable LiF-LiBr rich SEI by improving the electron transfer kinetics to accelerate the bond-breaking dynamics. Specifically, the high electron transport capacity of Br-TPOM skeleton increases the polarity of C-Br, thus promoting the generation of LiBr. Then, the enhancement of electron transfer kinetics further promotes the fracture of C-F from TFSI- to form LiF. Finally, the stable and homogeneous artificial-SEI with enriched lithium dihalide is constructed through the in situ co-growth mechanism of LiF and LiBr, which facilitatse the Li-ion transport kinetics and regulates the lithium deposition behavior. Impressively, the PEO-Br-TPOM paired with LiFePO4 delivers ultra-long cycling stability over 1000 cycles with 81 % capacity retention at 1 C while the pouch cells possess 88 % superior capacity retention after 550 cycles with initial discharge capacity of 145 mAh g-1at 0.2 C in the absence of external pressure. Even under stringent conditions, the practical pouch cells possess the practical capacity with stable electric quantities plateau in 30 cycles demonstrates its application potential in energy storage field.

Failure Behavior and Fracture Evolution Mechanism of Coal with Fissures around Holes.

The fracture of coal is the main channel of gas flow and an important factor affecting the stability and efficiency of gas drainage boreholes. The coal structure, the development of hole cracks, and the degree of deformation are different. It affects the strength and mechanical deformation characteristics of coal to a great extent. In order to investigate the law of fracture evolution around the borehole of fractured coal, uniaxial and triaxial compression tests of raw coal samples have been carried out. The stress field evolution characteristics of fractured coal under compression were analyzed by Particle Flow Code (PFC2D). The strength, deformation, and fracture evolution behavior of fractured coal around boreholes under different confining pressures were studied. The results show that the compressive strength and fracture morphology evolution characteristics of coal around the hole are obviously related to the confining pressure and fracture occurrence of raw coal. The borehole structure itself has an important influence on the distribution location of the shear failure zone of the fracture around the hole, and its influence degree increases with the decrease of borehole confining pressure. During the deformation of coal with cracks around the hole, the initiation, propagation, and union behavior of cracks are related to the crack angle ß. The cracks with ß 0 and 180° are most easily closed during compression and the cracks with ß 90° have little effect on the crack propagation zone. When the crack angle ß is 45°, it is most easy to sprout and expand at the end; when the coal is compressed to the ultimate strength, the increase rate of the tensile crack increases, and the polymerization and combination behavior of the crack is more obvious. The evolution cloud map of the stress field can better reflect the evolution characteristics of fracture development, expansion, and fracture in the process of coal loading. Studying the failure behavior and fracture evolution mechanism of the coal around the hole can better predict and control the gas migration and extraction effect, which is of great significance to prevent the occurrence of gas accidents.

Ultra-low noise front-end design for smart optical sensors with high sensitivity and wide dynamic range.

Ultra-low noise is a critical component in the design of high-precision sensor front-ends. We introduced differential phase-sensitive detection (d-PSD) to mitigate both multiplicative and additive noise in optical sensors, aiming for an enhanced performance and cost-effectiveness. The d-PSD combines a capacitive transimpedance amplifier (C-TIA), a delta-sigma analog-to-digital converter (ΔΣ-ADC), and a software-based lock-in amplifier (s-LIA). The first two components utilize the DDC112 (a dual current input 20-bit ADC) for a minimal analog channel length, thus reducing noise efficiently, while the latter employs a cost-effective 32-bit microcontroller unit (MCU), the HC32F460. This approach was successfully implemented as the front-end for a smart optical sensor. Testing indicated that the sensor achieved an equivalent current noise level of 0.6 nA/√Hz, primarily attributed to the light source driver rather than the sensor's front-end circuit. The sensor exhibited an exceptional performance, with a 3σ measurement precision of 5.4 × 10-4 over a 1-second integration time and a dynamic range of 100 dB, leveraging the proposed method and design. Furthermore, the front-end of the sensor boasts a compact size, low power consumption, and affordability, making it an ideal, versatile solution for ultra-high precision, smart optical sensors.

Synergistic role of activated CD4+ memory T cells and CXCL13 in augmenting cancer immunotherapy efficacy.

The development of immune checkpoint inhibitors (ICIs) has significantly advanced cancer treatment. However, their efficacy is not consistent across all patients, underscoring the need for personalized approaches. In this study, we examined the relationship between activated CD4+ memory T cell expression and ICI responsiveness. A notable correlation was observed between increased activated CD4+ memory T cell expression and better patient survival in various cohorts. Additionally, the chemokine CXCL13 was identified as a potential prognostic biomarker, with higher expression levels associated with improved outcomes. Further analysis highlighted CXCL13's role in influencing the Tumor Microenvironment, emphasizing its relevance in tumor immunity. Using these findings, we developed a deep learning model by the Multi-Layer Aggregation Graph Neural Network method. This model exhibited promise in predicting ICI treatment efficacy, suggesting its potential application in clinical practice.

Case report: diagnosis and treatment of advanced high-grade serous ovarian carcinoma aided by 68Ga-FAPI PET/MR scan.

High-grade serous ovarian cancer (HGSOC) is the most common type of epithelial ovarian cancer with insidious onset, rapid growth, and invasive spread. Here, we reported the diagnosis and treatment of a 53-year-old patient with a history of hysterectomy aided by the 68Ga-FAPI PET/MR scan. The patient was first presented to the local hospital with a lump on the left side of the neck with a biopsy suggesting metastatic cancer. Pelvic ultrasonography revealed two irregular masses. After admission, tumor markers, pathology consultation of the biopsy, and the 68Ga-FAPI PET/MR scan were administered. The biopsy of the lump suggested poorly differentiated adenocarcinoma and CA125 was elevated at 530.6 U/ml. The 68Ga-FAPI PET/MR scan showed several abnormal lymph nodes and two soft tissue masses with borders of dispersed restriction displaying internally uneven signals depicted by slightly elongated T1 and T2 signals within the pelvic cavity suggesting that pelvic mass could be the primary lesion. The patient received cytoreductive surgery including bilateral adnexectomy, omentectomy, and appendectomy. Post-surgical pathology suggested left and right HGSOC with left fallopian tube invasion. The patient completed six courses of first-line chemotherapy and remained progression-free for 14 months up to date. To conclude, 68Ga-FAPI PET/MR aids in primary tumor determination and tumor burden assessment and provides a guide for the management of late-stage HGSOC patients.

Glutamine metabolism prognostic index predicts tumour microenvironment characteristics and therapeutic efficacy in ovarian cancer.

Mounting evidence has highlighted the multifunctional characteristics of glutamine metabolism (GM) in cancer initiation, progression and therapeutic regimens. However, the overall role of GM in the tumour microenvironment (TME), clinical stratification and therapeutic efficacy in patients with ovarian cancer (OC) has not been fully elucidated. Here, three distinct GM clusters were identified and exhibited different prognostic values, biological functions and immune infiltration in TME. Subsequently, glutamine metabolism prognostic index (GMPI) was constructed as a new scoring model to quantify the GM subtypes and was verified as an independent predictor of OC. Patients with low-GMPI exhibited favourable survival outcomes, lower enrichment of several oncogenic pathways, less immunosuppressive cell infiltration and better immunotherapy responses. Single-cell sequencing analysis revealed a unique evolutionary trajectory of OC cells from high-GMPI to low-GMPI, and OC cells with different GMPI might communicate with distinct cell populations through ligand-receptor interactions. Critically, the therapeutic efficacy of several drug candidates was validated based on patient-derived organoids (PDOs). The proposed GMPI could serve as a reliable signature for predicting patient prognosis and contribute to optimising therapeutic strategies for OC.

The sirtuin-associated human senescence program converges on the activation of placenta-specific gene PAPPA.

Sirtuins are pro-longevity genes with chromatin modulation potential, but how these properties are connected is not well understood. Here, we generated a panel of isogeneic human stem cell lines with SIRT1-SIRT7 knockouts and found that any sirtuin deficiency leads to accelerated cellular senescence. Through large-scale epigenomic analyses, we show how sirtuin deficiency alters genome organization and that genomic regions sensitive to sirtuin deficiency are preferentially enriched in active enhancers, thereby promoting interactions within topologically associated domains and the formation of de novo enhancer-promoter loops. In all sirtuin-deficient human stem cell lines, we found that chromatin contacts are rewired to promote aberrant activation of the placenta-specific gene PAPPA, which controls the pro-senescence effects associated with sirtuin deficiency and serves as a potential aging biomarker. Based on our survey of the 3D chromatin architecture, we established connections between sirtuins and potential target genes, thereby informing the development of strategies for aging interventions.

Unraveling the role of M1 macrophage and CXCL9 in predicting immune checkpoint inhibitor efficacy through multicohort analysis and single-cell RNA sequencing.

The exact function of M1 macrophages and CXCL9 in forecasting the effectiveness of immune checkpoint inhibitors (ICIs) is still not thoroughly investigated. We investigated the potential of M1 macrophage and C-X-C Motif Chemokine Ligand 9 (CXCL9) as predictive markers for ICI efficacy, employing a comprehensive approach integrating multicohort analysis and single-cell RNA sequencing. A significant correlation between high M1 macrophage and improved overall survival (OS) and objective response rate (ORR) was found. M1 macrophage expression was most pronounced in the immune-inflamed phenotype, aligning with increased expression of immune checkpoints. Furthermore, CXCL9 was identified as a key marker gene that positively correlated with M1 macrophage and response to ICIs, while also exhibiting associations with immune-related pathways and immune cell infiltration. Additionally, through exploring RNA epigenetic modifications, we identified Apolipoprotein B MRNA Editing Enzyme Catalytic Subunit 3G (APOBEC3G) as linked to ICI response, with high expression correlating with improved OS and immune-related pathways. Moreover, a novel model based on M1 macrophage, CXCL9, and APOBEC3G-related genes was developed using multi-level attention graph neural network, which showed promising predictive ability for ORR. This study illuminates the pivotal contributions of M1 macrophages and CXCL9 in shaping an immune-active microenvironment, correlating with enhanced ICI efficacy. The combination of M1 macrophage, CXCL9, and APOBEC3G provides a novel model for predicting clinical outcomes of ICI therapy, facilitating personalized immunotherapy.

A Trisulfide Bond Containing Biodegradable Polymer Delivering Pt(IV) Prodrugs to Deplete Glutathione and Donate H2S to Boost Chemotherapy and Antitumor Immunity.

The clinical application of cisplatin (CisPt) is limited by its dose-dependent toxicity. To overcome this, we developed reduction-responsive nanoparticles (NP(3S)s) for the targeted delivery of a platinum(IV) (Pt(IV)) prodrug to improve efficacy and reduce the toxicity. NP(3S)s could release Pt(II) and hydrogen sulfide (H2S) upon encountering intracellular glutathione, leading to potent anticancer effects. Notably, NP(3S)s induced DNA damage and activated the STING pathway, which is a known promoter for T cell activation. Comparative RNA profiling revealed that NP(3S)s outperformed CisPt in enhancing T cell immunity, antitumor immunity, and oxidative stress pathways. In vivo experiments showed that NP(3S)s accumulated in tumors, promoting CD8+ T cell infiltration and boosting antitumor immunity. Furthermore, NP(3S)s exhibited robust in vivo anticancer efficacy while minimizing the CisPt-induced liver toxicity. Overall, the results indicate NP(3S)s hold great promise for clinical translation due to their low toxicity profile and potent anticancer activity.

[Research progress of lower extremity alignment in total knee arthroplasty].

Knee osteoarthritis has become one of the common diseases of the elderly, total knee arthroplasty （TKA） is the most effective treatment for end-stage knee osteoarthritis at present. In TKA, the effective restoration of the lower extremity alignment is one of the key factors for the success of the operation, which greatly affects the postoperative clinical effect and prosthesis survival rate of patients. Mechanical alignment is a TKA alignment method which is first proposed, recognized and widely used in TKA. In recent years, with the in-depth research on the lower limb alignment and the rapid development of computer technology, the alignment technology in TKA has realized the transformation from "unified" to "individualized", two-dimensional to three-dimensional. New alignment methods, such as adjusted mechanical alignment, anatomic alignment, kinematic alignment, inverse kinematic alignment, restricted kinematic alignment and functional alignment have been proposed to provide surgeons with more choices. However, there is no conclusion on which alignment method is the best choice. This paper summarizes the current research status, advantages and disadvantages of various alignment methods in TKA, and aims to provide some reference for the selection of alignment methods in TKA.

Materials descriptors of machine learning to boost development of lithium-ion batteries.

Traditional methods for developing new materials are no longer sufficient to meet the needs of the human energy transition. Machine learning (ML) artificial intelligence (AI) and advancements have caused materials scientists to realize that using AI/ML to accelerate the development of new materials for batteries is a powerful potential tool. Although the use of certain fixed properties of materials as descriptors to act as a bridge between the two separate disciplines of AI and materials chemistry has been widely investigated, many of the descriptors lack universality and accuracy due to a lack of understanding of the mechanisms by which AI/ML operates. Therefore, understanding the underlying operational mechanisms and learning logic of AI/ML has become mandatory for materials scientists to develop more accurate descriptors. To address those challenges, this paper reviews previous work on AI, machine learning and materials descriptors and introduces the basic logic of AI and machine learning to help materials developers understand their operational mechanisms. Meanwhile, the paper also compares the accuracy of different descriptors and their advantages and disadvantages and highlights the great potential value of accurate descriptors in AI/machine learning applications for battery research, as well as the challenges of developing accurate material descriptors.

PBRM1 presents a potential ctDNA marker to monitor response to neoadjuvant chemotherapy in cervical cancer.

Neoadjuvant chemotherapy (NACT) is a therapeutic option for locally advanced cervical cancer (LACC) patients. This study was aimed to identify potential liquid biopsy biomarkers to monitor the NACT response. Through targeted next-generation sequencing (NGS) analysis of circulating tumor DNA (ctDNA) and tumor tissue DNA (ttDNA) taken from LACC patients undergoing platinum-based NACT, 64 genes with mutations emerge during NACT in the non-responders but none in the responders. Among them, the PBRM1, SETD2, and ROS1 mutations were frequently detected in the ctDNA and ttDNA of the non-responders, and mutant PBRM1 was associated with poorer survival of patients. In vitro, PBRM1 knockdown promoted resistance to cisplatin through boosting STAT3 signaling in cervical cancer cells, while it sensitized tumor cells to poly-ADP-ribose-polymerase inhibitor olaparib. These findings suggest that mutant PBRM1 is a potential ctDNA marker of emerging resistance to NACT and of increased sensitivity to olaparib, which warrants further clinical validation.

False recall is associated with larger caudate in males but not in females.

After learning semantically related words, some people are more likely than others to incorrectly recall unstudied but semantically related lures (i.e., Deese-Roediger-McDermott [DRM] false recall). Previous studies have suggested that neural activity in subcortical regions (e.g., the caudate) is involved in false memory, and that there may be sex differences in the neural basis of false memory. However, sex-specific associations between subcortical volumes and false memory are not well understood. This study investigated whether sex modulates the associations between subcortical volumes and DRM false recall in 400 healthy college students. Volumes of subcortical regions including the caudate, accumbens, amygdala, hippocampus, pallidum, putamen and thalamus were obtained from structural magnetic resonance images and measured using FreeSurfer. The results showed that males had lower true and false recall but larger subcortical volumes than females. Interestingly, higher false recall was associated with a larger caudate in males, but not in females. This association was significant after controlling for age and intracranial volume. This study provides new evidence on the neural basis of false recall. It suggests that the caudate plays a role in false recall in young men, and that future studies of the neural correlates of false memory should consider sex differences.

Establishment and validation of a nomogram predicting the risk of deep vein thrombosis before total knee arthroplasty.

PURPOSE: This study aimed to analyze the independent risk factors contributing to preoperative DVT in TKA and constructed a predictive nomogram to accurately evaluate its occurrence based on these factors. METHODS: The study encompassed 496 patients who underwent total knee arthroplasty at our hospital between June 2022 and June 2023. The dataset was randomly divided into a training set (n = 348) and a validation set (n = 148) in a 7:3 ratio. The least absolute shrinkage and selection operator (LASSO) and multivariate logistic regression analysis were used to screen the predictors of preoperative DVT occurrence in TKA and construct a nomogram. The performance of the predictive models was evaluated using the concordance index (C-index), calibration curves, and the receiver operating characteristic (ROC) curves. Decision curve analysis was used to analyze the clinical applicability of nomogram. RESULTS: A total of 496 patients who underwent TKA were included in this study, of which 28 patients were examined for lower extremity DVT preoperatively. Platelet crit, Platelet distribution width, Procalcitonin, prothrombin time, and D-dimer were predictors of preoperative occurrence of lower extremity DVT in the nomograms of the TKA patients. In addition, the areas under the curve of the ROC of the training and validation sets were 0.935 (95%CI: 0.880-0.990) and 0.854 (95%CI: 0.697-1.000), and the C-indices of the two sets were 0.919 (95%CI: 0.860-0.978) and 0.900 (95%CI: 0.791-1.009). The nomogram demonstrated precise risk prediction of preoperative DVT occurrence in TKA as confirmed by the calibration curve and decision curve analysis. CONCLUSIONS: This Nomogram demonstrates great differentiation, calibration and clinical validity. By assessing individual risk, clinicians can promptly detect the onset of DVT, facilitating additional life monitoring and necessary medical interventions to prevent the progression of DVT effectively.

Inhibition of iRhom1 by CD44-targeting nanocarrier for improved cancer immunochemotherapy.

The multifaceted chemo-immune resistance is the principal barrier to achieving cure in cancer patients. Identifying a target that is critically involved in chemo-immune-resistance represents an attractive strategy to improve cancer treatment. iRhom1 plays a role in cancer cell proliferation and its expression is negatively correlated with immune cell infiltration. Here we show that iRhom1 decreases chemotherapy sensitivity by regulating the MAPK14-HSP27 axis. In addition, iRhom1 inhibits the cytotoxic T-cell response by reducing the stability of ERAP1 protein and the ERAP1-mediated antigen processing and presentation. To facilitate the therapeutic translation of these findings, we develop a biodegradable nanocarrier that is effective in codelivery of iRhom pre-siRNA (pre-siiRhom) and chemotherapeutic drugs. This nanocarrier is effective in tumor targeting and penetration through both enhanced permeability and retention effect and CD44-mediated transcytosis in tumor endothelial cells as well as tumor cells. Inhibition of iRhom1 further facilitates tumor targeting and uptake through inhibition of CD44 cleavage. Co-delivery of pre-siiRhom and a chemotherapy agent leads to enhanced antitumor efficacy and activated tumor immune microenvironment in multiple cancer models in female mice. Targeting iRhom1 together with chemotherapy could represent a strategy to overcome chemo-immune resistance in cancer treatment.