ZHX2 mediates proteasome inhibitor resistance via regulating nuclear translocation of NF‐κB in multiple myeloma

Abstract Background Multiple myeloma (MM) is an incurable hematological malignancy. Although proteasome inhibitors and immunomodulators have significantly improved patient outcomes, some patients respond poorly to treatment and almost all patients will relapse. Mechanisms of proteasome inhibitor resistance in multiple myeloma have not been fully elucidated. ZHX2 is a transcription regulator degraded via proteasome and presents both oncogenic or tumor suppressive effect in different cancers, however, it is still unknown that the role of ZHX2 in myeloma. In this study, we aim to demonstrate the effect and mechanism of ZHX2 on proteasome inhibitor resistance in MM. Methods GSE24080 gene expression profile datasets from Gene Expression Omnibus (GEO) were analyzed to evaluate the relationship between ZHX2 expression level and survival in MM. Expression of ZHX2 in human MM cell lines at baseline and after bortezomib (BTZ) treatment was determined by Western blotting (WB). The proliferation and apoptosis rate of MM cells treated with BTZ after the knockdown of ZHX2 were analyzed by flow cytometry. Nuclear translocation of NF‐κB after the knockdown of ZHX2 was evaluated by WB and immunofluorescence, and the expression of NF‐κB target genes was measured by real‐time quantitative PCR. Co‐immunoprecipitation (Co‐IP) and WB were used to detect the interaction of ZHX2 with NF‐κB. Results We found that higher ZHX2 expression was correlated with poorer clinical outcomes of patients. In addition, ZHX2 expression was relatively higher in RPMI‐8226 and MM.1S cell lines and the level of ZHX2 protein was upregulated after BTZ treatment. Knockdown of ZHX2 significantly enhanced the sensitivity of MM cells to BTZ, inhibited nuclear translocation of NF‐κB, and reduced mRNA expression of NF‐κB target genes. It was also revealed that ZHX2 directly binds to NF‐κB. Conclusion Our study showed that ZHX2 can promote proteasome inhibitor resistance in MM cells by regulating the nuclear translocation of NF‐κB

Temperature-regulation liquid gating membrane with controllable gas/liquid separation

Membrane separation technology with the ability to regulate gas/liquid transport and separation is critical for environmental fields, such as sewerage treatment, multiphase separation, and desalination. Although numerous membranes can dynamically control liquid-phase fluids transport via external stimuli, the transport and separation of gas-phase fluids remains a challenge. Here, we show a temperature-regulation liquid gating membrane that allows in-situ dynamically controllable gas/liquid transfer and multiphase separation by integrating a thermo-wettability responsive porous membrane with functional gating liquid. Experiments and theoretical analysis have demonstrated the temperature-regulation mechanism of this liquid gating system, which is based on thermo-responsive changes of porous membrane surface polarity, leading to changes in affinity between the porous membrane and the gating liquid. In addition, the sandwich configuration with dense Au-coated surfaces and heterogeneous internal components by a bistable interface design enables the liquid gating system to enhance response sensitivity and maintain working stability. This temperature-regulation gas/liquid transfer strategy expands the application range of liquid gating membranes, which are promising in environmental governance, water treatment and multiphase separation

The loss of neoantigens is an important reason for immune escape in multiple myeloma patients with high intratumor heterogeneity

Abstract Objectives Intratumor heterogeneity (ITH) is an important factor for clinical outcomes in patients with multiple myeloma (MM). High ITH has been proven to be a key reason for tumor immune escape and treatment resistance. Neoantigens are thought to be associated with ITH, but the specific correlation and functional basis for this remains unclear. Methods We study this question through the whole‐exome sequencing (WES) data from 43 high ITH newly diagnosed MM patients in our center. Mutant allele tumor heterogeneity (MATH) was conducted to quantify ITH. The cutoff value for high intratumor heterogeneity was determined by comparing MATH of different kinds of tumors. NeoPredPipe was performed to predict neoantigens and binding affinity. Results Compared to other tumors, MM has a relatively low tumor mutation burden but a high ITH. Patients with high MATH had significantly shorter progression‐free survival times than those with low MATH (p = 0.001). In high ITH samples, there is a decrease in strong‐binding neoantigens (p = 0.019). The loss of strong‐binding neoantigens is a key factor for insensitivity to therapy (p = 0.015). Loss of heterozygosity in HLA was not observed. In addition, patients with fewer neoantigens loss had higher rates of disease remission (p = 0.047). CD8 + T cells (p = 0.012) and NK cells (p = 0.011) decreased significantly in patients with high neoantigens loss rate. A prediction model based on neoantigens was built to evaluate the strength of immune escape. Conclusion The loss of strong‐binding neoantigens explains why tumors with high ITH have a higher degree of immune escape and may be feasible for deciding the clinical treatment of MM

Lenalidomide Promotes Thrombosis Formation, but Does Not Affect Platelet Activation in Multiple Myeloma

Lenalidomide, a well-established drug for the treatment of multiple myeloma, significantly enhances patients’ survival. Previous clinical studies have demonstrated that its main side effect is an increased risk of thrombotic events. However, the underlying mechanism remains unexplored. Therefore, this study aims to elucidate the mechanism and offer insights into the selection of clinical thrombotic prophylaxis drugs. Firstly, we conducted a retrospective analysis of clinical data from 169 newly diagnosed multiple myeloma patients who received lenalidomide. To confirm the impact of lenalidomide on thrombosis formation, FeCl3-induced thrombosis and deep venous thrombosis models in mice were established. To investigate the effects of lenalidomide on platelet function, both in vivo and in vitro experiments were designed. During the follow-up period, 8 patients developed thrombotic events, including 8 venous and 1 arterial. Further investigation using mice models demonstrated that lenalidomide significantly promoted the formation of venous thrombosis, consistent with clinical findings. To elucidate the underlying mechanism, assays were conducted to assess platelet function and coagulation. We observed that lenalidomide did not have any noticeable impact on platelet function, both in vitro and in vivo, while administration of lenalidomide resulted in significant decreases in prothrombin time, thrombin time, and prothrombin time ratio in patients, as well as a remarkable reduction in tail-bleeding time in mice. The administration of lenalidomide had no significant impact on platelet function, which may affect venous thrombus formation by affecting coagulation. Therefore, anticoagulant drugs may be superior to antiplatelet drugs in the selection of clinical thrombus prophylaxis

A Machine Learning Model to Predict Survival and Therapeutic Responses in Multiple Myeloma

Multiple myeloma (MM) is a highly heterogeneous hematologic tumor. Ubiquitin proteasome pathways (UPP) play a vital role in its initiation and development. We used cox regression analysis and least absolute shrinkage and selector operation (LASSO) to select ubiquitin proteasome pathway associated genes (UPPGs) correlated with the overall survival (OS) of MM patients in a Gene Expression Omnibus (GEO) dataset, and we formed this into ubiquitin proteasome pathway risk score (UPPRS). The association between clinical outcomes and responses triggered by proteasome inhibitors (PIs) and UPPRS were evaluated. MMRF CoMMpass was used for validation. We applied machine learning algorithms to MM clinical and UPPRS in the whole cohort to make a prognostic nomogram. Single-cell data and vitro experiments were performed to unravel the mechanism and functions of UPPRS. UPPRS consisting of 9 genes showed a strong ability to predict OS in MM patients. Additionally, UPPRS can be used to sort out the patients who would gain more benefits from PIs. A machine learning model incorporating UPPRS and International Staging System (ISS) improved survival prediction in both datasets compared to the revisions of ISS. At the single-cell level, high-risk UPPRS myeloma cells exhibited increased cell adhesion. Targeted UPPGs effectively inhibited myeloma cells in vitro. The UPP genes risk score is a helpful tool for risk stratification in MM patients, particularly those treated with PIs

Bioinspired Photo-Responsive Liquid Gating Membrane

Stomata in the plant leaves are channels for gas exchange between the plants and the atmosphere. The gas exchange rate can be regulated by adjusting the opening and closing of stoma under the external stimuli, which plays a vital role in plant survival. Under visible light irradiation, the stomata open for gas exchange with the surroundings, while under intense UV light irradiation, the stomata close to prevent the moisture loss of plants from excessive transpiration. Inspired by this stomatal self-protection behavior, we have constructed a bioinspired photo-responsive liquid gating membrane (BPRLGM) through infusing the photo-responsive gating liquid obtained by dissolving the azobenzene-based photo-responsive surfactant molecules (AzoC8F15) in N,N-Dimethylacetamide (DMAC) into nylon porous substrate, which can reversibly switch the open/closed states under different photo-stimuli. Theoretical analysis and experimental data have demonstrated that the reversible photoisomerization of azobenzene-based surfactant molecules induces a change in surface tension of the photo-responsive gating liquid, which eventually results in the reversible variation of substantial critical pressure for gas through BPRLGM under alternating UV (PCritical (off)) and visible (PCritical (on)) light irradiations. Therefore, driven by a pressure difference ΔP between PCritical (on) and PCritical (off), the reversible switches on the open/closed states of this photo-responsive liquid gating membrane can be realized under photo-stimuli. This bioinspired membrane with switchable open/closed liquid gating performance under photo-stimuli has the opportunity to be used in the precise and contactless control of microfluidics

Efficient Spatial-Temporal Information Fusion for LiDAR-Based 3D Moving Object Segmentation

Accurate moving object segmentation is an essential task for autonomous driving. It can provide effective information for many downstream tasks, such as collision avoidance, path planning, and static map construction. How to effectively exploit the spatial-temporal information is a critical question for 3D LiDAR moving object segmentation (LiDAR-MOS). In this work, we propose a novel deep neural network exploiting both spatial-temporal information and different representation modalities of LiDAR scans to improve LiDAR-MOS performance. Specifically, we first use a range image-based dual-branch structure to separately deal with spatial and temporal information that can be obtained from sequential LiDAR scans, and later combine them using motion-guided attention modules. We also use a point refinement module via 3D sparse convolution to fuse the information from both LiDAR range image and point cloud representations and reduce the artifacts on the borders of the objects. We verify the effectiveness of our proposed approach on the LiDAR-MOS benchmark of SemanticKITTI. Our method outperforms the state-of-the-art methods significantly in terms of LiDAR-MOS IoU. Benefiting from the devised coarse-to-fine architecture, our method operates online at sensor frame rate. The implementation of our method is available as open source at: https://github.com/haomo-ai/MotionSeg3D.Comment: Accepted by IROS2022. Code: https://github.com/haomo-ai/MotionSeg3

Osteoclast-targeted delivery of anti-miRNA oligonucleotides by red blood cell extracellular vesicles

Osteoporosis (OP) affects millions worldwide but currently cannot be cured. Suppressing the level of miR-214 in osteoclasts by the anti-miRNA oligonucleotide (AMO) anti-miR-214 reverses bone absorption and provides a potential treatment. Here we report a peptide-guided delivery strategy using red blood cell extracellular vesicles (RBCEVs) as the vehicle to realize osteoclast-targeted delivery of anti-miR-214. A bi-functional peptide, TBP-CP05, which binds to both the CD63 on RBCEVs and receptors on osteoclasts, acts as the guide. TBP-CP05 binds with RBCEVs through CP05, displays the TRAP-binding peptide (TBP) on the surface of EVs, and endows RBCEVs with osteoclast-targeting capability both in vitro and in vivo. Intravenous injection of the osteoclast-targeting RBCEVs (OT-RBCEVs) led to the enrichment of EVs in the bone skeleton, significant inhibition of the osteoclast activity, elevated osteoblast activity, and improved bone density in osteoporotic mice. Altogether, this work demonstrates efficient guidance of drug-loaded EVs to the targeted cells in vivo using bi-functional fusion peptides, and showcases that targeted delivery of anti-miR-214 by OT-RBCEVs may be a viable method for OP treatment. SIGNIFICANCE STATEMENT. Surface functionalization of EVs endows these nanovesicles cell-specific targeting property which guides the drug cargos to specific tissues and cells with higher accuracy, longer retention, and minimal off-target effects. Methods to functionalize EVs with minimal procedures are highly desired for clinical applications. Here we present a facile method using a bifunctional fusion peptide to guide RBCEVs to osteoclasts. A simple incubation of the bifunctional peptide and RBCEVs results in osteoclast-targeting RBCEVs (OT-RBCEVs) that effectively deliver anti-miR-214 to osteoclasts in vivo in a mouse model of osteoporosis, bringing a potential therapy to osteoporotic patients. This is, to our knowledge, the first report on peptide functionalization of RBCEVs and osteoclast-targeted delivery using RBCEVs.</p

The evolving diagnosis and treatment paradigms of multiple myeloma in China: 15 years' experience of 1256 patients in a national medical center

Abstract Background Significant advances in multiple myeloma (MM) over the past 15 years led to exciting changes in the management of MM patients in China, which in turn brought about the early diagnoses, precise risk stratifications, and improved prognoses. Methods We summarized the dynamic changes in the management of newly diagnosed (ND) MM in a national medical center, crossing the old and novel drug era. Demographics, clinical characteristics, first‐line treatment, response rate, and survival were retrospectively collected among NDMMs diagnosed in Zhongshan Hospital Fudan University from January 2007 to October 2021. Results Of the 1256 individuals, median age was 64 (range 31–89) with 45.1% patients >65 years. About 63.5% were male, 43.1% were at ISS stage III and 9.9% had light‐chain amyloidosis. Patients with abnormal ratio of free light chain (80.4%), extramedullary disease (EMD, 22.0%), and high‐risk cytogenetic abnormalities (HRCA, 26.8%) were detected by novel detection techniques. The best confirmed ORR was 86.5%, including 39.4% with CR. Short‐ and long‐term PFS and OS rates persistently increased each year along with increasing novel drug applications. Median PFS and OS were 30.9 and 64.7 months. Advanced ISS stage, HRCA, light‐chain amyloidosis and EMD independently predicted an inferior PFS. First‐line ASCT indicated a superior PFS. Advanced ISS stage, elevated serum LDH, HRCA, light‐chain amyloidosis, and receiving PI/IMiD‐based regimen versus PI+IMiD‐based regimen independently indicated a poorer OS. Conclusions In brief, we illustrated a dynamic landscape of MM patients in a national medical center. Chinese MM patients evidently benefited from newly introduced techniques and drugs in this field