Fine-tuning p53 activity by modulating the interaction between eukaryotic translation initiation factor eIF4E and RNA-binding protein RBM38.

p53 is critical for tumor suppression but also elicits detrimental effects when aberrantly overexpressed. Thus, multiple regulators, including RNA-binding protein RBM38, are found to tightly control p53 expression. Interestingly, RBM38 is unique in that it can either suppress or enhance p53 mRNA translation via altered interaction with eIF4E potentially mediated by serine-195 (S195) in RBM38. Thus, multiple RBM38/eIF4E knock-in (KI) cell lines were generated to investigate the significance of eIF4E-RBM38 interaction in controlling p53 activity. We showed that KI of RBM38-S195D or -Y192C enhances, whereas KI of RBM38-S195K/R/L weakens, the binding of eIF4E to p53 mRNA and subsequently p53 expression. We also showed that KI of eIF4E-D202K weakens the interaction of eIF4E with RBM38 and thereby enhances p53 expression, suggesting that D202 in eIF4E interacts with S195 in RBM38. Moreover, we generated an Rbm38 S193D KI mouse model in which human-equivalent serine-193 is substituted with aspartic acid. We showed that S193D KI enhances p53-dependent cellular senescence and that S193D KI mice have a shortened life span and are prone to spontaneous tumors, chronic inflammation, and liver steatosis. Together, we provide in vivo evidence that the RBM38-eIF4E loop can be explored to fine-tune p53 expression for therapeutic development.

Clonal Deletion of Tumor-Specific T Cells by Interferon-γ Confers Therapeutic Resistance to Combination Immune Checkpoint Blockade.

Resistance to checkpoint-blockade treatments is a challenge in the clinic. We found that although treatment with combined anti-CTLA-4 and anti-PD-1 improved control of established tumors, this combination compromised anti-tumor immunity in the low tumor burden (LTB) state in pre-clinical models as well as in melanoma patients. Activated tumor-specific T cells expressed higher amounts of interferon-γ (IFN-γ) receptor and were more susceptible to apoptosis than naive T cells. Combination treatment induced deletion of tumor-specific T cells and altered the T cell repertoire landscape, skewing the distribution of T cells toward lower-frequency clonotypes. Additionally, combination therapy induced higher IFN-γ production in the LTB state than in the high tumor burden (HTB) state on a per-cell basis, reflecting a less exhausted immune status in the LTB state. Thus, elevated IFN-γ secretion in the LTB state contributes to the development of an immune-intrinsic mechanism of resistance to combination checkpoint blockade, highlighting the importance of achieving the optimal magnitude of immune stimulation for successful combination immunotherapy strategies.

Sprod for de-noising spatially resolved transcriptomics data based on position and image information.

Spatially resolved transcriptomics (SRT) provide gene expression close to, or even superior to, single-cell resolution while retaining the physical locations of sequencing and often also providing matched pathology images. However, SRT expression data suffer from high noise levels, due to the shallow coverage in each sequencing unit and the extra experimental steps required to preserve the locations of sequencing. Fortunately, such noise can be removed by leveraging information from the physical locations of sequencing, and the tissue organization reflected in corresponding pathology images. In this work, we developed Sprod, based on latent graph learning of matched location and imaging data, to impute accurate SRT gene expression. We validated Sprod comprehensively and demonstrated its advantages over previous methods for removing drop-outs in single-cell RNA-sequencing data. We showed that, after imputation by Sprod, differential expression analyses, pathway enrichment and cell-to-cell interaction inferences are more accurate. Overall, we envision de-noising by Sprod to become a key first step towards empowering SRT technologies for biomedical discoveries.

Ninjurin 2 Modulates Tumorigenesis, Inflammation, and Metabolism via Pyroptosis.

The nerve injury-induced protein 2 (NINJ2) belongs to a family of homophilic adhesion molecules and was initially found to be involved in nerve regeneration. However, the role of NINJ2 in other cellular processes is not well studied. The Ninj2-deficient mice generated in the current study had a short lifespan and were prone to spontaneous tumors, systemic inflammation, and metabolic defects. Comprehensive carbohydrate and lipid metabolic analyses were performed to better understand the metabolic traits that contribute to these phenotypes. Carbohydrate metabolic analyses showed that NINJ2 deficiency led to defects in monosaccharide metabolism along with accumulation of multiple disaccharides and sugar alcohols. Lipidomic analyses showed that Ninj2 deficiency altered patterns of several lipids, including triglycerides, phospholipids, and ceramides. To identify a cellular process that associated with these metabolic defects, the role of NINJ2 in pyroptosis, a programmed cell death that links cancer, inflammation, and metabolic disorders, was examined. Loss of NINJ2 promoted pyroptosis by activating the NOD-like receptor protein 3 (NLRP3) inflammasome. Taken together, these data reveal a critical role of NINJ2 in tumorigenesis, inflammatory response, and metabolism via pyroptosis.

Structural variation cooperates with permissive chromatin to control enhancer hijacking-mediated oncogenic transcription.

Structural variants (SVs) involving enhancer hijacking can rewire chromatin topologies to cause oncogene activation in human cancers, including hematologic malignancies; however, because of the lack of tools to assess their effects on gene regulation and chromatin organization, the molecular determinants for the functional output of enhancer hijacking remain poorly understood. Here, we developed a multimodal approach to integrate genome sequencing, chromosome conformation, chromatin state, and transcriptomic alteration for quantitative analysis of transcriptional effects and structural reorganization imposed by SVs in leukemic genomes. We identified known and new pathogenic SVs, including recurrent t(5;14) translocations that cause the hijacking of BCL11B enhancers for the allele-specific activation of TLX3 in a subtype of pediatric leukemia. Epigenetic perturbation of SV-hijacked BCL11B enhancers impairs TLX3 transcription, which are required for the growth of t(5;14) leukemia cells. By CRISPR engineering of patient-derived t(5;14) in isogenic leukemia cells, we uncovered a new mechanism whereby the transcriptional output of SV-induced BCL11B enhancer hijacking is dependent on the loss of DNA hypermethylation at the TLX3 promoter. Our results highlight the importance of the cooperation between genetic alteration and permissive chromatin as a critical determinant of SV-mediated oncogene activation, with implications for understanding aberrant gene transcription after epigenetic therapies in patients with leukemia. Hence, leveraging the interdependency of genetic alteration on chromatin variation may provide new opportunities to reprogram gene regulation as targeted interventions in human disease.

p73α1, a p73 C-terminal isoform, regulates tumor suppression and the inflammatory response via Notch1.

p73, a p53 family member, undergoes alternative splicing at the 3' end to produce multiple isoforms, but their expression and activity are largely unknown. Thus, CRISPR was used to knock out exon 12 (E12) in human cancer cell lines and mice, leading to isoform switch from p73α to isoform p73α1. We found that p73α1 is naturally expressed and induced by DNA damage. We also found that knockout of E12 suppresses cell growth and migration in H1299 and MIA PaCa-2 cells and promotes cellular senescence in mouse embryonic fibroblasts. Similarly, ectopic expression of p73α1 suppresses cell proliferation, whereas knockdown of p73α1 restores the cell proliferative and migratory capacities of E12−/− cells. Consistently, we found that E12+/− mice are not prone to spontaneous tumors. Instead, E12+/− mice are prone to systemic inflammation and exhibit elevated TNFα expression in inflamed tissues. Moreover, we found that Notch1, a master regulator of the inflammatory response, is regulated by p73α1 and highly expressed in E12−/− cells and inflamed E12+/− mouse tissues. Furthermore, through knockdown of p73α1 and/or Notch1 in E12−/− cells, we found that Notch1 is necessary for p73α1-mediated growth suppression. Together, these data suggest that p73α1 plays a critical role in tumor suppression and the inflammatory response via Notch1.

Flexible and Robust Core-Shell PANI/PVDF@PANI Nanofiber Membrane for High-Performance Electromagnetic Interference Shielding.

Developing high-performance electromagnetic interference (EMI) shielding materials that are lightweight and flexible and have excellent mechanical properties is an ideal choice for modern integrated electronic devices and microwave protection. Herein, we report the preparation of core-shell polyaniline (PANI)-based nanofiber membranes for EMI shielding through seed polymerization. Electrospinning a PANI solution leads to homogeneously dispersed PANI on the nanofiber surface, with abundant attachment sites for aniline through electrostatic adsorption and hydrogen bonding interaction, allowing PANI to grow on the nanofiber surfaces. This stable core-shell heterostructure provides more interfaces for reflecting and absorbing microwaves. The PANI/PVDF@PANI membranes achieved a shielding efficiency (SE) of 44.7 dB at a thickness of only 1.2 mm, exhibiting an exceptionally high specific EMI shielding effectiveness (SE/t) of 372.5 dB cm-1. Furthermore, the composite membrane exhibits outstanding mechanical stability, durability, air permeability, and moisture permeability, also making it suitable for applications such as EM shielding clothing.

Ferredoxin reductase is critical for p53-dependent tumor suppression via iron regulatory protein 2.

Ferredoxin reductase (FDXR), a target of p53, modulates p53-dependent apoptosis and is necessary for steroidogenesis and biogenesis of iron-sulfur clusters. To determine the biological function of FDXR, we generated a Fdxr-deficient mouse model and found that loss of Fdxr led to embryonic lethality potentially due to iron overload in developing embryos. Interestingly, mice heterozygous in Fdxr had a short life span and were prone to spontaneous tumors and liver abnormalities, including steatosis, hepatitis, and hepatocellular carcinoma. We also found that FDXR was necessary for mitochondrial iron homeostasis and proper expression of several master regulators of iron metabolism, including iron regulatory protein 2 (IRP2). Surprisingly, we found that p53 mRNA translation was suppressed by FDXR deficiency via IRP2. Moreover, we found that the signal from FDXR to iron homeostasis and the p53 pathway was transduced by ferredoxin 2, a substrate of FDXR. Finally, we found that p53 played a role in iron homeostasis and was required for FDXR-mediated iron metabolism. Together, we conclude that FDXR and p53 are mutually regulated and that the FDXR-p53 loop is critical for tumor suppression via iron homeostasis.

Epidermodysplasia Verruciformis and Vδ2 γδ T-cell Expansion in STK4 Deficiency.

The clinical penetrance of infectious diseases varies considerably among patients with inborn errors of immunity (IEI), even for identical genetic defects. This variability is influenced by pathogen exposure, healthcare access and host-environment interactions. We describe here a patient in his thirties who presented with epidermodysplasia verruciformis (EV) due to infection with a weakly virulent beta-papillomavirus (HPV38) and CD4+ T-cell lymphopenia. The patient was born to consanguineous parents living in the United States. Exome sequencing identified a previously unknown biallelic STK4 stop-gain mutation (p.Trp425X). The patient had no relevant history of infectious disease during childhood other than mild wart-like lesion on the skin, but he developed diffuse large B-cell lymphoma (DLBCL) and EBV viremia with a low viral load in his thirties. Despite his low CD4+ T-cell count, the patient had normal counts of CD3+ cells, predominantly double-negative T cells (67.4%), which turned out to be Vδ2+ γδ T cells. γδ T-cell expansion has frequently been observed in the 33 reported cases with STK4 deficiency. The Vδ2 γδ T cells of this STK4-deficient patient are mostly CD45RA-CD27+CCR7+ central memory γδT cells, and their ability to proliferate in response to T-cell activation was impaired, as was that of CD4+ T cells. In conclusion, γδ T-cell expansion may act as a compensatory mechanism to combat viral infection, providing immune protection in immunocompromised individuals.

SLF2 Interacts with the SMC5/6 Complex to Direct Hepatitis B Virus Episomal DNA to Promyelocytic Leukemia Bodies for Transcriptional Repression.

Hepatitis B virus (HBV) chronically infects approximately 300 million people worldwide, and permanently repressing transcription of covalently closed circular DNA (cccDNA), the episomal viral DNA reservoir, is an attractive approach toward curing HBV. However, the mechanism underlying cccDNA transcription is only partially understood. In this study, by illuminating cccDNA of wild-type HBV (HBV-WT) and transcriptionally inactive HBV that bears a deficient HBV X gene (HBV-ΔX), we found that the HBV-ΔX cccDNA more frequently colocalizes with promyelocytic leukemia (PML) bodies than that of HBV-WT cccDNA. A small interfering RNA (siRNA) screen targeting 91 PML body-related proteins identified SMC5-SMC6 localization factor 2 (SLF2) as a host restriction factor of cccDNA transcription, and subsequent studies showed that SLF2 mediates HBV cccDNA entrapment in PML bodies by interacting with the SMC5/6 complex. We further showed that the region of SLF2 comprising residues 590 to 710 interacts with and recruits the SMC5/6 complex to PML bodies, and the C-terminal domain of SLF2 containing this region is necessary for repression of cccDNA transcription. Our findings shed new light on cellular mechanisms that inhibit HBV infection and lend further support for targeting the HBx pathway to repress HBV activity. IMPORTANCE Chronic HBV infection remains a major public health problem worldwide. Current antiviral treatments rarely cure the infection, as they cannot clear the viral reservoir, cccDNA, in the nucleus. Therefore, permanently silencing HBV cccDNA transcription represents a promising approach for a cure of HBV infection. Our study provides new insights into the cellular mechanisms that restrict HBV infection, revealing the role of SLF2 in directing HBV cccDNA to PML bodies for transcriptional repression. These findings have important implications for the development of antiviral therapies against HBV.

Perovskites as oxygen storage materials for chemical looping partial oxidation and reforming of methane.

The traditional partial oxidation, dry reforming and steam reforming of methane technologies are separated into two reactors for execution by chemical looping technology, which can avoid the defects exposed in the traditional process (avoiding carbon accumulation, reducing costs, etc.). The key to chemical looping technology is to find suitable oxygen carriers (OCs), which can store and release oxygen to form a closed loop in the chemical looping. The purpose of this review is to summarize the current status of perovskite oxides for partial oxidation and reforming of methane in chemical looping, describe the structure, oxygen capacity, oxygen migration rate and common synthesis methods of perovskites in chemical looping. In addition, the effects of impregnation loading, ion doping, and structural morphology on the catalytic conversion of CH4 by perovskite OCs and the reaction mechanism on the OCs are also discussed.

Preface: Artificial intelligence (AI), machine learning ML) and digital pathology integration are the next major chapter in our diagnostic pathology and laboratory medicine arena.

This timely captivating topic is organized and presented in this special issue of the journal of Seminar in diagnostic pathology. This special issue will be dedicated to the utilization of machine learning within the digital pathology and laboratory medicine fields. Special thanks to all the authors whose contributions to this review series has not only enhanced our overall understanding of this exciting new field but will also enrich the reader's understanding of this important discipline.

Artificial intelligence in clinical multiparameter flow cytometry and mass cytometry-key tools and progress.

There are many research studies and emerging tools using artificial intelligence (AI) and machine learning to augment flow and mass cytometry workflows. Emerging AI tools can quickly identify common cell populations with continuous improvement of accuracy, uncover patterns in high-dimensional cytometric data that are undetectable by human analysis, facilitate the discovery of cell subpopulations, perform semi-automated immune cell profiling, and demonstrate potential to automate aspects of clinical multiparameter flow cytometric (MFC) diagnostic workflow. Utilizing AI in the analysis of cytometry samples can reduce subjective variability and assist in breakthroughs in understanding diseases. Here we review the diverse types of AI that are being applied to clinical cytometry data and how AI is driving advances in data analysis to improve diagnostic sensitivity and accuracy. We review supervised and unsupervised clustering algorithms for cell population identification, various dimensionality reduction techniques, and their utilities in visualization and machine learning pipelines, and supervised learning approaches for classifying entire cytometry samples.Understanding the AI landscape will enable pathologists to better utilize open source and commercially available tools, plan exploratory research projects to characterize diseases, and work with machine learning and data scientists to implement clinical data analysis pipelines.

Advances in molecular evaluation of myeloproliferative neoplasms.

Myeloproliferative neoplasms (MPN) are a group of clonal hematopoietic stem cell disorders with uncontrolled proliferation of one or more hematopoietic cell types, including myeloid, erythroid and megakaryocytic lineages, and minimal defect in maturation. Most MPN are associated with well-defined molecular abnormalities involving genes that encode protein tyrosine kinases that lead to constitutive activation of the downstream signal transduction pathways and confer cells proliferative and survival advantage. Genome-wide sequencing analyses have discovered secondary cooperating mutations that are shared by most of the MPN subtypes as well as other myeloid neoplasms and play a major role in disease progression. Without appropriate management, the natural history of most MPN consists of an initial chronic phase and a terminal blast phase. Molecular aberrations involving protein tyrosine kinases have been used for the diagnosis, classification, detection of minimal/measurable residual disease, and target therapy. We review recent advances in molecular genetic aberrations in MPN with a focus on MPN associated with gene rearrangements or mutations involving tyrosine kinase pathways.

Digital pathology and artificial intelligence as the next chapter in diagnostic hematopathology.

Digital pathology has a crucial role in diagnostic pathology and is increasingly a technological requirement in the field. Integration of digital slides into the pathology workflow, advanced algorithms, and computer-aided diagnostic techniques extend the frontiers of the pathologist's view beyond the microscopic slide and enable true integration of knowledge and expertise. There is clear potential for artificial intelligence (AI) breakthroughs in pathology and hematopathology. In this review article, we discuss the approach of using machine learning in the diagnosis, classification, and treatment guidelines of hematolymphoid disease, as well as recent progress of artificial intelligence in flow cytometric analysis of hematolymphoid diseases. We review these topics specifically through the potential clinical applications of CellaVision, an automated digital image analyzer of peripheral blood, and Morphogo, a novel artificial intelligence-based bone marrow analyzing system. Adoption of these new technologies will allow pathologists to streamline workflow and achieve faster turnaround time in diagnosing hematological disease.

Deep learning in digital pathology for personalized treatment plans of cancer patients.

Over the past decade, many new cancer treatments have been developed and made available to patients. However, in most cases, these treatments only benefit a specific subgroup of patients, making the selection of treatment for a specific patient an essential but challenging task for oncologists. Although some biomarkers were found to associate with treatment response, manual assessment is time-consuming and subjective. With the rapid developments and expanded implementation of artificial intelligence (AI) in digital pathology, many biomarkers can be quantified automatically from histopathology images. This approach allows for a more efficient and objective assessment of biomarkers, aiding oncologists in formulating personalized treatment plans for cancer patients. This review presents an overview and summary of the recent studies on biomarker quantification and treatment response prediction using hematoxylin-eosin (H&E) stained pathology images. These studies have shown that an AI-based digital pathology approach can be practical and will become increasingly important in improving the selection of cancer treatments for patients.

Effect of Layered Aminovanadic Oxalate Phosphate on Flame Retardancy of Epoxy Resin.

To alleviate the fire hazard of epoxy resin (EP), layered ammonium vanadium oxalate-phosphate (AVOPh) with the structural formula of (NH4)2[VO(HPO4)]2(C2O4)·5H2O is synthesized using the hydrothermal method and mixed into an EP matrix to prepare EP/AVOPh composites. The thermogravimetric analysis (TGA) results show that AVOPh exhibits a similar thermal decomposition temperature to EP, which is suitable for flame retardancy for EP. The incorporation of AVOPh nanosheets greatly improves the thermal stability and residual yield of EP/AVOPh composites at high temperatures. The residue of pure EP is 15.3% at 700 °C. In comparison, the residue of EP/AVOPh composites is increased to 23.0% with 8 wt% AVOPh loading. Simultaneously, EP/6 wt% AVOPh composites reach UL-94 V1 rating (t1 + t2 =16 s) and LOI value of 32.8%. The improved flame retardancy of EP/ AVOPh composites is also proven by the cone calorimeter test (CCT). The results of CCT of EP/8 wt% AVOPh composites show that the peak heat release rate (PHHR), total smoke production (TSP), peak of CO production (PCOP), and peak of CO2 production (PCO2P) decrease by 32.7%, 20.4%, 37.1%, and 33.3% compared with those of EP, respectively. This can be attributed to the lamellar barrier, gas phase quenching effect of phosphorus-containing volatiles, the catalytic charring effect of transition metal vanadium, and the synergistic decomposition of oxalic acid structure and charring effect of phosphorus phase, which can insulate heat and inhibit smoke release. Based on the experimental data, AVOPh is expected to serve as a new high-efficiency flame retardant for EP.

The Synthesis and Polymer-Reinforced Mechanical Properties of SiO2 Aerogels: A Review.

Silica aerogels are considered as the distinguished materials of the future due to their extremely low thermal conductivity, low density, and high surface area. They are widely used in construction engineering, aeronautical domains, environmental protection, heat storage, etc. However, their fragile mechanical properties are the bottleneck restricting the engineering application of silica aerogels. This review briefly introduces the synthesis of silica aerogels, including the processes of sol-gel chemistry, aging, and drying. The effects of different silicon sources on the mechanical properties of silica aerogels are summarized. Moreover, the reaction mechanism of the three stages is also described. Then, five types of polymers that are commonly used to enhance the mechanical properties of silica aerogels are listed, and the current research progress is introduced. Finally, the outlook and prospects of the silica aerogels are proposed, and this paper further summarizes the methods of different polymers to enhance silica aerogels.

The link between menin and pleiotrophin in the tumor biology of pancreatic neuroendocrine neoplasms.

MEN1, which encodes menin protein, is the most frequently mutated gene in pancreatic neuroendocrine neoplasms (pNEN). Pleiotrophin (PTN) has been reported as a downstream factor of menin that promotes metastasis in different tumor entities. In this study, the effect of menin and its link to PTN were assessed using features of pNEN cells and the outcome of patients with pNEN. The expression levels of menin and PTN in tissues from patients with pNEN were examined using qRT-PCR and western blot and compared with their metastasis status. Functional assays, including transwell migration/invasion and scratch wound-healing assays, were performed on specifically designed CRISPR/Cas9-mediated MEN1-knockout (MEN1-KO) pNEN cell lines (BON1MEN1-KO and QGP1MEN1-KO ) to study the metastasis of pNEN. Among 30 patients with menin-negative pNEN, 21 revealed a strong protein expression of PTN. This combination was associated with metastasis and shorter disease-free survival. Accordingly, in BON1MEN1-KO and QGP1MEN1-KO cells, PTN protein expression was positively associated with enhanced cell migration and invasion, which could be reversed using PTN silencing. PTN is a predicting factor of metastatic behavior of menin-deficient-pNEN. In vitro, menin is able to both promote and suppress the metastasis of pNEN by regulating PTN expression depending on the tumoral origin of pNEN cells.

Mast cell sarcoma: clinicopathologic and molecular analysis of 10 new cases and review of literature.

Mast cell sarcoma (MCS) is an exceedingly rare form of mastocytosis characterized by invasive malignant mast cell growth and metastatic potential. Diagnosis of MCS is very challenging due to its marked morphologic variations and significant immunophenotypic overlap with other neoplasms. In this study, we undertook an extensive study of 10 cases of MCS from our series, with review of additional 24 cases from the literature, to better clarify the clinicopathologic and molecular features of MCS. From the analyses of our 10 cases, MCS equally involved males and females with a median age of 54.5 years (range 1-63). The bone was the most common site of involvement, as noted in 9/10 of cases. Two patients had prior germ cell tumors (mediastinal germ cell tumor and ovarian dysgerminoma), and concurrent systemic mastocytosis was noted in one of nine patients. Serum tryptase levels were elevated in 6/7 of patients, and 3/9 of patients had mast cell activation symptoms. Morphologically, the tumor cells were typically large and pleomorphic with frequent reactive eosinophils. By immunohistochemical staining, MCS consistently expressed CD43 (8/8), CD117 (10/10), and mast cell tryptase (10/10), as well as CD13 (3/3) and CD33 (10/10), with variable positivity of CD2 (1/9), CD25 (4/9), CD30 (5/8), and CD68 (5/9). Notably, KIT D816V was not detected in nine cases in our study, although two cases had other mutations of KIT gene. Seven out of eight patients received chemotherapy with or without radiotherapy. However, the response was poor, and four out of eight patients died within a median follow-up interval of five months. Taken together, there are no standardized therapeutic regimens available for MCS at this time, and the prognosis is dismal. Therefore, it is critical to further investigate and characterize this rare entity, with the hope of improving diagnostic accuracy and providing more effective, targeted therapies.