Clofazimine broadly inhibits coronaviruses including SARS-CoV-2.

The COVID-19 pandemic is the third outbreak this century of a zoonotic disease caused by a coronavirus, following the emergence of severe acute respiratory syndrome (SARS) in 20031 and Middle East respiratory syndrome (MERS) in 20122. Treatment options for coronaviruses are limited. Here we show that clofazimine-an anti-leprosy drug with a favourable safety profile3-possesses inhibitory activity against several coronaviruses, and can antagonize the replication of SARS-CoV-2 and MERS-CoV in a range of in vitro systems. We found that this molecule, which has been approved by the US Food and Drug Administration, inhibits cell fusion mediated by the viral spike glycoprotein, as well as activity of the viral helicase. Prophylactic or therapeutic administration of clofazimine in a hamster model of SARS-CoV-2 pathogenesis led to reduced viral loads in the lung and viral shedding in faeces, and also alleviated the inflammation associated with viral infection. Combinations of clofazimine and remdesivir exhibited antiviral synergy in vitro and in vivo, and restricted viral shedding from the upper respiratory tract. Clofazimine, which is orally bioavailable and comparatively cheap to manufacture, is an attractive clinical candidate for the treatment of outpatients and-when combined with remdesivir-in therapy for hospitalized patients with COVID-19, particularly in contexts in which costs are an important factor or specialized medical facilities are limited. Our data provide evidence that clofazimine may have a role in the control of the current pandemic of COVID-19 and-possibly more importantly-in dealing with coronavirus diseases that may emerge in the future.

Single-cell RNA sequencing integrated with bulk RNA sequencing analysis identifies a tumor immune microenvironment-related lncRNA signature in lung adenocarcinoma.

BACKGROUND: Recently, long non-coding RNAs (lncRNAs) have been demonstrated as essential roles in tumor immune microenvironments (TIME). Nevertheless, researches on the clinical significance of TIME-related lncRNAs are limited in lung adenocarcinoma (LUAD). METHODS: Single-cell RNA sequencing and bulk RNA sequencing data are integrated to identify TIME-related lncRNAs. A total of 1368 LUAD patients are enrolled from 6 independent datasets. An integrative machine learning framework is introduced to develop a TIME-related lncRNA signature (TRLS). RESULTS: This study identified TIME-related lncRNAs from integrated analysis of single­cell and bulk RNA sequencing data. According to these lncRNAs, a TIME-related lncRNA signature was developed and validated from an integrative procedure in six independent cohorts. TRLS exhibited a robust and reliable performance in predicting overall survival. Superior prediction performance barged TRLS to the forefront from comparison with general clinical features, molecular characters, and published signatures. Moreover, patients with low TRLS displayed abundant immune cell infiltration and active lipid metabolism, while patients with high TRLS harbored significant genomic alterations, high PD-L1 expression, and elevated DNA damage repair (DDR) relevance. Notably, subclass mapping analysis of nine immunotherapeutic cohorts demonstrated that patients with high TRLS were more sensitive to immunotherapy. CONCLUSIONS: This study developed a promising tool based on TIME-related lncRNAs, which might contribute to tailored treatment and prognosis management of LUAD patients.

Integrated Exploration of Epigenetic Dysregulation Reveals a Stemness/EMT Subtype and MMP12 Linked to the Progression and Prognosis in Hepatocellular Carcinoma.

Epigenetic dysregulation drives aberrant transcriptional programs playing a critical role in hepatocellular carcinoma (HCC), which may provide novel insights into the heterogeneity of HCC. This study performed an integrated exploration on the epigenetic dysregulation of miRNA and methylation. We discovered and validated three patterns endowed with gene-related transcriptional traits and clinical outcomes. Specially, a stemness/epithelial-mesenchymal transition (EMT) subtype was featured by immune exhaustion and the worst prognosis. Besides, MMP12, a characteristic gene, was highly expressed in the stemness/EMT subtype, which was verified as a pivotal regulator linked to the unfavorable prognosis and further proven to promote tumor proliferation, invasion, and metastasis in vitro experiments. Proteomic analysis by mass spectrometry sequencing also indicated that the overexpression of MMP12 was significantly associated with cell proliferation and adhesion. Taken together, this study unveils innovative insights into epigenetic dysregulation and identifies a stemness/EMT subtype-specific gene, MMP12, correlated with the progression and prognosis of HCC.

Cellular Ligand-Receptor Perturbations Unravel MEIS2 as a Key Factor for the Aggressive Progression and Prognosis in Stage II/III Colorectal Cancer.

Approximately 10-15% of stage II and 25-30% of stage III colorectal cancer (CRC) patients experience recurrence within 5 years after surgery, and existing taxonomies are insufficient to meet the needs of clinical precision treatment. Thus, robust biomarkers and precise management were urgently required to stratify stage II and III CRC and identify potential patients who will benefit from postoperative adjuvant therapy. Alongside, interactions of ligand-receptor pairs point to an emerging direction in tumor signaling with far-reaching implications for CRC, while their impact on tumor subtyping has not been elucidated. Herein, based on multiple large-sample multicenter cohorts and perturbations of the ligand-receptor interaction network, four well-characterized ligand-receptor-driven subtypes (LRDS) were established and further validated. These molecular taxonomies perform with unique heterogeneity in terms of molecular characteristics, immune and mutational landscapes, and clinical features. Specifically, MEIS2, a key LRDS4 factor, performs significant associations with proliferation, invasion, migration, and dismal prognosis of stage II/III CRC, revealing promising directions for prognostic assessment and individualized treatment of CRC patients. Overall, our study sheds novel insights into the implications of intercellular communication on stage II/III CRC from a ligand-receptor interactome perspective and revealed MEIS2 as a key factor in the aggressive progression and prognosis for stage II/III CRC.

Ultrafast Formation of a Delocalized Triplet-Excited State in an Epigenetically Modified DNA Duplex under Direct UV Excitation.

Epigenetic modifications impart important functionality to nucleic acids during gene expression but may increase the risk of photoinduced gene mutations. Thus, it is crucial to understand how these modifications affect the photostability of duplex DNA. In this work, the ultrafast formation (<20 ps) of a delocalized triplet charge transfer (CT) state spreading over two stacked neighboring nucleobases after direct UV excitation is demonstrated in a DNA duplex, d(G5fC)9•d(G5fC)9, made of alternating guanine (G) and 5-formylcytosine (5fC) nucleobases. The triplet yield is estimated to be 8 ± 3%, and the lifetime of the triplet CT state is 256 ± 22 ns, indicating that epigenetic modifications dramatically alter the excited state dynamics of duplex DNA and may enhance triplet state-induced photochemistry.

Triplet Excimer Formation in a DNA Duplex with Silver Ion-Mediated Base Pairs.

The dynamics of excited electronic states in self-assembled structures formed between silver(I) ions and cytosine-containing DNA strands or monomeric cytosine derivatives were investigated by time-resolved infrared (TRIR) spectroscopy and quantum mechanical calculations. The steady-state and time-resolved spectra depend sensitively on the underlying structures, which change with pH and the nucleobase and silver ion concentrations. At pH ∼ 4 and low dC20 strand concentration, an intramolecularly folded i-motif is observed, in which protons, and not silver ions, mediate C-C base pairing. However, at the higher strand concentrations used in the TRIR measurements, dC20 strands associate pairwise to yield duplex structures containing C-Ag+-C base pairs with a high degree of propeller twisting. UV excitation of the silver ion-mediated duplex produces a long-lived excited state, which we assign to a triplet excimer state localized on a pair of stacked cytosines. The computational results indicate that the propeller-twisted motifs induced by metal-ion binding are responsible for the enhanced intersystem crossing that populates the triplet state and not a generic heavy atom effect. Although triplet excimer states have been discussed frequently as intermediates in the formation of cyclobutane pyrimidine dimers, we find neither computational nor experimental evidence for cytosine-cytosine photoproduct formation in the systems studied. These findings provide a rare demonstration of a long-lived triplet excited state that is formed in a significant yield in a DNA duplex, demonstrating that supramolecular structural changes induced by metal ion binding profoundly affect DNA photophysics.

Tertiary lymphoid structural heterogeneity determines tumour immunity and prospects for clinical application.

Tertiary lymphoid structures (TLS) are clusters of immune cells that resemble and function similarly to secondary lymphoid organs (SLOs). While TLS is generally associated with an anti-tumour immune response in most cancer types, it has also been observed to act as a pro-tumour immune response. The heterogeneity of TLS function is largely determined by the composition of tumour-infiltrating lymphocytes (TILs) and the balance of cell subsets within the tumour-associated TLS (TA-TLS). TA-TLS of varying maturity, density, and location may have opposing effects on tumour immunity. Higher maturity and/or higher density TLS are often associated with favorable clinical outcomes and immunotherapeutic response, mainly due to crosstalk between different proportions of immune cell subpopulations in TA-TLS. Therefore, TLS can be used as a marker to predict the efficacy of immunotherapy in immune checkpoint blockade (ICB). Developing efficient imaging and induction methods to study TA-TLS is crucial for enhancing anti-tumour immunity. The integration of imaging techniques with biological materials, including nanoprobes and hydrogels, alongside artificial intelligence (AI), enables non-invasive in vivo visualization of TLS. In this review, we explore the dynamic interactions among T and B cell subpopulations of varying phenotypes that contribute to the structural and functional diversity of TLS, examining both existing and emerging techniques for TLS imaging and induction, focusing on cancer immunotherapies and biomaterials. We also highlight novel therapeutic approaches of TLS that are being explored with the aim of increasing ICB treatment efficacy and predicting prognosis.

High ratio of resident to exhausted CD4 + T cells predicts favorable prognosis and potentially better immunotherapeutic efficacy in hepatocellular carcinoma.

BACKGROUND: Tumor-infiltrating lymphocytes (TILs) are significantly implicated in regulating the tumor immune microenvironment (TIME) and immunotherapeutic response. However, little is known about the impact of the resident and exhausted status of TILs in hepatocellular carcinoma (HCC). METHODS: Single-cell RNA sequencing data was applied to discover resident and exhausted signatures of TILs. Survival outcomes, biological function, immune infiltration, genomic variation, immunotherapeutic efficacy, and sorafenib response were further explored the clinical significance and molecular association of TILs in HCC. Moreover, a candidate gene with predictive capability for the dismal subtype was identified through univariate Cox regression analysis, survival analysis, and the BEST website. RESULTS: Single-cell analysis revealed that CD8 + T, CD4 + T, and NK cells were strongly associated with resident and exhausted patterns. Specific resident and exhausted signatures for each subpopulation were extracted in HCC. Further multivariate Cox analysis revealed that the ratio of resident to exhausted CD4 + T cells in TIME was an independent prognostic factor. After incorporating tumor purity with the ratio of resident to exhausted CD4 + T cells, we stratified HCC patients into three subtypes and found that (i) CD4 residencyhighexhaustionlow subtype was endowed with favorable prognosis, immune activation, and sensitivity to immunotherapy; (ii) CD4 exhaustionhighresidencylow subtype was characterized by genome instability and sensitivity to sorafenib; (iii) Immune-desert subtype was associated with malignant-related pathways and poor prognosis. Furthermore, spindle assembly abnormal protein 6 homolog (SASS6) was identified as a key gene, which accurately predicted the immune-desert subtype. Prognostic analysis as well as in vitro and in vivo experiments further demonstrated that SASS6 was closely associated with tumor prognosis, proliferation, and migration. CONCLUSIONS: The ratio of resident to exhausted CD4 + T cells shows promise as a potential biomarker for HCC prognosis and immunotherapy response and SASS6 may serve as a biomarker and therapeutic target for prognostic assessment of HCC.

A radiomics signature derived from CT imaging to predict MSI status and immunotherapy outcomes in gastric cancer: a multi-cohort study.

BACKGROUND: Accurate microsatellite instability (MSI) testing is essential for identifying gastric cancer (GC) patients eligible for immunotherapy. We aimed to develop and validate a CT-based radiomics signature to predict MSI and immunotherapy outcomes in GC. METHODS: This retrospective multicohort study included a total of 457 GC patients from two independent medical centers in China and The Cancer Imaging Archive (TCIA) databases. The primary cohort (n = 201, center 1, 2017-2022), was used for signature development via Least Absolute Shrinkage and Selection Operator (LASSO) and logistic regression analysis. Two independent immunotherapy cohorts, one from center 1 (n = 184, 2018-2021) and another from center 2 (n = 43, 2020-2021), were utilized to assess the signature's association with immunotherapy response and survival. Diagnostic efficiency was evaluated using the area under the receiver operating characteristic curve (AUC), and survival outcomes were analyzed via the Kaplan-Meier method. The TCIA cohort (n = 29) was included to evaluate the immune infiltration landscape of the radiomics signature subgroups using both CT images and mRNA sequencing data. RESULTS: Nine radiomics features were identified for signature development, exhibiting excellent discriminative performance in both the training (AUC: 0.851, 95%CI: 0.782, 0.919) and validation cohorts (AUC: 0.816, 95%CI: 0.706, 0.926). The radscore, calculated using the signature, demonstrated strong predictive abilities for objective response in immunotherapy cohorts (AUC: 0.734, 95%CI: 0.662, 0.806; AUC: 0.724, 95%CI: 0.572, 0.877). Additionally, the radscore showed a significant association with PFS and OS, with GC patients with a low radscore experiencing a significant survival benefit from immunotherapy. Immune infiltration analysis revealed significantly higher levels of CD8 + T cells, activated CD4 + B cells, and TNFRSF18 expression in the low radscore group, while the high radscore group exhibited higher levels of T cells regulatory and HHLA2 expression. CONCLUSION: This study developed a robust radiomics signature with the potential to serve as a non-invasive biomarker for GC's MSI status and immunotherapy response, demonstrating notable links to post-immunotherapy PFS and OS. Additionally, distinct immune profiles were observed between low and high radscore groups, highlighting their potential clinical implications.

Radiomics using CT images for preoperative prediction of lymph node metastasis in perihilar cholangiocarcinoma: a multi-centric study.

OBJECTIVES: To develop a CT-based radiomics model for preoperative prediction of lymph node (LN) metastasis in perihilar cholangiocarcinoma (pCCA). METHODS: The study enrolled consecutive pCCA patients from three independent Chinese medical centers. The Boruta algorithm was applied to build the radiomics signature for the primary tumor and LN. The k-means algorithm was employed to cluster the selected LNs based on the radiomics signature LN. Support vector machines were used to construct the prediction models. The diagnostic efficiency was measured by the area under the receiver operating characteristic curve (AUC). The optimal model was evaluated in terms of calibration, clinical usefulness, and prognostic value. RESULTS: A total of 214 patients were included in the study (mean age: 61.6 years ± 9.4; 130 male). The selected LNs were classified into two clusters, which were significantly correlated with LN metastasis in all cohorts (p < 0.001). The model incorporated the clinical risk factors, radiomics signature primary tumor, and the LN cluster obtained the best discrimination, with AUC values of 0.981 (95% CI: 0.962-1), 0.896 (95% CI: 0.810-0.982), and 0.865 (95% CI: 0.768-0.961) in the training, internal validation, and external validation cohorts, respectively. High-risk patients predicted by the optimal model had shorter overall survival than low-risk patients (median, 13.7 vs. 27.3 months, p < 0.001). CONCLUSIONS: The study proposed a radiomics model with good performance to predict LN metastasis in pCCA. As a noninvasive preoperative prediction tool, this model may help in patient risk stratification and personalized treatment. CLINICAL RELEVANCE STATEMENT: A CT-based radiomics model accurately predicts lymph node metastasis in perihilar cholangiocarcinoma patients. This noninvasive preoperative tool can aid in patient risk stratification and personalized treatment, potentially improving patient outcomes. KEY POINTS: • The radiomics model based on contrast-enhanced CT is a useful tool for preoperative prediction of lymph node metastasis in perihilar cholangiocarcinoma. • Radiomics features extracted from lymph nodes show great potential for predicting lymph node metastasis. • The study is the first to identify a lymph node phenotype with a high probability of metastasis based on radiomics.

Ferroptosis and EMT: key targets for combating cancer progression and therapy resistance.

Iron-dependent lipid peroxidation causes ferroptosis, a form of regulated cell death. Crucial steps in the formation of ferroptosis include the accumulation of ferrous ions (Fe2+) and lipid peroxidation, of which are controlled by glutathione peroxidase 4 (GPX4). Its crucial role in stopping the spread of cancer has been shown by numerous studies undertaken in the last ten years. Epithelial-mesenchymal transition (EMT) is the process by which epithelial cells acquire mesenchymal characteristics. EMT is connected to carcinogenesis, invasiveness, metastasis, and therapeutic resistance in cancer. It is controlled by a range of internal and external signals and changes the phenotype from epithelial to mesenchymal like. Studies have shown that mesenchymal cancer cells tend to be more ferroptotic than their epithelial counterparts. Drug-resistant cancer cells are more easily killed by inducers of ferroptosis when they undergo EMT. Therefore, understanding the interaction between ferroptosis and EMT will help identify novel cancer treatment targets. In-depth discussion is given to the regulation of ferroptosis, the potential application of EMT in the treatment of cancer, and the relationships between ferroptosis, EMT, and signaling pathways associated with tumors. Invasion, metastasis, and inflammation in cancer all include ferroptosis and EMT. The goal of this review is to provide suggestions for future research and practical guidance for applying ferroptosis and EMT in clinical practice.

SARS-CoV-2 hijacks macropinocytosis to facilitate its entry and promote viral spike-mediated cell-to-cell fusion.

Revealing the mechanisms of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) entry and cell-to-cell spread might provide insights for understanding the underlying mechanisms of viral pathogenesis, tropism, and virulence. The signaling pathways involved in SARS-CoV-2 entry and viral spike-mediated cell-to-cell fusion remain elusive. In the current study, we found that macropinocytosis inhibitors significantly suppressed SARS-CoV-2 infection at both the entry and viral spike-mediated cell-to-cell fusion steps. We demonstrated that SARS-CoV-2 entry required the small GTPase Rac1 and its effector kinase p21-activated kinase 1 by dominant-negative and RNAi assays in human embryonic kidney 293T-angiotensin-converting enzyme 2 cells and that the serine protease transmembrane serine protease 2 reversed the decrease in SARS-CoV-2 entry caused by the macropinocytosis inhibitors. Moreover, in the cell-to-cell fusion assay, we confirmed that macropinocytosis inhibitors significantly decreased viral spike-mediated cell-to-cell fusion. Overall, we provided evidence that SARS-CoV-2 utilizes a macropinocytosis pathway to enter target cells and to efficiently promote viral spike-mediated cell-to-cell fusion.

Multifaceted role of redox pattern in the tumor immune microenvironment regarding autophagy and apoptosis.

The reversible oxidation-reduction homeostasis mechanism functions as a specific signal transduction system, eliciting related physiological responses. Disruptions to redox homeostasis can have negative consequences, including the potential for cancer development and progression, which are closely linked to a series of redox processes, such as adjustment of reactive oxygen species (ROS) levels and species, changes in antioxidant capacity, and differential effects of ROS on downstream cell fate and immune capacity. The tumor microenvironment (TME) exhibits a complex interplay between immunity and regulatory cell death, especially autophagy and apoptosis, which is crucially regulated by ROS. The present study aims to investigate the mechanism by which multi-source ROS affects apoptosis, autophagy, and the anti-tumor immune response in the TME and the mutual crosstalk between these three processes. Given the intricate role of ROS in controlling cell fate and immunity, we will further examine the relationship between traditional cancer therapy and ROS. It is worth noting that we will discuss some potential ROS-related treatment options for further future studies.

Radiogenomics: a key component of precision cancer medicine.

Radiogenomics, focusing on the relationship between genomics and imaging phenotypes, has been widely applied to address tumour heterogeneity and predict immune responsiveness and progression. It is an inevitable consequence of current trends in precision medicine, as radiogenomics costs less than traditional genetic sequencing and provides access to whole-tumour information rather than limited biopsy specimens. By providing voxel-by-voxel genetic information, radiogenomics can allow tailored therapy targeting a complete, heterogeneous tumour or set of tumours. In addition to quantifying lesion characteristics, radiogenomics can also be used to distinguish benign from malignant entities, as well as patient characteristics, to better stratify patients according to disease risk, thereby enabling more precise imaging and screening. Here, we have characterised the radiogenomic application in precision medicine using a multi-omic approach. we outline the main applications of radiogenomics in diagnosis, treatment planning and evaluations in the field of oncology with the aim of developing quantitative and personalised medicine. Finally, we discuss the challenges in the field of radiogenomics and the scope and clinical applicability of these methods.

CRISPR/dCas9-Mediated Specific Molecular Assembly Facilitates Genotyping of Mutant Circulating Tumor DNA.

Breakthroughs in circulating tumor DNA (ctDNA) analysis are critical in tumor liquid biopsies but remain a technical challenge due to the double-stranded structure, extremely low abundance, and short half-life of ctDNA. Here, we report an electrochemical CRISPR/dCas9 sensor (E-dCas9) for sensitive and specific detection of ctDNA at a single-nucleotide resolution. The E-dCas9 design harnesses the specific capture and unzipping of target ctDNA by dCas9 to introduce a complementary reporter probe for specific molecular assembly and signal amplification. By efficient homogeneous assembly and interfacial click reaction, the assay demonstrates superior sensitivity (up to 2.86 fM) in detecting single-base mutant ctDNA and a broad dynamic range spanning 6 orders of magnitude. The sensor is also capable of measuring 10 fg/µL of a mutated target in excess of wild-type ones (1 ng/µL), equivalent to probing 0.001% of the mutation relative to the wild type. In addition, our sensor can monitor the dynamic expression of cellular genomic DNA and allows accurate analysis of blood samples from patients with nonsmall cell lung cancer, suggesting the potential of E-dCas9 as a promising tool in ctDNA-based cancer diagnosis.

Machine learning algorithm-generated and multi-center validated melanoma prognostic signature with inspiration for treatment management.

BACKGROUND: Although immunotherapy and targeted treatments have dramatically improved the survival of melanoma patients, the intra- or intertumoral heterogeneity and drug resistance have hindered the further expansion of clinical benefits. METHODS: The 96 combination frames constructed by ten machine learning algorithms identified a prognostic consensus signature based on 1002 melanoma samples from nine independent cohorts. Clinical features and 26 published signatures were employed to compare the predictive performance of our model. RESULTS: A machine learning-based prognostic signature (MLPS) with the highest average C-index was developed via 96 algorithm combinations. The MLPS has a stable and excellent predictive performance for overall survival, superior to common clinical traits and 26 collected signatures. The low MLPS group with a better prognosis had significantly enriched immune-related pathways, tending to be an immune-hot phenotype and possessing potential immunotherapeutic responses to anti-PD-1, anti-CTLA-4, and MAGE-A3. On the contrary, the high MLPS group with more complex genomic alterations and poorer prognoses is more sensitive to the BRAF inhibitor dabrafenib, confirmed in patients with BRAF mutations. CONCLUSION: MLPS could independently and stably predict the prognosis of melanoma, considered a promising biomarker to identify patients suitable for immunotherapy and those with BRAF mutations who would benefit from dabrafenib.

Neuropilin-1 Facilitates Pseudorabies Virus Replication and Viral Glycoprotein B Promotes Its Degradation in a Furin-Dependent Manner.

Pseudorabies virus (PRV), which is extremely infectious and can infect numerous mammals, has a risk of spillover into humans. Virus-host interactions determine viral entry and spreading. Here, we showed that neuropilin-1 (NRP1) significantly potentiates PRV infection. Mechanistically, NRP1 promoted PRV attachment and entry, and enhanced cell-to-cell fusion mediated by viral glycoprotein B (gB), gD, gH, and gL. Furthermore, through in vitro coimmunoprecipitation (Co-IP) and bimolecular fluorescence complementation (BiFC) assays, NRP1 was found to physically interact with gB, gD, and gH, and these interactions were C-end Rule (CendR) motif independent, in contrast to currently known viruses. Remarkably, we illustrated that the viral protein gB promotes NRP1 degradation via a lysosome-dependent pathway. We further demonstrate that gB promotes NRP1 degradation in a furin-cleavage-dependent manner. Interestingly, in this study, we generated gB furin cleavage site (FCS)-knockout PRV (Δfurin PRV) and evaluated its pathogenesis; in vivo, we found that Δfurin PRV virulence was significantly attenuated in mice. Together, our findings demonstrated that NRP1 is an important host factor for PRV and that NRP1 may be a potential target for antiviral intervention. IMPORTANCE Recent studies have shown accelerated PRV cross-species spillover and that PRV poses a potential threat to humans. PRV infection in humans always manifests as a high fever, tonic-clonic seizures, and encephalitis. Therefore, understanding the interaction between PRV and host factors may contribute to the development of new antiviral strategies against PRV. NRP1 has been demonstrated to be a receptor for several viruses that harbor CendR, including SARS-CoV-2. However, the relationships between NRP1 and PRV are poorly understood. Here, we found that NRP1 significantly potentiated PRV infection by promoting PRV attachment and enhanced cell-to-cell fusion. For the first time, we demonstrated that gB promotes NRP1 degradation via a lysosome-dependent pathway. Last, in vivo, Δfurin PRV virulence was significantly attenuated in mice. Therefore, NRP1 is an important host factor for PRV, and NRP1 may be a potential target for antiviral drug development.

Computational Modeling to Determine the Effect of Phenotypic Heterogeneity in Tumors on the Collective Tumor-Immune Interactions.

Tumor immunotherapy aims to maintain or enhance the killing capability of CD8+ T cells to clear tumor cells. The tumor-immune interactions affect the function of CD8+ T cells. However, the effect of phenotype heterogeneity of a tumor mass on the collective tumor-immune interactions is insufficiently investigated. We developed the cellular-level computational model based on the principle of cellular Potts model to solve the case mentioned above. We considered how asymmetric division and glucose distribution jointly regulated the transient changes in the proportion of proliferating/quiescent tumor cells in a solid tumor mass. The evolution of a tumor mass in contact with T cells was explored and validated by comparing it with previous studies. Our modeling exhibited that proliferating/quiescent tumor cells, exhibiting distinct anti-apoptotic and suppressive behaviors, redistributed within the domain accompanied by the evolution of a tumor mass. Collectively, a tumor mass prone to a quiescent state weakened the collective suppressive functions of a tumor mass on cytotoxic T cells and triggered a decline of apoptosis of tumor cells. Although quiescent tumor cells did not sufficiently do their inhibitory functions, the possibility of long-term survival was improved due to their interior location within a mass. Overall, the proposed model provides a useful framework to investigate collective-targeted strategies for improving the efficiency of immunotherapy.

Evaluating angiotensin-converting enzyme 2-mediated SARS-CoV-2 entry across species.

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic represents a global threat, and the interaction between the virus and angiotensin-converting enzyme 2 (ACE2), the primary entry receptor for SARS-CoV-2, is a key determinant of the range of hosts that can be infected by the virus. However, the mechanisms underpinning ACE2-mediated viral entry across species remains unclear. Using infection assay, we evaluated SARS-CoV-2 entry mediated by ACE2 of 11 different animal species. We discovered that ACE2 of Rhinolophus sinicus (Chinese rufous horseshoe bat), Felis catus (domestic cat), Canis lupus familiaris (dog), Sus scrofa (wild pig), Capra hircus (goat), and Manis javanica (Malayan pangolin) facilitated SARS-CoV-2 entry into nonsusceptible cells. Moreover, ACE2 of the pangolin also mediated SARS-CoV-2 entry, adding credence to the hypothesis that SARS-CoV-2 may have originated from pangolins. However, the ACE2 proteins of Rhinolophus ferrumequinum (greater horseshoe bat), Gallus gallus (red junglefowl), Notechis scutatus (mainland tiger snake), or Mus musculus (house mouse) did not facilitate SARS-CoV-2 entry. In addition, a natural isoform of the ACE2 protein of Macaca mulatta (rhesus monkey) with the Y217N mutation was resistant to SARS-CoV-2 infection, highlighting the possible impact of this ACE2 mutation on SARS-CoV-2 studies in rhesus monkeys. We further demonstrated that the Y217 residue of ACE2 is a critical determinant for the ability of ACE2 to mediate SARS-CoV-2 entry. Overall, these results clarify that SARS-CoV-2 can use the ACE2 receptors of multiple animal species and show that tracking the natural reservoirs and intermediate hosts of SARS-CoV-2 is complex.

Biological and pharmacological roles of m6A modifications in cancer drug resistance.

Cancer drug resistance represents the main obstacle in cancer treatment. Drug-resistant cancers exhibit complex molecular mechanisms to hit back therapy under pharmacological pressure. As a reversible epigenetic modification, N6-methyladenosine (m6A) RNA modification was regarded to be the most common epigenetic RNA modification. RNA methyltransferases (writers), demethylases (erasers), and m6A-binding proteins (readers) are frequently disordered in several tumors, thus regulating the expression of oncoproteins, enhancing tumorigenesis, cancer proliferation, development, and metastasis. The review elucidated the underlying role of m6A in therapy resistance. Alteration of the m6A modification affected drug efficacy by restructuring multidrug efflux transporters, drug-metabolizing enzymes, and anticancer drug targets. Furthermore, the variation resulted in resistance by regulating DNA damage repair, downstream adaptive response (apoptosis, autophagy, and oncogenic bypass signaling), cell stemness, tumor immune microenvironment, and exosomal non-coding RNA. It is highlighted that several small molecules targeting m6A regulators have shown significant potential for overcoming drug resistance in different cancer categories. Further inhibitors and activators of RNA m6A-modified proteins are expected to provide novel anticancer drugs, delivering the therapeutic potential for addressing the challenge of resistance in clinical resistance.