Immune responses and reinfection of SARS-CoV-2 Omicron variant in patients with lung cancer.

A significant Omicron wave emerged in China in December 2022. To explore the duration of humoral and cellular response postinfection and the efficacy of hybrid immunity in preventing Omicron reinfection in patients with lung cancer, a total of 447 patients were included in the longitudinal study after the Omicron wave from March 2023 to August 2023. Humoral responses were measured at pre-Omicron wave, 3 months and 7 months postinfection. The detected severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) specific antibodies including total antibodies, anti-receptor binding domain (RBD) specific IgG, and neutralizing antibodies against SARS-CoV-2 wild type (WT) and BA.4/5 variant. T cell responses against SARS-CoV-2 WT and Omicron variant were evaluated in 101 patients by ELISpot at 3 months postinfection. The results showed that Omicron-infected symptoms were mild, while fatigue (30.2%), shortness of breath (34.0%) and persistent cough (23.6%) were long-lasting, and vaccines showed efficacy against fever in lung cancer patients. Humoral responses were higher in full or booster vaccinated patients than those unvaccinated (p < .05 for all four antibodies), and the enhanced response persisted for at least 7 months. T cell response to Omicron was higher than WT peptides (21.3 vs. 16.0 SFUs/106 PBMCs, p = .0093). Moreover, 38 (9.74%) patients were reinfected, which had lower antibody responses than non-reinfected patients (all p < .05), and those patients of unvaccinated at late stage receiving anti-cancer immunotherapy alone were at high risk of reinfection. Collectively, these data demonstrate the Omicron infection induces a high and durable immune response in vaccinated patients with lung cancer, which protects vaccinated patients from reinfection.

Tunlametinib (HL-085) plus vemurafenib in patients with advanced BRAF V600-mutant solid tumors: an open-label, single-arm, multicenter, phase I study.

BACKGROUND: Tunlametinib (HL-085) is a novel, highly selective MEK inhibitor with substantial clinical activities in patients with NRAS-mutant melanoma. This phase I study evaluated the safety and preliminary efficacy of tunlametinib plus vemurafenib in patients with advanced BRAF V600-mutant solid tumors. METHODS: Patients with confirmed advanced BRAF V600-mutant solid tumors who had progressed on or shown intolerance or no available standard therapies were enrolled and received tunlametinib plus vemurafenib. This study consisted of a dose-escalation phase and a dose-expansion phase. Primary end points of this study were safety, the recommended phase II dose (RP2D), and preliminary efficacy. RESULTS: From August 17, 2018 to April 19, 2022, 72 patients were enrolled. No dose-limiting toxicities occurred, and the maximum tolerated dose was not reached. The RP2D for BRAF V600-mutant non-small cell lung cancer (NSCLC) patients was tunlametinib 9 mg plus vemurafenib 720 mg, twice daily (BID, bis in die). Until the data cut-off date of December 15, 2023, of 33 NSCLC patients with evaluable disease, the objective response rate (ORR) was 60.6% (20/33; 95% confidence interval [CI], 42.1-77.1), the median progression free survival (PFS) was 10.5 months (95%CI, 5.6-14.5) and median duration of response (DoR) was 11.3 months (95%CI, 6.8-NE). At the RP2D, ORR was 60.0% (9/15; 95% CI, 32.3-83.7), the median PFS was 10.5 months (95%CI, 5.6 -NE) and median DoR was 11.3 months (95%CI, 3.9-NE). Of 24 colorectal cancer patients with evaluable disease, the ORR was 25.0% (6/24; 95% CI, 5.6-NE). All 72 patients had treatment-related adverse events (TRAEs), and the most common grade 3-4 TRAEs were anemia (n = 13, 18.1%) and blood creatine phosphokinase increased (n = 10, 13.9%). Tunlametinib was absorbed rapidly with Tmax of 0.5-1 h. Vemurafeinib did not influence the system exposure of tunlametinib and vice versa, indicating no drug-drug interaction for this combination. CONCLUSIONS: Tunlametinib (HL-085) plus vemurafenib had a favorable safety profile and showed promising antitumor activity in patients with BRAF V600-mutant solid tumors. The RP2D for NSCLC was tunlametinib 9 mg BID plus vemurafeinib 720 mg BID. TRIAL REGISTRATION: ClinicalTrials.gov, NCT03781219.

Single-cell and spatial transcriptomics reveal a high glycolysis B cell and tumor-associated macrophages cluster correlated with poor prognosis and exhausted immune microenvironment in diffuse large B-cell lymphoma.

BACKGROUND: Diffuse large B-cell lymphoma (DLBCL) is a heterogeneous malignancy characterized by varied responses to treatment and prognoses. Understanding the metabolic characteristics driving DLBCL progression is crucial for developing personalized therapies. METHODS: This study utilized multiple omics technologies including single-cell transcriptomics (n = 5), bulk transcriptomics (n = 966), spatial transcriptomics (n = 10), immunohistochemistry (n = 34), multiple immunofluorescence (n = 20) and to elucidate the metabolic features of highly malignant DLBCL cells and tumor-associated macrophages (TAMs), along with their associated tumor microenvironment. Metabolic pathway analysis facilitated by scMetabolism, and integrated analysis via hdWGCNA, identified glycolysis genes correlating with malignancy, and the prognostic value of glycolysis genes (STMN1, ENO1, PKM, and CDK1) and TAMs were verified. RESULTS: High-glycolysis malignant DLBCL tissues exhibited an immunosuppressive microenvironment characterized by abundant IFN_TAMs (CD68+CXCL10+PD-L1+) and diminished CD8+ T cell infiltration. Glycolysis genes were positively correlated with malignancy degree. IFN_TAMs exhibited high glycolysis activity and closely communicating with high-malignancy DLBCL cells identified within datasets. The glycolysis score, evaluated by seven genes, emerged as an independent prognostic factor (HR = 1.796, 95% CI: 1.077-2.995, p = 0.025 and HR = 2.631, 95% CI: 1.207-5.735, p = 0.015) along with IFN_TAMs were positively correlated with poor survival (p < 0.05) in DLBCL. Immunohistochemical validation of glycolysis markers (STMN1, ENO1, PKM, and CDK1) and multiple immunofluorescence validation of IFN_TAMs underscored their prognostic value (p < 0.05) in DLBCL. CONCLUSIONS: This study underscores the significance of glycolysis in tumor progression and modulation of the immune microenvironment. The identified glycolysis genes and IFN_TAMs represent potential prognostic markers and therapeutic targets in DLBCL.

Mutational variant allele frequency profile as a biomarker of response to immune checkpoint blockade in non-small cell lung Cancer.

INTRODUCTION: Identifying new biomarkers for predicting immune checkpoint inhibitors (ICIs) response in non-small cell lung cancer (NSCLC) is crucial. We aimed to assess the variant allele frequency (VAF)-related profile as a novel biomarker for NSCLC personalized therapy. METHODS: We utilized genomic data of 915 NSCLC patients via cBioPortal and a local cohort of 23 patients for model construction and mutational analysis. Genomic, transcriptomic data from 952 TCGA NSCLC patients, and immunofluorescence (IF) assessment with the local cohort supported mechanism analysis. RESULTS: Utilizing the random forest algorithm, a 15-gene VAF-related model was established, differentiating patients with durable clinical benefit (DCB) from no durable benefit (NDB). The model demonstrated robust performance, with ROC-AUC values of 0.905, 0.737, and 0.711 across training (n = 313), internal validation (n = 133), and external validation (n = 157) cohorts. Stratification by the model into high- and low-score groups correlated significantly with both progression-free survival (PFS) (training: P < 0.0001, internal validation: P < 0.0001, external validation: P = 0.0066) and overall survival (OS) (n = 341) (P < 0.0001). Notably, the stratification system was independent of PD-L1 (P < 0.0001) and TMB (P < 0.0001). High-score patients exhibited an increased DCB ratio and longer PFS across both PD-L1 and TMB subgroups. Additionally, the high-score group appeared influenced by tobacco exposure, with activated DNA damage response pathways. Whereas, immune/inflammation-related pathways were enriched in the low-score group. Tumor immune microenvironment analyses revealed higher proportions of exhausted/effector memory CD8 + T cells in the high-score group. CONCLUSIONS: The mutational VAF profile is a promising biomarker for ICI therapy in NSCLC, with enhanced therapeutic stratification and management as a supplement to PD-L1 or TMB.

Development and validation of a deep learning-based model to predict response and survival of T790M mutant non-small cell lung cancer patients in early clinical phase trials using electronic medical record and pharmacokinetic data.

Background: Epidermal growth factor receptor (EGFR) T790M mutation is the standard predictive biomarker for third-generation epidermal growth factor receptor tyrosine kinase inhibitor (EGFR-TKI) treatment. While not all T790M-positive patients respond to third-generation EGFR-TKIs and have a good prognosis, it necessitates novel tools to supplement EGFR genotype detection for predicting efficacy and stratifying EGFR-mutant patients with various prognoses. Mixture-of-experts (MoE) is designed to disassemble a large model into many small models. Meanwhile, it is also a model ensembling method that can better capture multiple patterns of intrinsic subgroups of enrolled patients. Therefore, the combination of MoE and Cox algorithm has the potential to predict efficacy and stratify survival in non-small cell lung cancer (NSCLC) patients with EGFR mutations. Methods: We utilized the electronic medical record (EMR) and pharmacokinetic parameters of 326 T790M-mutated NSCLC patients, including 283 patients treated with Abivertinib in phase I (n=177, for training) and II (n=106, for validation) clinical trials and an additional validation cohort 2 comprising 43 patients treated with BPI-7711. Furthermore, 18 patients underwent whole-exome sequencing for biological interpretation of CoxMoE. We evaluated the predictive performance for therapeutic response using the area under the curve (AUC) and the Concordance index (C-index) for progression-free survival (PFS). Results: CoxMoE exhibited AUCs of 0.73-0.83 for predicting efficacy defined by best overall response (BoR) and achieved C-index values of 0.64-0.65 for PFS prediction in training and validating cohorts. The PFS of 198 patients with a low risk [median, 6.0 (range, 1.0-23.3) months in the abivertinib treated cohort; median 16.5 (range, 1.4-27.4) months in BPI-7711 treated cohort] of being non-responder increased by 43% [hazard ratio (HR), 0.56; 95% confidence interval (CI), 0.40-0.78; P=0.0013] and 50% (HR, 0; 95% CI, 0-0; P=0.01) compared to those at high-risk [median, 4.2 (range, 1.0-35) months in the abivertinib treated cohort; median, 11.0 (range, 1.4-25.1) months in BPI-7711 treated cohort]. Additionally, activated partial thromboplastin time (APTT), creatinine clearance (Ccr), monocyte, and steady-state plasma trough concentration utilited to construct model were found significantly associated with drug resistance and aggressive tumor pathways. A robust correlation was observed between APTT and Ccr with PFS (log-rank test; P<0.01) and treatment response (Wilcoxon test; P<0.05), respectively. Conclusions: CoxMoE offers a valuable approach for patient selection by forecasting therapeutic response and PFS utilizing laboratory tests and pharmacokinetic parameters in the setting of early-phase clinical trials. Simultaneously, CoxMoE could predict the efficacy of third-generation EGFR-TKI non-invasively for T790M-positive NSCLC patients, thereby complementing existing EGFR genotype detection.

A systematic review and meta-analysis of the morbidity of efficacy endpoints and bleeding events in elderly and young patients treated with the same dose rivaroxaban.

Rivaroxaban is a new direct oral anticoagulant, and the same dose is recommended for older and young patients. However, recent real-world studies show that older patients may need dose adjustment to prevent major bleeding. At present, the evidence for dose adjustment in older patients is extremely limited with only a few reports on older atrial fibrillation patients. The aim of this study was to review the morbidity data of adverse events and bleeding events across all indications for older and young patients treated with the same dose of rivaroxaban to provide some support for dosage adjustment in older patients. The PubMed, EMBASE, ClinicalTrials, Cochrane and Web of Science databases were searched for randomized controlled trials (RCTs) published between January 1, 2005, and October 10, 2023. The primary outcomes were the morbidity of bleeding events and efficacy-related adverse events. Summary estimates were calculated using a random effects model. Eighteen RCTs were included in the qualitative analysis. The overall morbidity of primary efficacy endpoints was higher in older patients compared to the young patients (3.37% vs. 2.60%, χ2 = 5.24, p = 0.022). Similarly, a higher morbidity of bleeding was observed in older patients compared to the young patients (4.42% vs. 6.03%, χ2 = 13.22, p < 0.001). Among all indications, deep vein thrombosis, pulmonary embolism and atrial fibrillation were associated with the highest incidence of bleeding in older patients, suggesting that these patients may be most need dose adjustment. Patients older than 75 years may require extra attention to prevent bleeding. The same dose of rivaroxaban resulted in higher bleeding morbidity and morbidity of efficacy-related adverse events in older patients compared to the young patients. An individualized dose adjustment may be preferred for older patients rather than a fixed dose that fits all.

The Neurotranscriptome of Monochamus alternatus.

The Japanese pine sawyer Monochamus alternatus serves as the primary vector for pine wilt disease, a devastating pine disease that poses a significant threat to the sustainable development of forestry in the Eurasian region. Currently, trap devices based on informational compounds have played a crucial role in monitoring and controlling the M. alternatus population. However, the specific proteins within M. alternatus involved in recognizing the aforementioned informational compounds remain largely unclear. To elucidate the spatiotemporal distribution of M. alternatus chemosensory-related genes, this study conducted neural transcriptome analyses to investigate gene expression patterns in different body parts during the feeding and mating stages of both male and female beetles. The results revealed that 15 genes in the gustatory receptor (GR) gene family exhibited high expression in the mouthparts, most genes in the odorant binding protein (OBP) gene family exhibited high expression across all body parts, 22 genes in the odorant receptor (OR) gene family exhibited high expression in the antennae, a significant number of genes in the chemosensory protein (CSP) and sensory neuron membrane protein (SNMP) gene families exhibited high expression in both the mouthparts and antennae, and 30 genes in the ionotropic receptors (IR) gene family were expressed in the antennae. Through co-expression analyses, it was observed that 34 genes in the IR gene family were co-expressed across the four developmental stages. The Antenna IR subfamily and IR8a/Ir25a subfamily exhibited relatively high expression levels in the antennae, while the Kainate subfamily, NMDA subfamily, and Divergent subfamily exhibited predominantly high expression in the facial region. MalIR33 is expressed only during the feeding stage of M. alternatus, the MalIR37 gene exhibits specific expression in male beetles, the MalIR34 gene exhibits specific expression during the feeding stage in male beetles, the MalIR8 and MalIR39 genes exhibit specific expression during the feeding stage in female beetles, and MalIR8 is expressed only during two developmental stages in male beetles and during the mating stage in female beetles. The IR gene family exhibits gene-specific expression in different spatiotemporal contexts, laying the foundation for the subsequent selection of functional genes and facilitating the full utilization of host plant volatiles and insect sex pheromones, thereby enabling the development of more efficient attractants.

Machine learning assists prediction of genes responsible for plant specialized metabolite biosynthesis by integrating multi-omics data.

BACKGROUND: Plant specialized (or secondary) metabolites (PSM), also known as phytochemicals, natural products, or plant constituents, play essential roles in interactions between plants and environment. Although many research efforts have focused on discovering novel metabolites and their biosynthetic genes, the resolution of metabolic pathways and identified biosynthetic genes was limited by rudimentary analysis approaches and enormous number of candidate genes. RESULTS: Here we integrated state-of-the-art automated machine learning (ML) frame AutoGluon-Tabular and multi-omics data from Arabidopsis to predict genes encoding enzymes involved in biosynthesis of plant specialized metabolite (PSM), focusing on the three main PSM categories: terpenoids, alkaloids, and phenolics. We found that the related features of genomics and proteomics were the top two crucial categories of features contributing to the model performance. Using only these key features, we built a new model in Arabidopsis, which performed better than models built with more features including those related with transcriptomics and epigenomics. Finally, the built models were validated in maize and tomato, and models tested for maize and trained with data from two other species exhibited either equivalent or superior performance to intraspecies predictions. CONCLUSIONS: Our external validation results in grape and poppy on the one hand implied the applicability of our model to the other species, and on the other hand showed enormous potential to improve the prediction of enzymes synthesizing PSM with the inclusion of valid data from a wider range of species.

High-Throughput Antigen Microarray Identifies Longitudinal Prognostic Autoantibody for Chemoimmunotherapy in Advanced Non-Small Cell Lung Cancer.

Chemoimmunotherapy has evolved as a standard treatment for advanced non-small cell lung cancer (aNSCLC). However, inevitable drug resistance has limited its efficacy, highlighting the urgent need for biomarkers of chemoimmunotherapy. A three-phase strategy to discover, verify, and validate longitudinal predictive autoantibodies (AAbs) for aNSCLC before and after chemoimmunotherapy was employed. A total of 528 plasma samples from 267 aNSCLC patients before and after anti-PD1 immunotherapy were collected, plus 30 independent formalin-fixed paraffin-embedded samples. Candidate AAbs were firstly selected using a HuProt high-density microarray containing 21,000 proteins in the discovery phase, followed by validation using an aNSCLC-focused microarray. Longitudinal predictive AAbs were chosen for ELISA based on responders versus non-responders comparison and progression-free survival (PFS) survival analysis. Prognostic markers were also validated using immunohistochemistry and publicly available immunotherapy datasets. We identified and validated a panel of two AAbs (MAX and DHX29) as pre-treatment biomarkers and another panel of two AAbs (MAX and TAPBP) as on-treatment predictive markers in aNSCLC patients undergoing chemoimmunotherapy. All three AAbs exhibited a positive correlation with early responses and PFS (p < 0.05). The kinetics of MAX AAb showed an increasing trend in responders (p < 0.05) and a tendency to initially increase and then decrease in non-responders (p < 0.05). Importantly, MAX protein and mRNA levels effectively discriminated PFS (p < 0.05) in aNSCLC patients treated with immunotherapy. Our results present a longitudinal analysis of changes in prognostic AAbs in aNSCLC patients undergoing chemoimmunotherapy.

Single-cell and spatial analyses revealed the co-location of cancer stem cells and SPP1+ macrophage in hypoxic region that determines the poor prognosis in hepatocellular carcinoma.

In hepatocellular carcinoma (HCC), classical cancer stem cells (CSC) markers were shared by normal stem cells, targeting which may hinder hepatic regeneration and cause liver failure. Additionally, the spatial structure of CSC still remained elusive. To address these limitations, we undertook a comprehensive study combining single-cell data (56,022 cells from 20 samples) and spatial data (38,191 spots from eight samples) to obtain CSC signature and uncover its spatial structure. Utilizing the CytoTRACE algorithm, we discretely identified CSC, which displayed upregulated proliferation pathways regulated by HIF1A. A CSC signature of 107 genes was then developed using Weighted Gene Co-expression Network Analysis (WGCNA). Notably, HCC patients with high CSC levels exhibited an accumulation of SPP1+ macrophages (Macro_SPP1) expressing metalloproteinases (MMP9, MMP12, and MMP7) regulated by HIF1A, suggesting a hypoxic tumor region connecting Macro_SPP1 and CSC. Both CSC and Macro_SPP1 correlated with worse prognosis and undesirable immunotherapy response. Spatial analysis revealed the co-location of CSC and Macro_SPP1, with CD8 T cells excluded from the tumor region. The co-location area and non-tumor area of boundary exhibited a high level of hypoxia, with the HAVRC2 checkpoint highly expressed. Within the co-location area, the SPP1 signaling pathway was most active in cell-cell communication, with SPP1-CD44 and SPP1-ITGA/ITGB identified as the main ligand-receptor pairs. This study successfully constructed a CSC signature and demonstrated the co-location of CSC and Macro_SPP1 in a hypoxic region that exacerbates the tumor microenvironment in HCC.

The construction and evaluation of secretory expression engineering bacteria for the trans-Cry3Aa-T-HasA fusion protein against the Monochamus alternatus vector.

Pine wood nematode disease is currently the most deadly forest disease in China, and the Monochamus alternatus is its primary vector. Controlling the M. alternatus is crucial for managing pine wood nematode disease. This study, based on the selected HasA (pGHKW4) secretory expression vector, used electroporation to combine the genetically modified high-toxicity toxin Cry3Aa-T with the entomopathogenic bacterium Yersinia entomophaga isolated from the gut of the M. alternatus. The SDS-PAGE and Western blotting techniques were employed to confirm the toxin protein's secretion capability. The engineered bacteria's genetic stability and effectiveness in controlling M. alternatus were assessed for their insecticidal activity. The results of the SDS-PAGE and Western blotting analyses indicate that the HasA system effectively expresses toxin protein secretion, demonstrates certain genetic stability, and exhibits high insecticidal activity against M. alternatus. This study constructed a highly toxic entomopathogenic engineered bacterial strain against M. alternatus larvae, which holds significant implications for controlling M. alternatus, laying the foundation for subsequent research and application of this strain.

Longitudinal plasma proteomic profiling of EML4-ALK positive lung cancer receiving ALK-TKIs therapy.

BACKGROUND: Anaplastic lymphoma kinase-tyrosine kinase inhibitors (ALK-TKIs) has demonstrated remarkable therapeutic effects in ALK-positive non-small cell lung cancer (NSCLC) patients. Identifying prognostic biomarkers can enhance the clinical efficacy of relapsed or refractory patients. METHODS: We profiled 737 plasma proteins from 159 pre-treatment and on-treatment plasma samples of 63 ALK-positive NSCLC patients using data-independent acquisition-mass spectrometry (DIA-MS). The consensus clustering algorithm was used to identify subtypes with distinct biological features. A plasma-based prognostic model was constructed using the LASSO-Cox method. We performed the Mfuzz analysis to classify the patterns of longitudinal changes in plasma proteins during treatment. 52 baseline plasma samples from another independent ALK-TKI treatment cohort were collected to validate the potential prognostic markers using ELISA. RESULTS: We identified three subtypes of ALK-positive NSCLC with distinct biological features and clinical efficacy. Patients in subgroup 1 exhibited activated humoral immunity and inflammatory responses, increased expression of positive acute-phase response proteins, and the worst prognosis. Then we constructed and verified a prognostic model that predicts the efficacy of ALK-TKI therapy using the expression levels of five plasma proteins (SERPINA4, ATRN, APOA4, TF, and MYOC) at baseline. Next, we explored the longitudinal changes in plasma protein expression during treatment and identified four distinct change patterns (Clusters 1-4). The longitudinal changes of acute-phase proteins during treatment can reflect the treatment status and tumor progression of patients. Finally, we validated the prognostic efficacy of baseline plasma CRP, SAA1, AHSG, SERPINA4, and TF in another independent NSCLC cohort undergoing ALK-TKI treatment. CONCLUSIONS: This study contributes to the search for prognostic and drug-resistance biomarkers in plasma samples for ALK-TKI therapy and provides new insights into the mechanism of drug resistance and the selection of follow-up treatment.

Longitudinal plasma proteomic analysis identifies biomarkers and combinational targets for anti-PD1-resistant cancer patients.

The response rate of anti-PD1 therapy is limited, and the influence of anti-PD1 therapy on cancer patients is unclear. To address these challenges, we conducted a longitudinal analysis of plasma proteomic changes with anti-PD1 therapy in non-small cell lung cancer (NSCLC), alveolar soft part sarcoma (ASPS), and lymphoma patients. We included 339 plasma samples before and after anti-PD1 therapy from 193 patients with NSCLC, ASPS, or lymphoma. The plasma proteins were detected using data-independent acquisition-mass spectrometry and customable antibody microarrays. Differential proteomic characteristics in responders (R) and non-responders (NR) before and after anti-PD1 therapy were elucidated. A total of 1019 proteins were detected using our in-depth proteomics platform and distributed across 10-12 orders of abundance. By comparing the differential plasma proteome expression between R and NR groups, 50, 206, and 268 proteins were identified in NSCLC, ASPS, and lymphoma patients, respectively. Th17, IL-17, and JAK-STAT signal pathways were identified upregulated in NR group, while cellular senescence and transcriptional misregulation pathways were activated in R group. Longitudinal proteomics analysis revealed the IL-17 signaling pathway was downregulated after treatment. Consistently, many proteins were identified as potential combinatorial therapeutic targets (e.g., IL-17A and CD22). Five noninvasive biomarkers (FLT4, SFTPB, GNPTG, F5, and IL-17A) were further validated in an independent lymphoma cohort (n = 39), and another three noninvasive biomarkers (KIT, CCL3, and TNFSF1) were validated in NSCLC cohort (n = 76). Our results provide molecular insights into the anti-PD1 therapy in cancer patients and identify new therapeutic strategies for anti-PD1-resistant patients.

Assessing the impact of pine wilt disease on aboveground carbon storage in planted Pinus massoniana Lamb. forests via remote sensing.

The continuous spread of Bursaphelenchus xylophilus (Steiner and Buhrer) Nickle, commonly known as the organism that causes pine wilt disease (PWD), has become a notable threat to forest security in East Asia and southern Europe, and an assessment of the carbon loss caused by PWD damage is important to achieving carbon neutrality. This study used satellite remote sensing and 15-year ground monitoring data to measure the impact of PWD on the carbon storage of Pinus massoniana Lamb. (P. massoniana), the conifer with the largest planted area in southern China. This study showed that the occurrence of PWD had an impact on the increase in carbon storage of P. massoniana. The infected and dead P. massoniana trees accounted for only 1.46 % of the total number of trees but caused a carbon storage loss of 1.99 t/ha, which accounted for 6.23 % of the total carbon sink in healthy P. massoniana forests over the last 15 years. The most pronounced decline in carbon storage occurred in the first five years of PWD invasion. After 10 years of clearcutting and replanting of Schima superba Gardn. et Champ., the increase in carbon storage of the reformed forest far exceeded that of the healthy forest during the same period, which was 2.04 times (10 years) and 1.56 times (15 years) that of the healthy P. massoniana forest. In addition, our study found that during the 15-year period (from the forest age of 22 to the forest age of 37), the average carbon storage of P. massoniana forest was 31.9 t/ha. This study helps to evaluate the impact of PWD on the carbon sink of pine forests and provides methodological references for analyzing the impact of biological disturbances on the carbon cycle.

Identification of novel prognostic autoantibodies in diffuse large B-cell lymphoma treated with rituximab plus cyclophosphamide, doxorubicin, vincristine, and prednisone via a high-throughput antigen microarray.

BACKGROUND: R-CHOP (rituximab plus cyclophosphamide, doxorubicin, vincristine, and prednisone) is a standard first-line treatment for diffuse large B-cell lymphoma (DLBCL). However, 20%-40% of patients survive less than 5 years. Novel prognostic biomarkers remain in demand. METHODS: Baseline plasma autoantibodies (AAbs) were assessed in 336 DLBCLs. In the discovery phase (n = 20), a high-density antigen microarray (∼21,000 proteins) was used to expound AAb profiles. In the verification phase (n = 181), with a DLBCL-focused microarray, comparative results based on event-free survival at 24 months (EFS24) and lasso Cox regression models of progression-free survival (PFS) and overall survival (OS) were integrated to identify potential biomarkers. They were further validated by enzyme-linked immunosorbent assay in validation phase 1 (n = 135) and a dynamic cohort (n = 12). In validation phase 2, a two-AAb-based risk score was established. They were further validated in an immunohistochemistry cohort (n = 55) and four independent Gene Expression Omnibus datasets (n = 1598). RESULTS: Four AAbs (CREB1, N4BP1, UBAP2, and DEAF1) were identified that showed associations with EFS24 status (p < .05) and superior PFS and OS (p < .05). A novel risk score model based on CREB1 and N4BP1 AAbs was developed to predict PFS with areas under the curve of 0.72, 0.71, 0.76, and 0.82 at 1, 3, 5, and 7 years, respectively, in DLBCL treated with R-CHOP independent of the International Prognostic Index (IPI) and provided significant additional recurrence risk discrimination (p < .05) for the IPI. CREB1 and N4BP1 proteins and messenger RNAs were also associated with better PFS and OS (p < .05). CONCLUSIONS: This study identified a novel prognostic panel of CREB1, N4BP1, DEAF1, and UBAP2 AAbs that is independent of the IPI in DLBCL.

CIRBP Increases the synthesis and secretion of steroid hormones by in yak granulaso cells.

As a regulatory protein that upregulates transcription in response to various stresses, cold-induced RNA-binding protein (CIRBP) is involved in a variety of physiological pathological processes in cells. However, little is known about the role of CIRBP in regulating autophagy and the synthesis and secretion of ovarian steroid hormones (estradiol E2 and progesterone P4). This study aimed to explore whether the synthetic secretion of ovarian steroid hormones is related to CIRBP-regulated autophagy. We detected the differential expression of CIRBP, LC3, E2 and P4 in YGCs cultured at mild low temperature (32 °C) for 6 and 12 h. CIRBP, LC3, E2 and P4 expression was increased in response to low temperature in YGCs. In order to illustrate that the changes in secretion of E2/P4 and autophagy might be caused by CIRBP induced by low temperature, we overexpressed CIRBP in YGCs cultured in vitro to detect its effects on autophagy and steroid hormone synthesis and secretion. We found that overexpression of CIRBP can induce autophagy of YGCs and enhance the synthesis and secretion of E2 and P4, suggesting that mild hypothermia may activate autophagy by inducing the expression of CIRBP and enhance the synthesis and secretion of E2 and P4. To further explore the relationship between CIRBP regulated autophagy and steroid hormone synthesis and secretion, we verified it by regulating autophagy. The results showed that Inhibition of autophagy significantly reversed CIRBP overexpression-enhanced autophagy and synthetic secretion of E2, P4 in YGCs, while activated autophagy showed similar results to overexpression of CIRBP. In conclusion, our data suggest that autophagy is involved in the synthesis and secretion of YGCs E2 and P4 and is associated with overexpression of CIRBP.

Discovery and Characterization of MaK: A Novel Knottin Antimicrobial Peptide from Monochamus alternatus.

Knottin-type antimicrobial peptides possess exceptional attributes, such as high efficacy, low vulnerability to drug resistance, minimal toxicity, and precise targeting of drug sites. These peptides play a crucial role in the innate immunity of insects, offering protection against bacteria, fungi, and parasites. Knottins have garnered considerable interest as promising contenders for drug development due to their ability to bridge the gap between small molecules and protein-based biopharmaceuticals, effectively addressing the therapeutic limitations of both modalities. This work presents the isolation and identification of a novel antimicrobial peptide derived from Monochamus alternatus. The cDNA encodes a 56-amino acid knottin propeptide, while the mature peptide comprises only 34 amino acids. We have labeled this knottin peptide as MaK. Using chemically synthesized MaK, we evaluated its hemolytic activity, thermal stability, antibacterial properties, and efficacy against nematodes. The results of this study indicate that MaK is an exceptionally effective knottin-type peptide. It demonstrates low toxicity, superior stability, potent antibacterial activity, and the ability to suppress pine wood nematodes. Consequently, these findings suggest that MaK has potential use in developing innovative therapeutic agents to prevent and manage pine wilt disease.

Synthetic CRISPR/dCas9-KRAB system driven by specific PSA promoter suppresses malignant biological behavior of prostate cancer cells through negative feedback inhibition of PSA expression.

PSA is a type of proto-oncogene that is specifically and highly expressed in embryonic and prostate cancer cells, but not expressed in normal prostate tissue cells. The specific expression of prostate-specific antigen (PSA) is found to be related with the conditional transcriptional regulation of its promoter. Clustered regularly interspaced short palindromic repeats (CRISPR)-dCas9-KRAB is a newly developed transcriptional regulatory system that inhibits gene expression by interupting the DNA transcription process. Induction of CRISPR-dCas9-KRAB expression through the PSA promoter may help feedback inhibition of cellular PSA gene expression via single guide RNA (sgRNA), thereby monitoring and suppressing the malignant state of tumor cells. In this study, we examined the transcriptional activity of the PSA promoter in different prostate cancer cells and normal prostate epithelial cells and determined that it is indeed a prostate cancer cell-specific promoter.Then we constructed the CRISPR-dCas9-KRAB system driven by the PSA promoter, which can inhibit PSA gene expression in the prostate cancer cells at the transcriptional level, and therefore supress the malignant growth and migration of prostate cancer cells and promote their apoptosis in vitro. This study provides a potentially effective anti-cancer strategy for gene therapy of prostate cancer.

Immunogenicity assessment of elder hepatocellular carcinoma patients after inactivated whole-virion SARS-CoV-2 vaccination.

BACKGROUND: Research on immunogenicity after 3rd SARS-CoV-2 vaccine in elder hepatocellular carcinoma (HCC) was limited. This study aimed to investigate the efficacy and influencing factors of inactivated SARS-CoV-2 vaccine in elder HCC. RESEARCH DESIGN AND METHODS: We assessed total antibodies, anti-RBD IgG, and neutralizing antibodies (NAb) toward SARS-CoV-2 wild type (WT) as well as BA.4/5 in 304 uninfected HCC, 147 matched healthy control (HC), and 53 SARS-CoV-2 infected HCC, all aged over 60 years. The levels of antibodies were compared in the period 7-90, 91-180, and >180 days after 2nd or 3rd vaccination, respectively. RESULTS: HCC had lower seropositivity than HC after 2nd dose (total antibodies, 64% vs. 92%, P < 0.0001; anti-RBD IgG, 50% vs. 77%, P < 0.0001). But 3rd dose can efficaciously close the gap (total antibodies, 96% vs. 100%, P = 0.1212; anti-RBD IgG: 87% vs. 87%, P > 0.9999). Booster effect of 3rd dose can persist >180 days in HCC (2nd vs. 3rd: total antibodies, 0.60 vs. 3.20, P < 0.0001; anti-RBD IgG, 13.86 vs. 68.85, P < 0.0001; WT NAb, 11.70 vs. 22.47, P < 0.0001). Vaccinated HCC had more evident humoral responses than unvaccinated ones after infection (total antibodies: 3.85 vs. 3.20, P < 0.0001; anti-RBD IgG: 910.92 vs. 68.85, P < 0.0001; WT NAb: 96.09 vs. 22.47, P < 0.0001; BA.4/5 NAb: 86.53 vs. 5.59, P < 0.0001). CONCLUSIONS: Our findings highlight the booster effect and protective role of 3rd dose. Our results could provide a theoretical foundation for informing decisions regarding SARS-CoV-2 vaccination in elder HCC.

Rapid ultra-performance liquid chromatography-tandem mass spectrometry method for the simultaneous determination of three characteristic urinary saccharide metabolites in patients with glycogen storage diseases (type â b and â ¡).

Urinary 1,5-anhydroglucitol (1, 5-AG), 6-α-D-glucopyranosyl-maltotriose (Glc4) and maltotetraose (M4) are important biomarkers for glycogen storage disease (types Ib and Ⅱ). This study aimed to develop and validate an ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) to detect these three urinary saccharide metabolites. Urine samples were diluted and then analyzed. Chromatographic separation was performed on an Acquity™ UPLC Amide column (2.1 × 100 mm, 1.7 µm) with gradient elution. The quantitation of analytes was achieved on a 5500 Qtrap mass spectrometer using negative multiple reaction monitoring (MRM) mode. The calibration curves for all analytes were linear over the range of 0.500 to 100 µg/mL with a correlation coefficient, R2 ≥ 0.999. The percent relative standard deviations (RSD%) were ≤12.8%, and the percent relative errors (RE%) were in the range of -11.7%-11.0%. The relative matrix effects of all analytes were between 87.2% and 104% with RSD% < 3.10% across three concentrations. The developed analytical method was simple, accurate, and reliable for rapid and simultaneous analysis of these three urinary saccharide metabolites. It was applied to healthy volunteers and patients. To our knowledge, it was the first validated assay for urinary maltotetraose quantification. This work provides support for exploring the potential of maltotetraose as a biomarker for Pompe disease.