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Synthetic lethality is emerging as an important cancer therapeutic paradigm, while the comprehensive selective treatment opportunities for various tumors have not yet been explored. We develop the Synthetic Lethality Knowledge Graph (SLKG), presenting the tumor therapy landscape of synthetic lethality (SL) and synthetic dosage lethality (SDL). SLKG integrates the large-scale entity of different tumors, drugs and drug targets by exploring a comprehensive set of SL and SDL pairs. The overall therapy landscape is prioritized to identify the best repurposable drug candidates and drug combinations with literature supports, in vitro pharmacologic evidence or clinical trial records. Finally, cladribine, an FDA-approved multiple sclerosis treatment drug, is selected and identified as a repurposable drug for treating melanoma with CDKN2A mutation by in vitro validation, serving as a demonstrating SLKG utility example for novel tumor therapy discovery. Collectively, SLKG forms the computational basis to uncover cancer-specific susceptibilities and therapy strategies based on the principle of synthetic lethality. Various methods have been proposed to identify synthetic lethality interactions, but selective treatment opportunities for various tumors have not yet been explored. Here, the authors develop the Synthetic Lethality Knowledge Graph webserver (SLKG, http://www.slkg.net) to explore the comprehensive tumor therapy landscape and uncover cancer-specific susceptibilities based on the principle of synthetic lethality.

Acute myeloid leukemia (AML) is one of the most common hematopoietic malignancies that has an unfavorable outcome and a high rate of relapse. Autophagy plays a vital role in the development of and therapeutic responses to leukemia. This study identifies a potential autophagy-related signature to monitor the prognoses of patients of AML. Transcriptomic profiles of AML patients (GSE37642) with the relevant clinical information were downloaded from Gene Expression Omnibus (GEO) as the training set while TCGA-AML and GSE12417 were used as validation cohorts. Univariate regression analyses and multivariate stepwise Cox regression analysis were respectively applied to identify the autophagy-related signature. The univariate Cox regression analysis identified 32 autophagy-related genes (ARGs) that were significantly associated with the overall survival (OS) of the patients, and were mainly rich in signaling pathways for autophagy, p53, AMPK, and TNF. A prognostic signature that comprised eight ARGs (BAG3, CALCOCO2, CAMKK2, CANX, DAPK1, P4HB, TSC2, and ULK1) and had good predictive capacity was established by LASSO–Cox stepwise regression analysis. High-risk patients were found to have significantly shorter OS than patients in low-risk group. The signature can be used as an independent prognostic predictor after adjusting for clinicopathological parameters, and was validated on two external AML sets. Differentially expressed genes analyzed in two groups were involved in inflammatory and immune signaling pathways. An analysis of tumor-infiltrating immune cells confirmed that high-risk patients had a strong immunosuppressive microenvironment. Potential druggable OS-related ARGs were then investigated through protein–drug interactions. This study provides a systematic analysis of ARGs and develops an OS-related prognostic predictor for AML patients. Further work is needed to verify its clinical utility and identify the underlying molecular mechanisms in AML.

Glutathione peroxidases (GPxs) are a family of enzymes comprising eight members known for their peroxidase activity, which helps relieve oxidative stress by reducing hydrogen peroxide and lipid peroxides. GPxs play a crucial role in tumorigenesis, affecting DNA integrity, proliferation, cell adhesion, and survival. However, a comprehensive analysis of the expression and prognostic relevance of GPx members in gastric cancer (GC) remains underexplored. This study explored the relationship between GPx mRNA expression and prognosis in GC patients across different Lauren classifications (intestinal, diffuse, and mixed types). We found that GPx1 and GPx4 were highly expressed in all GC subtypes compared to normal tissues, while GPx7 expression was notably elevated in mixed-type GC. These findings were consistent across multiple Oncomine datasets and partially validated in TCGA GC versus normal samples. Kaplan-Meier survival analysis showed that high mRNA expression of GPx3, GPx5, GPx6, and GPx7 was associated with poor overall survival (OS) at both 5- and 10-year intervals. In contrast, elevated GPx1 expression correlated with better OS at both 5 and 10 years. Additionally, high GPx4, GPx5, and GPx6/7 expression were linked to reduced first progression (FP), while increased GPx3, GPx4, and GPx6/7 levels were associated with shorter post-progression survival (PPS). These trends were consistent for both 5- and 10-year FP and PPS. Prognostic associations were partially validated using TCGA data. Subgroup analyses based on Lauren classification, clinicopathological features, and treatment further supported these observations. This study highlights the distinct prognostic roles of GPx family members in GC. High GPx1 expression is associated with favorable outcomes, whereas elevated levels of GPx3, GPx4, GPx5, and GPx6/7 are linked to poor prognosis in GC patients, including OS, FP, and PPS. In addition to confirming previous findings, this study suggests that GPx4, GPx5, and GPx6/7 could serve as valuable prognostic markers and potential therapeutic targets in GC. Further clinical studies are needed to validate these findings and explore GPx-targeted therapies for GC.

Traditional Chinese medicine (TCM) has garnered attention for its potential in cancer therapy. Yinchen Wuling San (YWLS), a classical herbal formula, has been traditionally used for liver-related conditions, but its bioactive components and molecular mechanisms relevant to hematologic malignancies such as acute myeloid leukemia (AML) remain unclear. This study aims to identify the active compounds and potential molecular targets of Yinchen Wuling San in the context of AML through network pharmacology analysis, and to experimentally validate the effects of selected candidate compounds in AML models. Active ingredients from six YWLS herbs were screened via the TCMSP database using oral bioavailability ≥30% and DL ≥0.18 thresholds. Targets were predicted using SwissTargetPrediction, and AML-related genes were obtained from DisGeNET and GeneCards. Key overlapping targets were analyzed via STRING PPI networks and GO/KEGG enrichment. Molecular docking was performed between three core compounds (genkwanin, isorhamnetin, quercetin) and hub proteins (e.g., SRC) using Sybyl-X. ADME profiles were predicted using SwissADME, and molecular dynamics simulations (GROMACS) assessed complex stability. These compounds were further evaluated (viability, apoptosis, cell cycle, RT-qPCR, flow cytometry) and using an AML xenograft mouse model. Of 621 YWLS targets, 113 overlapped with 1,247 AML-related genes. PPI analysis identified hub genes, including AKT1, SRC, and EGFR. Enrichment analysis highlighted PI3K-AKT, MAPK, and JAK-STAT pathways. Genkwanin, isorhamnetin, and quercetin were predicted to target SRC, with strong molecular docking affinities. ADME analysis suggested favorable pharmacokinetics, and molecular dynamics simulations confirmed structural stability. , these compounds exhibited dose-dependent cytotoxicity, induced apoptosis, modulated the cell cycle, and downregulated SRC expression. Notably, Genkwanin promoted CD8 T cell proliferation and inhibited leukemia growth, improving survival in a leukemia xenograft model. YWLS compounds, particularly Genkwanin, exhibit significant anti-leukemic activity via apoptosis induction, cell cycle modulation, and promote T cells proliferation. Genkwanin emerges as a promising therapeutic candidate for AML, warranting further clinical investigation.

Aberrant fatty acid metabolism (FAM) plays a critical role in the tumorigenesis of human malignancies. However, studies on its impact in lung adenocarcinoma (LUAD) are limited. We developed a prognostic signature comprising 10 FAM-related genes (GPR115, SOAT2, CDH17, MOGAT2, COL11A1, TCN1, LGR5, SLC34A2, RHOV, and DKK1) using data from LUAD patients in The Cancer Genome Atlas (TCGA). This signature was validated using six independent LUAD datasets from the Gene Expression Omnibus (GEO). Patients were classified into high- and low-risk groups, and overall survival (OS) was compared by Kaplan-Meier analysis. The signature's independence as a prognostic indicator was assessed after adjusting for clinicopathological features. Receiver operating characteristic (ROC) analysis validated the signature. Tumor immune microenvironment (TIME) was analyzed using ESTIMATE and multiple deconvolution algorithms. Functional assays, including CCK8, cell cycle, apoptosis, transwell, and wound healing assays, were performed on MOGAT2-silenced H1299 cells using CRISPR/Cas9 technology. Low-risk group patients exhibited decreased OS. The signature was an independent prognostic indicator and demonstrated strong risk-stratification utility for disease relapse/progression. ROC analysis confirmed the signature's validity across validation sets. TIME analysis revealed higher infiltration of CD8+ T cells, natural killers, and B cells, and lower tumor purity, stemness index, and tumor mutation burden (TMB) in low-risk patients. These patients also showed elevated T cell receptor richness and diversity, along with reduced immune cell senescence. High-risk patients exhibited enrichment in pathways related to resistance to immune checkpoint blockades, such as DNA repair, hypoxia, epithelial-mesenchymal transition, and the G2M checkpoint. LUAD patients receiving anti-PD-1 treatment had lower risk scores among responders compared to non-responders. MOGAT2 was expressed at higher levels in low-risk LUAD patients. Functional assays revealed that MOGAT2 knockdown in H1299 cells promoted proliferation and migration, induced G2 cell cycle arrest, and decreased apoptosis. This FAM-related gene signature provides a valuable tool for prognostic stratification and monitoring of TIME and immunotherapy responses in LUAD. MOGAT2 is identified as a potential anti-tumor regulator, offering new insights into its role in LUAD pathogenesis.

Background Cancer neoantigens are expressed only in cancer cells and presented on the tumor cell surface in complex with major histocompatibility complex (MHC) class I proteins for recognition by cytotoxic T cells. Accurate and rapid identification of neoantigens play a pivotal role in cancer immunotherapy. Although several in silico tools for neoantigen prediction have been presented, limitations of these tools exist. Results We developed pTuneos , a computational pipeline for p rioritizing tu mor neo antigens from next-generation s equencing data. We tested the performance of pTuneos on the melanoma cancer vaccine cohort data and tumor-infiltrating lymphocyte (TIL)-recognized neopeptide data. pTuneos is able to predict the MHC presentation and T cell recognition ability of the candidate neoantigens, and the actual immunogenicity of single-nucleotide variant (SNV)-based neopeptides considering their natural processing and presentation, surpassing the existing tools with a comprehensive and quantitative benchmark of their neoantigen prioritization performance and running time. pTuneos was further tested on The Cancer Genome Atlas (TCGA) cohort data as well as the melanoma and non-small cell lung cancer (NSCLC) cohort data undergoing checkpoint blockade immunotherapy. The overall neoantigen immunogenicity score proposed by pTuneos is demonstrated to be a powerful and pan-cancer marker for survival prediction compared to traditional well-established biomarkers. Conclusions In summary, pTuneos provides the state-of-the-art one-stop and user-friendly solution for prioritizing SNV-based candidate neoepitopes, which could help to advance research on next-generation cancer immunotherapies and personalized cancer vaccines. pTuneos is available at https://github.com/bm2-lab/pTuneos , with a Docker version for quick deployment at https://cloud.docker.com/u/bm2lab/repository/docker/bm2lab/ptuneos .

Acute myeloid leukemia (AML) is one of the most aggressive hematological malignancies with a low 5-year survival rate and high rate of relapse. Developing more efficient therapies is an urgent need for AML treatment. Accumulating evidence showed that ferroptosis, an iron-dependent form of programmed cell death, is closely correlated with cancer initiation and clinical outcome through reshaping the tumor microenvironment. However, understanding of AML heterogeneity based on extensive profiling of ferroptosis signatures remains to be investigated yet. Herein, five independent AML transcriptomic datasets (TCGA-AML, GSE37642, GSE12417, GSE10358, and GSE106291) were obtained from the GEO and TCGA databases. Then, we identified two ferroptosis-related molecular subtypes (C1 and C2) with distinct prognosis and tumor immune microenvironment (TIME) by consensus clustering. Patients in the C1 subtype were associated with favorable clinical outcomes and increased cytotoxic immune cell infiltration, including CD8 + /central memory T cells, natural killer (NK) cells, and non-regulatory CD4 + T cells while showing decreased suppressive immune subsets such as M2 macrophages, neutrophils, and monocytes. Functional enrichment analysis of differentially expressed genes (DEGs) implied that cell activation involved in immune response, leukocyte cell–cell adhesion and migration, and cytokine production were the main biological processes. Phagosome, antigen processing and presentation, cytokine–cytokine receptor interaction, B-cell receptor, and chemokine were identified as the major pathways. To seize the distinct landscape in C1 vs. C2 subtypes, a 5-gene prognostic signature (LSP1, IL1R2, MPO, CRIP1, and SLC24A3) was developed using LASSO Cox stepwise regression analysis and further validated in independent AML cohorts. Patients were divided into high- and low-risk groups, and decreased survival rates were observed in high- vs. low-risk groups. The TIME between high- and low-risk groups has a similar scenery in C1 vs. C2 subtypes. Single-cell-level analysis verified that LSP1 and CRIP1 were upregulated in AML and exhausted CD8 + T cells. Dual targeting of these two markers might present a promising immunotherapeutic for AML. In addition, potential effective chemical drugs for AML were predicted. Thus, we concluded that molecular subtyping using ferroptosis signatures could characterize the TIME and provide implications for monitoring clinical outcomes and predicting novel therapies.

Bovine mastitis remains a globally prevalent disease, with the limitations of antibiotic-based treatments—such as the rise in antimicrobial resistance and the presence of drug residues—highlighting the urgent need for alternative therapeutic approaches. Inflammation is intricately linked to various cytokines and immunomodulatory proteins, among which cyclophilin A (CypA) serves as a pivotal inflammatory mediator, significantly contributing to the initiation and amplification of inflammatory responses under such conditions. The acquisition of high-purity recombinant protein is a fundamental prerequisite for in vitro functional studies of bovine CypA. This study aimed to construct a eukaryotic expression vector for bovine CypA and verify its expression in CHO-K1 cells. Utilizing the bovine CypA gene sequence available in GenBank, the coding region was artificially synthesized and optimized for codon usage, subsequently being inserted into the pPB[Exp] backbone vector via BsrGI and BstEII double digestion. The resulting polycistronic expression vector contained a CAG promoter driving the CypA transcription, an EF1α promoter driving the EGFP reporter gene, a PGK promoter controlling the puromycin resistance gene, and a C-terminal His-tag. Restriction enzyme digestion and bidirectional Sanger sequencing confirmed that the inserted fragment sequence was completely consistent with the optimized design. Robust EGFP fluorescence was observed 24 h post-transfection and remained stable after puromycin selection. qPCR analysis showed that the Ct value of CypA in the experimental group was 16.20 ± 0.04, while no amplification signal was detected in the control group. Additionally, Western blot analysis identified a CypA-specific band at approximately 18 kDa, confirming the correct expression of the exogenous CypA protein in CHO-K1 cells. Collectively, these results demonstrate the successful construction and validation of a bovine CypA eukaryotic expression vector. The established CHO-K1 expression system exhibited stable and efficient expression, thereby providing a robust foundation for future research on the production and application of recombinant CypA protein.

In the context of semen cryopreservation, egg yolk is frequently utilized as a protective agent; however, it poses a potential risk of contamination by pathogenic microorganisms. Pasteurization of egg yolk can effectively eliminate pathogenic bacteria while retaining its active components. This study established two groups for comparison: (1) the experimental group (PS), which utilized a diluent containing pasteurized chicken egg yolk, and (2) the control group (Control), which employed a diluent with chicken egg yolk mixed at ambient temperature. The diluents from both groups were subjected to microscopic structural observation, bacterial isolation and culture, as well as Gram staining. Boar semen was cryopreserved using two different diluents following standard methods. Following thawing, sperm motility parameters, acrosome and plasma membrane integrity, antioxidant indicators, reactive oxygen species (ROS) levels, and the expression of genes related to oxidative stress and apoptosis were assessed. Microscopic observation revealed no significant differences in yolk granule morphology between PS and the control. Bacterial isolation and Gram staining results indicated the presence of small, spherical Gram-positive bacteria in the control, whereas no bacterial growth was observed in the PS. Post-thaw sperm analysis showed that, compared to the control, the PS exhibited significantly lower sperm survival rate and motility ( P  < 0.05), but significantly higher values for straight line velocit (VSL), curvilinear velocity (VCL), and average path velocity (VAP) ( P  < 0.05). Although the integrity of the acrosome and plasma membrane in sperm from the PS group showed improvement compared to the control, this difference did not reach statistical significance ( P  > 0.05). The levels of malondialdehyde (MDA) and total antioxidant capacity (T-AOC) in the PS group were significantly lower ( P  < 0.05), while the levels of superoxide dismutase (SOD) and catalase (CAT) showed a decreasing trend, but the difference was not significant ( P  > 0.05).The content of reactive oxygen species (ROS) in the PS group was significantly lower than that in the control group ( P  < 0.05). Gene expression analysis related to cellular oxidative stress and apoptosis showed that the mRNA levels of CAT, SOD, P53, and Bax were lower in the PS than in the control, with CAT expression significantly diminished ( P  < 0.05), and Bcl-2 expression slightly elevated ( P  > 0.05). In conclusion, pasteurized chicken egg yolk diluent can effectively eliminate pathogenic bacteria, reduce oxidative damage to sperm, and lower sperm apoptosis rate. Nonetheless, it is important to note that in the PS group, the post-thaw survival rate and motility of porcine sperm were markedly diminished, accompanied by an upregulation of certain apoptosis-related genes.

Understanding the role of the STAT family in gastric cancer (GC) is essential for developing targeted therapies and improving patient outcomes. However, comprehensive analysis of STAT expression and its prognostic significance in GC is limited. This study aims to address this gap by examining STAT expression in normal and GC tissues and evaluating its prognostic value across clinical subgroups. STAT mRNA expression levels were compared between tumor and normal tissues using fold change analysis. Kaplan-Meier curves assessed the correlation between STAT expression and clinical outcomes, with statistical significance determined by the Log-rank test and hazard ratios (HR) with 95% confidence intervals. Subset analyses evaluated STAT expression across GC subtypes and its prognostic value, including in patients with oncogenic mutations. Most STAT family members, except STAT4, showed increased expression in GC tissues compared to normal tissues, consistent across various clinical subgroups, suggesting a role in GC pathogenesis. Kaplan-Meier analysis revealed the prognostic significance of STATs in GC. High STAT1 expression was associated with improved overall survival (OS), first progression (FP), and post-progression survival (PPS), indicating a favorable prognosis. In contrast, elevated STAT5A, STAT5B, and STAT6 expression correlated with poor prognosis. Subgroup analysis highlighted the consistent prognostic value of STATs across different histological subtypes, particularly in intestinal-type GC. Additionally, STAT expression had differential prognostic implications based on HER2 status. HER2-positive GC patients with high STAT expression had worse OS and FP rates, while HER2-negative patients with high STAT1 expression had better survival outcomes. This study provides valuable insights into STAT expression patterns and their prognostic significance in GC. The upregulation of STATs, except STAT4, suggests their involvement in GC oncogenesis. Notably, high STAT1 expression is a favorable prognostic marker, while increased STAT5A, STAT5B, and STAT6 expression correlates with poor prognosis. These findings underscore the potential of STATs as prognostic markers in GC, guiding personalized treatment strategies and improving patient outcomes.