Breast cancer (BC) is a heterogeneous disease with distinct molecular subtypes that exhibit variable immune responses and metabolic profiles. Recent studies have suggested that immunometabolic pathways play a role in tumor progression and treatment resistance. This study investigates the expression patterns of ALKBH7 and NLRP3 across BC molecular subtypes and explores their relationships with clinicopathological parameters and potential immunometabolic profiles. A total of 118 BC patients were classified into HER2+, TNBC, Luminal A, and Luminal B subtypes. Gene expression levels of ALKBH7 and NLRP3 were analyzed using quantitative real-time PCR (qRT-PCR), and correlations with clinical markers were assessed. ALKBH7 and NLRP3 expression levels varied significantly between subtypes, with the highest expression observed in HER2+ tumors. Strong positive correlations were found between ALKBH7 and NLRP3 in all subtypes, particularly in HER2+ (r = 0.812, p < 0.001). Additionally, NLRP3 correlated with Ki-67 in Luminal B tumors, indicating a link between inflammation and proliferative capacity. These findings suggest that ALKBH7 may function as a dual-role biomarker involved in metabolic adaptation and immune signaling in BC. The strong co-expression of ALKBH7 and NLRP3 suggests a functional association between these molecules that may be critical in shaping the tumor microenvironment. This co-expression set, particularly in aggressive subtypes (HER2+ and TNBC), warrants further mechanistic validation as a potential prognostic marker and a novel therapeutic vulnerability.

Personalizing ketamine therapy: Real-world predictors of response to IV ketamine and intranasal esketamine in treatment-resistant depression.

Introduction There is great promise in using genomic data to inform individual cancer treatment plans. Assessing intratumor genetic heterogeneity, studies have shown it may be possible to target biopsies to tumor subclones driving disease progression or treatment resistance. Here, we explore if the interpretation of tumor gene expression analysis varies across two specimens from the same patient. Material and methods We performed bulk RNA-seq using FFPE samples from 16 patients who also had a previous separate bulk RNA-seq performed and deposited in TCGA. We used three different deconvolution methods to compare cell type proportions for these paired data. We normalized study-specific gene expression values per gene by calculating transcripts per million and adjusted for batch effect across study to compare median expression values. We also compared the reliability of gene expression measurements. We selected KRAS, TP53, SMAD4 , and CDKN2A , as the most mutated genes in pancreatic cancer, and CTNNB1, JUN, SMAD3, SMAD7 , and TCF7, as these tend to be enriched in pancreatic cancer compared with adjacent normal tissue. Results We found that average cell type proportion varied the most between studies (i.e., samples for each patient) for NK and macrophages (using adjusted p-value 0.05/21 = 0.002). For the differential expression analysis, we did not observe significant differences in average expression of any of the selected genes. We observed substantial concordance (kappa = 0.75) only for JUN with low to moderate concordance (i.e., Kappa value 0.25–0.5) for the remaining 8 genes across the two studies. Discussion Together, the findings suggest that more than one tumor sample may be needed for effective treatment planning. Any potential difference in observed expression values across the paired samples could be related to the different cell type proportions across the samples. The sample size was small, and each study used different sequencing technologies, so any interpretation should be confirmed with additional studies.

Interpretable machine learning model for characterizing magnetic susceptibility-based biomarkers in first episode psychosis.

Advances of HDAC dual inhibitors in breast cancer treatment.

Decreased serum VEGF, NRG1, and Neuropilin-1 levels in male patients with treatment-resistant schizophrenia: implications for VEGF as a protective factor.

Targeting minichromosome maintenance proteins in cancer stem cells: mechanisms and therapeutic opportunities.

Identification of novel drug targets for mental disorders through genetic, colocalization, and network pharmacology approaches.

Cholangiocarcinoma-derived SPP1 drives tumor progression by inducing macrophage chemotaxis and M2 polarization.

CAR-T cell therapy for the treatment of lung cancer: Current challenges and emerging therapeutic strategies.

Metastatic melanoma is characterized by high rates of treatment resistance. While various factors have been studied for their prognostic significance, this study evaluated the potential prognostic value of the intrinsic disorder of T-cell receptor beta (TRB) polypeptides. TRB recombination sequencing reads were extracted from tumor RNA-seq files representing The Cancer Genome Atlas, Skin Cutaneous Melanoma dataset, and genomics files representing the National Institutes of Health, phs002683 dataset. Intrinsic disorder values were computed for the TRB V-complementarity determining region 3 (CDR3)-J amino acid sequences for all cases. Survival analyses assessed overall survival and disease-specific survival for case sets based on assigning cases to upper or lower 50 th percentile groups, based in turn on intrinsic disorder values. For the phs002683 dataset, intrinsic disorder values were compared between cases representing resistance to immune checkpoint inhibitors (ICIs) and cases representing no observed resistance. The results indicated that the upper 50 th percentile of the range of intrinsic disorder values was linked to better outcomes. This was obtained for two TRB datasets representing different RNA-seq file, recombination read extraction algorithms, and was observed for two different intrinsic disorder models. Furthermore, low minimum various long-3 and various short-long 2 values correlated with ICI treatment resistance. The findings of this study suggest that the diversity of intrinsic disorder values representing TRB V-CDR3-J assemblies may represent a novel prognostic biomarker for metastatic melanoma cases and a potential biomarker for indicating different personalized treatments.

Non-histone lysine lactylation: Emerging roles in tumor biology and therapeutic implications.

Gut microbiota and chemoradiotherapy response in rectal cancer: Biomarker opportunities.

Acute myeloid leukemia (AML) is a highly heterogeneous hematologic malignancy, characterized by complex molecular features and mechanisms of treatment resistance, which lead to a poor prognosis and high relapse rates. The complexity of multi‑pathway interactions and the dysregulated dynamics of tumor cell death pathways may contribute to the wide range of clinical outcomes observed despite advancements in current therapies. Most current research focuses on a single form of cell death, neglecting the mechanisms of other death pathways and their synergistic interactions, which hinders the development of novel therapeutic approaches. The present review systematically integrates and compares the molecular features of key cell death modalities in AML, including autophagy, apoptosis, pyroptosis, necroptosis, ferroptosis and cuproptosis. The present review analyzes their specific triggers, signaling hubs and regulatory networks within the metabolic microenvironment, and discusses the dynamic crosstalk among these pathways. A key focus is the therapeutic potential of exploiting this crosstalk to design synergistic combination therapies. To overcome the limitations of conventional treatments and improve patient outcomes, it is essential to further investigate the transition mechanisms of various cell death modes in AML progression, drug resistance and relapse. Additionally, establishing a theoretical foundation for the development of innovative therapies that synergistically regulate multiple death pathways is crucial.

Photodynamic therapy using talaporfin sodium and semiconductor laser induces dose and time dependent cytocidal effect for human glioma derived stem cells.

Chronic stress and brain kynurenine pathway: addressing unresolved issues with a meta-analytic approach of preclinical studies, translational implication for psychiatric disorders.

Apelin in glioblastoma: A dual target for tumor and vascular intervention.

Cytoplasmic SIRT1 enhances the stemness of polyploid giant cancer cells by promoting β-catenin protein stability and nuclear accumulation in ovarian carcinoma upon neoadjuvant chemotherapy.

Modulating metabolism to improve the therapeutic outcomes of CAR cell therapies: From bench to bedside.

Dual activation of PPARα/γ by bezafibrate triggers PINK1/Parkin-Mediated mitophagy to enhance lenvatinib sensitivity in hepatocellular carcinoma.