Heat shock proteins have been implicated in the process of carcinogenesis. HSPA14, a member of the heat shock protein family, remains poorly understood in terms of its significance and pathomechanisms in breast cancer.

We analyzed the expression levels of HSPA14 and its prognostic significance in breast cancer using TCGA data. TCGA data was used to investigate the association between HSPA14 expression and clinicopathological features in breast cancer patients. GSEA analysis was conducted to identify the biological function of HSPA14. Spearman's correlation analysis was performed to examine the correlation between HSPA14 expression and immune cell infiltration, as well as immune checkpoint genes. Single cell transcriptomic data from GSE114727 was utilized to calculate the expression of HSPA14 in different cell subpopulations. The data on HSPA14 levels and drug sensitivity were extracted from the CellMiner dataset. The mRNA expression of HSPA14 was validated through cell experiments.

HSPA14 expression is elevated in breast cancer, which is associated with poor overall survival. It can serve as a diagnostic biomarker for breast cancer patients. Pathway analysis revealed that HSPA14-associated differential genes are involved in cell cycle, apoptosis, cellular response to heat stress, and more. Additionally, HSPA14 expression is significantly correlated with the immune microenvironment. The expression of HSPA14 may also indicate drug sensitivity.

Our study elucidates the involvement of HSPA14 in tumorigenesis, particularly in modulating the immune response, shaping the immune microenvironment, and contributing to drug resistance, which are pivotal for the development of personalized breast cancer therapies.

The complex tumor microenvironment (TME) presents significant challenges to the development of effective therapies against solid tumors, highlighting the need for advanced in vitro models that better recapitulate TME biology. To address this, we developed a vascularized human liver tumor model using a microfluidic platform, designed to test both drug and cell-based therapies. This model mimics critical tumorigenic features such as hypoxia, extracellular matrix (ECM), and perfusable vascular networks. Intravascular administration of Sorafenib demonstrated its ability to disrupt vascular structures significantly, while eliciting heterogeneous responses in two distinct liver tumor cell lines, HepG2 and Hep3b. Furthermore, treatment with engineered T-cells revealed that the tumor vasculature impeded T-cell infiltration into the tumor core but preserved their cytotoxic capacity, albeit with reduced exhaustion levels. Cytokine analysis and spatial profiling of vascularized tumor samples identified proinflammatory factors that may enhance T-cell-mediated antitumor responses. By capturing key TME characteristics, this microfluidic platform provides a powerful tool enabling detailed investigation of tumor-immune and tumor-vascular interactions. Its versatility could serve as a promising bridge between preclinical studies and clinical testing, offering opportunities for developing and optimizing personalized therapeutic strategies for solid tumors.

Clear cell renal cell carcinoma (ccRCC) is one of the most common malignancies worldwide, but only a few markers have been used to diagnose ccRCC. Here, we report the critical roles of DEAD-box helicase 24 (DDX24), a member of the DEAD-box RNA helicase family, in ccRCC. The DDX24 expression level and its prognostic value were initially detected in public data and then verified in a ccRCC tissue microarray. Subsequent in vitro and in vivo experiments were conducted on representative ccRCC cell lines. RNA sequencing and experimental studies were performed to explore the underlying mechanisms, and the associations between DDX24 expression and immune characteristics were evaluated. DDX24 levels were significantly lower in ccRCC tissues and negatively correlated with advanced clinical stage and overall survival. Functional analyses showed that DDX24 overexpression inhibited ccRCC cell proliferation, migration, and invasion, while DDX24 knockdown enhanced these phenotypes. Mechanistic studies revealed that DDX24 regulated the expression of aldo-keto reductase family 1 member B10 (AKR1B10) and epithelial-mesenchymal transition (EMT)-related transcription factors. Given the low expression of DDX24, ccRCC patients may benefit more from immunotherapies. In conclusion, these findings demonstrate that DDX24 suppresses ccRCC progression through direct regulation of AKR1B10, potentially mediated by EMT-related pathways, which provides potential therapeutic targets for ccRCC.

Low-grade glioma (LGG) is a primary brain tumor with high cellular heterogeneity and recurrence, leading to poor prognosis. Standard treatments (surgery, radiotherapy, and chemotherapy) have limited efficacy. Ferroptosis, an iron-dependent form of regulated cell death, is a potential therapeutic target, while dysregulated ferroptosis-related genes (FRGs) may drive tumor progression and therapy resistance.

This study integrated multi-omics data from The Cancer Genome Atlas (TCGA), Chinese Glioma Genome Atlas (CGGA), and Gene Expression Omnibus (GEO) to identify FRGs associated with LGG prognosis. Single-cell RNA sequencing (scRNA-seq) and pseudotime trajectory analysis were performed to investigate their functional roles. Key findings were validated through in vitro and in vivo experiments.

We identified 345 FRGs associated with LGG prognosis, which are involved in oxidative stress response, cell proliferation, and immune regulation. High-risk patients exhibited an immunosuppressive tumor microenvironment with elevated levels of M2 macrophages and Treg cells but reduced CD8+ T cell infiltration. Pseudotime trajectory analysis highlighted the dynamic roles of macrophages and astrocytes in immune evasion and microenvironment remodeling. Notably, the NUAK2 gene emerged as a key driver of tumor progression and immune suppression. In vitro and in vivo experiments confirmed that targeting NUAK2 significantly reduced tumor cell viability and growth, underscoring its critical regulatory role in LGG.

Our study provides comprehensive insights into the role of FRGs in LGG prognosis and tumor microenvironment regulation, with a particular focus on the NUAK2 gene. As a potential therapeutic target, NUAK2's critical role in tumor progression and immune evasion offers a new direction for LGG treatment. Future research should focus on validating NUAK2's role in larger cohorts and exploring its clinical application as a biomarker and therapeutic target.

Strategies in immunotherapy often target the immunosuppressive environment of tumor cells. One route of therapeutic interference could involve negative checkpoint regulators of which V-domain immunoglobulin (Ig)-containing suppressor of T-cell activation (VISTA) has raised more interest recently. The protein is expressed on the surface of tumor cells, T-lymphocytes, and antigen-presenting cells (APCs), but its intracellular expression pattern has not been investigated yet. We examined the intracellular distribution of VISTA and its possible role in translocation processes by immunofluorescence and Western blots. We analyzed the expression and localization of VISTA in murine bone marrow-derived macrophages (BMDMs), human monocyte-derived macrophages, and human T lymphocytes (Jurkat). We obtained different cell fractions and organelles of various cell types and analyzed for the presence of VISTA. Monitoring a VISTA-GFP fusion construct in transfected cell lines HL-60 and THP-1 confirmed VISTA localization in these cell lines. All used cell lines showed the colocalization of VISTA and several vesicle markers together with VISTA staining along microtubule fibers. Additionally, we found VISTA in secreted exosomes and have the first hints for nucleic expression in all tested cell lines. Therefore, the storage of VISTA in vesicles and its potential presence in nuclei resembles two other well-described checkpoint regulators, CTLA-4 and PD-L1, respectively. We conclude that VISTA storage in vesicles enables a fast response to immunogenic stimuli, which needs to be considered for inhibitory experiments. The localization of VISTA in exosomes suggests a signaling function to facilitate cell-cell communication. Furthermore, the VISTA expression in the nucleus proposes a transcriptional role.

Endometrial cancer is a significant public health concern with rising incidence rates globally. Understanding the molecular mechanisms underlying this disease is crucial for developing effective therapeutic strategies. Our study aimed to characterize transcriptional changes in endometrial cancer tissues compared to adjusted healthy tissue. Using RNA sequencing, we identified 2483 differentially expressed genes (DEGs), including protein-coding genes, long non-coding RNAs (lncRNAs), and microRNAs (miRNAs). Notably, several known cancer-related genes were differentially expressed, such as MYC, AKT3, CCND1, and CDKN2A. Pathway analysis revealed significant alterations in cell cycle regulation, several signaling pathways, and metabolic processes. These findings provide valuable insights into the molecular pathways dysregulated in endometrial cancer. Our results may contribute to the development of novel therapeutic targets and biomarkers for this disease.

Cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC) pose significant global health challenges. While the mitochondrial unfolded protein response (UPRmt) is known to influence cancer biology, its specific role in CESC remains unclear.

We employed machine learning to analyze UPRmt genes in CESC using TCGA multi-omics data. Our comprehensive analysis included genetic alterations, prognostic significance, tumor-immune interactions, single-cell transcriptomics, pathway enrichment, and drug sensitivity assessments.

ATF5 emerged as the most significant prognostic factor among UPRmt genes, with high expression correlating with better overall survival. High ATF5 expression was associated with an immunologically active tumor microenvironment, characterized by enhanced immune cell infiltration, increased immune checkpoint expression, and higher tumor mutational burden. Single-cell RNA sequencing revealed ATF5's distinct expression patterns in stromal cells, particularly in endometrial stromal and smooth muscle cells. Gene set enrichment analysis provided mechanistic insight, revealing ATF5's connection to the immune response via the regulation of P-stalk ribosome functions, a finding that underscores a novel aspect of UPRmt's role in shaping the tumor immune landscape. Drug sensitivity analysis showed that low ATF5 expression correlated with resistance to conventional chemotherapeutics (cisplatin, paclitaxel, and etoposide) but increased sensitivity to imatinib, potentially through EP300-dependent mechanisms.

Our findings establish ATF5 as both a favorable prognostic marker and a key immune response regulator in CESC. Its influence on the tumor microenvironment and treatment response suggests potential therapeutic applications. These insights into UPRmt's role in CESC provide new directions for developing personalized treatment strategies.

Lung cancer remains the leading cause of malignant tumors worldwide in terms of the incidence and mortality, posing a significant threat to human health. Given that distant metastases typically occur at the time of initial diagnosis, leading to a poor 5-year survival rate among patients, it is crucial to identify markers for diagnosis, prognosis, and therapeutic efficacy monitoring. Abnormal glycosylation is a hallmark of cancer cells, characterized by the disruption of core fucosylation, which is predominantly driven by the enzyme fucosyltransferase 8 (FUT8). Evidence indicates that FUT8 is a pivotal enzyme in cancer onset and progression, influencing cellular glycosylation pathways. Utilizing bioinformatics approaches, we have investigated FUT8 in lung cancer, resulting in a more systematic and comprehensive understanding of its role in the disease's pathogenesis. In this study, we employed bioinformatics to analyze the differential expression of FUT8 between LUAD and LUSC. We observed upregulation of FUT8 in both LUAD and LUSC, associated with unfavorable prognosis, and higher diagnostic utility in LUAD. GO/KEGG analysis revealed a primary association between LUAD and the spliceosome. Immunologically, FUT8 expression was significantly associated with immune cell infiltration and immune checkpoint activity, with a notable positive correlation with M2 macrophage infiltration. Our analysis of FUT8 indicates that it may serve as a potential biomarker for lung cancer diagnosis and prognosis, and could represent a therapeutic target for LUAD and LUSC immunotherapy.

Immunohistochemistry (IHC) imaging is a powerful technique to study the subcelluar localization (SCL) of human proteins in both normal and pathological tissues. As the manual annotation of localization for IHC images is time-consuming and the number of annotated is limited, a computational tool is necessary to analyze IHC images. However, existing prediction models rarely incorporate protein sequences. In this paper, a novel protein SCL prediction model for IHC images, ProLoc-IHS, is proposed by combining with sequence features. First, a bimodal dataset is curated including IHC images and protein sequences, which are derived from the Human Protein Atlas (HPA) and UniProt respectively. Then, ProLoc-IHS extracts embeddings from IHC images and protein sequences using a visual language model, Vision Transformer (Vit), and a protein language model, ProtT5, respectively. Subsequently, these embeddings are fused using a cross-attention module, and the fused features are input into the feature learning module of ProLoc-IHS, which contains a multi-head attention mechanism, a feedforward neural network and a residual connection. Finally, binary cross entropy (BCE) and Focal loss function are incorporated into the feature learning module to solve multi-label classification tasks. Experimental results show that ProLoc-IHS outperforms other prediction models. The newly curated dataset and ProLoc-IHS code are available at https://github.com/xinshuaiiii/ProLoc-IHS.

Oral squamous cell carcinoma (OSCC) is characterized by high invasiveness and metastasis, with cancer stem cells (CSCs) playing a central role in tumor progression. This study investigates the effects of integrin-linked kinase (ILK) silencing and trichostatin A (TSA) treatment on CSCs, assessing their potential to diminish CSC properties and inhibit OSCC progression.

CSCs were enriched and isolated from primary OSCC samples and Tca8113 cell line and MOC1 cell line using side population (SP) analysis, with their characteristics and the therapeutic impact of treatments assessed through assays such as MTT, wound healing, cell invasion, cell cycle, and apoptosis.

Higher SP cell content correlated significantly with poor pathological classification, metastasis, and recurrence. Treated CSCs showed reduced proliferation, migration, and invasion, along with increased apoptosis. In vivo experiments demonstrated that the combined treatment substantially reduced tumor growth.

The study confirms the efficacy of targeting CSCs with ILK silencing and TSA treatment in OSCC, suggesting a promising strategy for CSC-directed therapies that merit further investigation.

High-grade serous ovarian cancer (HGSOC) is the most common and aggressive subtype of epithelial ovarian cancer, often diagnosed at advanced stages with a poor prognosis. Paclitaxel (PTX), a standard chemotherapeutic agent for HGSOC, exerts cytotoxic effects on cancer cells and modulates the tumor microenvironment. This study aimed to elucidate the molecular mechanisms of PTX in HGSOC using bioinformatics, machine learning, network pharmacology, and molecular docking, to identify potential diagnostic biomarkers and therapeutic targets. We identified differentially expressed genes (DEGs) between HGSOC and normal ovarian tissues using the GSE54388 dataset from the Gene Expression Omnibus database. The intersection of these DEGs with PTX targets, identified from the Swiss Target Prediction database, yielded 15 overlapping genes. These genes were analyzed via protein-protein interaction (PPI) network analysis to identify significant interaction relationships. Kaplan-Meier survival analysis was then performed to assess the prognostic significance of these genes. Their protein expression patterns in HGSOC tissues were validated using the Human Protein Atlas (HPA) database. Functional enrichment analysis was conducted using Gene Ontology and the Kyoto Encyclopedia of Genes and Genomes. A combined diagnostic model was developed using LASSO regression and validated in two independent external datasets (GSE26712 and GSE12470). Molecular docking experiments were conducted to confirm the binding affinity of PTX to key proteins. Immune infiltration analysis was performed to assess the tumor microenvironment, revealing significant differences in immune cell composition between normal and tumor tissues. A total of 2267 DEGs were identified, with 15 overlapping genes related to PTX targets. After PPI network analysis, Kaplan-Meier survival analysis, and HPA validation, five key genes (AURKA, CBX7, CCNA2, HSP90AA1, and TUBB3) were identified as associated with HGSOC progression. The combined diagnostic model demonstrated high accuracy in distinguishing HGSOC from normal tissues, with AUC values of 0.9892 and 0.9465 in the GSE26712 and GSE12470 validation datasets, respectively. Molecular docking confirmed stable binding of PTX to these key proteins, suggesting their role in PTX's therapeutic effects. Immune infiltration analysis revealed significant differences in immune cell composition between normal and tumor tissues, highlighting the potential impact of these genes on the tumor microenvironment. In summary, our findings provide a theoretical basis for improving clinical diagnosis and elucidating the underlying mechanisms of HGSOC.

Metabolic syndrome (MetS), a conglomerate of dysregulated metabolic traits that vary between individuals, is partially driven by modern diets high in fat, sucrose, or fructose and their interactions with host genes in metabolic tissues. To elucidate the roles of individual tissues and cell types in diet-induced MetS, we performed single-cell RNA sequencing on the hypothalamus, liver, adipose tissue, and small intestine of mice fed high-fat high-sucrose (HFHS) or fructose diets. We found that hypothalamic neurons were sensitive to fructose, while adipose progenitor cells and macrophages were responsive to HFHS. Ligand-receptor analysis revealed lipid metabolism and inflammation networks among peripheral tissues driven by HFHS, while both diets stimulated synaptic remodeling within the hypothalamus. mt-Rnr2, a top responder to both diets, mitigated diet-induced MetS by stimulating thermogenesis. Our study demonstrates that HFHS and fructose diets have differential cell type and network targets but also share regulators such as mt-Rnr2 to affect MetS risk.

Selective inhibition of TrxR1 over TrxR2 is a highly sought-after goal, because the two enzymes play distinct roles in cancer progression. However, achieving targeted inhibition is challenging due to their high homology and identical active site sequence. Herein we report a new subcellular photocatalysis approach for targeted inhibition by controllably activating organogold(I) prodrugs within the cytosol, the exclusive location of TrxR1. The NHC-Au(I)-alkynyl complexes are stable and evenly distributed in the cell; they can meanwhile be efficiently transformed into active NHC-Au(I)-L species (L = labile ligands) via a radical mechanism by photocatalysts released into the cytosol (from endosome/lysosome) upon light irradiation, leading to selective inhibition of TrxR1 without affecting TrxR2. This results in strong cytotoxicity to cancer cells with much higher selectivity than auranofin, a pan TrxR inhibitor that cannot discriminate TrxR1/2, along with potent antitumor activities in multiple zebrafish and mouse models. This subcellular prodrug activation may thus suggest a novel approach to precision targeting using the remarkable spatial control of photocatalysis.

Ras signaling regulates many cellular processes in cancer development. While well-known Ras-related oncogenes, such as KRAS, have been extensively explored, the role of other Ras-related genes in cancer remains poorly studied. Dexamethasone-induced Ras-related protein 1 (RASD1), a member of the Ras superfamily, is widely expressed across various tissues and is involved in inhibiting cell growth and inducing apoptosis, suggesting a potential role as a tumor suppressor. Here, we investigated RASD1 expression across multiple tissues and cancers, utilizing data from The Cancer Genome Atlas (TCGA), Human Protein Atlas, and Genotype-Tissue Expression (GTEx) databases. Our analysis revealed a significant downregulation of RASD1 mRNA expression in several cancer types compared to normal tissues, correlating with low levels of promoter methylation. Interestingly, high RASD1 expression correlated with a favorable prognosis in multiple cancers. Immune cell infiltration analysis indicated that elevated RASD1 expression is associated with an increased infiltration of CD4+ T cells and myeloid-derived dendritic cells in cancer. Furthermore, the expression of genes exhibiting similar expression patterns as RASD1 suggest that RASD1 may play a role in interleukin-4-mediated apoptosis and could regulate the transcription of the phosphatase and tensin homolog (PTEN) gene. Overall, these findings suggest that RASD1 may modulate immune signaling and tumor suppressive pathways.

Deoxycytidine triphosphate pyrophosphatase 1 (DCTPP1) is an important deoxycytidine triphosphate (dCTP) hydrolase responsible for eliminating noncanonical dCTP and maintaining deoxyribonucleoside triphosphate (dNTP) pool homeostasis. This regulation is vital for proper DNA replication and genome stability. Emerging evidence highlights the considerable role of DCTPP1 in tumor progression, chemotherapy resistance, and prognostic prediction. Consequently, DCTPP1 has emerged as a promising nucleotide metabolism-related target for cancer therapy. In this review, we provide a comprehensive summary of the structural and cellular biological features of DCTPP1, its functions, and its role in cancer. In addition, we discuss recent advancments in small molecules targeting DCTPP1, and propose potential directions for future research.

Cervical cancer (CC) is a leading cause of cancer-related death in women. The N-myc down-stream regulatory gene (NDRG) family has an unclear prognostic role in CC.

We analyzed NDRG mRNA and protein levels in CC using public databases. And NDRG1 expression was verified through immunohistochemistry in clinical samples. Additionally, we utilized other bioinformatics tools to analyze the correlations between NDRG and survival, as well as immune infiltration.

NDRG1 was elevated, and NDRG2 was reduced in CC tissues. High NDRG1 and low NDRG2/3 correlated with poorer survival and were associated with reduced immune cell infiltration, particularly CD8+ T cells. Genetic alterations in NDRG1/2/3 were primarily amplifications, while DNA hypomethylation of NDRG1 in CC tissues, particularly at specific CpG sites, was associated with prognosis. PPI and enrichment analyses implicated NDRGs in metabolic processes, HIF-1 signaling, and immune regulation, underscoring their roles in CC progression and prognosis.

NDRG1/2 present potential as new prognostic biomarkers, shedding light on therapeutic targets for CC.

Intraductal papillary mucinous neoplasms (IPMN) occur in 5% to 10% of the population, but only a small minority progress to pancreatic ductal adenocarcinoma (PDAC). The lack of accurate predictors of high-risk disease leads to both unnecessary operations for indolent neoplasms and missed diagnoses of PDAC. Digital spatial RNA profiling (DSP-RNA) provides an opportunity to define and associate transcriptomic states with cancer risk.

We performed whole-transcriptome DSP-RNA profiling on 10 IPMN specimens encompassing the spectrum of dysplastic changes from normal duct to cancer. Epithelial regions within each tissue were annotated as normal duct, low-grade dysplasia, high-grade dysplasia, or invasive carcinoma. The resulting digital gene expression data were analyzed with R/Bioconductor.

Our analysis uncovered three distinct epithelial transcriptomic states-"normal-like" (cNL), "low risk" (cLR), and "high risk" (cHR)-which were significantly associated with pathologic grade. Furthermore, the three states were significantly correlated with the exocrine, classical, and basal-like molecular subtypes described in PDAC. Specifically, exocrine function diminished in cHR, classical activation distinguished neoplasia (cLR and cHR) from cNL, and basal-like genes were specifically upregulated in cHR. Intriguingly, markers of cHR were detected in normal duct and low-grade dysplasia regions from specimens with PDAC but not from specimens containing only low-grade IPMN.

DSP-RNA of IPMN revealed low-risk (indolent) and high-risk (malignant) expression programs that correlated with the activity of exocrine and basal-like PDAC signatures, respectively, and distinguished pathologically low-grade specimens from malignant specimens. These findings contextualize IPMN pathogenesis and have the potential to improve risk stratification.

Immune checkpoint inhibitors have demonstrated limited efficacy in overcoming immunosuppression in patients with epithelial ovarian cancer (EOC). Although certain patients experience long-term treatment benefit, reliable biomarkers for responder pre-selection and the distinction of dominant immunosuppressive mechanisms have yet to be identified. Here, we used a 40-marker suspension mass cytometry panel to comprehensively phenotype peripheral blood leukocytes sampled over time from patients with relapsed EOC who underwent combination oleclumab (anti-CD73) and durvalumab (anti-PD-L1) immunotherapy in the NSGO-OV-UMB1/ENGOT-OV30 trial. We found that survival duration was impacted by baseline abundances of total peripheral blood mononuclear cells. Longitudinal analyses revealed a significant increase in CD14+CD16- myeloid cells during treatment, with significant expansion of monocytic myeloid-derived suppressor cells occurring in patients with shorter progression-free survival, who additionally showed a continuous decrease in central memory T-cell abundances. All patients demonstrated significant PD-L1 upregulation over time on most T-cell subsets. Higher CD73 and IDO1 expression on certain leukocytes at baseline significantly positively correlated with longer progression-free survival. Overall, our study proposes potential biomarkers for EOC immunotherapy personalization and response monitoring; however, further validation in larger studies is needed.

Osimertinib, a tyrosine kinase inhibitor (TKI), treats non-small cell lung cancer (NSCLC) with epidermal growth factor receptor (EGFR) mutations. However, its efficacy may vary due to heterogeneous drug distribution, assessable through microdosed radiolabeled drugs and positron emission tomography (PET). Precision dosing using microdosed TKI-PET encounters challenges due to pharmacokinetic (PK) variations between micro- and therapeutic doses. This study aims to predict osimertinib's tissue concentration-time profiles for both microdose and therapeutic dose scenarios using a whole-body physiologically based pharmacokinetic (PBPK) model, which incorporates nonlinear PK processes and target site occupancy. A target site PBPK model for osimertinib was developed to predict drug distribution across various tissues, including lung tumor, based on a previously published PBPK model. The model incorporated tissue-specific parameters and accounted for both linear and nonlinear pharmacokinetic processes, including EGFR-binding dynamics and tumor dynamics. Model predictions were verified with microdosed [11C]C-osimertinib PET imaging data and clinical pharmacokinetic profiles to assess accuracy and reliability. The developed target site-PBPK model accurately predicted osimertinib pharmacokinetics across multiple (tumor) tissues and dose levels within 2-fold error compared to observed PET data. This study underscores the utility of PBPK modeling in predicting osimertinib's pharmacokinetics across diverse tissues, offering insights into drug distribution and predictions of target engagement in NSCLC patients using microdose PET imaging data. The developed model serves as a promising tool for optimizing dosing strategies and evaluating novel EGFR-TKIs in NSCLC treatment.

Placental alkaline phosphatase (PLAP) is a protein with a poorly understood function that is normally only expressed in the placenta. In cancer, PLAP expression is a hallmark of germ cell neoplasms, but it can also occur in urothelial carcinoma. To evaluate the potential clinical significance of PLAP expression in bladder cancer, METHODS: PLAP protein was analyzed by immunohistochemistry in more than 2500 urothelial bladder carcinomas in a tissue microarray format.

PLAP staining was absent in normal urothelial cells but was observed in 15.9% of urothelial carcinomas, including 282 (11.5%) with weak, 57 (2.3%) with moderate, and 51 (2.1%) with strong staining. PLAP positivity occurred in 4.1% of 413 pTa G2 low-grade, 10.2% of 176 pTa G2 high-grade, and 7.2% of 97 pTa G3 tumors (p = 0.0636). As compared to pTa tumors, the PLAP positivity rate was markedly higher in 1341 pT2-4 carcinomas (19.8%, p < 0.0001). Within pT2-4 carcinomas, PLAP staining was unrelated to pT, pN, grade, L-status, V-status, overall survival, recurrence-free survival, and cancer-specific survival (p > 0.25). However, PLAP positivity was linked to p16 positivity (p = 0.0185), GATA3 positivity (p < 0.0001), and p63 expression loss (p = 0.0456).

In summary, these data show that PLAP is expressed in a significant fraction of pT2-4 urothelial carcinomas, unrelated to cancer aggressiveness but associated with specific molecular features. Once anti-PLAP cancer drugs become effective, urothelial carcinoma is a candidate tumor entity for clinical evaluation.

Oral squamous cell carcinoma (OSCC) is a prevalent cancer of the head and neck region. However, the potential role of RCN2 in OSCC is currently not well understood.

A series of molecular biology experiments were conducted to explore the mechanism by which RCN2 promotes OSCC growth through protein kinase A (PKA).

Our results revealed a significant increase in RCN2 levels in OSCC tissues. Moreover, OSCC patients with high RCN2 expression had a significantly worse prognosis than those with lower RCN2 expression. Interestingly, PKA activity was increased in RCN2-overexpressing YD-10B cells but reduced in RCN2-knockout Ca9-22 cells. These findings suggest that RCN2-mediated PKA activity is activated in OSCC cells. Moreover, the specific PKA inhibitor H89 significantly reduced the proliferation ability of RCN2-overexpressing Ca9-22 cells. Furthermore, we identified AKT/mTORC as a downstream pathway through which PKA promotes OSCC cell proliferation. The Tumor Immune Estimation Resource database revealed that the expression level of RCN2 was correlated with the infiltration levels of B cells, CD8+ T cells, CD4+ T cells, and neutrophils in the microenvironment of OSCC.

Our study revealed that RCN2 promotes tumor progression by activating PKA/AKT/mTORC signaling, which suggests that RCN2 may serve as a potential target for OSCC treatment.

Triple-negative breast cancer (TNBC) constitutes the molecular subtype exhibiting the poorest prognosis. Targeted therapy emerges as a pivotal strategy to enhance the clinical outcomes of individuals with TNBC. Identifying targets and corresponding therapeutic agents is essential for reducing TNBC-related mortality. Topotecan, a chemotherapeutic agent approved for treating metastatic breast cancer, remains under investigation regarding its specific targets and molecular mechanisms in TNBC. Data procured from CRISPR/Cas9 library screenings showed that TFDP1 may be a therapeutic target in TNBC, and the L1000FWD database suggested that TFDP1 serves as a potential target of topotecan. The overexpression of TFDP1 was observed in TNBC tissues, correlating with poorer prognosis. Knockdown of TFDP1 inhibited the cell growth, clonal expansion, and tumorigenicity of TNBC cells. Mechanistically, TFDP1 inhibited cellular senescence in TNBC cells. In vitro experiments demonstrated that topotecan inhibited TNBC cell growth and promoted cellular senescence, counteracting the effects of TFDP1 overexpression on TNBC cells. These findings suggest that topotecan impedes TNBC cell growth by targeting TFDP1. This interaction provides valuable insights into the molecular mechanisms governing TNBC cell senescence, presenting TFDP1 as a potential therapeutic target. Combining topotecan with senolytic therapies may offer a promising strategy for TNBC treatment.

Pancreatic ductal adenocarcinoma is a lethal malignancy, necessitating an understanding of its molecular mechanisms for the development of new therapeutic strategies. The tight junction protein claudin-1, known to influence cellular functions in various cancers and is considered a therapeutic target, remains unclear in pancreatic cancer.

This study assessed claudin-1 expression in resected pancreatic cancer samples, public databases, and pancreatic cancer cell lines. Claudin-1 knockout with CRISPR/Cas9 on poorly differentiated pancreatic cancer cell lines and a proteome analysis were performed to investigate the intracellular mechanisms of claudin-1.

Claudin-1 was markedly overexpressed in pancreatic ductal adenocarcinoma and intraepithelial neoplasia compared to normal ducts, and high claudin-1 levels were an independent predictor of poor prognosis. Claudin-1 knockout diminished cell proliferation, migration, invasion, and chemoresistance in pancreatic ductal adenocarcinoma. Proteome analysis revealed the significant downregulation of aldo-keto reductase family proteins (AKR1C2, AKR1C3, and AKR1B1) in claudin-1 knockout cells, which are linked to metabolic pathways. Aldo-keto reductase knockdown reduced chemoresistance, proliferation, and invasion in these cell lines.

These findings indicate that the abnormal expression of claudin-1 promotes tumor progression and drug resistance through its interaction with aldo-keto reductase proteins, highlighting claudin-1 and aldo-keto reductase family proteins as potential biomarkers and therapeutic targets for pancreatic cancer.

The current noninvasive prognostic evaluation methods for hepatocellular carcinoma (HCC), which are largely reliant on radiographic imaging features and serum biomarkers such as alpha-fetoprotein (AFP), have limited effectiveness in discriminating patient outcomes. Identification of new prognostic biomarkers is a critical unmet need to improve treatment decision-making. Epigenetic changes in cell-free DNA (cfDNA) have shown promise in early cancer diagnosis and prognosis. Thus, we aim to evaluate the potential of cfDNA methylation as a noninvasive predictor for prognostication in patients with active, radiographically viable HCC.

Using Illumina HumanMethylation450 array data of 377 HCC tumors and 50 adjacent normal tissues obtained from The Cancer Genome Atlas (TCGA), we identified 158 HCC-related DNA methylation markers associated with overall survival (OS). This signature was further validated in 29 HCC tumor tissue samples. Subsequently, we applied the signature to an independent cohort of 52 patients with plasma cfDNA samples by calculating the cfDNA methylation-based risk score (methRisk) via random survival forest models with 10-fold cross-validation for the prognostication of OS.

The cfDNA-based methRisk showed strong discriminatory power when evaluated as a single predictor for OS (3-year AUC = 0.81, 95% CI: 0.68-0.94). Integrating the methRisk with existing risk indices like Barcelona clinic liver cancer (BCLC) staging significantly improved the noninvasive prognostic assessments for OS (3-year AUC = 0.91, 95% CI: 0.80-1), and methRisk remained an independent predictor of survival in the multivariate Cox model (P = 0.007).

Our study serves as a pilot study demonstrating that cfDNA methylation biomarkers assessed from a peripheral blood draw can stratify HCC patients into clinically meaningful risk groups. These findings indicate that cfDNA methylation is a promising noninvasive prognostic biomarker for HCC, providing a proof-of-concept for its potential clinical utility and laying the groundwork for broader applications.

Organoid models are invaluable for studying organ processes in vitro, offering an unprecedented ability to replicate organ function. Despite recent advancements that have increased their cellular complexity, organoids generally lack key specialized cell types, such as neurons, limiting their ability to fully model organ function and dysfunction. Innervating organoids remains a significant challenge due to the asynchronous biological cues governing neural and organ development. Here, we present a versatile organ-on-a-chip platform designed to innervate organoids across diverse tissue types. Our strategy enables the development of innervated granular hydrogel tissue constructs, followed by the sequential addition of organoids. The microfluidic device features an open tissue chamber, which can be easily manipulated using standard pipetting or advanced bioprinting techniques. Engineered to accommodate microgels of any material larger than 50 μm, the chamber provides flexibility for constructing customizable hydrogel environments. Organoids and other particles can be precisely introduced into the device at any stage using aspiration-assisted bioprinting. To validate this platform, we demonstrate the successful growth of primary mouse superior cervical ganglia (mSCG) neurons and the platform's effectiveness in innervating prostate cancer spheroids and patient-derived renal cell carcinoma organoids. This platform offers a robust and adaptable tool for generating complex innervated organoids, paving the way for more accurate in vitro models of organ development, function, and disease.

The efficacy of immunotherapy in pancreatic ductal adenocarcinoma (PDAC) remains limited. The tumor microenvironment (TME), characterized by the accumulation of suppressive myeloid cells including neutrophils, attributes to immunotherapy resistance in PDAC. IgA monoclonal antibodies (mAbs) can activate neutrophils to kill tumor cells; this can be further enhanced by blocking the myeloid immune checkpoint CD47. In this study, we investigated the potential of this therapeutic strategy for PDAC. We determined the expression of tumor-associated antigens (TAAs) on PDAC cell lines and fresh patient samples, and the results showed that the TAAs epithelial cell adhesion molecule (EpCAM), trophoblast cell surface antigen 2 (TROP2) and mucin-1 (MUC1), as well as CD47 were consistently expressed on PDAC. In line with this, we showed that IgA mAbs against EpCAM can activate neutrophils to lyse various PDAC cell lines and tumor cells, which can be augmented by addition of CD47 blockade. In addition, we observed that neutrophils were present in patient tumors and expressed the receptor for IgA. In conclusion, our results indicate that a combination of IgA mAb with CD47 blockade is a promising preclinical treatment strategy for PDAC, which merits further investigation.

Colorectal cancer molecular signatures derived from omics data can be employed to stratify CRC patients and aid decisions about therapies or evaluate prognostic outcome. However, molecular biomarkers for identification of patients at increased risk of disease relapse are currently lacking. Here, we present a comprehensive multi-omics analysis of a Danish colorectal cancer tumor cohort composed of 412 biopsies from tumors of 371 patients diagnosed at TNM stage II or III. From mass spectrometry-based patient proteome profiles, we classified the tumors into four molecular subtypes, including a mesenchymal-like subtype. As the mesenchymal-rich tumors are known to represent the most invasive and metastatic phenotype, we focused on the protein signature defining this subtype to evaluate their potential as relapse risk markers. Among signature-specific proteins, we followed-up Caveolae-Associated Protein-1 (CAVIN1) and demonstrated its role in tumor progression in a 3D in vitro model of colorectal cancer. Compared to previous omics analyses of CRC, our multi-omics classification provided deeper insights into EMT in cancer cells with stronger correlations with risk of relapse.

Human ClpP protease contributes to mitochondrial protein quality control by degrading misfolded proteins. ClpP is overexpressed in cancers such as acute myeloid leukemia (AML), where its inhibition leads to the accumulation of damaged respiratory chain subunits and cell death. Conversely, hyperactivating ClpP with small-molecule activators, such as the recently discovered ONC201, disrupts mitochondrial protein degradation and impairs respiration in cancer cells. Despite its critical role in human health, the mechanism underlying the structural and functional properties of human ClpP remains elusive. Notably, human ClpP is paradoxically activated by active-site inhibitors. All available structures of human ClpP published to date are in the inactive compact or compressed states, surprisingly even when ClpP is bound to an activator molecule such as ONC201. Here, we present structures of human mitochondrial ClpP in the active extended state, including a pair of structures where ClpP is bound to an active-site inhibitor. We demonstrate that amino acid substitutions in the handle region (A192E and E196R) recreate a conserved salt bridge found in bacterial ClpP, stabilizing the extended active state and significantly enhancing ClpP activity. We elucidate the ClpP activation mechanism, highlighting a hormetic effect where substoichiometric inhibitor binding triggers an allosteric transition that drives ClpP into its active extended state. Our findings link the conformational dynamics of ClpP to its catalytic function and provide high-resolution structures for the rational design of potent and specific ClpP inhibitors, with implications for targeting AML and other disorders with ClpP involvement.

To explore novel biomarkers capable of predicting the prognosis of gastric cancer (GC) and investigate the mechanisms underlying the development of GC.

Firstly, differentially expressed genes (DEGs) in GC tumors and adjacent tissues were analyzed using transcriptome sequencing data. Then, the DEGs significantly associated with the prognosis of GC were selected. From this subset, genes with high protein expression levels in tumor tissues were focused. Multivariate hazard analysis was performed to further identify DEGs with independent prognostic value for GC patients. Eventually, the potential mechanisms involving DEGs that underlie the development of GC were investigated.

Altogether, 25 previously DEGs that have not been reported before were discovered in the context of GC. Among these genes, ADAMTSL2, DSCC1, COL5A3, F2RL2, GRIN2D, IGSF6, IER5L, PLA2G7, PODNL1, RCN3 and RTN4RL2 were significantly associated with the overall survival, first progression and post progression survival of GC patients. Moreover, protein levels of ADAMTSL2, COL5A3, DSCC1, GRIN2D, PODNL1 and RCN3 were consistently highly expressed in clinical GC specimens. Furthermore, multivariate hazard analysis identified ADAMTSL2 as an independent predictor of GC prognosis. Further exploration revealed a potential regulatory connection between ADAMTSL2 and hsa-miR-7-2-3p. hsa-miR-7-2-3p was significantly down-regulated in GC and GC patients with low expression of hsa-miR-7 had a poor overall survival. Additionally, ADAMTSL2 was significantly co-expressed with key molecules (NOTCH1, NOTCH3, NOTCH4 and HEY1) in Notch signaling pathway.

ADAMTSL2 stands out as an independent predictor for the prognosis of GC and may play a crucial pathological role in the development of GC.

Defensin beta 1 (DEFB1) is a key immune response gene, but its role in cancer remains unclear. This study aims to explore DEFB1 expression, genetic alterations, immune infiltration, and prognostic significance across various cancer types.

We analyzed DEFB1 expression and its association with cancer prognosis using data from public platforms, including The Cancer Genome Atlas (TCGA), Genotype-Tissue Expression (GTEx), and Human Protein Atlas (HPA). Additionally, we examined DEFB1 genetic alterations, immune cell infiltration, and its molecular partners using various bioinformatics tools.

DEFB1 expression was highest in salivary glands, kidneys, and pancreas. In cancers, DEFB1 was upregulated in cholangiocarcinoma, kidney chromophobe, and melanoma, but downregulated in breast, colon, and rectal cancers. High DEFB1 expression was linked to poorer overall survival in lung adenocarcinoma and pancreatic adenocarcinoma, but better survival in head and neck squamous cell carcinoma. Genetic analysis revealed alterations in liver and gastric cancers. Immune infiltration analysis showed a correlation between DEFB1 and cancer-associated fibroblasts in liver cancer, while neutrophil infiltration was linked to bladder carcinoma, diffuse large B-cell lymphoma, and lung squamous cell carcinoma. Key genes associated with DEFB1 included KLK1, BSND, and CLCNKB.

This study highlights DEFB1's potential as a prognostic biomarker and its influence on the tumor immune microenvironment across different cancers. These findings suggest DEFB1 could be a target for future cancer therapies, although further studies are needed to validate these results.

Clear cell renal cell carcinoma (ccRCC) is the most common form of kidney cancer that often displays resistance to conventional cancer therapies, including chemotherapy and radiation therapy. Targeted treatments, including immunotherapies and small molecular inhibitors, have been associated with improved outcomes. However, variations in the patient response and the development of resistance suggest that more models that better recapitulate the pathogenesis and metastatic mechanisms of ccRCC are required to improve our understanding and disease management. Here, we examined the transcriptional landscapes of in vitro cell culture as well as in vivo orthotopic and metastatic NOD/SCID-γ mouse models of ccRCC using a single patient-derived RCC243 cell line to allow unambiguous comparison between models. In our mouse model assays, RCC243 cells formed metastatic tumors, and all tumors retained clear cell morphology irrespective of model type. Notably, gene expression profiles differed markedly between the RCC243 tumor models-cell culture, orthotopic tumors, and metastatic tumors-suggesting an impact of the experimental model system and whether the tumor was orthotopic or metastatic. Furthermore, we found conserved prognostic markers between RCC243 tumor models and human ccRCC patient datasets, and genes upregulated in metastatic RCC243 were associated with worse patient outcomes.

Tumor metabolism has emerged as a critical target in cancer therapy, revolutionizing our understanding of how cancer cells grow, survive, and respond to treatment. Historically, cancer research focused on genetic mutations driving tumorigenesis, but in recent decades, metabolic reprogramming has been recognized as a hallmark of cancer. The TP53 inducible glycolysis and apoptosis regulator, or TIGAR, affects a wide range of cellular and molecular processes and plays a key role in cancer cell metabolism by regulating the balance between glycolysis and antioxidant defense mechanisms. Cancer cells often exhibit a shift towards aerobic glycolysis (the Warburg effect), which allows rapid energy production and gives rise to biosynthetic intermediates for proliferation. By inhibiting glycolysis, TIGAR can reduce the proliferation rate of cancer cells, particularly in early-stage tumors or specific tissue types. This metabolic shift may limit the resources available for rapid cell division, thereby exerting a tumor-suppressive effect. However, this metabolic shift also leads to increased levels of reactive oxygen species (ROS), which can damage the cell if not properly managed. TIGAR helps protect cancer cells from excessive ROS by promoting the pentose phosphate pathway (PPP), which generates NADPH-a key molecule involved in antioxidant defense. Through its actions, TIGAR decreases the glycolytic flux while increasing the diversion of glucose-6-phosphate into the PPP. This reduces ROS levels and supports biosynthesis and cell survival by maintaining the balance of nucleotides and lipids. The role of TIGAR has been emerging as a prognostic and potential therapeutic target in different types of cancers. This review highlights the role of TIGAR in different types of cancer, evaluating its potential role as a diagnostic marker and a therapeutic target.

E2F Transcription Factor 1 (E2F1) is a transcription factor that plays a crucial role in the growth of many cancers, including hepatocellular carcinoma (HCC). Herein, this study probed the functions and underlying mechanisms of E2F1 in HCC tumorigenesis.

The expression profiles of E2F1 and Exosome Component 10 (EXOSC10) were detected using qRT-PCR and western blotting. Functional experiments were carried out using 5-ethynyl-2'-deoxyuridine (EdU), flow cytometry, tube formation, and sphere formation assays in vitro, as well as xenograft experiments in vivo, respectively. Stemness-related proteins were assayed using western blotting. The interaction between E2F1 and EXOSC10 was verified using bioinformatics analysis and dual-luciferase reporter assay.

E2F1 was highly expressed in HCC tissues and cells, and was associated with advanced TNM stage, distant metastasis, and short survival rate. Functionally, knockdown of E2F1 suppressed HCC cell proliferation, angiogenesis, and stemness, and induced cell apoptosis. Mechanistically, E2F1 directly bound to the promoter region of EXOSC10 to up-regulate its expression. EXOSC10 silencing impaired HCC cell proliferation, angiogenesis, and stemness. Moreover, the anticancer effects of E2F1 knockdown were reversed by EXOSC10 elevation. In vivo assay, E2F1 deficiency suppressed HCC tumor growth and eliminated cancer stemness, while these effects were abolished by EXOSC10 up-regulation.

E2F1 promotes EXOSC10 transcription and then facilitates HCC growth and cancer stemness, revealing a potential target for HCC therapy.

Cancer prognosis markers are useful for treatment decisions; however, the omics-level landscape is not well understood across multiple cancer types. Pan-Cancer Analysis of Whole Genomes (PCAWG) provides unprecedented access to various types of molecular data, ranging from typical DNA mutations and RNA expressions to more deeply analyzed or whole-genomic features, such as HLA haplotypes and structural variations. We analyzed the PCAWG data of 13 cancer types from 1,514 patients to identify prognosis markers belonging to 17 molecular features in the survival analysis based on the Cox and Lasso regression methods. We found that germline features including HLA haplotypes, neoantigens, and the number of structural variations were associated with overall survival; however, mutational signatures were not. Measuring a few markers provided a sufficient prognostic performance evaluated by c-index for each cancer type. DNA markers demonstrated better or comparable prognostic performance compared to RNA markers in some cancer types. "Universal" markers strongly associated with overall survival across cancer types were not identified. These findings will give insights into the clinical implementation of prognosis markers.