Could cephalosporin antibiotics, extending beyond their established antimicrobial role, be repurposed as precision anticancer agents and chemosensitizers, particularly against inflammation-driven carcinogenesis? To address this question, this study systematically evaluated the anti-colorectal cancer efficacy of cephalosporins both as monotherapies and in synergistic combinations, elucidating their underlying molecular mechanisms. Employing combinatorial phenotypic screening (viability, cell cycle, apoptosis, colony formation), BALB/c nude mouse xenografts, and omics profiling (RNA-seq, RT-qPCR), we identified conserved anticancer pathways and core regulatory axes. Among 18 evaluated cephalosporins, therapeutic specificity was largely associated exclusively variable side-chain moieties, not the conserved β-lactam core. Cefamandole nafate (CAN) and cefuroxime sodium (CUS) demonstrated potent dual efficacy against colorectal cancer model while enhancing cisplatin chemosensitivity. Building on links to inflammation-driven chemosensitization, CUS synergistically potentiated cisplatin and levofloxacin cytotoxicity in colorectal cancer. This synergy was mechanistically driven by apoptosis induction, cell cycle arrest, significant up-regulation of HMOX1 (80-fold peak in combinations; 40-fold as monotherapy) and DDIT3, coupled with down-regulation of MUC1, CASC19, KRT23, SPNS3, LFNG, HS3ST1, NCOA5, and GJB4. Crucially, we reveal for the first time that CUS significantly up-regulates HMOX1 expression in HCT116 cells in a dose-dependent manner, establishing this ferroptosis regulator as the central effector governing both intrinsic anticancer activity and chemosensitization. This study unveils the translational potential of repurposing cephalosporins for combinatorial precision oncology strategies targeting inflammation-driven cancers.

Symptomatic malignant pleural effusions (MPE) are treated with chemical pleurodesis to prevent recurrence. The serum soluble receptor for advanced glycation end products (sRAGE) has been linked to lung cancer progression but its role in predicting talc pleurodesis failure is unclear. A prospective cohort study was conducted from November 2023 to December 2024, encompassing subjects with confirmed MPE. Pleural fluid samples were collected prior to intercostal drainage (ICD) insertion for the measurement of sRAGE, ADAM10, MMP9, and HMGB1 levels. Participants were monitored for 90-day post-pleurodesis failure, pleural interventions, and survival. Among seventy-three adults (median age 66 [IQR 53-74 years]) with MPE who received pleurodesis, lung adenocarcinoma was the most common. Talc pleurodesis failure (24.7%) was associated with greater pleural fluid output, multiple pleurodesis attempts, longer ICD retention, and lower pH and lymphocyte fraction. Pleural sRAGE and MMP9 levels were significantly diminished (p = 0.0033 and p = 0.029, respectively), whereas HMGB1 levels were substantially elevated (p = 0.019) in the failure cases. Among biomarkers, pleural sRAGE had the most predictive value for talc pleurodesis failure, followed by HMGB1 and MMP9. However, pleural sRAGE and MMP-9 lacked prognostic significance for 90-day mortality. The present study demonstrated that lower pleural sRAGE is a potential predictive biomarker for talc pleurodesis failure despite inferiority to pleural acidity. Imbalance between sRAGE and HMGB1 in MPE may be associated with the underlying mechanism for talc pleurodesis failure.

Clear cell renal cell carcinoma (ccRCC) is the most common subtype of renal cell carcinoma (RCC). Although we have made many achievements in the therapy of RCC with the progress of medicine, the clinical management of metastatic RCC remains a daunting challenge. SWI/SNF chromatin remodeling complex-related genes (SCRGs) are significantly associated with tumor progression and cancer cell evolution in ccRCC. This study aimed to investigate the prognostic significance of SCRGs in ccRCC to elucidate its molecular subtype characteristics. Using 29 known SCRGs, 532 ccRCC patients from the TCGA-KIRC cohort were classified into two subtypes (SCRGcluster A and SCRGcluster B). Patients in SCRGcluster B exhibited a significantly poorer prognosis compared to those in SCRGcluster A. Functional enrichment and immune microenvironment profiles significantly differed between the subtypes, with SCRGcluster B showing higher levels of immune infiltration. Five core genes (TMCC3, TOP2A, EPS8, PIK3R3, KCNK5) were identified through the integration of multiple machine learning approaches and multivariate Cox regression analysis. A novel prognostic model based on these core genes was validated in an external cohort. Additionally, single-cell data analysis revealed the expression patterns of these core genes in ccRCC. In vitro experiments demonstrated that KCNK5 is underexpressed in ccRCC cell lines and tissues, and that its overexpression suppresses malignant phenotypes. Specifically, KCNK5 overexpression significantly inhibited the proliferation, migration, and invasion capabilities of ccRCC cell lines. Although the precise functional mechanisms of these core genes in ccRCC are not yet fully elucidated, this study provides new insights for the treatment of ccRCC.

Chronic obstructive pulmonary disease (COPD) is characterized by chronic inflammation of the respiratory tract and is associated with an increased risk of lung cancer. Non-small cell lung cancer (NSCLC) patients with COPD have been shown to exhibit favorable responses to anti-PD-1/PD-L1 therapy. In the present study, we investigated T cell profiles and functions in the lung tissues of NSCLC patients with or without COPD to provide the rationale for immunotherapy of NSCLC patients with COPD. Abundant PD-1+ and Tim-3+ T cells were detected in the lung tumor tissues of NSCLC patients with COPD. On the other hand, CD103+ tissue-resident memory T (TRM) cells in non-tumor lung tissues were more abundant in NSCLC patients with than in those without COPD. Furthermore, the abundance of CD103+ TRM cells in non-tumor lung tissues correlated with IFN-γ production and COPD-related clinical parameters (pack-years smoking history and the FEV1/FVC ratio). In NSCLC patients with COPD, T cells were active participants in both the non-tumor and the lung tumor tissues, suggesting the potential response to immunotherapy.

The PEST-containing nuclear protein (PCNP) has been reported to play paradoxical roles in tumorigenesis. While PCNP functions as a tumor suppressor in neuroblastoma and lung adenocarcinoma, it has been identified as a tumor promoter in ovarian cancer. However, the underlying mechanisms driving these contrasting effects remain unclear. Gene Expression Profiling Interactive Analysis (GEPIA) was employed to analyze relevance of PCNP expression with prognosis in HCC. To evaluate the role of PCNP in hepatocellular carcinoma (HCC), we analyzed the expression of PCNP in 87 HCC tissues and 80 adjacent normal tissues. Correlation between PCNP and ubiquitin-like with PHD and ring finger domains 2 (UHRF2) was transcriptionally detected, and then their effects on malignant behaviors, including proliferation, invasion, tumor formation in vitro and in vivo were evaluated. According to tissues array results, it is found that PCNP was significantly upregulated in HCC tissues, which was further confirmed in HCC cell lines by western blotting. Importantly, both the cytoplasmic and nuclear PCNP fractions were correlated with pathological grade, T staging, clinical staging and recurrence, and patients with a high level of PCNP had lower overall survival and disease-free survival and a higher recurrence rate than those with a low PCNP level, indicating that PCNP might be an independent prognostic factor for HCC patients. Functional investigations revealed that PCNP knockdown inhibited malignant behaviors, including proliferation, invasion, colony formation and tumor formation, in vitro and in vivo. Pearson correlation analysis indicated a positive association between PCNP and UHRF2, with evidence that PCNP transcriptionally upregulates UHRF2. Furthermore, ectopic overexpression of PCNP activated the ErbB3/Ras/Raf1 signaling pathway through upregulation of UHRF2. Our findings suggest that PCNP promotes HCC progression by activating the ErbB3/Ras/Raf signaling pathway through upregulation of UHRF2. Consequently, PCNP holds potential as both a diagnostic biomarker and a therapeutic target for hepatocellular carcinoma.

Endometriosis (EMS) is a chronic gynecological condition affecting 6-10% of reproductive-age women. These lesions, albeit of benign nature, present cancer-like features, and may progress to epithelial ovarian cancer (EOC) through a multistep process. The coexistence of EMS and EOC in the presence of transitional lesions (TL) - i.e. atypical EMS/borderline lesions - is termed as endometriosis-correlated ovarian cancer (ECOC). Given the regulatory role of miRNAs in gene expression and biological pathways, we aimed to identify miRNAs that may drive or modulate the malignant transformation of ovarian EMS. Global miRNA profiling was evaluated on 81 samples (EMS, TL and ECOC) from 44 patients. Principal component analysis and unsupervised clustering revealed two distinct clusters formed by ECOC and ovarian EMS samples, whereas TL were dispersed among the other two. Differential expression analysis (DEA) of TL vs. ovarian EMS, revealed 30 significantly upregulated miRNAs. Comparison of ECOC vs. TL samples yielded 118 significantly upregulated and 77 downregulated miRNAs. Finally, DEA of ECOC vs. ovarian EMS lesions yielded 200 upregulated and 128 downregulated miRNAs. Evaluation of miRNAs commonly deregulated between the three groups showed 14 shared upregulated miRNAs (miR-429, miR-425-5p, miR-200c-3p, miR-200c-5p, miR-200b-3p, miR-200a-3p, miR-183-5p, miR-182-5p, miR-141-5p, miR-141-3p, miR-96-5p, miR-93-5p, miR-10a-5p, miR-10a-3p) with a progressive increase in expression levels, from ovarian EMS to TL and ultimately to ECOC. The identified miRNA expression profiles associated with the progression from ovarian EMS, TL and ECOC provide valuable insights into the molecular progression from benign to malignant lesions and could represent potential biomarkers for the early detection of ECOC.

SEPT9 methylation has been closely linked to breast cancer, yet its role in differentiating disease stages remains unclear. In particular, Few studies previously have examined differences in SEPT9 methylation between ductal carcinoma in situ (DCIS) and invasive ductal carcinoma (IDC), or among DCIS lesions of varying nuclear grades. This study investigated SEPT9 methylation across 105 breast cancer cases, classified into pure DCIS, DCIS with invasive components (DCIS-INV), IDC alone, and metastatic breast cancer (MBC). Methylation levels were measured using real-time PCR, and in vitro experiments were conducted using MCF-7 and T47D cell lines treated with decitabine to explore the relationship between methylation and microtubule stability. SEPT9 methylation was significantly elevated in cancer cells compared to normal breast epithelium, with positivity rates of 90.6% in DCIS-INV, 77.8% in IDC, and 79.2% in MBC, versus only 18.2% in pure DCIS. SEPT9 methylation was negtive in low-grade DCIS and positive in 28.6% of intermediate- to high-grade cases. Positive methylation was significantly associated with high Ki-67 expression and lymph node metastasis (P < 0.05), but showed no correlation with age, menopausal status, tumor size, or hormone receptor status. Additionally, decitabine treatment induced a reduction in SEPT9 methylation levels, which affects microtubule stability, suggesting a potential mechanistic link to tumor invasion. These findings indicate that SEPT9 methylation is a promising biomarker for distinguishing invasive breast cancer from DCIS and for identifying high-risk DCIS lesions with greater potential for progression.

To develop a postoperative recurrence/metastasis risk prediction model for cervical cancer based on circulating tumor cells (CTCs) and tumor fibrosis distance (TFD), and to validate its biological mechanisms through animal experiments. This model aims to guide preoperative risk stratification and personalized treatment strategies. A total of 148 patients with stage IB-IIA cervical cancer who underwent radical surgery between 2020 and 2022 were retrospectively enrolled. Preoperative CTC counts, TFD measurements, and clinicopathological data were collected. Independent prognostic factors were identified using Cox regression analysis. The model's performance was assessed using receiver operating characteristic (ROC) curves, and risk stratification was evaluated with Kaplan-Meier survival analysis. Additionally, an orthotopic tumor model was established in 60 Sprague-Dawley rats divided into six groups (Control, Model, HTFD, LTFD, HCTCs, and LH). Tumor burden, CD4+/CD8 + ratios, IL-6, TNF-α, MDA, and SOD levels were measured to explore the model's underlying metabolic and immune mechanisms. Patients with poor outcomes had significantly higher CTC counts (30.50 vs. 23.74/5 mL, P < 0.001) and lower TFD values (5.47 vs. 5.98 mm, P < 0.001). CTCs ≥ 28/5 mL (OR = 6.63) and TFD ≤ 5.7 mm (OR = 3.37) were identified as independent predictors of poor prognosis. The combined model yielded an AUC of 0.91, with a sensitivity of 90.6%, specificity of 84.5%, and a negative predictive value (NPV) of 94.7%. Patients were stratified into low-, intermediate-, and high-risk groups, with corresponding clinical management recommendations. In high-risk rat groups, elevated CTC release, reduced CD4+/CD8 + ratios, increased IL-6 and TNF-α levels, and significant oxidative damage were observed, supporting the biological plausibility of the clinical model. Unlike conventional models that mainly rely on clinicopathological features, our model incorporates both CTCs and TFD, providing superior discrimination for recurrence risk and offering a novel integrative approach for postoperative surveillance. This dual validation underscores the translational potential of the model, which may be incorporated into individualized postoperative monitoring strategies and multidisciplinary decision-making.

Papillary thyroid carcinoma (PTC) is a malignancy with an ambiguous etiology. The competitive endogenous RNA (ceRNA) hypothesis provides a framework for clarifying the molecular mechanisms that drive carcinogenesis. In this study, we constructed a novel ceRNA network to identify reliable diagnostic and prognostic indicators applicable across all stages of PTC. Transcriptome analysis was performed to identify stage-specific hub genes using the MCC, IVI, and MCODE algorithms. A novel five-layer ceRNA network and its associated regulatory network (DE-TF) were constructed. Receiver operating characteristic curves were used to evaluate the diagnostic performance of elements within both networks. A risk assessment model was developed by identifying key genes from the ceRNA and DE-TF components through univariable Cox regression and LASSO regression analyses. RNA-seq findings were validated by RT-qPCR. The correlations between gene expression levels and blood calcium levels were examined. The ceRNA and DE-TF networks contained 33 and 21 components, respectively. Logistic regression analysis identified PKMYT1, E2F1, NFATC1, STAT6, E2F3, LINC02910, GAS5, and TK1 as reliable diagnostic markers for PTC, achieving an AUC of 96.9%. Among these, PKMYT1 and GAS5 were stage-specific markers, showing significant upregulation in highly aggressive PTC tumors compared to less aggressive ones. Both genes demonstrated strong diagnostic value in differentiating high- from low-aggressive tumors, with AUCs of 0.81 and 0.87, respectively. circMET, which was overexpressed in both low- and high-aggressive tumors, showed diagnostic potential in distinguishing low-aggressive tumors from normal adjacent tissues (AUC = 0.81). GAS5 expression demonstrated an association with blood calcium levels. The SERN prognostic model, including STAT6, E2F1, RMI2, and NR4A1, illustrates the importance of these four genes as reliable prognostic markers for overall survival in PTC. Three components of the ceRNA network-PKMYT1, GAS5, and circMET-were significantly associated with PTC aggressiveness. PKMYT1 and GAS5 demonstrated strong diagnostic value in distinguishing high-aggressive from low-aggressive tumors, while circMET showed notable diagnostic efficacy in differentiating low-aggressive PTC tumors from adjacent normal tissues. Furthermore, GAS5 expression levels were correlated with blood calcium levels.

The prognosis of breast cancer varies by histologic subtype, with infiltrating ductal carcinoma (IDC) being the most prevalent, comprising 70% of infiltrating breast cancers. Long-term survival outcomes for IDC remain unclear, and some non-early-stage IDC patients exhibit better survival than initially expected. Dynamic survival probability offers a more accurate approach to life expectancy estimation compared to traditional methods such as Kaplan-Meier analysis and the tumor-node-metastasis (TNM) staging system-based nomogram (TNM nomogram) .This study aims to develop a conditional survival prediction model for non-early-stage infiltrating ductal carcinoma patients, with a particular focus on long-term survival assessment of female IDC patients at stage IIB and beyond (according to the AJCC classification), to support personalized treatment planning. Female IDC patients from the SEER database (2000-2022) were analyzed. Overall survival probabilities for additional y years after surviving x years were calculated using the Kaplan-Meier method. Lasso, subset regression, and multivariate Cox proportional hazards analysis were applied to identify significant predictors for constructing a conditional survival (CS) nomogram, where CS is defined as the probability of surviving y additional years given that a patient has already survived x years. The CS nomogram was compared to the TNM-nomogram using the concordance index, ROC curves, calibration plots and decision curve analysis (DCA). The conditional survival nomogram, incorporating 12 variables, predicted 3-, 5-, and 10-year survival, as well as 10-year conditional survival. It demonstrated higher predictive accuracy compared to the TNM-nomogram, reflected by a superior concordance index and improved ROC curves. Calibration plots further confirmed its greater precision, and decision curve analysis (DCA) highlighted better net benefits across varying risk thresholds. Unlike the traditional nomogram, which only provides unconditional survival probabilities at diagnosis, the CS-nomogram dynamically updates survival estimates according to the time already survived (CS(y|x) = OS(x + y)/OS(x)). The conditional survival nomogram provides more accurate and personalized survival predictions for non-early-stage IDC patients, surpassing traditional nomogram. This tool offers valuable guidance for clinical decision-making and improves the precision of survival estimations.

Malignant mesothelioma (MM) is a rare, aggressive cancer with poor outcomes due to its heterogeneity and therapy resistance. Patient-derived organoids (PDOs) have emerged as a promising tool for precision medicine, as they faithfully recapitulate key tumor characteristics. This study aimed to establish MM PDOs and develop a PDO-T cell co-culture system to evaluate their utility in guiding personalized MM treatment. MM PDOs were generated from malignant ascites, pleural effusions, fine-needle biopsies, and surgical tissues. Organoids were characterized using H&E staining, immunohistochemistry (IHC), and next-generation sequencing (NGS). PBMC-derived T cells were co-cultured with PDOs to assess immunotherapy and chemotherapy responses. Drug sensitivity testing was performed to evaluate treatment efficacy. 11 MM PDOs were successfully established, which recapitulated the histological features and genomic profiles of their parental tumors. Drug sensitivity testing revealed heterogeneous responses of PDOs, with sensitivity to anlotinib but resistance to cisplatin plus pemetrexed plus bevacizumab. Notably, PDOs established from the same patient at different time points displayed dynamic changes in genetic profiles and drug sensitivities, mirroring in vivo tumor progression. In the PDO-T cell co-culture system, anti-PD-1 immunotherapy, especially combined with chemotherapy, significantly reduced organoids viability of patient PM002. MM PDOs and the PDO-T cell co-culture system constitute robust models for investigating tumor progression, drug responses, and immunotherapy efficacy. These tools highlight their potential in advancing personalized medicine for MM.

ccRCC is an aggressive, heterogeneous tumor with a poor prognosis. Prognostic assessments need multi-modal data. Radiological images have limits, while pathological images offer micro-level details. Integrating these for ccRCC outcome prediction is important. Our study aimed to develop and validate a DL fusion model using multiphase CT images and WSI for postoperative risk stratification in ccRCC patients. This retrospective study included 274 ccRCC patients who underwent multiphase CT scans (Jan 2008-Mar 2021), with diagnoses confirmed by histopathology post-surgery. The patient cohort was divided into a training cohort of 164 patients for model development and a test cohort of 110 patients for model validation. The primary outcome was local recurrence or metastasis versus non-recurrence (NR) with a minimum follow-up of 3 years. DL models based on multiphase CT images and histopathological WSIs were developed and validated. Performance comparisons among models were made through accuracy (ACC) and receiver operating characteristic (ROC) curve analyses, with integrated discrimination improvement (IDI) analysis and the DeLong test assessing diagnostic performance. Decision curve analysis (DCA) evaluated clinical utility, and Kaplan-Meier analysis assessed variable-survival correlations. The CT and Pathology Mutual Guidance Fusion Diagnostic Network (CPNet) exhibited superior performance in predicting postoperative disease-free survival (DFS) in ccRCC patients. Among the models, the PCP-Pathology Fuse model achieved the highest AUC of 0.8363 and accuracy of 75.45%, outperforming the CMP-Pathology Fuse (AUC 0.7965, ACC 69.09%) and NP-Pathology Fuse (AUC 0.798, ACC 69.09%) models. Its performance was comparable to the Three-phase-Pathology Fuse model (AUC 0.8341, ACC 70.00%, P > 0.05). IDI and DCA confirmed significant net benefits (0.01-0.95) for the PCP-based model. The PCP-based CPNet model shows promise for predicting postoperative DFS in ccRCC patients, with performance comparable to three-phase CT-pathology models. It may serve as a potential bioimaging prognostic marker, pending external validation to support clinical integration.

Three-dimensional spheroid models play a crucial role in cancer stem cell (CSC) research and drug screening. However, traditional methods often struggle with issues such as inconsistent shapes, difficulties in nutrient diffusion, and technical complexities. In this study, we introduce the SpheroidSync (SS) method, an innovative approach that combines conventional techniques to create uniform and size-adjustable MCF7 breast cancer spheroids at a very low cost, without the need for special growth factors or supplements. Our research involved culturing MCF7 cells using both the standard methods and the new SS method. We meticulously assessed various factors, including spheroid shape and cell viability, through fluorescent staining, colony formation assays, and gene expression analysis. The results revealed that the SS method produced spheroids that were not only uniform but also showed better structural integrity and maintained viability over time compared to traditional methods. Fluorescent viability tests indicated that SS spheroids consistently exhibited healthy cell viability as evidenced by sustained intracellular esterase activity throughout more extended culture periods. In contrast, spheroids generated through conventional methods exhibited declining viability, characterized by core deterioration and uneven staining. Furthermore, gene expression analysis showed a significant increase in CSC markers in SS spheroids, with CD44 levels rising over 40-fold, ALDH1 increasing more than threefold, CD24 decreasing, and HIF-1α elevating over 11-fold when compared to two-dimensional cultures. This establishes the typical breast CSC characteristics and confirms that a hypoxic environment was effectively created. Notably, as esterase activity declined, we observed an increase in stem cell populations, indicating a successful shift towards a quiescent, stem-like state. In summary, SpheroidSync represents a significant advancement in three-dimensional cancer modeling. It enables the production of uniform spheroids in a cost-effective manner, while ensuring long-term viability and enriching CSC populations.

Hepatocellular carcinoma (HCC) is a prevalent type of tumor. Given the controversy surrounding atorvastatin and HCC, we conducted this study to determine whether atorvastatin has anticancer activity against HCC. The impact of varying concentrations of atorvastatin (ATO) on the biological function of HCC cells was studied in vitro, high-throughput mRNA assays on cells and tumor tissue. Finally, an examination was conducted to assess the correlation between the ATO and the prognosis of HCC. ATO significantly inhibited the proliferation, migration, and invasiveness of HCC cells. Furthermore, in vivo, animal experiments showed that a high-fat diet facilitated the progression of HCC and that ATO did not effectively counteract these detrimental consequences. Tumor sequencing of cells and normal diet mice revealed the disparities were primarily concentrated in the MAPK signaling pathway. Western blot demonstrated ATO reduced the expression of levels of p-MEK, p-RAF1, p-P38, p-ERK, and p-JNK proteins in HCC cells compared to controls. Clinical data showed that HCC patients with ATO exhibited improved recurrence-free survival (RFS) and overall survival (OS). Following the utilization of propensity score, HCC patients with ATO were found to have better OS, whereas there was no substantial difference in RFS. Atorvastatin effectively inhibits the proliferation, invasion, and migration of HCC cells in vitro through the MAPK pathway. Additionally, ATO may help improve the prognosis of some individuals with HCC.

Advanced cervical cancer (aCC) is associated with a poor prognosis. This study aimed to develop and validate a deep learning-based risk stratification model to predict overall survival in aCC patients using pre-treatment CT images. A total of 396 patients with aCC were retrospectively enrolled and randomly allocated into training (n = 198) and validation (n = 198) cohorts. A deep learning model integrating a Vision Transformer (ViT) for feature extraction and a Recurrent Neural Network (RNN) for sequence modeling was developed to generate a prognostic radiomic signature (Rad-score) from baseline CT scans. The Rad-score was incorporated into a Cox proportional hazards model alongside clinical variables to construct an integrative nomogram. The model's performance was evaluated using the concordance index (C-index), time-dependent receiver operating characteristic (ROC) analysis, calibration curves, and decision curve analysis (DCA). Multivariate Cox regression identified the Rad-score as a strong independent prognostic factor (Hazard Ratio [HR] = 4.06, 95% confidence interval [CI]: 2.46-6.70, p < 0.001). The integrative nomogram achieved C-indexes of 0.784 (95% CI: 0.733-0.835) and 0.726 (95% CI: 0.677-0.785) in the training and validation cohorts, respectively. Calibration and DCA curves indicated good clinical utility. Kaplan-Meier analysis confirmed that the model-based risk stratification significantly discriminated between high- and low-risk patients (p < 0.001). The proposed deep learning-based nomogram offers a non-invasive and reproducible tool for predicting survival in aCC patients. It shows potential for assisting clinicians in making personalized treatment decisions and warrants further validation in prospective, multi-center studies before widespread clinical application.

Programmed cell death ligand 1 (PD-L1) has emerged as a key biomarker in determining both the progression and prognosis of gastric cancer (GC). Consequently, its detection through immunohistochemical (IHC) analysis is essential for guiding appropriate treatment selection. We conducted an analytical, observational study based on a five-year retrospective cohort of patients diagnosed with gastric cancer at a comprehensive oncology center in Colombia. All patients underwent immunohistochemistry (IHC) to assess PD-L1 expression and calculate the Combined Positive Score (CPS). The objective of this study was to compare the positivity detection rates between the 28-8 and 22C3 assays and to evaluate the concordance between them. A descriptive analysis of clinical and pathological variables was performed. Univariate analysis was used to determine the frequency of PD-L1 expression and CPS distribution. Kaplan-Meier survival analysis was applied and stratified by PD-L1 status. Concordance between the two assays was assessed using the kappa (κ) index. A total of 175 patients diagnosed with gastric cancer (GC) and tested for PD-L1 expression were included in the study. Complete pathological and IHC data were available for 155 patients. Among them, 39.4% were tested with the 28-8 assay, and 60.6% with the 22C3 assay. PD-L1 positivity was observed in 34.4% of cases using the 28-8 assay and in 28.7% using the 22C3 assay. Among patients with available follow-up data (n = 34), PD-L1 testing was performed using the 22C3 clone, with a positivity rate of 35.3%. In the subgroup analysis of patients tested with both antibodies (n = 20), 60% were PD-L1 positive. Within this subset, 25% had a CPS of 1-4, 16.7% had a CPS of 5-9, and 58.3% had a CPS ≥ 10. For the 22C3 assay specifically, PD-L1 positivity was observed in 40% of cases, with 37.5% having a CPS of 1-4 and 62.5% a CPS ≥ 10; notably, no cases in this group had a CPS of 5-9. The concordance rate between the 28-8 and 22C3 assays was 61%, as measured by the kappa index. The 28-8 clone identified a higher proportion of patients with PD-L1 expression compared to the 22C3 antibody. However, both assays demonstrated a concordance rate of 61%. In the study population, the subgroup with a Combined Positive Score (CPS) ≥ 10 was the most prevalent, suggesting that high PD-L1 expression is relatively common and potentially clinically relevant in this cohort.

Obesity is associated with the increased incidence of various cancers. However, the connection between high body mass index and oral cancer risk is partly controversial, and the mechanistic role of adipocytes is largely unknown. We aimed to study the prognostic value and function of adipose tissue in oral tongue squamous cell carcinoma (OTSCC). The amount of adipocytes in OTSCC samples correlated positively with tumour size. High tumoural inflammatory cell count predicted better overall survival. Patient-derived adipose tissue and adipocytes (differentiated from adipose tissue-derived mesenchymal stem cells) induced the proliferation of OTSCC cells in vitro. Moreover, adipocytes increased the migration of cancer cells from both primary and metastatic sites without the need for direct cell-cell contact. Various cytokines, including interleukin 6 (IL-6), were present at high levels in adipocyte-OTSCC co-cultures, and inhibition of IL-6 signalling markedly reduced cancer cell migration. Moreover, the adipocyte-derived extracellular vesicles (EVs) induced OTSCC cell invasion. We conclude that adipocytes increase the proliferation of cancer cells and enhance their motility without direct cell contact. The protumourigenic effect of adipocytes is likely mediated by secreted cytokines, such as IL-6, and transported via EVs.

Melanin synthesis within melanosomes critically depends on the fibrillar architecture formed by the pigment cell-specific protein PMEL. Although PMEL fibrils have historically been classified as functional amyloids, their native supramolecular organization in situ and detailed molecular architecture have remained unresolved. In this study, we combine in situ cryo-electron tomography (cryo-ET) and cryo-electron microscopy (cryo-EM) to elucidate the native structural organization of PMEL fibrils within human melanosomes from both patient melanoma tissues and melanocyte cell lines. We demonstrate that PMEL does not form conventional isolated amyloid fibrils, but rather assembles into highly organized lamellar sheets consisting of laterally aligned fibrils interconnected by flexible linker regions. Cryo-EM structures reveal a distinctive butterfly-shaped fibril unit composed of multiple structured domains, including both the proteolytically cleaved Mα and Mβ fragments of PMEL, which assemble into a amyloid-like β-sheet arrangement. Notably, we identify intrinsically disordered regions critical for lamellar assembly and curvature and verify key glycosylation modifications in the structure. This architecture distinguishes PMEL fibrils from canonical amyloids and elucidates the molecular basis underlying melanosome integrity and pigmentation. Moreover, our work provides molecular insights relevant for pigmentation disorders and PMEL-associated diseases, including melanoma.

The contribution of rare pathogenic/likely pathogenic (P/LP) germline variants to pediatric central nervous system (CNS) tumor development remains understudied. Here, we characterize the prevalence and biological significance of germline P/LP variants in cancer predisposition genes across 830 CNS tumor patients from the Pediatric Brain Tumor Atlas (PBTA). We identify germline P/LP variants in 23.3% (193/830) of patients and the majority (137/193) lack clinical reporting of genetic tumor syndromes. Among P/LP carriers, 34.6% have putative somatic second hits or loss of function tumor alterations. Finally, we link pathogenic germline variation with somatic events and patient survival to highlight the impact of germline variation on tumorigenesis and patient outcomes.

Changes in the immune microenvironment are frequent in cancers occurring in adult patients, yet our understanding of the pediatric cancer immune microenvironment and its clinical relevance is limited. We investigate the immune microenvironment in pediatric T cell acute lymphoblastic leukemia (T-ALL), using single-cell CITE-seq and immune repertoire analyses. We identify a T-ALL subgroup characterized by a remodeled immune microenvironment, which is associated with adverse clinical outcome in minimal residual disease low patients. This adverse immune landscape is dominated by the presence of a population of non-malignant CD4-CD8-TCRαβ T cells that interact with CXCL16 expressing non-classical monocytes. Leukemia cell intrinsic transcriptional rewiring in these patients is associated with activation of Rap1 signaling. Inhibiting Rap1 signaling results in increased sensitivity to the BCL2/BCL-XL inhibitor navitoclax. Our study provides insights into the immune microenvironment of pediatric hematologic malignancies, forming the basis for identifying potential (immuno) therapeutic targets and risk stratification for treatment.