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.

Concurrent chemoradiotherapy (CCRT) has remained the standard treatment for unresectable locally advanced esophageal squamous cell carcinoma (ESCC), yet survival remains poor. This single-arm, phase II trial aims to evaluate the efficacy and safety of two cycles of induction chemotherapy with camrelizumab followed by CCRT in previously untreated patients with unresectable locally advanced ESCC. The primary endpoint, the 1-year overall survival (OS) rate in the per-protocol population (N = 46), was 87.0% (95% confidence interval [CI]: 77.7%-97.3%), exceeding the pre-specified target. Secondary endpoints included OS in the intention-to-treat (ITT) population, progression-free survival (PFS), overall response rate (ORR), disease control rate (DCR), duration of response, safety, and health-related quality of life. In the ITT population (N = 49), the 1-year OS rate was 85.7% (95% CI: 76.5%-96.1%). The 1-year PFS rates in the per-protocol and ITT populations were 71.7% (95% CI: 59.8%-86.0%) and 71.4% (95% CI: 59.8%-85.3%), respectively. The median OS, PFS, and duration of response were not reached. Following CCRT, the ORR was 93.5%, with a DCR of 95.7%. Lymphopenia was the most frequent Grade ≥3 adverse event (100%). One patient died from treatment-related myelosuppression. Health-related quality of life generally improved after induction therapy, with significant improvements in global health status, emotional functioning, and some symptom relief, despite a slight decline in physical functioning. Here, we show that induction chemoimmunotherapy followed by CCRT exhibits promising efficacy and manageable safety in patients with unresectable locally advanced ESCC, thus warranting further randomized controlled trials. Trial number: ChiCTR2000034304.

Lysine lactylation is a post-translational modification induced by lactate discovered in recent years. Abnormal lysine lactylation contributes to the occurrence and progression of various tumors. However, the mediators and downstream targets of lysine lactylation remain unclear. Here, we report that HAT1 serves as a potential lactyltransferase that can promote homologous recombination and lead to radioresistance by regulating lactylation of RPA1. Lactylation of RPA1 facilitates its binding to single-stranded DNA and MRE11-RAD50-NBS1 (MRN) complexes and promotes homologous recombination. HAT1 knockout inhibits DNA repair in lung adenocarcinoma cells, thereby increasing radiotherapy sensitivity. Interestingly, we also found that K15 auto-lactylation of HAT1 can modulate its lactyltransferase activity. In conclusion, our research reveals that HAT1-regulated RPA1 lactylation plays an important role in homologous recombination and radioresistance, suggesting that HAT1 may become a potential therapeutic target for reversing the radioresistance caused by lactate accumulation in cancer cells.

Many non-small cell lung cancer (NSCLC) patients remain unresponsive to the current standard of care, which includes chemotherapy and immune checkpoint inhibitors, like anti-PD-1/PD-L1 antibodies. While interleukin (IL)-1β is known to promote lung cancer growth in humans and mice, we show here that IL-1β administration or overexpression overcomes resistance to classical chemo-immunotherapy (cisplatin/pemetrexed/anti-PD-1) in mouse lung cancer models. The antitumor effects of IL-1β rely on cancer cell-derived CXCL10 which mediates CD8 T cell recruitment at the tumor site. In lung cancer cells, Thioredoxin Interacting Protein (TXNIP) induces mitochondrial DNA (mtDNA) release in the cytosol, activating Absence in Melanoma 2 (AIM2) inflammasome, which subsequently triggers IL-1β and CXCL10 secretion, thereby reversing chemo-immunotherapy resistance. The clinical relevance of our findings is supported by the transcriptomic analysis of patient tumors, showing that high expression of IL1B, IL1R1, AIM2 and/or TXNIP is associated with better response to immunotherapy in NSCLC patients. Additionally, drug screening identifies MEK and MDM2 inhibitors as inducers of TXNIP expression capable of reversing resistance to chemo-immunotherapy. This study highlights a positive role of IL-1β in lung cancer treatment and suggests that enhancing IL-1β production at the tumor site can overcome resistance to chemo-immunotherapy.

Ubiquitin carboxyl-terminal hydrolase L3 (UCHL3) is a deubiquitinating enzyme involved in various cancers, yet its role in gastric cancer (GC) requires further exploration. This study primarily investigates the expression, function, and mechanisms of UCHL3 in GC. Clinical samples and bioinformatics analysis indicated that UCHL3 is overexpressed in GC tissues compared to adjacent normal tissues, with higher expression levels correlating with worse prognosis. Functional assays demonstrated that UCHL3 promotes GC cell proliferation, invasion, and migration, accelerates cell cycle progression, and induces epithelial-mesenchymal transition (EMT). In vivo studies using a cell line-derived xenograft (CDX) model confirmed that UCHL3 enhances GC proliferation, and its therapeutic potential was validated in patient-derived xenografts (PDX). Mechanistically, transcriptomic analysis and validation experiments identified the AKT/CCND1 signaling pathway as a key mediator of UCHL3-driven GC progression. Co-immunoprecipitation (Co-IP) and liquid chromatography-mass spectrometry identified potential UCHL3-binding proteins, notably the AKT activator ENO1. Molecular docking simulations, Co-IP, and GST-pull down assays further confirmed the interaction, mapping the binding regions between UCHL3 (AA 179-230) and ENO1 (AA 140-434). Cycloheximide (CHX) and in vivo ubiquitination assays demonstrated that UCHL3 deubiquitinates and stabilizes ENO1, thus extending its half-life, while UCHL3 inhibition produced the opposite effect. A C95A point mutation significantly impaired UCHL3's deubiquitination function on ENO1. Further studies revealed UCHL3 removes K48-linked polyubiquitin chains from ENO1 at lysine 92, activating the AKT/CCND1 signaling pathway. In addition, the small-molecule inhibitor TCID, specific for UCHL3, inhibited this deubiquitination, counteracting pro-tumorigenic effects. In vitro and in vivo experiments demonstrated that TCID increased the sensitivity of GC cells to CDK4/6 inhibitors palbociclib. These findings suggest that UCHL3 contributes to GC progression and represents a promising therapeutic target for GC treatment.

Stress-induced alternative processing of mRNA is emerging as an essential mechanism to drive almost every hallmark of cancer. Through a genome-wide screening based on an abnormal transcriptional readthrough event favoring the malignant progression of ovarian carcinoma (OC), we identified novel mRNA processing regulators including RRN3, an essential factor for the transcriptional initiation of rRNA. The long-read RNA sequencing and PAR-CLIP analyses revealed that RRN3 was involved in the usage of alternative polyadenylation (APA) sites, resulting in the altered stability of autophagy-related mRNAs. More interestingly, we discovered that nutrient-deprivation-induced phosphorylation of RRN3 at serine 199 was sufficient to divert RRN3 out of the nucleolus to the nuclear plasma, where RRN3 regulated the APA of autophagy mRNAs, such as OPTN, to enhance their stability and eventually promoted autophagy. Further in vivo experiments showed that nutrient-stress-triggered switch of RRN3 from rRNA transcription to APA regulation was essential for the growth and dissemination of OC in mice.

Blood coagulation and cancer are intricately related. Hypercoagulation associated with cancer leads to aberrant thrombin generation, which contributes to thrombosis. Thrombin also activates anticoagulant protein C and the activated protein C (aPC), in addition to regulating the coagulation pathway, it also elicits cell signaling by binding to endothelial cell protein C receptor (EPCR) and activating protease-activated receptor 1 (PAR1)-mediated cell signaling. Earlier studies showed that aPC promotes lung adenocarcinoma survival and metastasis. However, the underlying mechanism remains largely unknown. Our present study provides mechanistic insight into how aPC promotes lung adenocarcinoma survival, metastasis, and drug resistance. Our study shows that aPC, through EPCR-PAR1-driven activation of RhoA-ROCKII-JNK1/2-MLC2 signaling, triggers extracellular vesicle (EV) release from lung adenocarcinoma cells. aPC-EVs, via the transfer of microRNA (miR)-200a, promote proliferation, migration, and invasion of normal lung epithelial cells. They also confer resistance to lung cancer against chemotherapeutic agents. Inhibition of miR-200a functions through the incorporation of anti-miR-200a abrogates aPC-EVs-mediated tumorigenic effects. Furthermore, loading miR-200a mimic into control EVs showed similar phenotypic responses to that of aPC-EVs. miR-200a is shown to target SOX17 in the recipient cells, leading to tumorigenesis. miR-200a upregulation and SOX17 downregulation are consistently observed in lung cancer tissues in the UALCAN portal database of clinical specimens. Consistent with these findings, our in vivo studies in BALB/c nude mice showed that aPC-EVs from lung cancer cells promote tumor growth, metastasis, and drug resistance through miR-200a transfer. Targeting EV biogenesis, EV's miR-200a, and/or EV uptake mechanisms may offer novel therapeutic strategies in limiting lung tumorigenesis, thereby increasing patients' survival.

Type-II topoisomerases resolve topological stress in DNA through double-strand breaks. While topoisomerases are chemotherapy targets linked to therapy-related genotoxicity, TOP2B is uniquely positioned to influence mutagenesis through its activity in non-dividing cells and sensitivity to topoisomerase poisons. To investigate this, we generated DNA-binding maps of TOP2B, CTCF, and RAD21 in human cancer samples and analyzed these for driver mutations and mutational processes across 6500 whole cancer genomes. TOP2B-CTCF-RAD21 and TOP2B-RAD21 sites are enriched in somatic mutations and structural variants, particularly at sites with evolutionary conservation, high transcription and long-range chromatin interactions. TOP2B binds driver genes such as TP53, MYC, FOXA1, and VHL, and many frequently mutated non-coding regions. We show that one non-coding TOP2B-bound element at the non-coding RNA gene RMRP drives tumor initiation and growth in vivo. Our study highlights TOP2B as a safeguard of genome integrity and a marker of mutational processes and hotspots in cancer, underscoring implications for cancer genomics research.

Head and neck cancer (HNC) comprises a heterogeneous group of malignancies with significant variation in epidemiology, clinical features, and treatment responses. However, large-scale data on the clinical epidemiology of HNC and the prognostic impact of human papillomavirus (HPV) infection have not yet been reported.

This study aims to develop and validate an explainable machine learning model for predicting postoperative survival in patients with locally advanced gastric cancer (LAGC), optimizing predictive accuracy while ensuring clinical applicability to facilitate personalized prognostication for patients.

In this issue of Cell Chemical Biology, Zhang et al.1 report the identification of a high-affinity EMBOW-derived inhibitor of WDR5, Ac7, which demonstrates in-cell target engagement and in vivo antileukemic efficacy. The microprotein-inspired inhibitor potently blocks the WDR5-MLL1 interaction, suppressing H3K4 methylation and transcription of target genes in mixed lineage leukemia (MLL)-rearranged leukemia.

Results from single-arm clinical trials can be contextualized by comparing against external controls (ECs) derived from real-world data (RWD). However, lack of randomization and differences in variable capture between data sources may introduce bias into estimates of treatment effect and standard error, the extent of which can be assessed via meta-analysis of comparisons between clinical trial control arms and their EC replicates.