Aug 2026· Diseases of the esophagus· Vol 39· 0 citations
TL;DR
Quantitative proteomic profiling of acquired chemoresistant oesophageal adenocarcinoma cell models identifies broad adaptive changes with both heterogeneous and recurrent components, and suggests a platinum-class component supported by overlap between oxaliplatin- and carboplatin-resistant models.
Abstract
Esophageal Cancer: Molecular Biology/Pathology
Oesophageal adenocarcinoma is a rapidly rising cancer with poor prognosis. Despite advances in surgery, chemotherapy, and targeted therapy, five-year survival remains below 20%. Treatment failure is largely driven by acquired chemoresistance, enabling tumour cells to survive under therapeutic pressure. Understanding resistance mechanisms is critical to identify vulnerabilities and improve outcomes.
Matched parental and acquired chemoresistant oesophageal adenocarcinoma cell models were profiled by quantitative proteomics. Cell lysates were processed by filter-aided sample preparation with tryptic digestion and analysed by data-independent acquisition LC-MS/MS. Peptides were identified and quantified using established DIA analysis pipelines with standard quality control, alignment and normalisation; thousands of proteins were consistently quantified across datasets. Protein abundance profiles were compared between resistant and parental counterparts and across resistant models generated against distinct chemotherapeutic agents to delineate shared versus agent-specific adaptations. Differential abundance testing used pre-specified thresholds for statistical significance (p < 0.05) and effect size (fold-change cut-offs), implemented in Perseus and complemented by custom R scripts for data integration, overlap analysis, and visualisation. Prioritisation focused on robustly upregulated proteins supported by reproducibility across models. Functional annotation, pathway enrichment, and protein interaction analyses were applied to identify convergent resistance programmes and nominate candidates for follow-up.
Thousands of proteins were consistently quantified across datasets, enabling robust comparison of chemoresistant versus parental counterparts and cross-model integration. Differential abundance analysis used p < 0.05 with an initial fold-change cut-off greater than 2 to define resistance-associated changes. Resistant and parental phenotypes segregated clearly, showing remodelling of metabolic, stress-response, and structural pathways. Cross-comparison of six resistant models identified substantial heterogeneity, with many alterations unique to individual models, but also recurrently enriched proteins shared across multiple datasets, including subsets shared between models exposed to the same agent or drug class. In dose-stratified oxaliplatin-resistant models (5 μM and 10 μM), low and high exposure states displayed highly concordant proteomic responses, with conserved alterations that became more pronounced at higher exposure. More stringent filtering (fold change >4) of the shared oxaliplatin response yielded nine consistently upregulated candidates. Three of these candidates also recurred in a carboplatin-resistant model, supporting a potential platinum-class resistance signature.
Quantitative proteomic profiling of acquired chemoresistant oesophageal adenocarcinoma cell models identifies broad adaptive changes with both heterogeneous and recurrent components. Cross-model integration highlights shared adaptations, including patterns consistent with drug class–specific responses, and suggests a platinum-class component supported by overlap between oxaliplatin- and carboplatin-resistant models. The prioritised candidates provide a focused starting point for orthogonal validation in independent models and translational settings, and for mechanistic studies to define actionable vulnerabilities relevant to therapy resistance.
Background Esophageal squamous cell carcinoma (ESCC) is a highly aggressive malignancy with poor prognosis and limited therapeutic options. Ferroptosis, a regulated form of cell death characterized by iron-dependent lipid peroxidation, plays a crucial role in tumor progression and immune regulation. Methods We integrated single-cell RNA sequencing (scRNA-seq) and bulk transcriptomic data to identify ferroptosis-active cellular subpopulations within the ESCC tumor microenvironment. A ferroptosis-related prognostic model was constructed using LASSO-Cox regression and validated across independent cohorts from TCGA and GEO. Associations with immune infiltration, tumor mutation burden, therapeutic response, and drug sensitivity were explored. Furthermore, functional experiments were conducted in vitro using the ESCC cell lines, and the four prognostic core genes were revalidated using an independent single-cell dataset, which was also fully confirmed in clinical ESCC tissue samples. In addition, Western blot analysis was performed to examine the expression levels of ferroptosis-related proteins following CDCA3 knockdown, and to further investigate the impact of CDCA3 depletion on the cellular response to the ferroptosis inducer RSL3. Results Four ferroptosis-related genes (CBS, CDCA3, GALNT14, and IDO1) were identified used to construct a robust risk model, effectively stratifying patients into high- and low-risk groups with significant differences in survival, immune infiltration, and predicted treatment response. In vitro experiments confirmed that CDCA3 knockdown significantly inhibited the proliferation and migration of ESCC cells and induced ferroptosis. GSE188900 single-cell sequencing data further confirmed that the aforementioned genes were significantly upregulated at single-cell resolution in tumor cells, with consistent validation in clinical ESCC tissue samples, Moreover,experimental results showed that knockdown of CDCA3 lead to the downregulation of ferroptosis inhibitor-related genes and upregulation of ferroptosis-promoting genes, thereby enhancing the sensitivity to RSL3-induced ferroptosis. Conclusions Our study presents a single-cell-resolved ferroptosis gene signature with strong prognostic and therapeutic implications for ESCC. The signature was validated in clinical tissue samples, and this model lays the foundation for ferroptosis-targeted therapeutic strategies.
Qin Xu, Yu Ma, Xuanqi Huang et al.· Frontiers in Oncology· 0 citations
ABSTRACT Background Chemoresistance to platinum‐based regimens, primarily gemcitabine plus cisplatin, remains a major obstacle in the treatment of advanced bladder cancer. Identifying the underlying molecular mechanisms is critical for developing effective therapeutic strategies to improve clinical outcomes. Methods Integrative analysis of transcriptomic profiles from chemoresistant bladder cancer models and clinical data sets from The Cancer Genome Atlas was performed to identify candidate resistance drivers. The biological function of the candidate gene was evaluated in vitro using bladder cancer cell lines. Mechanistic investigations, including transcriptomic analyses and immunoprecipitation, were conducted to elucidate downstream signaling. The therapeutic potential of targeting this axis was assessed in vitro and in an in vivo xenograft model using a small‐molecule inhibitor combined with chemotherapy. Results We identified β‐secretase 2 (BACE2) as a candidate mediator of cisplatin resistance. BACE2 is significantly upregulated in gemcitabine‐ and cisplatin‐resistant models, including patient‐derived organoids. Its elevated baseline expression correlates with advanced pathologic stage, poor prognosis, and diminished clinical benefit from platinum‐based therapy. Functionally, BACE2 promotes resistance to both gemcitabine and cisplatin. Mechanistically, BACE2 interacts with Jagged1 (JAG1) and promotes the generation of a soluble JAG1 fragment in a catalytic activity‐dependent manner. Mutation of the catalytic Asp303 residue markedly reduced JAG1 fragment generation and restored gemcitabine sensitivity, supporting a functional requirement for BACE2 enzymatic activity in this process. This fragment is associated with Notch signaling activation through autocrine and paracrine mechanisms, which concomitantly induces endogenous JAG1 expression, establishing a positive feedback loop that sustains chemoresistance. Pharmacologic inhibition of β‐secretase activity with verubecestat disrupted JAG1 cleavage, reduced downstream Notch signaling and enhanced chemotherapy efficacy in vitro without inducing apparent cytotoxicity alone. Furthermore, combination treatment with verubecestat and gemcitabine produced stronger tumor growth inhibition than either monotherapy in vivo. Conclusions These results define a novel BACE2‐JAG1‐Notch signaling axis that contributes to bladder cancer chemoresistance. Importantly, our findings identify BACE2 as a potential prognostic biomarker and a therapeutically actionable target to improve clinical outcomes in this disease.
Zekun Li, Sanxiang Li, Zhenyu Liu et al.· Cancer Innovation· 0 citations
Background Despite significantly improving outcomes in non-small cell lung cancer (NSCLC), neoadjuvant chemoimmunotherapy (NCIT) fails to achieve a major pathological response (MPR) in over 40% of patients. Consequently, the early identification of non-responders prior to treatment initiation remains a critical unmet clinical need. Methods In this study, we performed single-cell RNA sequencing (scRNA-seq) on pre-treatment NSCLC tissue samples and integrated data from two public databases to identify signaling pathways associated with poor treatment response. Key findings were subsequently validated using multiplex immunofluorescence (mIF), and the predictive value of identified molecules was finally assessed in our cohort and GEO datasets. Results Among the 83 patients, 23/57 (40.35%) of these radiological responders failed to achieve MPR. Data analysis revealed activation of stress-related signaling pathways in cancer-associated fibroblasts (CAFs) and T cells from nMPR patients, with elevated expression of stress-related markers, including BAG3 and IFITM2. MIF confirmed that BAG3+IFITM2+ CAFs and BAG3+CD8+ T cells were spatially adjacent and significantly more abundant in nMPR patients. In our cohort and the two public databases, the BAG3+ CAF-T Cell Neighborhood was significantly more abundant in the nMPR group compared to the MPR group (p<0.05). In the MPR group, there was no significant difference in BAG3+ CAF-T Cell Neighborhood between the radiological PR and non-PR subgroups. The AUC values of BAG3+IFITM2+ CAFs, BAG3+CD8+ T cells, and the BAG3+ CAF-T Cell Neighborhood were 0.84 [95%CI: 0.746-0.931], 0.72 [95%CI: 0.603-0.835], and 0.87 [95%CI: 0.787-0.948], respectively. The OS and DFS of the BAG3+ CAF-T Cell Neighborhood high group are significantly decreased than that of the low group (p<0.05). The level of BAG3+ CAF-T Cell Neighborhood outperformed other two indicators in predicting non-response to NCIT. Consistent results were observed in GSE126044 and GSE135222. Conclusion The BAG3+ CAF-T Cell Neighborhood may serve as a biomarker for predicting non-response to NCIT in NSCLC, with significant potential to inform clinical decision-making.
Jing Sun, Zhengqi Cao, Yueping Jin et al.· Frontiers in Immunology· 0 citations
Background Drug resistance and poor clinical outcomes in lung adenocarcinoma (LUAD) necessitate robust biomarkers for personalized therapy. Glycolysis reprogramming is a hallmark of cancer, but its clinical utility remains incompletely defined. Methods We integrated TCGA and GEO transcriptomic data with Weighted gene co−expression network analysis (WGCNA), least absolute shrinkage and selection operator (LASSO), and multivariate Cox regression to construct a glycolysis−related prognostic signature. A nomogram combining the risk score with clinicopathological factors was developed. Drug sensitivity was predicted using the pRRophetic algorithm. qRT−PCR and xenograft models using A549 and cisplatin−resistant A549/DDP cells validated the expression of candidate genes. Results Patients stratified by glycolysis-related risk scores exhibited significantly distinct survival outcomes, and the glycolysis-based signature functioned as an independent prognostic factor for overall survival in LUAD. The nomogram demonstrated robust predictive performance and effectively estimated patient sensitivity to three commonly used conventional chemotherapeutic agents. In vitro and in vivo studies using A549 cells and their cisplatin-resistant derivative A549/DDP revealed aberrant expression of VIPR1, ADRB2, RXFP1, PDGFB, WNT3A, and SPRY1 in the resistant cell line and in corresponding xenograft tumor tissues. These findings suggest that glycolytic activity is closely associated with both drug resistance and clinical prognosis in LUAD. Conclusions This study identifies a glycolysis-related gene signature with demonstrable utility for prognostic stratification and therapeutic response prediction in LUAD. The proposed integrative model holds promise for enhancing precision treatment decision-making through optimized risk assessment and rational selection of chemotherapeutic regimens.
Qian Zheng, Yunxiao Liu, Tianli Li et al.· Frontiers in Oncology· 0 citations
BACKGROUND
The mechanisms underlying immune microenvironment remodeling remain unclear for patients with unresectable hepatocellular carcinoma (uHCC) undergoing transarterial chemoembolization (TACE) combined with tyrosine kinase inhibitors (TKIs) and immune checkpoint inhibitors (ICIs). This study aims to identify the key features that change following the combination therapy in patients with uHCC.
METHODS
Single-cell transcriptomic profiling was conducted on uHCC samples from the control group, pre-treatment group, and post-treatment group. The Cancer Genome Atlas (TCGA) database was obtained for prognostic analysis. Enriched genes and pathways were identified, and the association and underlying mechanisms of the identified sub-cluster of cells were elucidated in relation to other cellular components.
RESULTS
A total of 82,687 cells were obtained from seven patients with uHCC. In the pre-treatment group, the CancerCells_1 was associated with epithelial-mesenchymal transition, indicating a poor prognosis, as evidenced by data from 370 HCC patients in TCGA database. In the post-treatment group, a high proportion of macrophages_FOLR2 was observed corresponding to an elevated interferon response signature score and a diminished pro-angiogenic signature score. The exhaustion of CD8+ effector T cell (CD8Teff) was mitigated by downregulating the notable expression of BHLHE40 and CXCL13. Following treatment, there was an increase in liver sinusoidal endothelial cell (LSEC), while both angiogenesis and TGF-β pathway scores were reduced. Notable changes were observed in the interactions across different cells, particularly concerning the key signatures of LGALS9_HAVCR2, CSF1_CSF1R, and VEGFB_FLT1.
CONCLUSION
After combined treatment, uHCC patients were characterized by macrophages_FOLR2, CD8Teff, and LSEC, indicating a remodeling of the immune microenvironment.
Haifeng Zhou, Bi-Fei Wu, W. Ding et al.· International Immunopharmaco...· 0 citations
Esophageal Cancer: Molecular Biology/Pathology
Resistance to perioperative FLOT chemotherapy remains a major determinant of poor outcome in esophageal adenocarcinoma. Epithelial–mesenchymal plasticity (EMP) enables dynamic cell state transitions that may promote adaptive chemoresistance, yet its functional contribution to chemoresistance in esophageal adenocarcinoma remains insufficiently characterized.
Esophageal adenocarcinoma cell models were engineered to stably express a dual-fluorescent reporter system driven by E-cadherin and vimentin promoters, allowing real-time visualization of epithelial, mesenchymal, and hybrid epithelial/mesenchymal (E/M) states. Fluorescence-Activated Cell Sorting was used to isolate phenotypically distinct subpopulations. Sensitivity to FLOT chemotherapy was assessed using cell viability and clonogenic survival. Dynamic state transitions were evaluated following chemotherapy exposure. RNA sequencing on sorted populations will enable the identification of transcriptional programs associated with chemoresistance and EMP.
Distinct epithelial–mesenchymal subpopulations were identified across several cellular models, with marked heterogeneity. One model, FLO1, exhibited all three phenotypic states, including a hybrid E/M population indicative of high plasticity. FLOT chemotherapy exposure induced significant phenotypic shifts toward hybrid states, accompanied by increased survival and persistence of this cell subset. These findings suggest a dynamic, reversible model of chemoresistance driven by EMP rather than fixed cell identity.
Epithelial–mesenchymal plasticity promotes adaptive resistance to FLOT chemotherapy in esophageal adenocarcinoma by enabling dynamic transitions toward therapy-tolerant states. Defining molecular programs underlying these transitions may support the development of treatment strategies that limit resistance and improve patient response to perioperative chemotherapy.
Laurie Clauzon, Kimiya Shams, Roberta Drago et al.· Diseases of the esophagus· 0 citations
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