Despite major therapeutic advances, multiple myeloma (MM) remains largely incurable. Moreover, side effects and toxicities of treatments compromise patients' quality of life. Dendritic cell (DC)-based cancer vaccines can induce long-term tumor-specific immune responses and are generally well tolerated. To improve the potency of this immunotherapeutic approach, researchers are now exploring combination strategies that integrate approved agents with DC-based vaccines. Proteasome inhibitors (PIs), including bortezomib and carfilzomib, are the standard of care for MM. PIs have been shown to induce so-called immunogenic cell death and could therefore be promising agents for combination approaches. However, careful selection of the optimal drug is mandatory, as off-target effects may also hamper the immune system, as previously shown for bortezomib.

By flow cytometry, we systematically evaluated the effects of the PI carfilzomib on the phenotype and expression of immune checkpoint molecules in monocyte-derived human DCs (moDCs) compared to bortezomib. Functional analyses included endocytosis, migration, cytokine secretion, and T cell stimulatory capacity in mixed lymphocyte reactions (MLRs), with and without PD-1 blockade. We assessed DC frequencies in peripheral blood and bone marrow of MM patients at diagnosis, during carfilzomib-based therapy, and in remission and further generated DCs using monocytes of carfilzomib-treated patients.

Carfilzomib exposure did not compromise moDC characteristics, including phenotype, endocytosis, migration, and cytokine secretion, in vitro, whereas bortezomib-exposed moDCs differed significantly in several parameters. Carfilzomib modestly increased PD-L1 expression on moDCs and significantly reduced both their allostimulatory capacity and the IFN-γ production of cocultured T cells. PD-1 blockade with nivolumab fully reversed this effect and significantly enhanced it in MLR. We assessed reduced numbers of circulating DCs in MM patients at diagnosis, but numbers were comparable to those in healthy donors, patients receiving carfilzomib-based therapy and patients in remission. Furthermore, we could generate moDCs with a typical surface phenotype from monocytes of patients receiving carfilzomib-based therapy.

Our findings show that carfilzomib does not cause the broad impairment seen with bortezomib, and that the discrete deficit it does produce is reversible with PD-1 blockade. We hypothesize that carfilzomib is a more suitable proteasome inhibitor partner for DC-based immunotherapeutic strategies.

Background: Immune checkpoint inhibitors targeting programmed cell death protein 1 (PD-1) have substantially improved the treatment of multiple cancers; however, only a small proportion of gastric cancer (GC) patients achieve durable clinical benefit. The underlying tumor-intrinsic mechanisms driving resistance to anti-PD-1 therapy remain poorly understood. This study aimed to identify key regulators of immunotherapy resistance in GC and to elucidate their functional and mechanistic roles. Methods: Transcriptomic data from anti-PD-1-responsive and anti-PD-1-resistant GC patients were analyzed and integrated with mouse model data and publicly available single-cell RNA sequencing datasets. Functional experiments, including in vitro assays and in vivo tumor models, were performed to validate candidate genes and explore their roles in tumor progression and immunotherapy resistance. Results: GULP PTB domain-containing engulfment adaptor 1 (GULP1) was identified as a key driver of resistance to anti-PD-1 therapy in GC. Elevated GULP1 expression was associated with poor prognosis and unfavorable clinical responses to PD-1 blockade. GULP1 promoted GC progression and attenuated the therapeutic efficacy of anti-PD-1 treatment. Functionally, GULP1 facilitated the accumulation and metabolic reprogramming of CD36⁺ programmed death-ligand 1 (PD-L1)⁺ tumor-associated macrophages (TAMs) by shaping a lipid-enriched tumor microenvironment, thereby impairing CD8⁺ T-cell function. Mechanistically, GULP1 promoted insulin-induced gene 2 (INSIG2) palmitoylation through the recruitment of zinc finger DHHC-type palmitoyltransferase 8 (zDHHC8), resulting in sterol regulatory element-binding protein 1 (SREBP1) nuclear translocation and enhanced de novo fatty acid biosynthesis. Importantly, pharmacological inhibition of Gulp1 with glycyrrhizic acid significantly restored sensitivity to anti-PD-1 therapy in vivo. Conclusions: Collectively, these findings uncovered a previously unrecognized GULP1-fatty acid-CD36⁺PD-L1⁺ TAM-CD8⁺ T-cell axis that drove resistance to PD-1 blockade in GC, highlighting GULP1 as a promising therapeutic target and predictive biomarker for immunotherapy responsiveness.

Over the past 5 decades, small cell lung cancer (SCLC) has persisted as one of the most formidable malignancies, largely attributed to its aggressive early metastasis, limited therapeutic arsenal in both first-line and subsequent treatments, and rapid onset of treatment resistance. The dawn of a new era in the treatment of SCLC appeared in 2018, with the introduction of first-line chemotherapy combined with immune checkpoint inhibitors, as well as tarlatamab for later-line treatment. However, the improvements in survival, although tangible, were still unsatisfactory. Therefore, this review focuses on unraveling the mechanisms underlying cancer initiation, progression, and particularly metastasis, as well as emerging advances in molecular subtyping and drug resistance from the epigenetic perspective. Simultaneously, we outline their hallmark characteristics-high plasticity, heterogeneity, redundancy, and ambiguity driven by intercellular crosstalk under spatiotemporal dependency. Furthermore, we highlight the evolving progress of various successful drugs or therapeutic strategies and molecular biomarkers in clinical practice for SCLC, as well as promising agents under investigation. Finally, we also discuss how to leverage artificial intelligence and innovative biomedical technologies, as well as learn from various challenges in order to improve the therapeutic landscape of SCLC.

Tumor mutational burden (TMB) is widely utilized as a predictive biomarker for response to immune checkpoint inhibitors (ICIs). However, a subset of hypermutated tumors exhibits primary resistance to immunotherapy, indicating that additional tumor-intrinsic mechanisms may override immunogenicity. Aberrant Hedgehog (Hh) signaling, frequently driven by PTCH1 inactivation in basal cell carcinoma (BCC), has been implicated in immune exclusion and suppression of antitumor immunity.

We report a case of a 64-year-old male initially diagnosed with cutaneous squamous cell carcinoma (SCC). Comprehensive genomic profiling (CGP) of archival tumor tissue revealed an ultra-high TMB (95 muts/Mb) accompanied by a distinct ultraviolet (UV) mutational signature, with negative PD-L1 status. Based on the elevated TMB, dual immune checkpoint blockade was initiated; however, the patient did not achieve objective tumor regression. Reassessment of the genomic data, specifically the presence of a pathogenic truncating PTCH1 (Y977fs*16) alteration alongside the UV signature, raised a strong suspicion of basal cell carcinoma with squamous differentiation, prompting a diagnostic revision. Given the established role of PTCH1 loss in constitutive Hedgehog (Hh) pathway activation and immune exclusion, we considered aberrant Hedgehog signaling to be a biologically plausible contributor to the limited objective response observed during initial immune checkpoint blockade. Consequently, a rational combinatorial strategy utilizing vismodegib (an Hh pathway inhibitor) and pembrolizumab was initiated.

Following the introduction of the targeted-immunotherapy combination, the patient achieved a durable and ongoing clinical response. Serial liquid biopsy analysis showed that the same PTCH1 alteration remained detectable during longitudinal assessment, supporting the biological relevance of Hedgehog pathway dysregulation in this case.

This case highlights the limitations of relying solely on conventional biomarkers, such as TMB, even in the context of extreme hypermutation and UV-induced mutagenesis. CGP may be essential not only for therapeutic guidance but also diagnostic refinement. Our findings support the hypothesis that Hedgehog pathway inhibition may contribute to overcoming apparent resistance to immune checkpoint blockade in selected PTCH1-altered BCCs, supporting a biology-guided combinatorial approach in biomarker-discordant tumors with high TMB.

Liver depression syndrome (LDS) is a core Chinese medicine (CM) syndrome implicated in the onset and progression of breast cancer, whose molecular mechanisms remain poorly understood, hindering further investigation.

We prospectively enrolled 146 participants and conducted transcriptomic, proteomic, and metabolomic analyses using peripheral blood samples. A graph-attention-based multi-omics model embedded with a Transformer-derived multi-head self-attention module served as an exploratory tool to integrate multi-omics datasets. The identified candidate molecules were subsequently validated via enzyme-linked immunosorbent assay (ELISA).

In internal five-fold cross-validation, the Multi-Omics Graph Attention Network (MOGAT) achieved 96.6% accuracy in distinguishing LDS in breast cancer patients for biomarker-screening purposes, with proteomic features contributing predominantly to the classification. Moreover, both conventional multi-omics analyses and MOGAT analyses identified stimulator of interferon genes (STING), single immunoglobulin IL-1 receptor-related molecule (SIGIRR), tripartite motif-containing protein 56 (TRIM56), and anexelekto (AXL) as pivotal hub proteins, and subsequent ELISA validation confirmed differential expression of TRIM56 and AXL across pairwise comparisons. Multi-omics analysis identified noradrenaline as a candidate metabolite associated with BC-LDS related molecular alterations. The pathways underlying LDS in breast cancer were predominantly implicated in cytokine-cytokine receptor interactions, neuroactive ligand-receptor interaction, immune response regulation, and steroid hormone biosynthesis. These findings suggest candidate molecular features and a potential "neuro-immune-tumor-related" pathways associated with LDS in breast cancer.

This study examined the integration of multi-omics data with MOGAT to investigate the biological underpinnings of CM syndrome. These findings provide a preliminary paradigm that combines CM syndrome omics data with deep learning approaches, offering a hypothesis-generating framework for deciphering the scientific mechanisms of CM syndrome.

http://itmctr.ccebtcm.org.cn/, identifier ITMCTR2025000446.

Immune and malignant epithelial cells shape each other through ligand-receptor signaling in ovarian cancer. SPP1 interacts with CD44 and several integrins, but its cellular organization and clinical relevance remain unclear.

We integrated GSE184880 scRNA-seq data with TCGA-OV and three independent cohorts. Single-cell clustering, CNV inference, and cell communication analysis were used to characterize macrophage states and SPP1-related signaling. Based on the SPP1 ligand-receptor network identified by CellChat, an 11-gene set comprising SPP1 and its CD44/integrin receptor components was constructed and subsequently used for molecular subtyping. Four machine learning models were compared for prognostic prediction. PI3 was subsequently silenced in ES-2 and SKOV3 cells. SPP1 expression and secretion, cell proliferation, wound closure, migration, invasion, xenograft growth, and macrophage phenotypes after coculture were then evaluated.

Four macrophage states were identified: Resident Macro, Inflammatory Macro, SPP1+ TAM, and Activated Macro. Cell communication was extensively reorganized in ovarian tumors. SPP1+ TAM occupied a central position in the SPP1 network and communicated with malignant epithelial cells, fibroblasts, endothelial cells, and other macrophage populations through SPP1-CD44 and SPP1-integrin interactions. SPP1-related genes separated patients into SPP1-High and SPP1-Low subtypes. The SPP1-High subtype showed stronger immune- and cytokine-related activity and poorer overall survival. Among the four machine learning models, GBM-Cox achieved the highest C-index of 0.768 and maintained prognostic stratification across three independent cohorts. PI3 also ranked highly in several models. Silencing PI3 in tumor cells increased TNF, IL1B, CXCL10, and CD86 expression in cocultured macrophages, while reducing CD163, MRC1, CCL18, and IL10. Consistently, TNF-α and IL-12p70 levels increased, whereas IL-10 and CCL18 levels decreased. PI3 silencing reduced SPP1 mRNA expression and secretion and suppressed ovarian cancer cell proliferation, wound closure, migration, and invasion. Stable PI3 knockdown also delayed ES-2 xenograft growth and reduced terminal tumor volume and weight.

The SPP1-associated ligand-receptor network represents an immune-parenchymal communication axis linking macrophages with malignant epithelial and stromal cells in ovarian cancer. This network captures differences in immune state and clinical outcome and supports both molecular classification and prognostic assessment. PI3 may contribute to tumor cell-mediated regulation of macrophage phenotype and could serve as a candidate biomarker or intervention target. PI3 may promote ovarian cancer progression while contributing to tumor-cell-derived SPP1 production and macrophage regulation, supporting its potential value as a candidate biomarker and therapeutic target.

Patients undergoing esophagectomy frequently experience diverse and complex symptoms. This study aimed to identify clusters of early postoperative symptoms and determine core symptoms among these patients, to facilitate targeted symptom management strategies.

This prospective cohort study included 361 patients who underwent esophageal cancer surgery at a tertiary Grade A hospital in Harbin between 2023 and 2024. The European Organisation for Research and Treatment of Cancer Quality of Life Questionnaire Core 30 (QLQ-C30) and the Esophageal Cancer-Specific Module (QLQ-OES18) were used to assess 18 symptoms one month postoperatively. Exploratory factor analysis and network analysis were conducted to identify symptom clusters and core symptoms, respectively. A 1-month landmark survival analysis was performed to examine their associations with 1-year postoperative survival, using a parsimonious multivariable Cox regression model.

Five distinct symptom clusters were identified: eating-related (eating difficulty, reflux, choking, appetite loss, nausea, vomiting, dysphagia; prevalence 49.0%), breathing-related (cough, dyspnea, insomnia; prevalence 47.0%), pain-related (esophageal pain, generalized pain; prevalence 48.0%), fatigue-speech related (fatigue, dry mouth, trouble talking; prevalence 51.0%), and excretion-related (constipation, diarrhea; prevalence 50.0%). Network analysis identified fatigue (relative strength [rS] = 2.83), pain (rS = 1.69), and insomnia (rS = 1.58) as core symptoms, with fatigue serving as the key bridge symptom. In the 1-month landmark analysis, no statistically significant association was detected between symptom clusters or core symptoms and 1-year postoperative survival.

This study identified distinct symptom clusters and core symptoms one month post-esophagectomy that merit clinical attention during postoperative follow-up. Specifically, fatigue represents a key therapeutic target for developing intervention strategies.

To evaluate the cost-effectiveness of aumolertinib versus osimertinib as first-line treatment for advanced epidermal growth factor receptor (EGFR)-mutated non-small cell lung cancer (NSCLC) from the perspective of the Chinese healthcare system, and to explore economic outcomes across clinically relevant subgroups.

A partitioned survival model with three health states was developed over a 10-year horizon with a 28-day cycle length. Clinical inputs were derived from indirect evidence based on the AENEAS and FLAURA trials. In the base-case analysis, the progression-free survival (PFS) effect was informed by a published simulated treatment comparison, whereas the overall survival (OS) hazard ratio for aumolertinib versus osimertinib was conservatively set at 1.00. Costs and health outcomes were discounted at 5% annually. Outcomes included total costs, quality-adjusted life-years (QALYs), and incremental net monetary benefit (iNMB) at a willingness-to-pay threshold of 298,995 Chinese Yuan (CNY) per QALY. One-way sensitivity, probabilistic sensitivity, scenario, threshold, and exploratory subgroup analyses were performed.

In the overall population, osimertinib was associated with a total cost of 193,447.40 CNY and 1.981 QALYs, whereas aumolertinib was associated with a total cost of 207,484.66 CNY and 2.000 QALYs. Compared with osimertinib, aumolertinib yielded an additional 0.019 QALYs at an additional cost of 14,037.26 CNY, resulting in an iNMB of -8,307.60 CNY. Thus, aumolertinib was not economically favorable in the base-case analysis. At the prespecified threshold, the probability of being cost-effective was 0.58 for osimertinib and 0.42 for aumolertinib. Scenario and threshold analyses showed that the results were sensitive to drug price and the comparative OS effect. Exploratory subgroup analyses showed differences in the direction of point estimates across subgroups, but uncertainty remained substantial across all subgroups.

Under the current Chinese pricing environment and available indirect comparative evidence, aumolertinib and osimertinib showed broadly similar economic profiles as first-line treatment for advanced EGFR-mutated NSCLC.

Large hepatocellular carcinoma (HCC) adjacent to gastrointestinal (GI) organs presents a constrained radiotherapy problem because dose escalation is limited by both hepatic reserve and serial-organ tolerance. Although intensity-modulated proton therapy (IMPT) can reduce uninvolved liver irradiation, its achievable advantage over volumetric modulated arc therapy (VMAT) may depend on baseline liver function and robustness to treatment uncertainties.

To present and demonstrate a robust isotoxic dose-escalation framework for evaluating IMPT and VMAT in large HCC adjacent to GI organs while accounting for baseline liver function and treatment uncertainty.

Thirteen patients with HCC (equivalent tumor diameter, 3.0-20.9 cm) underwent comparative IMPT and VMAT treatment planning. Robust optimization incorporated 5-mm setup uncertainty for both modalities and 3% range uncertainty for IMPT. Dose escalation was performed using a fixed dose per fraction of 3.87 Gy while varying the maximum acceptable number of fractions, N_max, under non-cirrhotic, Child-Pugh A (CP-A), and Child-Pugh B (CP-B) liver-function assumptions. Liver mean dose constraints were evaluated on nominal dose, while serial-organ constraints were assessed using both nominal dose and voxel-wise maximum dose across uncertainty scenarios. Unirradiated liver volume normalized to standard liver volume (ULV/SLV) was used to estimate the relative hazard of radiation-induced liver disease (RILD).

In the nominal-dose analysis, IMPT achieved a higher N_max than VMAT in 5 of 13, 8 of 13, and 8 of 13 patients under non-cirrhotic, CP-A, and CP-B assumptions, respectively, with mean ΔN_max values of 0.38, 1.23, and 1.69 fractions. Similar trends were observed in the voxel-wise maximum-dose analysis, where mean ΔN_max values were 0.00, 1.08, and 1.77 fractions, respectively. VMAT dose escalation was predominantly limited by mean liver dose, whereas IMPT was more frequently constrained by GI maximum-dose limits, indicating a shift from liver reserve to serial-organ tolerance as the primary limiting factor. Among patients with an IMPT dose-escalation advantage, IMPT maintained higher ULV/SLV and correspondingly lower estimated RILD hazard despite treatment escalation.

IMPT provides greater isotoxic dose-escalation potential than VMAT for selected patients with large HCC, particularly when impaired baseline liver function causes photon therapy to be limited by mean liver dose. The proton advantage is ultimately constrained by robust GI organ-at-risk tolerances, emphasizing the importance of integrating baseline liver function, liver reserve, and uncertainty-aware serial-organ evaluation into modality selection and treatment planning.

Glioblastoma (GBM) is the most aggressive primary malignant tumor of the central nervous system and is characterized by rapid progression, frequent recurrence, and poor survival outcomes. The current standard of care, comprising maximal safe surgical resection followed by radiotherapy with concomitant and adjuvant temozolomide (TMZ), has improved clinical management; however, the therapeutic benefit remains limited by both intrinsic and acquired resistance to TMZ. O6-methylguanine-DNA methyltransferase (MGMT), a DNA repair protein that removes TMZ-induced O6-methylguanine adducts, is a major determinant of TMZ responsiveness. In particular, methylation of the MGMT promoter is associated with reduced MGMT expression and improved sensitivity to TMZ, although this molecular marker alone does not fully explain interpatient variability in treatment response, which is further modulated by the immunosuppressive tumor microenvironment. Increasing evidence indicates that non-coding RNAs (ncRNAs), including microRNAs (miRNAs), long non-coding RNAs (lncRNAs), and circular RNAs (circRNAs), participate in the regulatory network controlling MGMT expression. These ncRNAs may regulate MGMT directly at the posttranscriptional level or indirectly through competing endogenous RNA networks, epigenetic mechanisms, and signaling pathways associated with DNA repair and chemoresistance. Consequently, dysregulated ncRNA expression may contribute to TMZ resistance and GBM progression. Moreover, ncRNAs have potential clinical value as biomarkers for molecular stratification and prognostic assessment, as well as therapeutic targets for restoring TMZ sensitivity. This narrative review summarizes current evidence regarding ncRNA-mediated regulation of MGMT in GBM and discusses the potential implications of targeting these regulatory mechanisms to overcome TMZ resistance.