Discover. Oncology最新文献

B-cell non-Hodgkin lymphoma (B-NHL) is a highly heterogeneous group of lymphopoietic malignancies that account for 85% to 90% of all non-Hodgkin lymphomas. In recent years, CD19 Chimeric antigen receptor T (CAR T) cell immunotherapy has significantly improved the cure rate of B-NHL patients, but there are still some patients who cannot achieve remission after treatment, or relapse after remission. Therefore, it is of great importance to overcome the drug resistance of CD19 CAR T cells after B-NHL treatment and reduce the recurrence rate of CD19 CAR T cells after B-NHL treatment. We found that low concentrations of chidamide did not enhance the ability of CD19 CAR T cells to kill B-NHL cells during and after preparation. B-NHL cells pretreated with chidamide were more likely to be killed by CD19 CAR T cells. CD19 CAR T cells secreted more cytokines (IL-2, TNF-α, and IFN-γ) after co-culture with B-NHL cells pretreated with chidamide. At the same time, the expression of CD19 on B-NHL cell surface was increased by chidamide. In vivo experiments showed that infusion of CD19 CAR T cells after chidamide bridging intervention can enhance the therapeutic effect of B-NHL and prolong the overall survival of mice. This study provides a new direction and theoretical foundation for CD19 CAR T cell therapy in B-NHL.

Early diagnosis and disease management based on risk stratification have a very positive impact on colon adenocarcinoma (COAD) prognosis. It is of positive significance to further explore risk stratification of COAD patients and identify predictive molecular biomarkers. PANoptosis is defined as a form of inflammatory cell death regulated by PANoptosome, with common features of pyroptosis, apoptosis and necroptosis. The role of PANoptosis in COAD has not been fully studied. In this study, we analyzed significant differences in the expression of PANoptosis-related gene (PRG) features in COAD. Subsequently, the PANoptosis associated lncRNAs (PALs) associated with PRGs were analyzed by LASSO algorithm and multivariate Cox analysis, and PALs related to the prognosis of COAD were selected. Based on the expression patterns of prognostic PAL features, we performed unsupervised consensus cluster analysis to categorize COAD samples into distinct PAL molecular subtypes and investigate their associated immune infiltration characteristics. We subsequently constructed PAL score model based on prognostic characteristics and verified its independent prognostic value for COAD. The nomogram diagnostic model was established to confirm the prognostic value of PAL scoring system again. Pathway enrichment analysis, somatic mutation profiling, and drug sensitivity analysis were employed to comprehensively assess the clinical value of the PAL score. Additionally, qRT-PCR was used to further validate the abnormal expression of the selected targets in COAD. Our results provide a new idea for clinical risk stratification and new evidence for the role of PANoptosis in COAD.

Background: Pancreatic ductal adenocarcinoma (PDAC) has a heterogeneous make-up of myeloid cells that influences the therapeutic response and prognosis. However, understanding the myeloid cell at both a genetic and cellular level remains a significant challenge.

Methods: Single-cell RNA sequencing (scRNA-seq) data were downloaded from t the Tumor Immune Single-cell Hub and gene expression data were retrieved from The Cancer Genome Atlas (TCGA) database and the Gene Expression Omnibus (GEO) database. Gene set variation analysis (GSVA) was used to estimate the relative proportions of each cell type based on the signatures identified by scRNA-seq or previous literature. Cell-type identification by estimating relative subsets of RNA transcripts (CIBERSORT) was performed to evaluate the abundance of immune infiltrating cells. For further analysis, LASSO and Cox analyses were used to construct a risk model using univariate Cox regression.

Results: Using the scRNA-seq dataset, we identified 7 clusters of myeloid cells, and these clusters were assigned a cell type based on their marker genes. In addition, the results of the CellChat analysis and SCENIC analysis indicate that TAM-spp1 cells may promote the migration of pancreatic tumor cells on different levels. Moreover, the TAM-spp1 cell is most closely related to poor prognoses. An 8-gene risk model was constructed by using univariate Cox and LASSO analyses. In the GEO cohorts, this risk model demonstrated excellent predictive abilities for prognosis. Further, patients with high-risk scores had a lower likelihood of benefiting from immunotherapy.

Conclusion: Using bulk RNA-seq and single-cell RNA-seq, we analyzed myeloid heterogeneity at the single-cell level, and we developed an 8-gene model that predicts survival outcomes and immunotherapy response in PADC.

Background: Esophageal squamous cell carcinoma (ESCC) has a poor prognosis, with chemoradiotherapy (CRT) being a key treatment method. This study focused on circulating cytokines as potential predictors of treatment response and prognosis in patients with ESCC.

Materials and methods: Serum samples were collected from 36 ESCC patients, and 12 different cytokines were quantified using a multiplex immunofluorescence assay. We used non-parametric Wilcoxon unpaired rank tests to examine the relationship between cytokine concentrations and clinical outcomes. The duration of progression-free survival was assessed through imaging studies and telephone follow-ups. Kaplan-Meier survival plots, analyzed with the log-rank test, were utilized to depict survival trends.

Results: Pre-treatment serum IL-8 levels were significantly elevated in patients with lymphoid metastases (p = 0.036). Lower initial levels of IL-8 and IL-1β were observed in patients with partial response group compared to those with stable disease (p = 0.002, p = 0.01). Elevated baseline levels of IL-8 and interferon-gamma (IFN-γ) were correlated with a poorer prognosis. Higher levels of IL-5 and IFN-γ levels following therapy were associated with worse outcomes.

Conclusions: Our findings indicate that IL-8, IL-1β, IL-5, and IFN-γ may serve as potential biomarkers for treatment efficacy and prognosis in ESCC. Patients with low levels of IL-8 and IL-1β demonstrate a favorable response to CRT. Elevated serum levels of IL-8, IL-1β, IFN-γ, and IL-5 may predict poorer clinical outcomes.

Background: The role of adjuvant chemotherapy in early-stage small cell lung cancer (SCLC) and large cell neuroendocrine carcinoma (LCNEC) remains unclear, particularly for small tumors. This study assesses the survival benefits of adjuvant chemotherapy after surgical resection with a novel focus on tumors less than 1 cm.

Materials and methods: Data from the National Cancer Database (NCDB) was extracted for patients with SCLC (n = 11,962) and LCNEC (n = 6821) who underwent surgical resection between 2004 and 2020. Exclusion criteria were limited survival (< 30 days), positive lymph nodes, distant metastases, large tumors (> 5 cm), residual microscopic disease, and neoadjuvant therapy. The primary outcome was overall survival (OS) from diagnosis, which was evaluated using Kaplan-Meier methods and multivariate Cox regression analyses. A propensity score matching (PSM) analysis was performed to compare outcomes in patients with SCLC and tumors ≤ 1 cm who received adjuvant chemotherapy versus surgery alone.

Results: The study involved 4114 SCLC and 3954 LCNEC patients. Adjuvant chemotherapy was associated with a significant increase median OS in both SCLC (6.26 vs. 4.18 years; p < 0.001) and LCNEC (7.02 years vs. 4.89 years; p < 0.001), while also being an independent predictor of better OS in SCLC (HR: 0.74) and LCNEC (HR: 0.75) (p < 0.001). The benefit was more noticeable in tumors ≤ 1 cm, showing a significant OS increase after PSM (median OS 7.34 vs. 5.02 years; p = 0.0048).

Conclusion: Adjuvant chemotherapy after surgery is associated with improved overall survival in stage I SCLC and LCNEC, particularly in SCLC tumors of 1 cm or less.

Liver cancer is one of the most challenging malignancies, often associated with poor prognosis and limited treatment options. Recent advancements in nanotechnology and artificial intelligence (AI) have opened new frontiers in the fight against this disease. Nanotechnology enables precise, targeted drug delivery, enhancing the efficacy of therapeutics while minimizing off-target effects. Simultaneously, AI contributes to improved diagnostic accuracy, predictive modeling, and the development of personalized treatment strategies. This review explores the convergence of nanotechnology and AI in liver cancer treatment, evaluating current progress, identifying existing research gaps, and discussing future directions. We highlight how AI-powered algorithms can optimize nanocarrier design, facilitate real-time monitoring of treatment efficacy, and enhance clinical decision-making. By integrating AI with nanotechnology, clinicians can achieve more accurate patient stratification and treatment personalization, ultimately improving patient outcomes. This convergence holds significant promise for transforming liver cancer therapy into a more precise, individualized, and efficient process. However, data privacy, regulatory hurdles, and the need for large-scale clinical validation remain. Addressing these issues will be essential to fully realizing the potential of these technologies in oncology.

Background: Gastric cancer (GC) remains a significant health burden, calling for the discovery of novel biomarkers. Golgi apparatus, a crucial cellular organelle involved in tumorigenesis, remains underexplored in GC research. A comprehensive understanding of its role and associated mechanisms is urgently needed.

Materials and methods: Utilizing the TCGA-STAD dataset as the training cohort and GSE84433 as the validation cohort, we explored potential associations between Golgi apparatus-related genes (GARG) and GC clinical risk. We aimed to decipher the prognostic significance and underlying biological mechanisms of these genes via consistent clustering, differential expression analysis, enrichment analyses, and immune infiltration profiling. To assess the relationship between risk stratification and survival outcomes, drug sensitivity, and immune infiltration, we developed the Golgi Apparatus-Related Risk Signature (GARRS). The reliability of GARRS was further corroborated using immunohistochemical staining.

Results: Consensus clustering based on 17 GARG identified two patient subgroups, C1 and C2, exhibiting differential survival, immune scores, and immune cell infiltration. We developed a GARRS using Cox-Lasso regression analysis, accurately stratifying patients into high- and low-risk groups. GARRS' validity was confirmed in the validation set and immunohistochemical staining. Our findings underline the Golgi apparatus' significance in the GC immune microenvironment and GARRS' utility in predicting GC survival outcomes.

Conclusion: This study underscores the association between Golgi apparatus subtypes and GC immunotumor microenvironment. GARRS, validated for its prognostic, immune infiltration, and drug sensitivity predictive abilities, offers new insights into gastric cancer treatment strategies.

Objective: In today's fast-paced society, stress has become a widespread phenomenon, garnering increasing attention for its impact on cancer. This study aims to investigate the current status and research hotspots of chronic stress in cancer research from 2014 to 2024, with the goal of providing valuable insights for future studies.

Methods: We retrieved 618 articles published between 2014 and 2024 from the Web of Science database and analyzed them using R software, VOSviewer, and CiteSpace.

Results: There is an overall upward trend in chronic stress-related cancer research, with China leading in publications, followed by the United States, India, Australia, and Italy. The journal most cited is Brain Behavior and Immunity. Key themes identified include 'inflammation', 'breast cancer', 'anxiety', 'psychological stress', and 'oxidative stress'. The primary focus of the research is the impact of chronic stress on various cancer types, the underlying molecular mechanisms, and the implications of chronic stress-related treatments on cancer outcomes.

Conclusion: Chronic stress is increasingly recognized as a Carcinogenic factors. This study provides a comprehensive analysis of chronic stress-related cancer research from 2014 to 2024, offering valuable guidance for future research in this field.

Aim: This study aimed to identify the genes associated with the development of lung adenocarcinoma (LUAD) and potential therapeutic targets.

Methods: Differentially expressed genes (DEGs) were identified by self-transcriptome sequencing of tumor tissues and paracancerous tissues resected during surgery and combined with The Cancer Genome Atlas (TCGA) data to screen for the genes associated with LUAD prognosis. The expression was validated at mRNA and protein levels, and the gene knockdown was used to examine the impact and underlying mechanisms on lung cancer cells.

Results: A total of 227 DEGs were identified by transcriptome sequencing, and the 20 DEGs with the most significant differences were used for co-analysis with TCGA data. The findings suggested that KRT16 and ANXA10 might have an important role in the development of LUAD after validating the mRNA and protein expression levels at the cellular level. The knockdown of KRT16 and ANXA10 inhibited the proliferation of lung cancer cells, and the cell cycle was blocked in the G1 phase. The expression of the G1/S-phase cell cycle checkpoint-related proteins cyclin D1 and cyclin E was inhibited by KRT16 and ANXA10 knockdown, respectively. The tumor formation ability decreased after KRT16 or ANXA10 knockdown in vivo.

Conclusions: KRT16 and ANXA10 are potential genes regulating the development of LUAD. Also, they may be potential targets for the targeted therapy of LUAD by inhibiting the proliferation of lung cancer cells and blocking the cell cycle by affecting key protein expression levels at cell cycle checkpoints.

Cancer remains the second leading cause of death globally, driving the need for innovative therapies. Among natural compounds, maytansinoids have shown significant promise, contributing to nearly 25% of recently approved anticancer drugs. Despite their potential, early clinical trials faced challenges due to severe side effects, prompting advancements in delivery systems such as antibody-maytansinoid conjugates (AMCs). This review highlights the anticancer activity of maytansinoids, with a focus on AMCs designed to target cancer cells specifically. Preclinical and clinical studies show that AMCs, including FDA-approved drugs like Kadcyla and Elahere, effectively inhibit tumor growth while reducing systemic toxicity. Key developments include improved synthesis methods, linker chemistry and payload design. Ongoing research aims to enhance the safety and efficacy of AMCs, integrate nanotechnology for drug delivery, and identify novel therapeutic targets. These advancements hold potential to transform maytansinoid-based cancer treatments in the future.