Discover. Oncology最新文献

Background: Clear cell renal cell carcinoma (ccRCC) remains a challenging cancer type due to its resistance to standard treatments. Immunogenic cell death (ICD) has the potential to activate anti-tumor immunity, presenting a promising avenue for ccRCC therapies.

Methods: We analyzed data from GSE29609, TCGA-KIRC, and GSE159115 to identify ICD-related prognostic genes in ccRCC. By applying consensus clustering, patients were categorized based on ICD modification patterns, and an ICD signature (ICDS) model was developed using a PCA approach. Functional studies were conducted with FOXP3 knockdown in ccRCC cell lines to explore its impact on cell behavior.

Results: Eleven ICD-related genes were identified as key prognostic indicators in ccRCC, with high ICDS linked to worse survival outcomes. High ICDS also correlated with increased levels of immune-suppressive cells within the tumor microenvironment. FOXP3 was highlighted as a critical gene influencing ICD, where its knockdown significantly reduced ccRCC cell proliferation and migration, underscoring its role in tumor progression.

Conclusions: This study establishes FOXP3 as a pivotal factor in ICD regulation and ccRCC progression. Targeting FOXP3 and other ICD pathways could enhance treatment efficacy in ccRCC, providing a foundation for ICD-based therapeutic strategies. Evaluating ICD patterns in ccRCC may guide patient-specific interventions, paving the way for improved management of this aggressive cancer.

Background: Lung adenocarcinoma (LUAD) is a leading form of non-small cell lung cancer characterized by a complex tumor microenvironment (TME) that influences disease progression and therapeutic response. Tumor-associated macrophages (TAMs) within the TME promote tumorigenesis and evasion of immune surveillance, though their heterogeneity poses challenges in understanding their roles and therapeutic targeting. Additionally, traditional Chinese medicine (TCM) offers potential anti-cancer agents that could modulate the immune landscape.

Methods: We conducted single-cell RNA sequencing (scRNA-seq) on LUAD samples, performing an in-depth analysis of macrophage populations and their expression signatures. Network pharmacology was used to identify TCM components with potential TAM-modulatory effects, focusing on Astragalus membranaceus. Pseudotime trajectory analysis, immunofluorescence staining, and in vitro assays examined the functional roles of TAMs and the effects of selected compounds on macrophage polarization.

Results: Our scRNA-seq analysis identified notable heterogeneity among macrophages, revealing predominant M2-like phenotypes within TAMs. Network pharmacology highlighted active TCM ingredients, including quercetin, isorhamnetin, and kaempferol, targeting genes related to macrophage function. Survival analysis implicated AHSA1, CYP1B1, SPP1, and STAT1 as prognostically significant factors. Further experiments demonstrated kaempferol's efficacy in inhibiting M2 polarization, underlining a selective influence on TAM functionality.

Conclusions: This study delineates the diverse macrophage landscape in LUAD and suggests a pivotal role for STAT1 in TAM-mediated immunosuppression. Kaempferol, identified from TCM, emerges as an influential agent capable of altering TAM polarization, potentially enhancing anti-tumoral immunity. These findings underscore the translational potential of integrating TCM-derived compounds into immunotherapeutic strategies for LUAD.

Aim: To construct a predictive model based on the LODDS stage established for patients with late-onset colon adenocarcinoma to enhance survival stratification.

Methods: Late-onset colon adenocarcinoma data were obtained from the public database. After determining the optimal LODDS truncation value for the training set via X-tile software, we created a new staging system by integrating the T stage and M stage. Nomograms of the prognostic model were created after Cox analyses identified independent risk factors for overall survival (OS) and cause-specific survival (CSS) and were validated internally and externally. The efficacy of the nomograms was assessed by calibration, time-dependent area under the curve (AUC) and decision curve analysis (DCA). Finally, the prognoses of the patients were compared by plotting survival curves on the basis of risk scores.

Results: A total of 103,291 and 100 patients with late-onset colon adenocarcinoma (50-80 years old) were screened from the Surveillance, Epidemiology, and End Results (SEER) and The Cancer Genome Atlas (TCGA) databases, respectively. Cox regression analysis revealed independent risk factors for OS and CSS, including age, gender, race, size, LODDS stage, PLN stage, LNR stage, and TNM stage. A comparison of the four models constructed on the basis of different stages revealed that the model constructed with the LODDS stage had the minimum AIC (Akaike information criterion), maximum C-index (concordance index) and time-dependent AUC. Nomograms based on the LODDS stage were constructed and successfully validated for accuracy and clinical utility.

Conclusion: For patients with late-onset colon adenocarcinoma, LODDS may achieve optimal predictive performance. Furthermore, compared to the 8th edition of the AJCC classification system, the nomogram based on LODDS stage may demonstrate superior survival prediction capabilities.

Background: Diseases are often caused by multiple factors, angiogenesis-related genes (ARGs) have been shown to be associated with cancer, however, their role in colon cancer had not been fully explored. This study investigated potential biomarkers based on ARGs to improve prognosis and treatment effect in colon cancer.

Methods: ARGs associated with colon cancer prognosis were identified using Cox regression analysis and LASSO analysis. Furthermore, a prognostic model was constructed in colon cancer based on the 3 ARGs, and its biological function were analyzed. We evaluated the differences in tumor immune microenvironment based on prognostic signature. Finally, cell experiments confirmed the function of genes in colon cancer.

Results: The prognostic value of ARGs in colon cancer patients has been comprehensively analyzed for the first time and identified 3 ARGs with prognostic values. A prognosis risk model was constructed based on 3 ARGs and its prognostic value was validated on an independent external colon cancer dataset. In colon cancer patients, this prognostic feature was an independent risk factor and was significantly correlated with clinical feature information of colon cancer patients. This feature was also related to the immune microenvironment of colon cancer. Cell experiments showed that high expression of TNF Receptor Superfamily Member 1B (TNFRSF1B) significantly promoted apoptosis and inhibited proliferation of colon cancer cells. Therefore, TNFRSF1B may become an important regulatory factor in the progression of colon cancer by participating in intracellular functional regulation.

Conclusions: This study constructed a prognostic risk model based on three ARGs and for the first time discovered that TNFRSF1B may become an important regulatory factor in cancer progression by participating in intracellular functional regulation.

Background: Lung adenocarcinoma is one of the most common malignant tumors worldwide. Its complex molecular mechanisms and high tumor heterogeneity pose significant challenges for clinical treatment. The manganese ion metabolism family plays a crucial role in various biological processes, and the abnormal expression of the NUDT3 gene in multiple cancers has drawn considerable attention. This study aims to systematically analyze the expression characteristics of the NUDT3 gene in lung adenocarcinoma and its association with tumor progression, integrating single-cell transcriptomic analysis and experimental validation using cell lines.

Methods: This study employed a comprehensive set of analytical approaches. Single-cell transcriptomic analysis of two normal and four lung adenocarcinoma samples from the GSE149655 dataset was performed using the Seurat package to identify and annotate distinct cell populations, focusing on epithelial and macrophage subtypes. Non-negative matrix factorization (NMF) and gene set variation analysis (GSVA) were applied to assess the functional enrichment and expression profiles of the manganese ion metabolism family across 14 cancers. Quantitative PCR (qPCR) was conducted to evaluate the relative mRNA expression of NUDT3 in A549 lung adenocarcinoma cell lines compared to BEAS-2B normal bronchial epithelial cell lines. GAPDH was used as the reference gene for normalization, and the relative expression levels of NUDT3 in these cell lines were analyzed to confirm bioinformatics findings.

Results: NUDT3 was found to be significantly upregulated in lung adenocarcinoma and highly correlated with tumor mutation burden (TMB) and mutation enrichment (MEs). Single-cell transcriptomic analyses demonstrated elevated NUDT3 expression in lung adenocarcinoma epithelial cells, with expression levels increasing in cells associated with advanced tumor stages. Furthermore, qPCR analysis confirmed the upregulation of NUDT3 in A549 cells compared to BEAS-2B cells, consistent with transcriptomic data. These results also highlighted significant expression differences of the manganese ion metabolism family across various cancers, including BLCA, BRCA, and COAD, with notable NUDT3 mutations enriched in these cancers.

Conclusion: This study underscores the critical role of NUDT3 in lung adenocarcinoma progression and its potential as a therapeutic target. These findings contribute to the understanding of the manganese ion metabolism family in cancer biology and provide a foundation for precision therapies targeting NUDT3 in lung adenocarcinoma.

Non-small cell lung cancer (NSCLC) remains a dire disease being the first cause of cancer death among both genders. Early-stage NSCLC often has better treatment outcomes despite it being a highly heterogeneous disease. So far, the neo-adjuvant chemotherapy strategies have led to a small benefit with an improvement of 5% in overall survival as an absolute benefit. Recently, the introduction of immune checkpoint inhibitors combined with chemotherapy has shown robust efficacy in terms of event-free survival and overall survival. Thus, these combinations are today considered a new standard of care in early-stage NSCLC. The application of these strategies to all-comer population lead to confounding definitive results regarding the efficacy and predictive biomarkers are urgently needed balancing the promise of healing than toxicities. At present, the clinical staging TNM system guides the clinical choice, however it is not entirely sufficient. Circulant tumoral DNA (ctDNA) emerged as a promising prognostic and predictive biomarker that may guide the future perioperative strategy and pave the way to personalized medicine also in this exciting field. This narrative review aims to put in the context the employment of ctDNA, give some perspective and suggestions weighing the pros and cons of this technique for our tomorrow clinical practice.

Background: Pancreatic cancer (PAC) has a complex tumor immune microenvironment, and currently, there is a lack of accurate personalized treatment. Establishing a novel consensus machine learning driven signature (CMLS) that offers a unique predictive model and possible treatment targets for this condition was the goal of this study.

Methods: This study integrated multiple omics data of PAC patients, applied ten clustering techniques and ten machine learning approaches to construct molecular subtypes for PAC, and created a new CMLS.

Results: Using multi-omics clustering, we discovered two cancer subtypes (CSs) associated with prognosis, among which CS1 exhibited poor prognostic outcomes. Subsequently, 13 central genes were identified through screening, constituting CMLS with a significant prognostic ability. The low CMLS group had a better prognosis and was more likely to possess a "hot" tumor phenotype. The prognosis for the high CMLS group was dismal. Still, the tumor mutation burden (TMB) and tumor neoantigen burden (TNB) levels in this group of patients were higher than in the low CMLS group, which were more favorable for immune therapy response.

Conclusion: This study emphasizes that CMLS provides a beneficial instrument for early prediction of patient prognosis and screening of probable patients appropriate for immunotherapy and has broad implications for clinical practice.

Background and aims: Alcoholic hepatitis (AH) and hepatocellular carcinoma (HCC) are common liver diseases. Chronic inflammation caused by AH can progress to alcoholic cirrhosis (AC) and eventually HCC.

Methods: This study sought to ascertain potential shared genes between AH and HCC through the utilization of multiple transcriptome databases. Employing an immune infiltration analysis, and calculating the correlation between shared genes and immune infiltration results, in conjunction with independent bulk transcriptome validation sets, led to the identification of core shared genes. Subsequently, single-cell transcriptome data, clinical sample immunohistochemistry experiments, and overexpressed core shared genes in HepG2 cells were employed to validate the core shared genes of AH and HCC.

Results: Through the bulk transcriptome discovery sets of AH and HCC, 206 potential shared genes were identified. After screening with two machine learning algorithms, five shared genes remained. Combining the results of the immune infiltration and bulk transcriptome results from an independent validation cohort, the core shared gene was determined to be RASGRF2. Single-cell data further demonstrated that RASGRF2 and its downstream genes were highly expressed in AH, AC, and HCC tissues. Spatial transcriptome data indicated that RASGRF2 was highly expressed in HCC tumor tissues. Compared with the paracancerous tissues, the RASGRF2 gene was significantly overexpressed in HCC tissues. Overexpression of RASGRF2 in HepG2 cells resulted in significantly enhanced migration, invasion, and proliferation abilities.

Conclusion: RASGRF2 serve as a pathogenic gene that mediates the progression of AH to AC and potentially to HCC.

Purpose: This retrospective single-center study aimed to determine the correlation between The Paris System (TPS) urine cytology classification, cystoscopy findings, and non-muscle-invasive bladder cancer diagnosis. In addition, we sought to identify factors that might explain the abnormal cytology classification in cases in which no malignancy was detected.

Methods: A Total of 855 patients evaluated with urine cytology between 2017 and 2020 at Kuopio University Hospital were included. Histological diagnoses and urinalysis results were correlated with cytology (TPS). Chi-squared and Fisher's exact tests were used to calculate statistical significance.

Results: In the absence of exophytic tumors on cystoscopy, the risks of bladder cancer was 0.1% for NHGUC, 1.5% for AUC, 22.7% for SHGUC, and 83.3% for HGUC. Positive urinalysis corresponded to lower cytological diagnostic categories in both males and females. A statistically significant difference was observed in males with respect to moderate pyuria, hematuria, and higher cytological categories.

Conclusions: This study provides evidence that a biopsy or follow-up may not be necessary for patients without a prior history of urothelial carcinoma and without exophytic tumors observed on cystoscopy, when the cytological diagnosis is NHGUC or AUC. Furthermore, concurrent hematuria and pyuria may result in a higher cytological classification.