Cancer Science最新文献

Bladder cancers are heterogeneous in nature, showing diverse molecular profiles and histopathological characteristics, which pose challenges for diagnosis and treatment. However, understanding the molecular basis of such heterogeneity has remained elusive. This study aimed to elucidate the molecular landscape of neuroendocrine-like bladder tumors, focusing on the involvement of β-catenin localization. Analyzing the transcriptome data and benefiting from the molecular classification tool, we undertook an in-depth analysis of muscle-invasive bladder cancers to uncover the molecular characteristics of the neuroendocrine-like differentiation. The study explored the contribution of transcription factors and chromatin remodeling complexes to neuroendocrine differentiation in bladder cancer. The study revealed a significant correlation between β-catenin localization and neuroendocrine differentiation in muscle-invasive bladder tumors, highlighting the molecular complexity of neuroendocrine-like tumors. Enrichment of YY1 transcription factor, E2F family members, and Polycomb repressive complex components in β-catenin-positive tumors suggest their potential contribution to neuroendocrine phenotypes. Our findings contribute valuable insights into the molecular complexity of neuroendocrine-like bladder tumors. By identifying potential therapeutic targets and refining diagnostic strategies, this study advances our understanding of endocrinology in the context of bladder cancer. Further investigations into the functional implications of these molecular relationships are warranted to enhance our knowledge and guide future therapeutic interventions.

Precise vaccination data is essential to accurately estimate the effectiveness of the human papillomavirus (HPV) vaccine against HPV-related cancers. In Japan, the number of subsidized HPV vaccinations can be tracked through registries, but the number of self-funded vaccinations has not been tracked. The number of individuals who chose to receive the vaccine at their own expense, despite being ineligible for public subsidies due to their age, is unknown and has been nominally considered to be zero. Our aim is to produce a more accurate estimate of this number using recently released proprietary data. First, we estimated the total number of self-funded HPV vaccinations occurring from 2010 to 2012 using public data from the Ministry of Health, Labour and Welfare and our previously reported data on the number of HPV vaccinations eligible for public subsidy. Second, using proprietary data from the vaccine manufacturer, we calculated the distribution of self-funded vaccination shots by age. Finally, we combined these data to estimate the number of self-funded HPV vaccinations by birth fiscal year (FY) relative to a yearly reference population. We found that 78,264 individuals born in FY1993 and 58,190 born in FY1992 self-funded their vaccinations, representing 13.6% and 10.0% of the reference population, respectively. Additionally, we found that 5%–10% of individuals born from FY1986 to FY1991 self-funded their vaccinations. Our study revealed for the first time that a certain number of individuals from the “HPV unvaccinated generation,” ineligible for subsidies due to age restrictions, chose to self-fund their vaccinations.

Uveal melanoma (UM) patients face a significant risk of distant metastasis, closely tied to a poor prognosis. Despite this, there is a dearth of research utilizing big data to predict UM distant metastasis. This study leveraged machine learning methods on the Surveillance, Epidemiology, and End Results (SEER) database to forecast the risk probability of distant metastasis. Therefore, the information on UM patients from the SEER database (2000–2020) was split into a 7:3 ratio training set and an internal test set based on distant metastasis presence. Univariate and multivariate logistic regression analyses assessed distant metastasis risk factors. Six machine learning methods constructed a predictive model post-feature variable selection. The model evaluation identified the multilayer perceptron (MLP) as optimal. Shapley additive explanations (SHAP) interpreted the chosen model. A web-based calculator personalized risk probabilities for UM patients. The results show that nine feature variables contributed to the machine learning model. The MLP model demonstrated superior predictive accuracy (Precision = 0.788; ROC AUC = 0.876; PR AUC = 0.788). Grade recode, age, primary site, time from diagnosis to treatment initiation, and total number of malignant tumors were identified as distant metastasis risk factors. Diagnostic method, laterality, rural–urban continuum code, and radiation recode emerged as protective factors. The developed web calculator utilizes the MLP model for personalized risk assessments. In conclusion, the MLP machine learning model emerges as the optimal tool for predicting distant metastasis in UM patients. This model facilitates personalized risk assessments, empowering early and tailored treatment strategies.

Reprogramming of cellular energy metabolism, including deregulated lipid metabolism, is a hallmark of head and neck squamous cell carcinoma (HNSCC). However, the underlying molecular mechanisms remain unclear. Long-chain acyl-CoA synthetase 4 (ACSL4), which catalyzes fatty acids to form fatty acyl-CoAs, is critical for synthesizing phospholipids or triglycerides. Despite the differing roles of ACSL4 in cancers, our data showed that ACSL4 was highly expressed in HNSCC tissues, positively correlating with poor survival rates in patients. Knockdown of ACSL4 in HNSCC cells led to reduced cell proliferation and invasiveness. RNA sequencing analyses identified interferon-induced protein 44 (IFI44) and interferon-induced protein 44-like (IFI44L), encoded by two interferon-stimulated genes, as potential effectors of ACSL4. Silencing IFI44 or IFI44L expression in HNSCC cells decreased cell proliferation and invasiveness. Manipulating ACSL4 expression or activity modulated the expression levels of JAK1, tyrosine kinase 2 (TYK2), signal transducer and activator of transcription 1 (STAT1), interferon α (IFNα), IFNβ, and interferon regulatory factor 1 (IRF1), which regulate IFI44 and IFI44L expression. Knockdown of IRF1 reduced the expression of JAK1, TYK2, IFNα, IFNβ, IFI44, or IFI44L and diminished cell proliferation and invasiveness. Our results suggest that ACSL4 upregulates interferon signaling, enhancing IFI44 and IFI44L expression and promoting HNSCC cell proliferation and invasiveness. Thus, ACSL4 could serve as a novel therapeutic target for HNSCC.

The incomplete prediction of prognosis in esophageal squamous cell carcinoma (ESCC) patients is attributed to various therapeutic interventions and complex prognostic factors. Consequently, there is a pressing demand for enhanced predictive biomarkers that can facilitate clinical management and treatment decisions. This study recruited 491 ESCC patients who underwent surgical treatment at Huashan Hospital, Fudan University. We incorporated 14 blood metabolic indicators and identified independent prognostic indicators for overall survival through univariate and multivariate analyses. Subsequently, a metabolism score formula was established based on the biochemical markers. We constructed a nomogram and machine learning models utilizing the metabolism score and clinically significant prognostic features, followed by an evaluation of their predictive accuracy and performance. We identified alkaline phosphatase, free fatty acids, homocysteine, lactate dehydrogenase, and triglycerides as independent prognostic indicators for ESCC. Subsequently, based on these five indicators, we established a metabolism score that serves as an independent prognostic factor in ESCC patients. By utilizing this metabolism score in conjunction with clinical features, a nomogram can precisely predict the prognosis of ESCC patients, achieving an area under the curve (AUC) of 0.89. The random forest (RF) model showed superior predictive ability (AUC = 0.90, accuracy = 86%, Matthews correlation coefficient = 0.55). Finally, we used an RF model with optimal performance to establish an online predictive tool. The metabolism score developed in this study serves as an independent prognostic indicator for ESCC patients.

Cancer brain metastasis has a poor prognosis, is commonly observed in clinical practice, and the number of cases is increasing as overall cancer survival improves. However, experiments in mouse models have shown that brain metastasis itself is an inefficient process. One reason for this inefficiency is the brain microenvironment, which differs significantly from that of other organs, making it difficult for cancer cells to adapt. The brain microenvironment consists of unique resident cell types such as neurons, oligodendrocytes, astrocytes, and microglia. Accumulating evidence over the past decades suggests that the interactions between cancer cells and glial cells can positively or negatively influence the development of brain metastasis. Nevertheless, elucidating the complex interactions between cancer cells and glial cells remains challenging, in part due to the limitations of existing experimental models for glial cell culture. In this review, we first provide an overview of glial cell culture methods and then examine recent discoveries regarding the interactions between brain metastatic cancer cells and the surrounding glial cells, with a special focus on astrocytes and microglia. Finally, we discuss future perspectives for understanding the multifaceted interactions between cancer cells and glial cells for the treatment of metastatic brain tumors.

The global phase 3 DESTINY-Breast03 study (ClinicalTrials.gov; NCT03529110) showed statistically significant and clinically meaningful improvements in progression-free survival (PFS) and overall survival (OS) with trastuzumab deruxtecan (T-DXd) over trastuzumab emtansine (T-DM1) in patients with human epidermal growth factor receptor 2 (HER2)-positive metastatic breast cancer (mBC) previously treated with trastuzumab and a taxane. Here, we report a subgroup analysis of Asian patients enrolled in DESTINY-Breast03. In total, 309 patients (149 in the T-DXd arm and 160 in the T-DM1 arm) from Asian countries and regions were randomized. At data cutoff (July 25, 2022), the median duration of follow-up in the Asian subpopulation was 29.0 months with T-DXd and 26.0 months with T-DM1. The PFS (determined by blinded independent central review) hazard ratio was 0.30 (95% confidence interval 0.22–0.41) favoring T-DXd over T-DM1 (median PFS 25.1 vs. 5.4 months). Median OS was not reached in the T-DXd arm and was 37.7 months in the T-DM1 arm. The median treatment duration was 15.4 months with T-DXd and 5.5 months with T-DM1. The incidence of grade ≥3 drug-related treatment-emergent adverse events was similar between both treatment arms (49.0% vs. 46.5%) and was consistent with the overall DESTINY-Breast03 population. Adjudicated drug-related interstitial lung disease or pneumonitis occurred in 12.9% of patients treated with T-DXd and 2.5% treated with T-DM1, with a higher incidence in Japanese patients; none of these were grade ≥4 events. These efficacy and safety data reinforce the favorable benefit–risk profile of T-DXd in HER2-positive mBC, including in the Asian subgroup.

The relationship among polycystic ovary syndrome (PCOS), endometrial cancer (EC), and glycometabolism remains unclear. We explored shared genes between PCOS and EC, using bioinformatics to unveil their pathogenic connection and influence on EC prognosis. Gene Expression Omnibus datasets GSE226146 (PCOS) and GSE196033 (EC) were used. A protein–protein interaction (PPI) network was constructed to identify the central genes. Candidate markers were screened using dataset GSE54250. Differences in marker expression were confirmed in mouse PCOS and human EC tissues using RT-PCR and immunohistochemistry. The effect of PGD on EC proliferation and migration was explored using Ki-67 and Transwell assays. PGD's impact on the glycometabolic pathway within carbon metabolism was assessed by quantifying glucose content and lactic acid production. R software identified 31 common genes in GSE226146 and GSE196033. Gene Ontology functional classification revealed enrichment in the “purine nucleoside triphosphate metabolism process,” with key Kyoto Encyclopedia of Genes and Genomes pathways related to “carbon metabolism.” The PPI network identified 15 hub genes. HK2, NDUFS8, PHGDH, PGD, and SMAD3 were confirmed as candidate markers. The RT-PCR analysis validated distinct HK2 and PGD expression patterns in mouse PCOS ovarian tissue and human EC tissue, as well as in normal and EC cells. Transfection experiments with Ishikawa cells further confirmed PGD's influence on cell proliferation and migration. Suppression of PGD expression impeded glycometabolism within the carbon metabolism of EC cells, suggesting PGD as a significant PCOS risk factor impacting EC proliferation and migration through modulation of single carbon metabolism. These findings highlight PGD's pivotal role in EC onset and prognosis.

The bromodomain is a conserved protein–protein interaction module that functions exclusively to recognize acetylated lysine residues on histones and other proteins. It is noteworthy that bromodomain-containing proteins are involved in transcriptional modulation by recruiting various transcription factors and/or protein complexes such as ATP-dependent chromatin remodelers and acetyltransferases. Bromodomain-containing protein 8 (BRD8), a molecule initially recognized as skeletal muscle abundant protein and thyroid hormone receptor coactivating protein of 120 kDa (TrCP120), was shown to be a subunit of the NuA4/TIP60-histone acetyltransferase complex. BRD8 has been reported to be upregulated in a subset of cancers and implicated in the regulation of cell proliferation as well as in the response to cytotoxic agents. However, little is still known about the underlying molecular mechanisms. In recent years, it has become increasingly clear that the bromodomain of BRD8 recognizes acetylated and/or nonacetylated histones H4 and H2AZ, and that BRD8 is associated with cancer development in both a NuA4/TIP60 complex-dependent and -independent manner. In this review, we will provide an overview of the current knowledge on the molecular function of BRD8, focusing on the biological role of the bromodomain of BRD8 in cancer cells.