The transcription factor PAX5 activates human LINE1 retrotransposons to induce cellular senescence.

As a hallmark of senescent cells, the derepression of Long Interspersed Elements 1 (LINE1) transcription results in accumulated LINE1 cDNA, which triggers the secretion of the senescence-associated secretory phenotype (SASP) and paracrine senescence in a cGAS-STING pathway-dependent manner. However, transcription factors that govern senescence-associated LINE1 reactivation remain ill-defined. Here, we predict several transcription factors that bind to human LINE1 elements to regulate their transcription by analyzing the conserved binding motifs in the 5'-untranslated regions (UTR) of the commonly upregulated LINE1 elements in different types of senescent cells. Further analysis reveals that PAX5 directly binds to LINE1 5'-UTR and the binding is enhanced in senescent cells. The enrichment of PAX5 at the 5'-UTR promotes cellular senescence and SASP by activating LINE1. We also demonstrate that the longevity gene SIRT6 suppresses PAX5 transcription by directly binding to the PAX5 promoter, and overexpressing PAX5 abrogates the suppressive effect of SIRT6 on stress-dependent cellular senescence. Our work suggests that PAX5 could serve as a potential target for drug development aiming to suppress LINE1 activation and treat senescence-associated diseases.

Ferroptosis is a protective factor for the prognosis of cancer patients: a systematic review and meta-analysis.

BACKGROUND: Cancer is a leading global cause of death. Conventional cancer treatments like surgery, radiation, and chemotherapy have associated side effects. Ferroptosis, a nonapoptotic and iron-dependent cell death, has been identified and differs from other cell death types. Research has shown that ferroptosis can promote and inhibit tumor growth, which may have prognostic value. Given the unclear role of ferroptosis in cancer biology, this meta-analysis aims to investigate its impact on cancer prognosis. METHODS: This systematic review and meta-analysis conducted searches on PubMed, Embase, and the Cochrane Library databases. Eight retrospective studies were included to compare the impact of ferroptosis inhibition and promotion on cancer patient prognosis. The primary endpoints were overall survival (OS) and progression-free survival (PFS). Studies lacking clear descriptions of hazard ratios (HR) and 95% confidence intervals for OS and PFS were excluded. Random-effects meta-analysis and meta-regression were performed on the included study data to assess prognosis differences between the experimental and control groups. Meta-analysis results included HR and 95% confidence intervals. This study has been registered with PROSPERO, CRD 42023463720 on September 27, 2023. RESULTS: A total of 2,446 articles were screened, resulting in the inclusion of 5 articles with 938 eligible subjects. Eight studies were included in the meta-analysis after bias exclusion. The meta-analysis, after bias exclusion, demonstrated that promoting ferroptosis could increase cancer patients' overall survival (HR 0.31, 95% CI 0.21-0.44) and progression-free survival (HR 0.26, 95% CI 0.16-0.44) compared to ferroptosis inhibition. The results showed moderate heterogeneity, suggesting that biological activities promoting cancer cell ferroptosis are beneficial for cancer patient's prognosis. CONCLUSIONS: This systematic review and meta-analysis demonstrated that the promotion of ferroptosis yields substantial benefits for cancer prognosis. These findings underscore the untapped potential of ferroptosis as an innovative anti-tumor therapeutic strategy, capable of addressing challenges related to drug resistance, limited therapeutic efficacy, and unfavorable prognosis in cancer treatment. REGISTRATION: CRD42023463720.

Artificial Intelligence Applications in the Treatment of Colorectal Cancer: A Narrative Review.

Colorectal cancer is the third most prevalent cancer worldwide, and its treatment has been a demanding clinical problem. Beyond traditional surgical therapy and chemotherapy, newly revealed molecular mechanisms diversify therapeutic approaches for colorectal cancer. However, the selection of personalized treatment among multiple treatment options has become another challenge in the era of precision medicine. Artificial intelligence has recently been increasingly investigated in the treatment of colorectal cancer. This narrative review mainly discusses the applications of artificial intelligence in the treatment of colorectal cancer patients. A comprehensive literature search was conducted in MEDLINE, EMBASE, and Web of Science to identify relevant papers, resulting in 49 articles being included. The results showed that, based on different categories of data, artificial intelligence can predict treatment outcomes and essential guidance information of traditional and novel therapies, thus enabling individualized treatment strategy selection for colorectal cancer patients. Some frequently implemented machine learning algorithms and deep learning frameworks have also been employed for long-term prognosis prediction in patients with colorectal cancer. Overall, artificial intelligence shows encouraging results in treatment strategy selection and prognosis evaluation for colorectal cancer patients.

Diagnostic Performance of Node Reporting and Data System Magnetic Resonance Imaging Score in Detecting Metastatic Cervical Lymph Nodes of Nasopharyngeal Carcinoma.

Background: The Node Reporting and Data System (Node-RADS) is a recently proposed classification system for the categorization of lymph nodes in radiological images. This study was conducted to retrospectively evaluate the diagnostic accuracy of the Node-RADS score for metastatic cervical lymph nodes on magnetic resonance imaging (MRI) of patients with nasopharyngeal carcinoma (NPC). Methods: We retrospectively analyzed cervical lymph nodes of NPC cases. Two radiologists independently evaluated each lymph node on the MRI scans using Node-RADS. Interobserver agreement between 2 radiologists for Node-RADS score assessment was evaluated by linear weighted kappa statistics. The correlation between metastasis and the Node-RADS score of each lymph node was analyzed using multivariate regression analysis. To investigate the diagnostic performance of the Node-RADS score, we further conducted receiver operating characteristic curve analysis. Correspondently, the sensitivity, specificity, positive predictive value, and negative predictive value of each different cutoff (>1, >2, >3, and >4) were computed. Results: In all, 119 patients with NPC were assessed, including 203 cervical lymph nodes consisting of 140 (69%) of 203 metastatic and 63 (31%) of 203 benign. The kappa agreement between the 2 readers for the Node-RADS score was 0.863 (95% CI = 0.830-0.897, P < .001). Node-RADS score on MRI scan was shown to be an independent predictive factor of lymph node metastasis after multivariate regression analysis (odds ratio [OR] = 6.745, 95% CI = 3.964-11.474, P < .001). Node-RADS achieved an area under the curve (AUC) of 0.950 (95% CI = 0.921-0.979) in diagnosing metastatic lymph nodes. When Node-RADS >2 was identified as the best cutoff based on balanced values, the sensitivity and positive predictive value were 0.92 and 0.94, respectively. Conclusions: Our study suggests that the Node-RADS score has high accuracy in predicting NPC cervical lymph node metastasis. Nevertheless, this conclusion requires confirmation in a larger cohort of patients with NPC.

Revealing the crucial roles of suppressive immune microenvironment in cardiac myxoma progression.

Cardiac myxoma is a commonly encountered tumor within the heart that has the potential to be life-threatening. However, the cellular composition of this condition is still not well understood. To fill this gap, we analyzed 75,641 cells from cardiac myxoma tissues based on single-cell sequencing. We defined a population of myxoma cells, which exhibited a resemblance to fibroblasts, yet they were distinguished by an increased expression of phosphodiesterases and genes associated with cell proliferation, differentiation, and adhesion. The clinical relevance of the cell populations indicated a higher proportion of myxoma cells and M2-like macrophage infiltration, along with their enhanced spatial interaction, were found to significantly contribute to the occurrence of embolism. The immune cells surrounding the myxoma exhibit inhibitory characteristics, with impaired function of T cells characterized by the expression of GZMK and TOX, along with a substantial infiltration of tumor-promoting macrophages expressed growth factors such as PDGFC. Furthermore, in vitro co-culture experiments showed that macrophages promoted the growth of myxoma cells significantly. In summary, this study presents a comprehensive single-cell atlas of cardiac myxoma, highlighting the heterogeneity of myxoma cells and their collaborative impact on immune cells. These findings shed light on the complex pathobiology of cardiac myxoma and present potential targets for intervention.