KDM6A-SND1 interaction maintains genomic stability by protecting the nascent DNA and contributes to cancer chemoresistance.

Genomic instability is one of the hallmarks of cancer. While loss of histone demethylase KDM6A increases the risk of tumorigenesis, its specific role in maintaining genomic stability remains poorly understood. Here, we propose a mechanism in which KDM6A maintains genomic stability independently on its demethylase activity. This occurs through its interaction with SND1, resulting in the establishment of a protective chromatin state that prevents replication fork collapse by recruiting of RPA and Ku70 to nascent DNA strand. Notably, KDM6A-SND1 interaction is up-regulated by KDM6A SUMOylation, while KDM6AK90A mutation almost abolish the interaction. Loss of KDM6A or SND1 leads to increased enrichment of H3K9ac and H4K8ac but attenuates the enrichment of Ku70 and H3K4me3 at nascent DNA strand. This subsequently results in enhanced cellular sensitivity to genotoxins and genomic instability. Consistent with these findings, knockdown of KDM6A and SND1 in esophageal squamous cell carcinoma (ESCC) cells increases genotoxin sensitivity. Intriguingly, KDM6A H101D & P110S, N1156T and D1216N mutations identified in ESCC patients promote genotoxin resistance via increased SND1 association. Our finding provides novel insights into the pivotal role of KDM6A-SND1 in genomic stability and chemoresistance, implying that targeting KDM6A and/or its interaction with SND1 may be a promising strategy to overcome the chemoresistance.

Qigui-Yishen decoction delays renal fibrosis in mice with chronic kidney disease by regulating TM and PAI-1.

OBJECTIVE: To explore the mechanism of Qigui-Yishen decoction in delaying renal fibrosis in mice by regulating thrombin regulatory protein (Thrombomodulin, TM) and plasminogen activator inhibitor-1 (PAI-1) based on network pharmacology. METHODS: The active ingredients of Qigui Yishen decoction and their target molecules associated with chronic kidney disease (CKD) were retrieved from websites and databases, sorted out, and screened, and the possible targets of Qigui Yishen decoction for reducing CKD renal fibrosis were predicted and analyzed. Forty Institute of Cancer research (ICR) rats were used to establish a unilateral ureteral obstruction (UUO) model, and divided into several groups: sham operation group, model group, high concentration decoction group (1 g/mL), low concentration decoction group (0.46 g/mL), and benazepril group (0.1 g/mL). At the end of the experiment, the levels of serum creatinine (Scr) and blood urea nitrogen (BUN) were detected. Masson staining was used to observe changes in the renal interstitial fibrosis index. Immunohistochemistry and western blot were used to detect the expressions of TM, PAI-1, transforming growth factor-ß1 (TGF-ß1) and collagen I (Col I) in kidney tissues, and the differences between groups were compared. RESULTS: Qigui Yishen decoction contains 42 effective ingredients such as sitosterol, mannitol, and quercetin, with 662 drug targets and 16154 disease targets. Analysis revealed 570 potential targets, including TM4SF19, PAIP1, TGF-ß1, and Col I-AI. Compared to the sham operation group, all treatment groups exhibited increased Scr and BUN levels (P<0.05) and enhanced renal interstitial fibrosis (P<0.05) after UUO model establishment. Moreover, immunohistochemical results showed significant increases in PAI-1, TGF-ß1, and Col I (all P<0.05), and a significant decrease in TM expression (P<0.05). Compared to the model group, the high concentration decoction group, low concentration decoction group and benazepril group had no significant difference in Scr and BUN values (P>0.05), but the renal interstitial fibrosis index was lower (P<0.05). Also, the relative expressions of PAI-1, TGF-ß1 and Col I in the kidney tissue of mice were decreased, while the relative expression of TM was increased (P<0.05). CONCLUSION: Qigi Yishen decoction has the characteristics of multiple components and multiple targets, and can play a role in delaying renal fibrosis by regulating the expression of PAI-1, TGF-ß1, Col I, and TM.

Integrative analysis of senescence-related genes identifies robust prognostic clusters with distinct features in hepatocellular carcinoma.

INTRODUCTION: Senescence refers to a state of permanent cell growth arrest and is regarded as a tumor suppressive mechanism, whereas accumulative evidence demonstrate that senescent cells play an adverse role during cancer progression. The scarcity of specific and reliable markers reflecting senescence level in cancer impede our understanding of this biological basis. OBJECTIVES: Senescence-related genes (SRGs) were collected for integrative analysis to reveal the role of senescence in hepatocellular carcinoma (HCC). METHODS: Consensus clustering was used to subtype HCC based on SRGs. Several computational methods, including single sample gene set enrichment analysis (ssGSEA), fuzzy c-means algorithm, were performed. Data of drug sensitivities were utilized to screen potential therapeutic agents for different senescence patients. Additionally, we developed a method called signature-related gene analysis (SRGA) for identification of markers relevant to phenotype of interest. Experimental strategies consisting quantitative real-time PCR (qRT-PCR), ß-galactosidase assay, western blot, and tumor-T cell co-culture system were used to validate the findings in vitro. RESULTS: We identified three robust prognostic clusters of HCC patients with distinct survival outcome, mutational landscape, and immune features. We further extracted signature genes of senescence clusters to construct the senescence scoring system and profile senescence level in HCC at bulk and single-cell resolution. Senescence-induced stemness reprogramming was confirmed both in silico and in vitro. HCC patients with high senescence were immune suppressed and sensitive to Tozasertib and other drugs. We suggested that MAFG, PLIN3, and 4 other genes were pertinent to HCC senescence, and MAFG potentially mediated immune suppression, senescence, and stemness. CONCLUSION: Our findings provide insights into the role of SRGs in patients stratification and precision medicine.

From the Public Health Perspective: a Scalable Model for Improving Epidemiological Testing Efficacy in Low- and Middle-Income Areas.

The globe is an organically linked whole, and in the pandemic era, COVID-19 has brought heavy public safety threats and economic costs to humanity as almost all countries began to pay more attention to taking steps to minimize the risk of harm to society from sudden-onset diseases. It is worth noting that in some low- and middle-income areas, where the environment for epidemic detection is complex, the causative and comorbid factors are numerous, and where public health resources are scarce. It is often more difficult than in other areas to obtain timely and effective detection and control in the event of widespread virus transmission, which, in turn, is a constant threat to local and global public health security. Pandemics are preventable through effective disease surveillance systems, with nonpharmacological interventions (NPIs) as the mainstay of the control system, effectively controlling the spread of epidemics and preventing larger outbreaks. However, current state-of-the-art NPIs are not applicable in low- and middle-income areas and tend to be decentralized and costly. Based on a 3-year case study of SARS-CoV-2 preventive detection in low-income areas in south-central China, we explored a strategic model for enhancing disease detection efficacy in low- and middle-income areas. For the first time, we propose an integrated and comprehensive approach that covers structural, social, and personal strategies to optimize the epidemic surveillance system in low- and middle-income areas. This model can improve the local epidemic detection efficiency, ensure the health care needs of more people, reduce the public health costs in low- and middle-income areas in a coordinated manner, and ensure and strengthen local public health security sustainably.

tiRNA-Val-CAC-2 interacts with FUBP1 to promote pancreatic cancer metastasis by activating c­MYC transcription.

Cumulative studies have established the significance of transfer RNA-derived small RNA (tsRNA) in tumorigenesis and progression. Nevertheless, its function and mechanism in pancreatic cancer metastasis remain largely unclear. Here, we screened and identified tiRNA-Val-CAC-2 as highly expressed in pancreatic cancer metastasis samples by tsRNA sequencing. We also observed elevated levels of tiRNA-Val-CAC-2 in the serum of pancreatic cancer patients who developed metastasis, and patients with high levels of tiRNA-Val-CAC-2 exhibited a worse prognosis. Additionally, knockdown of tiRNA-Val-CAC-2 inhibited the metastasis of pancreatic cancer in vivo and in vitro, while overexpression of tiRNA-Val-CAC-2 promoted the metastasis of pancreatic cancer. Mechanically, we discovered that tiRNA-Val-CAC-2 interacts with FUBP1, leading to enhanced stability of FUBP1 protein and increased FUBP1 enrichment in the c-MYC promoter region, thereby boosting the transcription of c-MYC. Of note, rescue experiments confirmed that tiRNA-Val-CAC-2 could influence pancreatic cancer metastasis via FUBP1-mediated c-MYC transcription. These findings highlight a potential novel mechanism underlying pancreatic cancer metastasis, and suggest that both tiRNA-Val-CAC-2 and FUBP1 could serve as promising prognostic biomarkers and potential therapeutic targets for pancreatic cancer.