Construction of a tumor mutational burden-derived LncRNA prognostic computational framework associated with therapy sensitivity in skin cutaneous melanoma.

BACKGROUND: Skin cutaneous melanoma (SKCM) poses a significant public health challenge due to its aggressive nature and limited treatment options. To address this, the study introduces the Tumor Mutational Burden-Derived Immune lncRNA Prognostic Index (TILPI) as a potential prognostic tool for SKCM. METHODS: TILPI was developed using a combination of gene set variation analysis, differential expression analysis, and COX regression analysis. Additionally, functional experiments were conducted to validate the findings, focusing on the effects of STARD4-AS1 knockdown on SKCM tumor cell behavior. These experiments encompassed assessments of tumor cell proliferation, gene and protein expression, migration, invasion, and in vivo tumor growth. RESULTS: The results demonstrated that knockdown of STARD4-AS1 led to a significant reduction in tumor cell proliferation and impaired migration and invasion abilities. Moreover, it resulted in the downregulation of ADCY4, PRKACA, and SOX10 gene expression, as well as decreased protein expression of ADCY4, PRKACA, and SOX10. In vivo experiments further confirmed the efficacy of STARD4-AS1 knockdown in reducing tumor growth. CONCLUSIONS: This study elucidates the mechanistic role of STARD4-AS1 and its downstream targets in SKCM progression, highlighting the importance of the ADCY4/PRKACA/SOX10 pathway. The integration of computational analysis with experimental validation enhances the understanding of TILPI and its clinical implications. Overall, the findings underscore the potential of novel computational frameworks like TILPI in predicting and managing SKCM, particularly through targeting the ADCY4/PRKACA/SOX10 pathway.

[In Vitro Amplification of NK Cells from Feeder Layer Cells Expressing IL-21].

OBJECTIVE: To investigate the effect of feeder layer cells expressing interleukin (IL)-21 on the amplification of NK cells In Vitro . METHODS: The K562 cell line with IL-21 expression on its membrane was constructed by electroporation, and co-cultured with NK cells after inactivation. The proliferation of NK cells was observed. The killing function of the amplified NK cells In Vitro was evaluated by the lactate dehydrogenase (LDH) and interferon-γ (IFN-γ) release assay. A colorectal cancer xenograft model in NOD/SCID mice was established, and a blank control group, a NK cell group and an amplified NK cell group were set up to detect the tumor killing effect of amplified NK cells in vivo. RESULTS: K562 cells expressing IL-21 on the membrane were successfully constructed by electroporation. After co-culturing with K562 cells expressing IL-21 on the membrane for 17 days, the NK cells increased to 700 times, which showed an enhanced amplification ability compared with control group (P < 0.001). In the tumor cell killing experiment In Vitro , there was no significant difference in the killing activity on tumor cells between NK cells and amplified NK cells, and there was also no significant difference in mice in vivo. CONCLUSION: K562 cells expressing IL-21 on the membrane can significantly increase the amplification ability of NK cells In Vitro , but do not affect the killing function of NK cells In Vitro and in vivo. It can be used for the subsequent large-scale production of NK cells In Vitro .

Multitask machine learning-based tumor-associated collagen signatures predict peritoneal recurrence and disease-free survival in gastric cancer.

BACKGROUND: Accurate prediction of peritoneal recurrence for gastric cancer (GC) is crucial in clinic. The collagen alterations in tumor microenvironment affect the migration and treatment response of cancer cells. Herein, we proposed multitask machine learning-based tumor-associated collagen signatures (TACS), which are composed of quantitative collagen features derived from multiphoton imaging, to simultaneously predict peritoneal recurrence (TACSPR) and disease-free survival (TACSDFS). METHODS: Among 713 consecutive patients, with 275 in training cohort, 222 patients in internal validation cohort, and 216 patients in external validation cohort, we developed and validated a multitask machine learning model for simultaneously predicting peritoneal recurrence (TACSPR) and disease-free survival (TACSDFS). The accuracy of the model for prediction of peritoneal recurrence and prognosis as well as its association with adjuvant chemotherapy were evaluated. RESULTS: The TACSPR and TACSDFS were independently associated with peritoneal recurrence and disease-free survival in three cohorts, respectively (all P < 0.001). The TACSPR demonstrated a favorable performance for peritoneal recurrence in all three cohorts. In addition, the TACSDFS also showed a satisfactory accuracy for disease-free survival among included patients. For stage II and III diseases, adjuvant chemotherapy improved the survival of patients with low TACSPR and low TACSDFS, or high TACSPR and low TACSDFS, or low TACSPR and high TACSDFS, but had no impact on patients with high TACSPR and high TACSDFS. CONCLUSIONS: The multitask machine learning model allows accurate prediction of peritoneal recurrence and survival for GC and could distinguish patients who might benefit from adjuvant chemotherapy.

Microbiota-induced S100A11-RAGE axis underlies immune evasion in right-sided colon adenomas and is a therapeutic target to boost anti-PD1 efficacy.

BACKGROUND: Tumourigenesis in right-sided and left-sided colons demonstrated distinct features. OBJECTIVE: We aimed to characterise the differences between the left-sided and right-sided adenomas (ADs) representing the early stage of colonic tumourigenesis. DESIGN: Single-cell and spatial transcriptomic datasets were analysed to reveal alterations between right-sided and left-sided colon ADs. Cells, animal experiments and clinical specimens were used to verify the results. RESULTS: Single-cell analysis revealed that in right-sided ADs, there was a significant reduction of goblet cells, and these goblet cells were dysfunctional with attenuated mucin biosynthesis and defective antigen presentation. An impairment of the mucus barrier led to biofilm formation in crypts and subsequent bacteria invasion into right-sided ADs. The regions spatially surrounding the crypts with biofilm occupation underwent an inflammatory response by lipopolysaccharide (LPS) and an apoptosis process, as revealed by spatial transcriptomics. A distinct S100A11+ epithelial cell population in the right-sided ADs was identified, and its expression level was induced by bacterial LPS and peptidoglycan. S100A11 expression facilitated tumour growth in syngeneic immunocompetent mice with increased myeloid-derived suppressor cells (MDSC) but reduced cytotoxic CD8+ T cells. Targeting S100A11 with well-tolerated antagonists of its receptor for advanced glycation end product (RAGE) (Azeliragon) significantly impaired tumour growth and MDSC infiltration, thereby boosting the efficacy of anti-programmed cell death protein 1 therapy in colon cancer. CONCLUSION: Our findings unravelled that dysfunctional goblet cells and consequential bacterial translocation activated the S100A11-RAGE axis in right-sided colon ADs, which recruits MDSCs to promote immune evasion. Targeting this axis by Azeliragon improves the efficacy of immunotherapy in colon cancer.

Predicting gastric cancer response to anti-HER2 therapy or anti-HER2 combined immunotherapy based on multi-modal data.

The sole use of single modality data often fails to capture the complex heterogeneity among patients, including the variability in resistance to anti-HER2 therapy and outcomes of combined treatment regimens, for the treatment of HER2-positive gastric cancer (GC). This modality deficit has not been fully considered in many studies. Furthermore, the application of artificial intelligence in predicting the treatment response, particularly in complex diseases such as GC, is still in its infancy. Therefore, this study aimed to use a comprehensive analytic approach to accurately predict treatment responses to anti-HER2 therapy or anti-HER2 combined immunotherapy in patients with HER2-positive GC. We collected multi-modal data, comprising radiology, pathology, and clinical information from a cohort of 429 patients: 310 treated with anti-HER2 therapy and 119 treated with a combination of anti-HER2 and anti-PD-1/PD-L1 inhibitors immunotherapy. We introduced a deep learning model, called the Multi-Modal model (MuMo), that integrates these data to make precise treatment response predictions. MuMo achieved an area under the curve score of 0.821 for anti-HER2 therapy and 0.914 for combined immunotherapy. Moreover, patients classified as low-risk by MuMo exhibited significantly prolonged progression-free survival and overall survival (log-rank test, P < 0.05). These findings not only highlight the significance of multi-modal data analysis in enhancing treatment evaluation and personalized medicine for HER2-positive gastric cancer, but also the potential and clinical value of our model.

Virtual multiplexed immunofluorescence staining from non-antibody-stained fluorescence imaging for gastric cancer prognosis.

BACKGROUND: Multiplexed immunofluorescence (mIF) staining, such as CODEX and MIBI, holds significant clinical value for various fields, such as disease diagnosis, biological research, and drug development. However, these techniques are often hindered by high time and cost requirements. METHODS: Here we present a Multimodal-Attention-based virtual mIF Staining (MAS) system that utilises a deep learning model to extract potential antibody-related features from dual-modal non-antibody-stained fluorescence imaging, specifically autofluorescence (AF) and DAPI imaging. The MAS system simultaneously generates predictions of mIF with multiple survival-associated biomarkers in gastric cancer using self- and multi-attention learning mechanisms. FINDINGS: Experimental results with 180 pathological slides from 94 patients with gastric cancer demonstrate the efficiency and consistent performance of the MAS system in both cancer and noncancer gastric tissues. Furthermore, we showcase the prognostic accuracy of the virtual mIF images of seven gastric cancer related biomarkers, including CD3, CD20, FOXP3, PD1, CD8, CD163, and PD-L1, which is comparable to those obtained from the standard mIF staining. INTERPRETATION: The MAS system rapidly generates reliable multiplexed staining, greatly reducing the cost of mIF and improving clinical workflow. FUNDING: Stanford 2022 HAI Seed Grant; National Institutes of Health 1R01CA256890.

POU2F1 inhibits miR-29b1/a cluster-mediated suppression of PIK3R1 and PIK3R3 expression to regulate gastric cancer cell invasion and migration.

BACKGROUND: The transcription factor POU2F1 regulates the expression levels of microRNAs in neoplasia. However, the miR-29b1/a cluster modulated by POU2F1 in gastric cancer (GC) remains unknown. METHODS: Gene expression in GC cells was evaluated using reverse-transcription polymerase chain reaction (PCR), western blotting, immunohistochemistry, and RNA in situ hybridization. Co-immunoprecipitation was performed to evaluate protein interactions. Transwell migration and invasion assays were performed to investigate the biological behavior of GC cells. MiR-29b1/a cluster promoter analysis and luciferase activity assay for the 3'-UTR study were performed in GC cells. In vivo tumor metastasis was evaluated in nude mice. RESULTS: POU2F1 is overexpressed in GC cell lines and binds to the miR-29b1/a cluster promoter. POU2F1 is upregulated, whereas mature miR-29b-3p and miR-29a-3p are downregulated in GC tissues. POU2F1 promotes GC metastasis by inhibiting miR-29b-3p or miR-29a-3p expression in vitro and in vivo. Furthermore, PIK3R1 and/or PIK3R3 are direct targets of miR-29b-3p and/or miR-29a-3p, and the ectopic expression of PIK3R1 or PIK3R3 reverses the suppressive effect of mature miR-29b-3p and/or miR-29a-3p on GC cell metastasis and invasion. Additionally, the interaction of PIK3R1 with PIK3R3 promotes migration and invasion, and miR-29b-3p, miR-29a-3p, PIK3R1, and PIK3R3 regulate migration and invasion via the phosphatidylinositol 3-kinase/protein kinase B/mammalian target of rapamycin (PI3K/Akt/mTOR) pathway in GC cells. In addition, POU2F1, PIK3R1, and PIK3R3 expression levels negatively correlated with miR-29b-3p and miR-29a-3p expression levels in GC tissue samples. CONCLUSIONS: The POU2F1-miR-29b-3p/miR-29a-3p-PIK3R1/PIK3R1 signaling axis regulates tumor progression and may be a promising therapeutic target for GC.

Icariside I enhances the effects of immunotherapy in gastrointestinal cancer via targeting TRPV4 and upregulating the cGAS-STING-IFN-I pathway.

Gastrointestinal cancer is among the most common cancers worldwide. Immune checkpoint inhibitor-based cancer immunotherapy has become an innovative approach in cancer treatment; however, its efficacy in gastrointestinal cancer is limited by the absence of infiltration of immune cells within the tumor microenvironment. Therefore, it is therefore urgent to develop a novel therapeutic drug to enhance immunotherapy. In this study, we describe a previously unreported potentiating effect of Icariside I (ICA I, GH01), the main bioactive compound isolated from the Epimedium species, on anti-tumor immune responses. Mechanistically, molecular docking and SPR assay result show that ICA I binding with TRPV4. ICA I induced intracellular Ca2+ increasing and mitochondrial DNA release by targeting TRPV4, which triggered cytosolic ox-mitoDNA release. Importantly, these intracellular ox-mitoDNA fragments were taken up by immune cells in the tumor microenvironment, which amplified the immune response. Moreover, our study shows the remarkable efficacy of sequential administration of ICA I and anti-α-PD-1 mAb in advanced tumors and provides a strong scientific rationale for recommending such a combination therapy for clinical trials. ICA I enhanced the anti-tumor effects with PD-1 inhibitors by regulating the TRPV4/Ca2+/Ox-mitoDNA/cGAS/STING axis. We expect that these findings will be translated into clinical therapies, which will benefit more patients with cancer in the near future.

18F-FDG PET/CT Radiomics-Based Multimodality Fusion Model for Preoperative Individualized Noninvasive Prediction of Peritoneal Metastasis in Advanced Gastric Cancer.

PURPOSE: This study was designed to develop and validate a machine learning-based, multimodality fusion (MMF) model using 18F-fluorodeoxyglucose (FDG) PET/CT radiomics and kernelled support tensor machine (KSTM), integrated with clinical factors and nuclear medicine experts' diagnoses to individually predict peritoneal metastasis (PM) in advanced gastric cancer (AGC). METHODS: A total of 167 patients receiving preoperative PET/CT and subsequent surgery were included between November 2006 and September 2020 and were divided into a training and testing cohort. The PM status was confirmed via laparoscopic exploration and postoperative pathology. The PET/CT signatures were constructed by classic radiomic, handcrafted-feature-based model and KSTM self-learning-based model. The clinical nomogram was constructed by independent risk factors for PM. Lastly, the PET/CT signatures, clinical nomogram, and experts' diagnoses were fused using evidential reasoning to establish the MMF model. RESULTS: The MMF model showed excellent performance in both cohorts (area under the curve [AUC] 94.16% and 90.84% in training and testing), and demonstrated better prediction accuracy than clinical nomogram or experts' diagnoses (net reclassification improvement p < 0.05). The MMF model also had satisfactory generalization ability, even in mucinous adenocarcinoma and signet ring cell carcinoma which have poor uptake of 18F-FDG (AUC 97.98% and 89.71% in training and testing). CONCLUSIONS: The 18F-FDG PET/CT radiomics-based MMF model may have significant clinical implications in predicting PM in AGC, revealing that it is necessary to combine the information from different modalities for comprehensive prediction of PM.

Preparation of ethyl cellulose bimodal nanofibrous membrane by green electrospinning based on molecular weight regulation for high-performance air filtration.

Preparing bio-based air filtration membrane through green electrospinning strategy is a vital approach to alleviating environmental and energy crises. However, the development of related biomaterials and method for regulating membrane structure are still lacking. In this study, ethyl cellulose (EC) bimodal nanofibrous membrane was prepared by electrospinning using ethanol and water as solvents to achieve high-performance air filtration. A new strategy for bimodal fiber molding based on molecular weight modulation was proposed. The EC polymer chains with medium molecular weights were subject to the highest degree of inhomogeneity of solvent intrusion, and there were significant differences in viscous forces "microscopically", leading to the formation of bimodal structure by inhomogeneous stretching of the jet. The well-defined bimodal structure endowed EC membrane with excellent air filtration performance. The filtration efficiency for PM0.3, pressure drop, quality factor were 99.11 %, 42.2 Pa, and 0.112 Pa-1, respectively. Compared to the commonly used zein, EC cost just 12.77 %, and its solution had a 50 % longer shelf life, making it a more desirable biomaterial. This work will facilitate the application of more biomaterials in air filtration, promote the green fabrication of high-performance air filtration membranes, and realize sustainable development.

3D MXene/PVA Aerogel Enabling a Dendrite-Free Zn Metal Anode.

Aqueous zinc-ion batteries have attracted widespread attention due to their low cost and high safety. Unfortunately, their commercial applications are greatly inhibited by the negative effects of zinc dendrites and side reactions. A solution that utilizes a 3D host can help mitigate these issues. In this paper, we present a 3D host that is composed of an aerogel scaffold with a poly(vinyl alcohol) and MXene structure. The embedded Zn can be densely packed inside the host due to its zincophilic properties. During cycling, the fluorine-based functional groups on the surface of MXene were able to react with the electrolyte to form the ZnF2 solid electrolyte interphase, which can effectively protect the composite anode. As a result, the symmetrical battery was capable of stable cycling for >300 h at a high current density of 10 mA cm-2. More impressively, the assembled full cell retained 93.86% after 800 cycles at a current density of 5 A g-1. This work provides an effective idea for improving the cycling performance of aqueous zinc-ion batteries.

Data-Driven Design of Triple-Targeted Protein Nanoprobes for Multiplexed Imaging of Cancer Lymphatic Metastasis.

Targeted imaging of cancer lymphatic metastasis remains challenging due to its highly heterogeneous molecular and phenotypic diversity. Herein, triple-targeted protein nanoprobes capable of specifically binding to three targets for imaging cancer lymphatic metastasis, through a data-driven design approach combined with a synthetic biology-based assembly strategy, are introduced. Specifically, to address the diversity of metastatic lymph nodes (LNs), a combination of three targets, including C-X-C motif chemokine receptor 4 (CXCR4), transferrin receptor protein 1 (TfR1), and vascular endothelial growth factor receptor 3 (VEGFR3) is identified, leveraging machine leaning-based bioinformatics analysis and examination of LN tissues from patients with gastric cancer. Using this identified target combination, ferritin nanocage-based nanoprobes capable of specifically binding to all three targets are designed through the self-assembly of genetically engineered ferritin subunits using a synthetic biology approach. Using these nanoprobes, multiplexed imaging of heterogeneous metastatic LNs is successfully achieved in a polyclonal lymphatic metastasis animal model. In 19 freshly resected human gastric specimens, the signal from the triple-targeted nanoprobes significantly differentiates metastatic LNs from benign LNs. This study not only provides an effective nanoprobe for imaging highly heterogeneous lymphatic metastasis but also proposes a potential strategy for guiding the design of targeted nanomedicines for cancer lymphatic metastasis.

Fruquintinib plus paclitaxel versus placebo plus paclitaxel for gastric or gastroesophageal junction adenocarcinoma: the randomized phase 3 FRUTIGA trial.

The vascular endothelial growth factor pathway plays a key role in the pathogenesis of gastric cancer. In the multicenter, double-blind phase 3 FRUTIGA trial, 703 patients with advanced gastric or gastroesophageal junction adenocarcinoma who progressed on fluorouracil- and platinum-containing chemotherapy were randomized (1:1) to receive fruquintinib (an inhibitor of vascular endothelial growth factor receptor-1/2/3; 4 mg orally, once daily) or placebo for 3 weeks, followed by 1 week off, plus paclitaxel (80 mg/m2 intravenously on days 1/8/15 per cycle). The study results were positive as one of the dual primary endpoints, progression-free survival (PFS), was met (median PFS, 5.6 months in the fruquintinib arm versus 2.7 months in the placebo arm; hazard ratio 0.57; 95% confidence interval 0.48-0.68; P < 0.0001). The other dual primary endpoint, overall survival (OS), was not met (median OS, 9.6 months versus 8.4 months; hazard ratio 0.96, 95% confidence interval 0.81-1.13; P = 0.6064). The most common grade ≥3 adverse events were neutropenia, leukopenia and anemia. Fruquintinib plus paclitaxel as a second-line treatment significantly improved PFS, but not OS, in Chinese patients with advanced gastric or gastroesophageal junction adenocarcinoma and could potentially be another treatment option for these patients. ClinicalTrials.gov registration: NCT03223376 .

Development and interpretation of a pathomics-driven ensemble model for predicting the response to immunotherapy in gastric cancer.

BACKGROUND: Only a subset of patients with gastric cancer experience long-term benefits from immune checkpoint inhibitors (ICIs). Currently, there is a deficiency in precise predictive biomarkers for ICI efficacy. The aim of this study was to develop and validate a pathomics-driven ensemble model for predicting the response to ICIs in gastric cancer, using H&E-stained whole slide images (WSI). METHODS: This multicenter study retrospectively collected and analyzed H&E-stained WSIs and clinical data from 584 patients with gastric cancer. An ensemble model, integrating four classifiers: least absolute shrinkage and selection operator, k-nearest neighbors, decision trees, and random forests, was developed and validated using pathomics features, with the objective of predicting the therapeutic efficacy of immune checkpoint inhibition. Model performance was evaluated using metrics including the area under the curve (AUC), sensitivity, and specificity. Additionally, SHAP (SHapley Additive exPlanations) analysis was used to explain the model's predicted values as the sum of the attribution values for each input feature. Pathogenomics analysis was employed to explain the molecular mechanisms underlying the model's predictions. RESULTS: Our pathomics-driven ensemble model effectively stratified the response to ICIs in training cohort (AUC 0.985 (95% CI 0.971 to 0.999)), which was further validated in internal validation cohort (AUC 0.921 (95% CI 0.839 to 0.999)), as well as in external validation cohort 1 (AUC 0.914 (95% CI 0.837 to 0.990)), and external validation cohort 2 (0.927 (95% CI 0.802 to 0.999)). The univariate Cox regression analysis revealed that the prediction signature of pathomics-driven ensemble model was a prognostic factor for progression-free survival in patients with gastric cancer who underwent immunotherapy (p<0.001, HR 0.35 (95% CI 0.24 to 0.50)), and remained an independent predictor after multivariable Cox regression adjusted for clinicopathological variables, (including sex, age, carcinoembryonic antigen, carbohydrate antigen 19-9, therapy regime, line of therapy, differentiation, location and programmed death ligand 1 (PD-L1) expression in all patients (p<0.001, HR 0.34 (95% CI 0.24 to 0.50)). Pathogenomics analysis suggested that the ensemble model is driven by molecular-level immune, cancer, metabolism-related pathways, and was correlated with the immune-related characteristics, including immune score, Estimation of STromal and Immune cells in MAlignant Tumor tissues using Expression data score, and tumor purity. CONCLUSIONS: Our pathomics-driven ensemble model exhibited high accuracy and robustness in predicting the response to ICIs using WSIs. Therefore, it could serve as a novel and valuable tool to facilitate precision immunotherapy.

Two-Photon Absorption Aggregation-Induced Emission Luminogen/Paclitaxel Nanoparticles for Cancer Theranostics.

Multifaceted nanoplatforms integrating fluorescence imaging and chemotherapy have garnered acknowledgment for their potential potency in cancer diagnosis and simultaneous in situ therapy. However, some drawbacks remain for traditional organic photosensitizers, such as poor photostability, short excitation wavelength, and shallow penetration depth, which will greatly lower the chemotherapy treatment efficiency. Herein, we present lipid-encapsulated two-photon active aggregation-induced emission (AIE) luminogen and paclitaxel (PTX) nanoparticles (AIE@PTX NPs) with bright red fluorescence emission, excellent photostability, and good biocompatibility. The AIE@PTX NPs exhibit dual functionality as two-photon probes for visualizing blood vessels and tumor structures, achieving penetration depth up to 186 and 120 µm, respectively. Furthermore, the tumor growth of the HeLa-xenograft model can be effectively prohibited after the fluorescence imaging-guided and PTX-induced chemotherapy, which shows great potential in the clinical application of two-photon cell and tumor fluorescence imaging and cancer treatment.

Biomimetic copper-doped polypyrrole nanoparticles induce glutamine metabolism inhibition to enhance breast cancer cuproptosis and immunotherapy.

Cuproptosis, a newly discovered mechanism of inducing tumor cell death, primarily relies on the intracellular accumulation of copper ions. The utilization of Cu-based nanomaterials to induce cuproptosis holds promising prospects in future biomedical applications. However, the presence of high levels of glutathione (GSH) within tumor cells hinders the efficacy of cuproptosis. In this study, we have developed a BPTES-loaded biomimetic Cu-doped polypyrrole nanoparticles (CuP) nanosystem (PCB) for enhanced cuproptosis and immune modulation. PCB comprises an internal BPTES and CuP core and an external platelet membrane (PM) that facilitates active targeting to tumor sites following intravenous administration. Subsequently, PCB effectively suppresses glutaminase (GLS1) activity, thereby reducing GSH content. Moreover, CuP catalyze intracellular H2O2, amplifying oxidative stress while simultaneously inducing dihydrolipoyl transacetylase (DLAT) oligomerization through released Cu2+, resulting in cuproptosis. PCB not only inhibits primary tumors but also exhibits inhibitory effects on abscopal tumors. This work represents the first instance where GLS inhibition has been employed to enhance cuproptosis and immunotherapy. It also provides valuable insights into further investigations on cuproptosis.

Relationship between family resilience and dyadic coping in colorectal cancer patients and their spouses, based on the actor-partner interdependence model.

PURPOSE: To explore the relationship between dyadic coping and family resistance in colorectal cancer patients and their spouses. METHODS: 178 pairs of colorectal cancer patients and their spouses hospitalized in a three tertiary hospital in Changsha were selected from July 2021 to March 2022. The Family Resilience Assessment Scale and the Dyadic Coping Inventory were used to investigate, which relationship was analyzed by APIM. RESULTS: The total score of patients' dyadic coping was 121.51 ± 16.8, and spouses' score was 123.72 ± 16.6. The total score of family resilience was 176.42 ± 16.0, and spouses' score was 182.72 ± 17.03. There was a significant positive relationship between dyadic coping and family resistance of colorectal cancer patients and their spouses (r > 0.7, P < 0.001). The positive dyadic coping of colorectal cancer patients and their spouses had a positive effect on their own and their spouses' family resilience and the effect was the same. The negative dyadic coping of colorectal cancer patients and their spouses had a negative impact on their own family resilience, and the overall model showed a subject pattern. CONCLUSIONS: The level of family resilience of colorectal cancer patients and their spouses was affected by the level of dyadic coping. Medical workers should regard patients and their spouses as a whole and formulate mutually supportive coping strategies with family as the center, so as to increase positive coping behavior and enhance their family's ability to cope with cancer.

Influence of comorbidity of chronic diseases on basic activities of daily living among older adults in China: a propensity score-matched study.

Rationale: With the accelerating process of population aging, the comorbidity of chronic disease (CCD) has become a major public health problem that threatens the health of older adults. Objective: This study aimed to assess whether CCD is associated with basic activities of daily living (BADL) and explore the factors influencing BADL in older adults. Method: A cross-sectional community health survey with stratified random sampling among older residents (≥60 years old) was conducted in 2022. A questionnaire was used to collect information on BADL, chronic diseases, and other relevant aspects. Propensity score matching (PSM) was used to match the older adults with and without CCD. Univariate and multivariate logistic regression analyses were used to explore the factors influencing BADL. PSM was used to match participants with single-chronic disease (SCD) and CCD. Results: Among the 47,720 participants, those with CCD showed a higher prevalence of BADL disability (13.07%) than those with no CCD (6.33%) and SCD (7.39%). After adjusting for potential confounders with PSM, 6,513 pairs of cases with and without CCD were matched. The univariate analysis found that the older adults with CCD had a significantly higher prevalence of BADL disability (13.07%, 851 of 6,513) than those without CCD (9.83%, 640 of 6,513, P < 0.05). The multivariate logistic regression analysis revealed that CCD was a risk factor for BADL in older adults [OR = 1.496, 95% CI: 1.393-1.750, P < 0.001]. In addition, age, educational level, alcohol intake, social interaction, annual physical examination, retirement benefits, depression, weekly amount of exercise, and years of exercise were related to BADL disability (P < 0.05). PSM matching was performed on participants with CCD and SCD and showed that the older adults with CCD had a significantly higher prevalence of BADL disability (13.07%, 851 of 6,513) than those with SCD (11.39%, 742 of 6,513, P < 0.05). Conclusion: The older adults with CCD are at a higher risk of BADL disability than their counterparts with no CCD or SCD. Therefore, we advocate paying attention to and taking measures to improve the health and quality of life of these individuals.

POLQ inhibition attenuates the stemness and ferroptosis resistance in gastric cancer cells via downregulation of dihydroorotate dehydrogenase.

Gastric cancer (GC) contains subpopulations of cancer stem cells (CSCs), which are described as the main contributors in tumor initiation and metastasis. It is necessary to clarify the molecular mechanism underlying CSCs phenotype and develop novel biomarkers and therapeutic targets for gastric cancer. Here, we show that POLQ positively regulates stem cell-like characteristics of gastric cancer cells, knockdown of POLQ suppressed the stemness of GC cells in vitro and in vivo. Further mechanistic studies revealed that POLQ knockdown could downregulate the expression of dihydroorotate dehydrogenase (DHODH). DHODH overexpression rescued the reduced stemness resulted by POLQ knockdown. Furthermore, we found that POLQ expression correlated with resistance to ferroptosis, and POLQ inhibition renders gastric cancer cells more vulnerable to ferroptosis. Further investigation revealed that POLQ regulated DHODH expression via the transcription factors E2F4, thereby regulating ferroptosis resistance and stemness of gastric cancer cells. Given the importance of POLQ in stemness and ferroptosis resistance of GC, we further evaluated the therapeutic potential of POLQ inhibitor novobiocin, the results show that novobiocin attenuates the stemness of GC cells and increased ferroptosis sensitivity. Moreover, the combination of POLQ inhibitor and ferroptosis inducer synergistically suppressed MGC-803 xenograft tumor growth and diminished metastasis. Our results identify a POLQ-mediated stemness and ferroptosis defense mechanism and provide a new therapeutic strategy for gastric cancer.