Circumventing drug resistance in gastric cancer: A spatial multi-omics exploration of chemo and immuno-therapeutic response dynamics.

BACKGROUND: Gastric Cancer (GC) characteristically exhibits heterogeneous responses to treatment, particularly in relation to immuno plus chemo therapy, necessitating a precision medicine approach. This study is centered around delineating the cellular and molecular underpinnings of drug resistance in this context. METHODS: We undertook a comprehensive multi-omics exploration of postoperative tissues from GC patients undergoing the chemo and immuno-treatment regimen. Concurrently, an image deep learning model was developed to predict treatment responsiveness. RESULTS: Our initial findings associate apical membrane cells with resistance to fluorouracil and oxaliplatin, critical constituents of the therapy. Further investigation into this cell population shed light on substantial interactions with resident macrophages, underscoring the role of intercellular communication in shaping treatment resistance. Subsequent ligand-receptor analysis unveiled specific molecular dialogues, most notably TGFB1-HSPB1 and LTF-S100A14, offering insights into potential signaling pathways implicated in resistance. Our SVM model, incorporating these multi-omics and spatial data, demonstrated significant predictive power, with AUC values of 0.93 and 0.84 in the exploration and validation cohorts respectively. Hence, our results underscore the utility of multi-omics and spatial data in modeling treatment response. CONCLUSION: Our integrative approach, amalgamating mIHC assays, feature extraction, and machine learning, successfully unraveled the complex cellular interplay underlying drug resistance. This robust predictive model may serve as a valuable tool for personalizing therapeutic strategies and enhancing treatment outcomes in gastric cancer.

Design and Experiment of Capacitive Rice Online Moisture Detection Device.

To solve the problems of poor stability and low monitoring precision in the online detection of rice moisture in the drying tower, we designed an online detection device for rice moisture at the outlet of the drying tower. The structure of a tri-plate capacitor was adopted, and the electrostatic field of the tri-plate capacitor was simulated using COMSOL software. A central composite design of three factors and five levels was carried out with the thickness, spacing, and area of the plates as the influencing factors and the capacitance-specific sensitivity as the test index. This device was composed of a dynamic acquisition device and a detection system. The dynamic sampling device was found to achieve dynamic continuous sampling and static intermittent measurements of rice using a ten-shaped leaf plate structure. The hardware circuit of the inspection system with STM32F407ZGT6 as the main control chip was designed to realize stable communication between the master and slave computers. Additionally, an optimized BP neural network prediction model based on the genetic algorithm was established using the MATLAB software. Indoor static and dynamic verification tests were also carried out. The results showed that the optimal plate structure parameter combination includes a plate thickness of 1 mm, plate spacing of 100 mm, and relative area of 18,000.069 mm2 while satisfying the mechanical design and practical application needs of the device. The structure of the BP neural network was 2-90-1, the length of individual code in the genetic algorithm was 361, and the prediction model was trained 765 times to obtain a minimum MSE value of 1.9683 × 10-5, which was lower than that of the unoptimized BP neural network with an MSE of 7.1215 × 10-4. The mean relative error of the device was 1.44% under the static test and 2.103% under the dynamic test, which met the accuracy requirements for the design of the device.

NCAPG promotes the oncogenesis and progression of non-small cell lung cancer cells through upregulating LGALS1 expression.

BACKGROUND: Numerous common oncogenic driver events have been confirmed in non-small cell lung cancer (NSCLC). Although targeted therapy has revolutionized NSCLC treatment, some patients still do not respond. NCAPG, also known as non-SMC condensin I complex subunit G, was positively associated with proliferation and migration in several tumor types. METHODS: We used transcriptional sequencing and TCGA database analysis to identify NCAPG as a new therapeutic target for NSCLC. The oncogenic roles of NCAPG in NSCLC tumor growth and metastasis were detected in vitro and in vivo. Ncapg+/+ or Ncapg+/- mice with urethane treatment were analyzed for oncogenesis of NSCLC. RESULTS: We investigated NCAPG as a new oncogenic driver which promoted NSCLC tumorigenesis and progression. We used transcriptome sequencing and the Cancer Genome Atlas (TCGA) database analysis to screen and found that NCAPG was negatively correlated with NSCLC survival. Using immunohistochemistry, we demonstrated that NCAPG overexpression was an independent risk factor for NSCLC survival. Functionally, NCAPG knockdown inhibited proliferation, migration, and invasion of NSCLC cells in vitro and in vivo. We exposed wildtype or Ncapg+/- mice to urethane and discovered that urethane-induced lung tumors were reduced in Ncapg+/- mice. Mechanistically, the function of NCAPG in promoting initiation and progression of NSCLC was closely related to LGALS1, which was also upregulated in NSCLC and might interact directly with NCAPG. CONCLUSIONS: This study indicates that NCAPG is one of the essential factors for NSCLC oncogenesis and progression, providing a new target for prognosis prediction and treatment of NSCLC.

Quality of pediatric clinical practice guidelines.

BACKGROUND: There is a lack of a comprehensive evaluation for pediatric clinical practice guidelines (CPGs) published in recent years. Here, we assessed the quality of pediatric CPGs, considering factors that might affect their quality. The aim of the study is to promote a more coherent development and application of CPGs. METHODS: Pediatric CPGs published in PubMed, MedLive, Guidelines International Network, National Institute for Health and Care Excellence, and World Health Organization between 2017 and 2019 were searched and collected. Paired researchers conducted screening, data extraction, and quality assessment using the Appraisal of Guidelines for Research and Evaluation II (AGREE II). Linear regression analysis determined the factors affecting CPGs' quality. RESULTS: The study included a total of 216 CPGs, which achieved a mean score of 4.26 out of 7 points (60.86%) in the AGREE II assessment. Only 6.48% of the CPGs reached the "recommend" level. The remaining 69.91% should have been modified before recommendation, while the other 23.61% did not reach the recommended level at all. The overall quality of recent pediatric CPGs was higher than previously, and the proportion of CPGs with low-quality decreased over time. However, there were still too few CPGs that reached a high-quality level. The "applicability" and "rigor of development" domains had generally low scores. CPGs formulated by developing countries or regions, those that are not under an organizations or groups responsibility, and those that used non-evidence-based methods were found to be associated with poorer quality in different domains as independent or combinational factors. CONCLUSIONS: The quality of pediatric CPGs still needs to be improved. Specifically, a quality control before applying new CPGs should be essential to ensure their quality and applicability.

Stem cell landscape aids in tumor microenvironment identification and selection of therapeutic agents in gastric cancer.

Gastric cancer stem cells (GCSCs) are strongly associated with the refractory characteristics of gastric cancer, including drug resistance, recurrence, and metastasis. The prognosis for advanced gastric cancer patients treated with multimodal therapy after surgery remains discouraging. GCSCs hold promise as therapeutic targets for GC patients. We obtained 26 sets of stem cell-related genes from the StemChecker database. The Consensus clustering algorithm was employed to discern three distinct stemness subtypes. Prognostic outcomes, components of the tumor microenvironment (TME), and responses to therapies were compared among these subtypes. Following this, a stemness-risk model was formulated using weighted gene correlation network analysis (WGCNA), alongside Cox regression and random survival forest analyses. The C2 subtype predominantly showed enrichment in negative prognostic CSC gene sets and demonstrated an immunosuppressive TME. This specific subtype exhibited minimal responsiveness to immunotherapies and demonstrated reduced sensitivity to drugs. Four pivotal genes were integrated into the construction of the stemness model. Gastric cancer patients with higher stemness-risk scores demonstrated poorer prognoses, a greater presence of immunosuppressive components in TME, and lower rates of treatment response. Subset analysis indicated that only the low-stemness risk subtype derives benefit from 5-fluorouracil-based adjuvant chemotherapy. The model's effectiveness in immunotherapeutic prediction was further validated in the PRJEB25780 cohort. Our study categorized gastric cancer patients into three stemness subtypes, each demonstrating distinct prognoses, components of TME infiltration, and varying sensitivity or resistance to standard chemotherapy or targeted therapy. We propose that the stemness risk model may help the development of well-grounded treatment recommendations and prognostic assessments.

Sulfotransferase SULT2B1 facilitates colon cancer metastasis by promoting SCD1-mediated lipid metabolism.

Metastasis is responsible for at least 90% of colon cancer (CC)-related deaths. Lipid metabolism is a critical factor in cancer metastasis, yet the underlying mechanism requires further investigation. Herein, through the utilisation of single-cell sequencing and proteomics, we identified sulfotransferase SULT2B1 as a novel metastatic tumour marker of CC, which was associated with poor prognosis. CC orthotopic model and in vitro assays showed that SULT2B1 promoted lipid metabolism and metastasis. Moreover, SULT2B1 directly interacted with SCD1 to facilitate lipid metabolism and promoted metastasis of CC cells. And the combined application of SCD1 inhibitor CAY with SULT2B1- konockout (KO) demonstrated a more robust inhibitory effect on lipid metabolism and metastasis of CC cells in comparison to sole application of SULT2B1-KO. Notably, we revealed that lovastatin can block the SULT2B1-induced promotion of lipid metabolism and distant metastasis in vivo. Further evidence showed that SMC1A transcriptionally upregulated the expression of SULT2B1. Our findings unveiled the critical role of SULT2B1 in CC metastasis and provided a new perspective for the treatment of CC patients with distant metastasis.

The role of FERMT2 in the tumor microenvironment and immunotherapy in pan-cancer using comprehensive single-cell and bulk sequencing.

FERMT2 has been identified as a participant in integrin-linked kinase signaling pathways, influencing epithelial-mesenchymal transition and thereby affecting tumor initiation, progression, and invasion. While the character of FERMT2 in the tumor microenvironment (TME) as well as its implications for immunotherapy remain unclear. Thus, we conducted a comprehensive analysis to assess the prognostic significance of FERMT2 using Kaplan-Meier analysis. In addition, we employed enrichment analysis to uncover potential underlying molecular mechanisms. Using "Immunedeconv" package, we evaluated the immune characteristics of FERMT2 within TME. Furthermore, we determined the expression levels of FERMT2 in various cell types within TME, based on single-cell sequencing data. To confirm the co-expression of FERMT2 and markers of cancer-associated fibroblasts (CAFs), we performed multiplex immunofluorescence staining on tissue paraffin sections across various cancer types. Our analysis disclosed a significant correlation between elevated FERMT2 expression and unfavorable prognosis in specific cancer types. Furthermore, we identified a strong correlation between FERMT2 expression and diverse immune-related factors, including immune checkpoint molecules, immune cell infiltration, microsatellite instability (MSI), and tumor mutational burden (TMB). Additionally, there was a significant correlation between FERMT2 expression and immune-related pathways, particularly those associated with activating, migrating, and promoting the growth of fibroblasts in diverse cancer types. Interestingly, we observed consistent co-expression of FERMT2 in both malignant tumor cells and stromal cells, particularly within CAFs. Notably, our findings also indicated that FERMT2, in particular, exhibited elevated expression levels within tumor tissues and co-expressed with α-SMA in CAFs based on the multiplex immunofluorescence staining results.

The Establishment and Verification of a Nomogram Model for Predicting the Overall Survival of Medullary Thyroid Carcinoma: An Analysis Based on the SEER Database.

(1) Background: This study aimed to establish a nomogram model for predicting the overall survival (OS) of medullary thyroid carcinoma (MTC) patients based on the Surveillance, Epidemiology, and End Results (SEER) database. (2) Methods: Patients with MTC in the SEER database from 2004 to 2015 were included and divided into a modeling group and an internal validation group. We also selected MTC patients from our center from 2007 to 2019 to establish an external validation group. Univariate and multivariate Cox regression analyses were used to screen for significant independent variables and to establish a nomogram model. Kaplan-Meier (K-M) curves were plotted to evaluate the influence of the predictors. The C-indexes, areas under the curves (AUCs), and calibration curves were plotted to validate the predictive effect of the model. (3) Results: A total of 1981 MTC patients from the SEER database and 85 MTC patients from our center were included. The univariate and multivariate Cox regression analyses showed that age, tumor size, N stage, and M stage were significant factors, and a nomogram model was established. The C-index of the modeling group was 0.792, and the AUCs were 0.811, 0.825, and 0.824. The C-index of the internal validation group was 0.793, and the AUCs were 0.847, 0.846, and 0.796. The C-index of the external validation group was 0.871, and the AUCs were 0.911 and 0.827. The calibration curves indicated that the prediction ability was reliable. (4) Conclusions: A nomogram model based on age, tumor size, N stage, and M stage was able to predict the OS of MTC patients.

Investigating the Prognostic Significance of Pyroptosis-Related Genes in Gastric Cancer and Their Impact on Cells' Biological Functions.

Objective: To probe into the role of pyroptosis-related genes in gastric cancer. Methods: To establish pyroptosis-related genes, observe their expression in gastric cancer, and analyze the prognosis of pyroptosis-related genes in gastric cancer by single-factor COX, which showed that only GSDME had prognostic significance in gastric cancer. The mRNA expression profiles and lncRNA expression profiles of gastric cancer downloaded from the Cancer Genome Atlas were combined for weighted gene regulatory network analysis, after which the lncRNA nodes of the module to which GSDME belongs were extracted to obtain the lncRNAs-GSDME interactions, which were visualized with Cytoscape network plots. Finally, the effects of GSDME on the proliferation, migration, and apoptosis of gastric cancer cells were observed with CCK8, and flow cytometry. Results: Our results show that only GSDME has prognostic significance in gastric cancer, and show that it has an important role in a variety of tumors. In addition, our results show that 16 lncRNAs have a significant interaction with GSDME. Finally, the experimental analysis showed that knocking down the expression level of GSDME could affect the growth as well as apoptosis of gastric cancer cells. Conclusion: The significant prognostic significance of GSDME in gastric cancer and the fact that affecting GSDME expression inhibits gastric cancer cell growth suggest that GSDME can be used as a predictive biomarker.

Ciclopirox Olamine Exerts Tumor-Suppressor Effects via Topoisomerase II Alpha in Lung Adenocarcinoma.

BACKGROUND: Globally, lung cancer is one of the most malignant tumors, of which lung adenocarcinoma (LUAD) is the most common subtype, with a particularly poor prognosis. Ciclopirox olamine (CPX) is an antifungal drug and was recently identified as a potential antitumor agent. However, how CPX and its mechanism of action function during LUAD remain unclear. METHODS: The effects of CPX on cell proliferation, cell cycle, reactive oxygen species (ROS) levels, and apoptosis were assessed using the 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyl-2H-tetrazolium bromide (MTT) assay, colony formation, western blotting, flow cytometry assays, and immunohistochemistry. Global gene expression levels were compared between control and CPX-treated LUAD cells. A LUAD xenograft mouse model was used to evaluate the potential in vivo effects of CPX. RESULTS: We observed that CPX displayed strong antitumorigenic properties in LUAD cells, inhibited LUAD proliferation, induced ROS production, caused DNA damage, and activated the ATR-CHK1-P53 pathway. Topoisomerase II alpha (TOP2A) is overexpressed in LUAD and associated with a poor prognosis. By analyzing differentially expressed genes (DEGs), TOP2A was significantly down-regulated in CPX-treated LUAD cells. Furthermore, CPX treatment substantially inhibited in vivo LUAD xenograft growth without toxicity or side effects to the hematological system and internal organs. CONCLUSIONS: Collectively, for the first time, we showed that CPX exerted tumor-suppressor effects in LUAD via TOP2A, suggesting CPX could potentially function as a promising chemotherapeutic for LUAD treatment.

Molecular Classification of Genes Associated with Hypoxic Lipid Metabolism in Pancreatic Cancer.

Abnormal lipid metabolism often occurs under hypoxic microenvironment, which is an important energy supplement for cancer cell proliferation and metastasis. We aimed to explore the lipid metabolism characteristics and gene expression features of pancreatic ductal adenocarcinoma (PDAC) related to hypoxia and identify biomarkers for molecular classification based on hypoxic lipid metabolism that are evaluable for PDAC prognosis and therapy. The multiple datasets were analyzed integratively, including corresponding clinical information of samples. PDAC possesses a distinct metabolic profile and oxygen level compared with normal pancreatic tissues, according to the bioinformatics methods. In addition, a study on untargeted metabolomics using Ultra Performance Liquid Chromatography Tandem Mass Spectrometry(UPLC-MS) revealed lipid metabolites differences affected by oxygen. Analysis of PDAC gene expression profiling in The Cancer Genome Atlas (TCGA) revealed that the sphingolipid process correlates closely with HIF1α. According to the characters of HIF-1 and sphingolipid, samples can be clustered into three subgroups using non-negative matrix factorization clustering. In cluster2, patients had an increased survival time. Relatively high MUC16 mutation arises in cluster2 and may positively influence the cancer survival rates. This study explored the expression pattern of lipid metabolism under hypoxia microenvironment in PDAC. On the basis of metabolic signatures, we identified the prognosis subtypes linking lipid metabolism to hypoxia. The classifications may be conducive to developing personalized treatment programs targeting metabolic profiles.

A Review of ApoE4 Interference Targeting Mitophagy Molecular Pathways for Alzheimer's Disease.

Alzheimer's disease (AD) is one of the major worldwide causes of dementia that is characterized by irreversible decline in learning, memory loss, and behavioral impairments. Mitophagy is selective autophagy through the clearance of aberrant mitochondria, specifically for degradation to maintain energy generation and neuronal and synaptic function in the brain. Accumulating evidence shows that defective mitophagy is believed to be as one of the early and prominent features in AD pathogenesis and has drawn attention in the recent few years. APOE ε4 allele is the greatest genetic determinant for AD and is widely reported to mediate detrimental effects on mitochondria function and mitophagic process. Given the continuity of the physiological process, this review takes the mitochondrial dynamic and mitophagic core events into consideration, which highlights the current knowledge about the molecular alterations from an APOE-genotype perspective, synthesizes ApoE4-associated regulations, and the cross-talk between these signaling, along with the focuses on general autophagic process and several pivotal processes of mitophagy, including mitochondrial dynamic (DRP1, MFN-1), mitophagic induction (PINK1, Parkin). These may shed new light on the link between ApoE4 and AD and provide novel insights for promising mitophagy-targeted therapeutic strategies for AD.

S100A16 induces epithelial-mesenchymal transition in human PDAC cells and is a new therapeutic target for pancreatic cancer treatment that synergizes with gemcitabine.

Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal cancers, with a poor 5-year survival rate of approximately 6%, mostly due to poor treatment response and early progression. The S100 gene family participates in various pathophysiological processes in various malignancies. S100A16 is a member of the S100 family, which is abnormally expressed in PDAC; however, its biological functions and mechanisms of action remain unclear. We analysed the Gene Expression Omnibus (GEO) public database and the gene ChIP data collected in our previous study of human PDAC cell line PANC-1 cocultured with M2 macrophages to identify differentially expressed genes (DEGs). Twenty-three overexpressed genes were identified by screening. Then, the selected genes were analysed using The Cancer Genome Atlas (TCGA) database to assess whether they have significant impact on the overall survival (OS) of PDAC patients. Of the 14 DEGs identified, S100A16 was associated with poor prognosis and was selected for further investigation; the results indicate that S100A16 is positively correlated with epithelial-mesenchymal transition (EMT)-related genes in the TCGA dataset. Subsequent in vitro and in vivo experiments demonstrated that S100A16 induces the EMT to promote the metastasis of human PDAC cells and that the effect is mediated by the enhanced expression of TWIST1 and activation of the STAT3 signalling pathway. The antitumour effect of gemcitabine (GEM) was enhanced in combination with S100A16 downregulation. In conclusion, our findings suggest that S100A16 is a novel potential therapeutic target for human PDAC treatment.

Trends in Incidence and Survival of Patients with Pancreatic Neuroendocrine Neoplasm, 1987-2016.

BACKGROUND: Pancreatic neuroendocrine neoplasm (pNEN), with the lowest 5-year survival rates in neuroendocrine tumors (NETs), exerts great threat to human health. Because large-scale population research aimed at pNEN is rare, we aimed to explore the tendencies and differences of changes in incidences and survival rates of pNEN in each decade from 1987 to 2016 and evaluate the impacts of age, sex, race, socioeconomic status (SES), and grade. METHODS: Data on pNEN cases from 1987 to 2016 were extracted from the Surveillance, Epidemiology, and End Results Program (SEER) database. Kaplan-Meier, Cox proportional hazards regression analyses, and relative survival rates (RSRs) were used to identify risk factors for pNEN. RESULTS: The incidence and survival duration of pNEN increase every decade due to medical developments. The disparities of long-term survival in different age, sex, and grade groups expanded over time while that in race and SES groups narrowed. Older age and higher grade are independent risk factors for poorer survival. Females have lower incidence and longer survival than males. Prognosis of Black patients and poor (medium and high poverty) patients improved. CONCLUSIONS: This study depicted changes in incidence and survival rates of pNEN over the past three decades and evaluated potential risk factors related to pNEN, benefiting future prediction of vulnerable and clinical options.

Expression and clinical significance of PD-L1 and c-Myc in non-small cell lung cancer.

BACKGROUND: It is known that there are insufficient prognostic factors for non-small cell lung cancer (NSCLC). It was reported that PD-L1 was a prognostic factor for NSCLC,and c-Myc regulated the expression of PD-L1. Herein, we investigated c-Myc and PD-L1 expression and their association with overall survival (OS) in NSCLC. METHODS: Formalin-fixed paraffin-embedded specimens were obtained from 128 patients with surgically resected primary NSCLC. Immunohistochemistry was used to assess the expression of PD-L1 and c-Myc in this study. Pearson's Chi squared test or Fisher's exact test was used to analyze the correlation of the expression of PD-L1 and c-Myc with clinicopathologic features. The relationship between OS and the expression of PD-L1 and c-Myc was evaluated by the Kaplan-Meier method and Cox proportional hazards model, respectively. RESULTS: Positive expression of PD-L1 was detected in 59 patients (46.1%). Patients with negative expression of PD-L1 had remarkably longer OS than those with positive expression of PD-L1. The positive expression rate of c-Myc in NSCLC accounted for 58.6% (75/128) and its expression was significantly more frequent in males (p = 0.002) and patients with lymph node metastasis (p = 0.029). PD-L1 expression was positively correlated with c-Myc expression (r = 0.459, p < 0.001). The PD-L1 and c-Myc double-positive group had a worse prognosis than other subgroups (p < 0.05), and the PD-L1 and c-Myc double-negative group had a better OS than other subgroups (p < 0.05). CONCLUSION: Conjoint analysis of the expression of PD-L1 and c-Myc was a better prognostic approach for NSCLC patients.

Trends in incidence and survival in patients with melanoma, 1974-2013.

Melanoma is a rare malignancy that invades the skin and the mucosa. Research has been conducted on melanoma incidence and the survival of patients with melanoma; however, no studies in melanoma incidence and the survival spanning 40 years and based on a large population have thus far been reported. We obtained data on patients with melanoma for each decade from 1974 to 2013 from the Surveillance, Epidemiology, and End Results (SEER) database. Disparities in survival by decade, age group, gender, race, site, and socioeconomic status (SES) within the aforementioned period were analyzed by comparison of Kaplan-Meier curves. We collected data on 133,996 melanoma patients in 18 SEER registry regions for the period 1974-2013. Our study found that the melanoma incidence increased continuously for the total population as well as for most age groups. The survival of patients with melanoma (except mucosal melanoma) also increased. This study showed increases in incidence and survival in melanoma across four decades in a large sample; meanwhile, the survival rates for mucosal melanoma decreased in the latter three decades, suggesting the need to improve melanoma diagnosis, broaden melanoma awareness among health care providers, and initiate the development of more effective treatments than the existing ones.