BPTF Drives Gastric Cancer Resistance to EGFR Inhibitor by Epigenetically Regulating the C-MYC/PLCG1/Perk Axis.

Erlotinib, an EGFR tyrosine kinase inhibitor, is used for treating patients with cancer exhibiting EGFR overexpression or mutation. However, the response rate of erlotinib is low among patients with gastric cancer (GC). The findings of this study illustrated that the overexpression of bromodomain PHD finger transcription factor (BPTF) is partially responsible for erlotinib resistance in GC, and the combination of the BPTF inhibitor AU-1 with erlotinib synergistically inhibited tumor growth both in vivo and in vitro. AU-1 inhibited the epigenetic function of BPTF and decreased the transcriptional activity of c-MYC on PLCG1 by attenuating chromosome accessibility of the PLCG1 promoter region, thus decreasing the expression of p-PLCG1 and p-Erk and eventually improving the sensitivity of GC cells to erlotinib. In patient-derived xenograft (PDX) models, AU-1 monotherapy exhibited remarkable tumor-inhibiting activity and is synergistic anti-tumor effects when combined with erlotinib. Altogether, the findings illustrate that BPTF affects the responsiveness of GC to erlotinib by epigenetically regulating the c-MYC/PLCG1/pErk axis, and the combination of BPTF inhibitors and erlotinib is a viable therapeutic approach for GC.

A quick and reliable image-based AI algorithm for evaluating cellular senescence of gastric organoids.

OBJECTIVE: Organoids are a powerful tool with broad application prospects in biomedicine. Notably, they provide alternatives to animal models for testing potential drugs before clinical trials. However, the number of passages for which organoids maintain cellular vitality ex vivo remains unclear. METHODS: Herein, we constructed 55 gastric organoids from 35 individuals, serially passaged the organoids, and captured microscopic images for phenotypic evaluation. Senescence-associated ß-galactosidase (SA-ß-Gal), cell diameter in suspension, and gene expression reflecting cell cycle regulation were examined. The YOLOv3 object detection algorithm integrated with a convolutional block attention module (CBAM) was used to evaluate organoid vitality. RESULTS: SA-ß-Gal staining intensity; single-cell diameter; and expression of p15, p16, p21, CCNA2, CCNE2, and LMNB1 reflected the progression of aging in organoids during passaging. The CBAM-YOLOv3 algorithm precisely evaluated aging organoids on the basis of organoid average diameter, organoid number, and number × diameter, and the findings positively correlated with SA-ß-Gal staining and single-cell diameter. Organoids derived from normal gastric mucosa had limited passaging ability (passages 1-5), before aging, whereas tumor organoids showed unlimited passaging potential for more than 45 passages (511 days) without showing clear senescence. CONCLUSIONS: Given the lack of indicators for evaluating organoid growth status, we established a reliable approach for integrated analysis of phenotypic parameters that uses an artificial intelligence algorithm to indicate organoid vitality. This method enables precise evaluation of organoid status in biomedical studies and monitoring of living biobanks.

Recent progress in targeting the sialylated glycan-SIGLEC axis in cancer immunotherapy.

Malignant tumors are complex structures composed of cancer cells and tumor microenvironmental cells. In this complex structure, cells cross-talk and interact, thus jointly promoting cancer development and metastasis. Recently, immunoregulatory molecule-based cancer immunotherapy has greatly improved treatment efficacy for solid cancers, thus enabling some patients to achieve persistent responses or cure. However, owing to the development of drug-resistance and the low response rate, immunotherapy against the available targets PD-1/PD-L1 or CTLA-4 has limited benefits. Although combination therapies have been proposed to enhance the response rate, severe adverse effects are observed. Thus, alternative immune checkpoints must be identified. The SIGLECs are a family of immunoregulatory receptors (known as glyco-immune checkpoints) discovered in recent years. This review systematically describes the molecular characteristics of the SIGLECs, and discusses recent progress in areas including synthetic ligands, monoclonal antibody inhibitors, and Chimeric antigen receptor T (CAR-T) cells, with a focus on available strategies for blocking the sialylated glycan-SIGLEC axis. Targeting glyco-immune checkpoints can expand the scope of immune checkpoints and provide multiple options for new drug development.

Patient-derived organoids in translational oncology and drug screening.

Patient-derived organoids (PDO) are a new biomedical research model that can reconstruct phenotypic and genetic characteristics of the original tissue and are useful for research on pathogenesis and drug screening. To introduce the progression in this field, we review the key factors of constructing organoids derived from epithelial tissues and cancers, covering culture medium and matrix, morphological characteristics, genetic profiles, high-throughput drug screening, and application potential. We also discuss the co-culture system of cancer organoids with tumor microenvironment (TME) associated cells. The co-culture system is widely used in evaluating crosstalk of cancer cells with TME components, such as fibroblasts, endothelial cells, immune cells, and microorganisms. The article provides a prospective for standardized cultivation mode, automatic morphological evaluation, and drug sensitivity screening using high-throughput methods.

Study of Flow Stress Models and Ductile Fracture Criteria for CHN327 Nickel-Based Superalloy.

The plastic deformation behavior of a CHN327 nickel-based superalloy under temperatures ranging from 600 °C to 700 °C and strain rates ranging from 0.001 to 0.1 s-1 was investigated using uniaxial high-temperature tensile tests. The stress-strain curves obtained by the tests showed that the maximum stress decreased as the temperature increased, while it increased as the strain rate increased. Based on the extensive data obtained in the experiment, three constitutive models (Hollomon, Swift, and the modified Voce equation) were employed to predict the constitutive relation. It was found that the modified Voce equation had the highest correlation coefficient and the best prediction accuracy. Thereafter, in order to predict the fracture of CHN327 during high-temperature tensile deformation, five ductile fracture criteria (Freudenthal, C&L, Brozzo, Ayada, and the R&T model), and the modified Voce equation obtained were incorporated into the finite element software (DEFORM). According to the results, except for the C&L and Brozzo models, all of the other ductile fracture criteria (DFCs) were suitable for predicting the damage distribution of the CHN327 alloy in tensile tests. For all of the DFCs considered, the R&T model provided the most accurate predictions, whose mean error was only 8.9%, far less than the values that other models predicted.

Benchmark for establishment of organoids from gastrointestinal epithelium and cancer based on available consumables and reagents.

Gastrointestinal cancers are a public health problem that threatens the lives of human being. A good experimental model is a powerful tool to promote the uncovering pathogenesis and establish novel treatment methods. High-quality biomedical research requires experimental models to recapitulate the physiological and pathological states of their parental tissues as much as possible. Organoids are such experimental models. Organoids refer to small organ-like cellular clusters formed by the expansion and passaging of living tissues in 3D culture medium in vitro. Organoids are highly similar to the original tissues in terms of cellular composition, cell functions, and genomic profiling. Organoids have many advantages, such as short preparation cycles, long-term storage based on cryopreservation, and reusability. In recent years, researchers carried out the establishment of organoids from gastrointestinal mucosa and cancer tissues, and accumulated valuable experiences. In order to promote effective usage and further development of organoid-related technologies in the research of gastrointestinal diseases, this study proposes a benchmark based on utilization of available experimental consumables and reagents, which are involved in the key steps such as collection and pretreatment of biospecimen, organoid construction, organoid cryopreservation and recovery, growth status evaluation, and organoid quality control. We believe that the standard for the construction and preservation of organoids derived from human gastrointestinal epithelium and cancer tissues can provide an important reference for the majority of scientific researchers.

Pangenomic analysis of Chinese gastric cancer.

Pangenomic study might improve the completeness of human reference genome (GRCh38) and promote precision medicine. Here, we use an automated pipeline of human pangenomic analysis to build gastric cancer pan-genome for 185 paired deep sequencing data (370 samples), and characterize the gene presence-absence variations (PAVs) at whole genome level. Genes ACOT1, GSTM1, SIGLEC14 and UGT2B17 are identified as highly absent genes in gastric cancer population. A set of genes from unaligned sequences with GRCh38 are predicted. We successfully locate one of predicted genes GC0643 on chromosome 9q34.2. Overexpression of GC0643 significantly inhibits cell growth, cell migration and invasion, cell cycle progression, and induces cell apoptosis in cancer cells. The tumor suppressor functions can be reversed by shGC0643 knockdown. The GC0643 is approved by NCBI database (GenBank: MW194843.1). Collectively, the robust pan-genome strategy provides a deeper understanding of the gene PAVs in the human cancer genome.

Multi-target combinatory strategy to overcome tumor immune escape.

Immune therapy has become the fourth approach after surgery, chemotherapy, and radiotherapy in cancer treatment. Many immune checkpoints were identified in the last decade since ipilimumab, which is the first immune checkpoint inhibitor to cytotoxic T-lymphocyte associated protein 4, had been approved by the US Food and Drug Administration (FDA) for the treatment of unresectable or metastatic melanoma in 2011. The use of several antibody drugs that target PD1/PD-L1 for various cancer treatments has been approved by the FDA. However, fewer people are benefitting from immune checkpoint inhibitor treatment in solid cancers. Approximately 80% of patients do not respond appropriately because of primary or acquired therapeutic resistance. Along with the characterization of more immune checkpoints, the combinatory treatment of multiimmune checkpoint inhibitors becomes a new option when monotherapy could not receive a good response. In this work, the author focuses on the combination therapy of multiple immune checkpoints (does not include targeted therapy of oncogenes or chemotherapy), introduces the current progression of multiple immune checkpoints and their related inhibitors, and discusses the advantages of combination therapy, as well as the risk of immune-related adverse events.

Tracking cancer lesions on surgical samples of gastric cancer by artificial intelligent algorithms.

To quickly locate cancer lesions, especially suspected metastatic lesions after gastrectomy, AI algorithms of object detection and semantic segmentation were established. A total of 509 macroscopic images from 381 patients were collected. The RFB-SSD object detection algorithm and ResNet50-PSPNet semantic segmentation algorithm were used. Another 57 macroscopic images from 48 patients were collected for prospective verification. We used mAP as the metrics of object detection. The best mAP was 95.90% with an average of 89.89% in the test set. The mAP reached 92.60% in validation set. We used mIoU for evaluation of semantic segmentation. The best mIoU was 80.97% with an average of 79.26% in the test set. In addition, 81 out of 92 (88.04%) gastric specimens were accurately predicted for the cancer lesion located at the serosa by ResNet50-PSPNet semantic segmentation model. The positive rate and accuracy of AI prediction were different based on cancer invasive depth. The metastatic lymph nodes were predicted in 24 cases by semantic segmentation model. Among them, 18 cases were confirmed by pathology. The predictive accuracy was 75.00%. Our well-trained AI algorithms effectively identified the subtle features of gastric cancer in resected specimens that may be missed by naked eyes. Taken together, AI algorithms could assist clinical doctors quickly locating cancer lesions and improve their work efficiency.

Dexamethasone suppresses immune evasion by inducing GR/STAT3 mediated downregulation of PD-L1 and IDO1 pathways.

T cell exhaustion plays critical roles in tumor immune evasion. Novel strategies to suppress immune evasion are in urgent need. We aimed to identify potential compounds to target T cell exhaustion and increase response to immune checkpoint inhibitors (ICIs). Differentially expressed genes (DEGs) were identified between tumors with different immune evasion potential by comparing the transcriptome data. DEGs were then analyzed in the Connectivity Map (CMap) platform to identify potential compounds to increase response to ICIs. Gene set enrichment analysis, LDH release assay, Chromatin immunoprecipitation (ChIP), and Co-IP were performed to explore the potential mechanisms in vitro. Patients derived organoids and humanized xenograft mouse model were utilized to validate the finding ex vivo and in vivo. We identified 25 potential compounds that may play critical roles in regulating tumor immune evasion. We further pinpointed a specific compound, dexamethasone, which shows potent anti-tumor effect in multiple cancer cell lines when cocultured with T cells. Dexamethasone can suppress T cell exhaustion by decreasing the activity of two immune checkpoints simultaneously, including PD-L1 and IDO1. Functional study shows dexamethasone can increase the sensitivity of ICIs in coculture system, 3D organoid model and humanized mouse model. Mechanism study shows dexamethasone mediated transcriptional suppression of PD-L1 and IDO1 depends on the nuclear translocation of GR/STAT3 complex. These findings demonstrate dexamethasone can suppress immune evasion by inducing GR/STAT3 mediated downregulation of PD-L1 and IDO1 pathways.

Glucocorticoids are double-edged sword in the treatment of COVID-19 and cancers.

Glucocorticoids are important steroid hormones. As an outstanding scientific discovery, the scientist who discovered glucocorticoids was awarded the Nobel Prize in Physiology and Medicine in 1950. Cortisone (hydrocortisone) is a natural glucocorticoid, which is secreted with circadian rhythm by the cortical cells of adrenal glands. Physiologically, about 10-20 mg of hydrocortisone are secreted each day for maintaining homeostasis. Since the biological half-life of natural glucocorticoid is short, scientists developed various synthetic glucocorticoids including prednisone, prednisolone, methylprednisolone, triamcinolone, dexamethasone, betamethasone, and so on. These synthetic glucocorticoids are generated by modifying some structures based on the cortisone backbone, leading to extension of their biological half-life with stronger activities. In the face of severe infection, allergy, shock, trauma, pain, and other stresses, the demand for glucocorticoids increases dramatically. It is critical to supplement extra glucocorticoids to protect the biological functions of vital organs. However, the amount and duration of glucocorticoid administration need to be carefully adjusted, because a series of side effects may occur after long-term or high-dose usage of glucocorticoids. This review article will discuss the application of glucocorticoids in the treatment of patients with severe or critical COVID-19 and solid tumors of advanced stage. The controversy of using glucocorticoid in medical community will also be discussed. This review article will help doctors and basic researchers better understand the practical application of glucocorticoids.

Artificial Convolutional Neural Network in Object Detection and Semantic Segmentation for Medical Imaging Analysis.

In the era of digital medicine, a vast number of medical images are produced every day. There is a great demand for intelligent equipment for adjuvant diagnosis to assist medical doctors with different disciplines. With the development of artificial intelligence, the algorithms of convolutional neural network (CNN) progressed rapidly. CNN and its extension algorithms play important roles on medical imaging classification, object detection, and semantic segmentation. While medical imaging classification has been widely reported, the object detection and semantic segmentation of imaging are rarely described. In this review article, we introduce the progression of object detection and semantic segmentation in medical imaging study. We also discuss how to accurately define the location and boundary of diseases.

Artificial Intelligence-Based Multiclass Classification of Benign or Malignant Mucosal Lesions of the Stomach.

Gastric cancer (GC) is one of the leading causes of cancer-related death worldwide. It takes some time from chronic gastritis to develop in GC. Early detection of GC will help patients obtain timely treatment. Understanding disease evolution is crucial for the prevention and treatment of GC. Here, we present a convolutional neural network (CNN)-based system to detect abnormalities in the gastric mucosa. We identified normal mucosa, chronic gastritis, and intestinal-type GC: this is the most common route of gastric carcinogenesis. We integrated digitalizing histopathology of whole-slide images (WSIs), stain normalization, a deep CNN, and a random forest classifier. The staining variability of WSIs was reduced significantly through stain normalization, and saved the cost and time of preparing new slides. Stain normalization improved the effect of the CNN model. The accuracy rate at the patch-level reached 98.4%, and 94.5% for discriminating normal → chronic gastritis → GC. The accuracy rate at the WSIs-level for discriminating normal tissue and cancerous tissue reached 96.0%, which is a state-of-the-art result. Survival analyses indicated that the features extracted from the CNN exerted a significant impact on predicting the survival of cancer patients. Our CNN model disclosed significant potential for adjuvant diagnosis of gastric diseases, especially GC, and usefulness for predicting the prognosis.

Genetic Profiles Affect the Biological Effects of Serine on Gastric Cancer Cells.

A high serine content in body fluid was identified in a portion of patients with gastric cancer, but its biological significance was not clear. Here, we investigated the biological effect of serine on gastric cancer cells. Serine was added into the culture medium of MGC803 and HGC27 cancer cells, and its influence on multiple biological functions, such as cell growth, migration and invasion, and drug resistance was analyzed. We examined the global transcriptomic profiles in these cultured cells with high serine content. Both MGC803 and HGC27 cell lines were originated from male patients, however, their basal gene expression patterns were very different. The finding of cell differentiation-associated genes, ALPI, KRT18, TM4SF1, KRT81, A2M, MT1E, MUC16, BASP1, TUSC3, and PRSS21 in MGC803 cells suggested that this cell line was more poorly differentiated, compared to HGC27 cell line. When the serine concentration was increased to 150mg/ml in medium, the response of these two gastric cancer cell lines was different, particularly on cell growth, cell migration, and invasion and 5-FU resistance. In animal experiment, administration of high concentration of serine promoted cancer cell metastasis to local lymph node. Taken together, we characterized the basal gene expressing profiles of MGC803 and HGC27. The HGC27 cells were more differentiated than MGC803 cells. MGC803 cells were more sensitive to the change of serine content. Our results suggested that the responsiveness of cancer cells to microenvironmental change is associated with their genetic background.

Glucocorticoids improve severe or critical COVID-19 by activating ACE2 and reducing IL-6 levels.

COVID-19 is a public health emergency that has rapidly spread to over 200 countries and regions, and no effective treatment has been established to date. Severe and critical cases have been associated with higher mortality due to acute respiratory distress syndrome (ARDS) and cytokine storm. Based on the novelty and recent emergence of COVID-19, no effective treatment regimen has been identified, thus prompting clinicians to engage in drug repurposing to address the immediate therapeutic need. This study focused on the molecular target angiotensin-converting enzyme 2 (ACE2) of SARS-CoV-2 and screened a group of ACE2 agonists by bioinformatics. Glucocorticoids are a type of ACE2 activator. We verified the efficacy of nine chemicals on regulating ACE2 expression in human GES-1, an upper digestive tract epithelial cell line, and THP-1, a human monocyte cell line, and found that several glucocorticoids imparted activating effects on ACE2 in both cell lines. The drugs triciribine and kinetin riboside activate ACE2 expression or inhibit IL-6 production in macrophages to some extent. In addition, we compared the efficacies of several glucocorticoids. Hydrocortisone showed the strongest effect on ACE2 activation, followed by prednisolone, dexamethasone, and methylprednisolone. We retrospectively analyzed the therapeutic efficacy of nine severe or critical patients from a cohort of 90 COVID-19 cases, who received medium to small doses of glucocorticoids from our integrated medical team in Wuhan. Seven out of nine patients revealed significant improvement in clinical parameters and chest CT images. This study provides experimental and clinical evidence that medium-to-low-dose glucocorticoids may play a protective role in the respiratory and digestive systems by activating ACE2 and suppressing cytokine storm.

Thrombin Induces Secretion of Multiple Cytokines and Expression of Protease-Activated Receptors in Mouse Mast Cell Line.

BACKGROUND: Thrombin could elicit degranulation of mast cells involved in numerous physiologic and pathologic processes; however, the detailed scrutiny of this procedure and further research of possible cell signaling pathways are lacking. METHODS: P815 mouse mast cells were exposed to various concentrations of thrombin for 16 h. Expression of protease-activated receptor (PAR)1, PAR2, PAR3, and PAR4 mRNA in P815 was analyzed by quantitative real-time PCR (qRT-PCR) and the fittest concentration of thrombin was decided. Then, secretions of mediators from P815 stimulated by thrombin 0.2 U/ml were determined using enzyme-linked immunosorbent assay (ELISA) and Luminex liquichip; the possible cell signaling pathways were measured by immunoblotting. Furthermore, inhibition of thrombin inhibitor (hirudin), PAR1 inhibitor (SCH79797), and MAPK inhibitors (SB203580, PD98059, and SP600125) on the mediator section was evaluated by ELISA and Luminex liquichip. RESULTS: Thrombin 0.2 U/ml induced the elevated expression of PAR1, PAR2, PAR3, and PAR4, as well as the increasing level of phospho-IκBα, phospho-SAPK/JNK MAPK, phospho-P38 MAPK (Thr180/Tyr182), and phospho-ERK1/2 MAPK (p44/42) in P815. Secretion of vascular endothelial growth factor (VEGF), tumor necrosis factor-α (TNF-α), interleukin- (IL-) 2, IL-6, chemokine ligand- (CCL-) 2, chemokine (C-X-C motif) ligand- (CXCL-) 1, and CXCL-5 from P815 increased apparently; this effect could be diminished by hirudin, whereas SCH79797 and MAPK inhibitors (SB203580, PD98059, and SP600125) diminish the secretions with weaker effect. CONCLUSION: We found the expression of PAR mRNA in P815, activation of signaling pathways of nuclear factor-kappaB (NF-κB), and mitogen-activated protein kinases (MAPKs) including C-Jun NH2-terminal kinase (JNK), P38, and extracellular signal-regulated kinase 1/2 (ERK1/2), and the release of multiple inflammatory mediators stimulated by thrombin, as well as the inhibition of the inflammatory releases by hirudin, SCH79797, and MAPK inhibitors including SB203580, PD98059, and SP600125.

Expression pattern of CDK12 protein in gastric cancer and its positive correlation with CD8+ cell density and CCL12 expression.

Background: The aims of this study were to investigate the expression pattern of CDK12 protein in gastric cancer, and to analyze the correlations of CDK12 expression between CD8+ cell density and CCL12 expression. Methods: Eighty-six paired tumor and non-tumor samples were collected from patients who underwent radical surgery and had pathological confirmed gastric adenocarcinoma. Immunohistochemistry was used to assess CDK12 expression and CD8+ cell density. Expression of CDK12 and CCL21 mRNA was detected by quantitative reverse transcription-polymerase chain reaction. Results: CDK12 expression in gastric tumor tissues was significantly higher than it in paired non-tumor tissues (P<0.001). High expression of CDK12 was identified in 43 cases (50%), and it was significantly correlated with Lauren's classification (diffuse type) and number of metastatic lymph nodes (≥15). High CDK12 protein level indicated a relative poorer overall survival than patients with CKD12 low expression, while it was not identified as an independent prognostic factor. Median number of CD8+ cells in tumor tissues was 51 (range: 0-292). Number of CD8+ cells was positively correlated with CDK12 expression score in tumor tissues (r=0.243, P=0.024). Positive correlation was also found between CDK12 and CCL21 mRNA expression (r=0.419, P=0.017). Conclusion: High CDK12 expression was detected in gastric cancer which was correlated with malignant phenotypes and worse outcome. Positive correlations of CD8+ cell number and CCL21 mRNA expression with CDK12 level were identified.