CircPDIA3/miR-449a/XBP1 feedback loop curbs pyroptosis by inhibiting palmitoylation of the GSDME-C domain to induce chemoresistance of colorectal cancer.

Although oxaliplatin (OXA) is widely used in the frontline treatment of colorectal cancer (CRC), CRC recurrence is commonly observed due to OXA resistance. OXA resistance is associated with a number of factors, including abnormal regulation of pyroptosis. It is therefore important to elucidate the abnormal regulatory mechanism underlying pyroptosis. Here, we identified that the circular RNA circPDIA3 played an important role in chemoresistance in CRC. CircPDIA3 could induce chemoresistance in CRC by inhibiting pyroptosis both in vitro and in vivo. Mechanistically, RIP, RNA pull-down and co-IP assays revealed that circPDIA3 directly bonded to the GSDME-C domain, subsequently enhanced the autoinhibitory effect of the GSDME-C domain through blocking the GSDME-C domain palmitoylation by ZDHHC3 and ZDHHC17, thereby restraining pyroptosis. Additionally, it was found that the circPDIA3/miR-449a/XBP1 positive feedback loop increased the expression of circPDIA3 to induce chemoresistance. Furthermore, our clinical data and patient-derived tumor xenograft (PDX) models supported the positive association of circPDIA3 with development of chemoresistance in CRC patients. Taken together, our findings demonstrated that circPDIA3 could promote chemoresistance by amplifying the autoinhibitory effect of the GSDME-C domain through inhibition of the GSDME-C domain palmitoylation in CRC. This study provides novel insights into the mechanism of circRNA in regulating pyroptosis and providing a potential therapeutic target for reversing chemoresistance of CRC.

The ratio of serum C-reactive protein level on postoperative day 3 to day 2 is a good marker to predict postoperative complications after laparoscopic radical gastrectomy for gastric cancer.

PURPOSE: Study reported that C-reactive protein (CRP) would peak at 48 h after the initiation of an acute inflammatory response. We proposed that the ratio of CRP level on postoperative day 3 to day 2 (POD3/2 CRP) can be used to early predict major postoperative complications (PCs) for patients who underwent laparoscopic radical gastrectomy. METHODS: Patients were randomized into training cohort and validation cohort at a ratio of 7:3. PCs greater than grade II or more, according to Clavien-Dindo classification, were defined as major PCs. Three predictive models for major PCs based on CRP level were constructed, including POD3/2 CRP, the CRP level on POD3 (POD3 CRP), and the ratio of CRP level on POD3 to POD1 (POD3/1 CRP). The performances of three prediction models were assessed by AUC. Univariate and multivariate logistic regression analyses were performed to identify risk factors of major PCs. RESULTS: 344 patients were included. Major PCs were observed in 57 patients (16.6%). In the training cohort, POD3/2 CRP provided the best diagnostic accuracy with an AUC of 0.929 at an optimal cut-off value of 1.08, and the sensitivity and specificity were 0.902 and 0.880, respectively. In the validation cohort, the corresponding AUC was 0.917. BMI ≥ 25 kg/m2 and POD3/2 CRP > 1 were identified as risk factors for major PCs. CONCLUSION: POD3/2 CRP is a reliable marker to predict major PCs after laparoscopic radical gastrectomy. If CRP is higher on POD3 than on POD2, major PCs are highly likely.

Is Preoperative Fibrinogen Associated with the Survival Prognosis of Gastric Cancer Patients? A Multi-centered, Propensity Score-Matched Retrospective Study.

BACKGROUND: The prognostic significance of preoperative plasma fibrinogen in patients with operable gastric cancer remains under debate. This study aimed to elucidate the prognostic value of fibrinogen in gastric cancer patients underwent gastrectomy. METHODS: A total of 4351 patients with gastric cancer collected from three comprehensive medical centers were retrospectively evaluated. Patients were categorized by minimum P value using X-tile, while the baseline confounders for fibrinogen was balanced through propensity score matching (PSM). The relationships between fibrinogen and other clinicopathologic features were evaluated, and nomogram was constructed to assess its prognostic improvement compared with TNM staging system. RESULTS: Fibrinogen was significantly correlated with macroscopic type, tumor differentiation, tumor size, and T and N stage. The factors, fibrinogen and T stage as well as N stage, were identified to be independent prognostic factors after PSM. Nomogram based on fibrinogen demonstrated a smaller Akaike information criterion (AIC) and a larger concordance index (C-index) than TNM staging system, illustrating that fibrinogen might be able to improve the prognostic accuracy. CONCLUSIONS: Preoperative plasma fibrinogen levels in gastric cancer patients were significantly correlated with tumor progression, which could be regarded as a reliable marker for survival prognostic prediction.

Health Communication Through News Media During the Early Stage of the COVID-19 Outbreak in China: Digital Topic Modeling Approach.

BACKGROUND: In December 2019, a few coronavirus disease (COVID-19) cases were first reported in Wuhan, Hubei, China. Soon after, increasing numbers of cases were detected in other parts of China, eventually leading to a disease outbreak in China. As this dreadful disease spreads rapidly, the mass media has been active in community education on COVID-19 by delivering health information about this novel coronavirus, such as its pathogenesis, spread, prevention, and containment. OBJECTIVE: The aim of this study was to collect media reports on COVID-19 and investigate the patterns of media-directed health communications as well as the role of the media in this ongoing COVID-19 crisis in China. METHODS: We adopted the WiseSearch database to extract related news articles about the coronavirus from major press media between January 1, 2020, and February 20, 2020. We then sorted and analyzed the data using Python software and Python package Jieba. We sought a suitable topic number with evidence of the coherence number. We operated latent Dirichlet allocation topic modeling with a suitable topic number and generated corresponding keywords and topic names. We then divided these topics into different themes by plotting them into a 2D plane via multidimensional scaling. RESULTS: After removing duplications and irrelevant reports, our search identified 7791 relevant news reports. We listed the number of articles published per day. According to the coherence value, we chose 20 as the number of topics and generated the topics' themes and keywords. These topics were categorized into nine main primary themes based on the topic visualization figure. The top three most popular themes were prevention and control procedures, medical treatment and research, and global or local social and economic influences, accounting for 32.57% (n=2538), 16.08% (n=1258), and 11.79% (n=919) of the collected reports, respectively. CONCLUSIONS: Topic modeling of news articles can produce useful information about the significance of mass media for early health communication. Comparing the number of articles for each day and the outbreak development, we noted that mass media news reports in China lagged behind the development of COVID-19. The major themes accounted for around half the content and tended to focus on the larger society rather than on individuals. The COVID-19 crisis has become a worldwide issue, and society has become concerned about donations and support as well as mental health among others. We recommend that future work addresses the mass media's actual impact on readers during the COVID-19 crisis through sentiment analysis of news data.

An Innovative Artificial Intelligence-Based App for the Diagnosis of Gestational Diabetes Mellitus (GDM-AI): Development Study.

BACKGROUND: Gestational diabetes mellitus (GDM) can cause adverse consequences to both mothers and their newborns. However, pregnant women living in low- and middle-income areas or countries often fail to receive early clinical interventions at local medical facilities due to restricted availability of GDM diagnosis. The outstanding performance of artificial intelligence (AI) in disease diagnosis in previous studies demonstrates its promising applications in GDM diagnosis. OBJECTIVE: This study aims to investigate the implementation of a well-performing AI algorithm in GDM diagnosis in a setting, which requires fewer medical equipment and staff and to establish an app based on the AI algorithm. This study also explores possible progress if our app is widely used. METHODS: An AI model that included 9 algorithms was trained on 12,304 pregnant outpatients with their consent who received a test for GDM in the obstetrics and gynecology department of the First Affiliated Hospital of Jinan University, a local hospital in South China, between November 2010 and October 2017. GDM was diagnosed according to American Diabetes Association (ADA) 2011 diagnostic criteria. Age and fasting blood glucose were chosen as critical parameters. For validation, we performed k-fold cross-validation (k=5) for the internal dataset and an external validation dataset that included 1655 cases from the Prince of Wales Hospital, the affiliated teaching hospital of the Chinese University of Hong Kong, a non-local hospital. Accuracy, sensitivity, and other criteria were calculated for each algorithm. RESULTS: The areas under the receiver operating characteristic curve (AUROC) of external validation dataset for support vector machine (SVM), random forest, AdaBoost, k-nearest neighbors (kNN), naive Bayes (NB), decision tree, logistic regression (LR), eXtreme gradient boosting (XGBoost), and gradient boosting decision tree (GBDT) were 0.780, 0.657, 0.736, 0.669, 0.774, 0.614, 0.769, 0.742, and 0.757, respectively. SVM also retained high performance in other criteria. The specificity for SVM retained 100% in the external validation set with an accuracy of 88.7%. CONCLUSIONS: Our prospective and multicenter study is the first clinical study that supports the GDM diagnosis for pregnant women in resource-limited areas, using only fasting blood glucose value, patients' age, and a smartphone connected to the internet. Our study proved that SVM can achieve accurate diagnosis with less operation cost and higher efficacy. Our study (referred to as GDM-AI study, ie, the study of AI-based diagnosis of GDM) also shows our app has a promising future in improving the quality of maternal health for pregnant women, precision medicine, and long-distance medical care. We recommend future work should expand the dataset scope and replicate the process to validate the performance of the AI algorithms.

Oncometabolic surgery: Emergence and legitimacy for investigation.

Studies on morbid obesity have shown remarkable improvement of diabetes in patients who have undergone bariatric operations. It was subsequently shown that these operations induce diabetes remission independent of the resultant weight loss; as a result, surgeons began to investigate whether operations for gastric cancer (GC) could have the same beneficial effect on diabetes as bariatric operations. It was then shown in multiple reports that followed that certain operations for GC were able to improve or even cure type 2 diabetes mellitus (T2DM) in GC patients. This finding gave rise to the concept of "oncometabolic surgery", in which a patient diagnosed with both GC and T2DM undergo a single operation with the purpose of treating both diseases. With the increasing incidence of T2DM, oncometabolic surgery has the potential to improve the quality of life and even extend survival of many GC patients. However, because the GC patient population and the bariatric patient population are wildly different and because different GC operations have different properties, the effect of oncometabolic surgery must be carefully assessed and engineered in order to maximize benefit and avoid harm. This manuscript aims to summarize the findings made so far in the field of oncometabolic surgery and to provide an outlook regarding the possibility of oncometabolic surgery being incorporated into standard clinical practice.

Superiority of Tumor Location-Modified Lauren Classification System for Gastric Cancer: A Multi-Institutional Validation Analysis.

BACKGROUND: The tumor location-modified Lauren classification (mLC) has been proposed recently, but its clinical significance remains under debate. This study aimed to elucidate the clinical relevance of mLC and evaluate its superiority to the Lauren classification (LC) for gastric cancer patients with gastrectomy. METHODS: This study retrospectively evaluated 2764 consecutive gastric cancer patients from three comprehensive medical institutions. The patients were categorized into training, inner-validation, and independent validation sets. The relationships between mLC and other clinicopathologic factors were analyzed, and independent prognostic factors were identified. Survival prognostic discriminatory ability and predictive accuracy were compared between mLC and LC using the concordance index (C-index) and Akaike's information criterion (AIC), and a nomogram based on mLC was constructed to compare its prognostic improvement with the tumor-node metastasis (TNM) staging system. RESULTS: A significant association between mLC and gender, age, histologic type, T stage, N stage, and M stage was found. The findings showed that mLC, not LC, is an independent prognostic factor, with a smaller AIC and a higher C-index than LC. The nomogram based on mLC showed a better predictive ability than TNM alone. CONCLUSIONS: Compared with LC, mLC, which could be considered a more reliable prognostic factor, may improve the prognostic discriminatory ability and predictive accuracy for gastric cancer patients with gastrectomy.

Tumor necrosis and >20 mitoses per 50 high-power fields can distinguish 'very high-risk' and 'highest-risk' within 'high-risk' gastric gastrointestinal stromal tumor.

AIM: We aimed to investigate the optimal criteria for classifying higher risk forms of gastric gastrointestinal stromal tumor (gGIST). MATERIALS & METHODS: A total of 246 high-risk gGIST patients were enrolled. Univariate and multivariate analyses were conducted to determine the association between clinicopathological features and overall survival. Appropriate cut-off values were calculated to identify those at higher risk of gGIST. RESULTS: Multivariate and univariate analyses revealed that tumor necrosis and mitotic counts are independent risk factors for overall survival. The optimal cut-off value of mitotic counts was 20. Patients with both necrosis and >20 mitoses/50 high-power fields were worse than those with either one. CONCLUSION: Tumor necrosis and >20 mitoses/50 high-power fields are independent risk factors for high-risk gGIST. Patients with both risk factors indicate worse prognosis.

GLT8D2 is a prognostic biomarker and regulator of immune cell infiltration in gastric cancer.

Because of the considerable tumor heterogeneity in gastric cancer (GC), only a limited group of patients experiences positive outcomes from immunotherapy. Herein, we aim to develop predictive models related to glycosylation genes to provide a more comprehensive understanding of immunotherapy for GC. RNA sequencing (RNA-seq) data and corresponding clinical outcomes were obtained from GEO and TCGA databases, and glycosylation-related genes were obtained from GlycoGene DataBase. We identified 48 differentially expressed glycosylation-related genes and established a prognostic model (seven prognosis genes including GLT8D2, GALNT6, ST3GAL6, GALNT15, GBGT1, FUT2, GXYLT2) based on these glycosylation-related genes using the results from Cox regression analysis. We found that these glycosylation-related genes revealed a robust correlation with the abundance of Tumor Infiltrating Lymphocytes (TILs), especially the GLT8D2 which is associated with many TILs. Finally, we employed immunohistochemistry and Multiplex Immunohistochemical to discover that GLT8D2 serves as a valuable prognostic biomarker in GC and is closely associated with macrophage-related markers. Collectively, we established a prognostic model based on glycosylation-related genes to provide a more comprehensive understanding of prediction for GC prognosis, and identified that GLT8D2 is closely correlated with adverse prognosis and may underscore its role in regulating immune cell infiltration in GC patients.

The prognostic implications and tumor-promoting functions of CHSY3 in gastric cancer.

Chondroitin sulfate synthase 3 (CHSY3) is an important enzyme that regulates glycosylation, but its role in tumors has not been determined. Here, we showed that high CHSY3 expression promotes proliferation in gastric cancer (GC) cells and is associated with poor prognosis in GC patients. We analyzed the immunohistochemistry data of 150 gastric cancer patients to determine the clinicopathological and survival significance of CHSY3. Immunofluorescence was used to detect the colocalization of CHSY3 with infiltrating immune cells. Additionally, CHSY3 was predominantly found in tumor tissues and showed higher abundance compared to matched adjacent tissues. High CHSY3 expression was associated with more advanced tumor stage, higher recurrence risk and worse survival. Immunohistochemistry and bioinformatic analysis revealed that CHSY3 expression was significantly positively correlated with tumor-associated macrophage (TAM) infiltration. Moreover, after knocking down CHSY3, the proliferation of cells was decreased, and the migration ability was reduced, as shown by scratch, monoclonal and transwell assays. In conclusion, this study revealed that CHSY3 has a tumor-promoting effect on GC, suggesting a novel therapeutic strategy against this disease.

Effect of body mass index and cholesterol-rich apolipoprotein-B-containing lipoproteins on clinical outcome in NSCLC patients treated with immune checkpoint inhibitors-based therapy: A retrospective analysis.

OBJECTIVES: Obesity and hypercholesterolemia are linked to unfavor clinical outcomes. Recent studies declared the paradox that high body mass index (BMI) and serum cholesterol were independently connected to better clinical outcome of immune checkpoint inhibitors (ICIs) monotherapy in non-small cell lung cancer (NSCLC). The aim of the study is to investigate the prognosis of BMI and serum cholesterol in ICIs-based therapy. METHODS: This is a retrospective study of 95 NSCLC patients treated with ICIs-based therapy at the Department of Oncology and Lung Cancer Center of China-Japan Friendship Hospital. Treatment efficacy was assessed using durable clinical benefit (DCB) versus nondurable benefit (NDB), best response (active vs. nonactive), and progression-free survival (PFS). The prognostic value of BMI, LDL-C, and RC was determined by multivariate regression analyses, while controlling for confounding factors including age, gender, diabetes status, smoking history, and statin usage. BMI was considered a confounding factor in the analysis when examining the impact of lipoproteins. RESULTS: In our study, we found that in the whole group, BMI ≥25 kg/m2 was linked to a higher risk of poor therapeutic response (OR = 5.92, 95% CI 1.99-19.51, p.val = 0.002) and shorter progression-free survival (HR = 3.00, 95% CI 1.59-5.68, p.val = 0.001). In addition, low levels of RC were associated with better therapeutic response (OR = 0.12, 95% CI 0.02-0.64, p.val = 0.019), while low levels of serum LDL-C were found to predict longer PFS (HR = 0.40, 95% CI 0.19-0.82, p.val = 0.012). These associations were consistent in advanced NSCLC patients receiving ICIs and chemotherapy. CONCLUSIONS: Our study suggest that BMI ≥25 kg/m2 and elevated levels of apoB-containing lipoproteins, including LDL-C and RC, could potentially serve as useful prognostic markers for predicting poor treatment outcomes in advanced NSCLC patients treated with the combination of chemotherapy and ICIs.

Development and validation of a computed tomography-based radiomics signature to predict "highest-risk" from patients with high-risk gastrointestinal stromal tumor.

Background: Some patients with high-risk gastrointestinal stromal tumor (GIST) experience disease progression after complete resection and adjuvant therapy. It is of great significance to distinguish these patients among those with high-risk GIST. Radiomics has been demonstrated as a promising tool to predict various tumors prognosis. Methods: From January 2006 to December 2018, a total of 100 high-risk GIST patients (training cohort: 60; validation cohort: 40) from Guangdong Provincial People's Hospital with preoperative enhanced computed tomography (CT) images were enrolled. The radiomics features were extracted and a risk score was built using least absolute shrinkage and selection operator-Cox model. The clinicopathological factors were analyzed and a nomogram was established with and without radiomics risk score. The concordance index (C-index), calibration plot, and decision curve analysis (DCA) were used to evaluate the performance of the radiomics nomograms. Results: We selected 11 radiomics features associated with recurrence or metastasis. The risk score was calculated and significantly associated with disease-free survival (DFS) in both the training and validation group. Cox regression analysis showed that Ki67 was an independent risk factor for DFS [P=0.004, hazard ratio 4.615, 95% confidence interval (CI): 1.624-13.114]. The combined radiomics nomogram, which integrated the radiomics risk score and significant clinicopathological factors, showed good performance in predicting DFS, with a C-index of 0.832 (95% CI: 0.761-0.903), which was better than the clinical nomogram (C-index 0.769, 95% CI: 0.679-0.859) in training cohort. The calibration curves and the DCA plot suggested satisfying accuracy and clinical utility of the model. Conclusions: The CT-based radiomics nomogram, combined with the clinicopathological factors and risk score, has good potential to assess the recurrence or metastasis of patients with high-risk GIST.

Comprehensive analysis of a novel subtype of immune microenvironment-derived HPV-infected colorectal cancer.

BACKGROUND: The current study proposed a novel subtype, Human papillomavirus (HPV)-infected colorectal cancer (CRC), to understand the impact of HPV on CRC. METHODS: We assessed the prevalence and clinical implications of HPV in CRC by integrating a single cohort in Guangdong Provincial People's Hospital and public datasets. Differential gene, pathway enrichment, and immune infiltration analysis were conducted to explore the patterns in HPV-infected CRC. Quantitative polymerase chain reaction, cell proliferation, scratch, and flow cytometry assays were employed to validate the impact of HPV on CRC. RESULTS: The study revealed a high prevalence of HPV infection in CRC, with infection rates ranging from 10% to 31%. There was also a significant increase in tumor proliferation in HPV-infected CRC. The study showed increased immune cell infiltration, including T cells, γδ T cells, cytotoxic cells, and plasmacytoid dendritic cells in HPV-infected CRC (P < 0.05). Furthermore, our findings confirmed that HPV infection promoted M1 polarization. Our results demonstrated that low ISM2 expression was associated with a less advanced clinical stage (P < 0.001) and better survival outcomes (P = 0.039). Low ISM2 expression correlated with a strong tumor immune response, potentially contributing to the improved survival observed in HPV-infected CRC. CONCLUSIONS: These findings provided a novel subtype of HPV-infected CRC. The subtype with a better prognosis showed a "hot" tumor immune microenvironment that may be responsive to immunotherapy.

KDM3A Ablation Activates Endogenous Retrovirus Expression to Stimulate Antitumor Immunity in Gastric Cancer.

The success of immunotherapy for cancer treatment is limited by the presence of an immunosuppressive tumor microenvironment (TME); Therefore, identifying novel targets to that can reverse this immunosuppressive TME and enhance immunotherapy efficacy is essential. In this study, enrichment analysis based on publicly available single-cell and bulk RNA sequencing data from gastric cancer patients are conducted, and found that tumor-intrinsic interferon (IFN) plays a central role in TME regulation. The results shows that KDM3A over-expression suppresses the tumor-intrinsic IFN response and inhibits KDM3A, either genomically or pharmacologically, which effectively promotes IFN responses by activating endogenous retroviruses (ERVs). KDM3A ablation reconfigures the dsRNA-MAVS-IFN axis by modulating H3K4me2, enhancing the infiltration and function of CD8 T cells, and simultaneously reducing the presence of regulatory T cells, resulting in a reshaped TME in vivo. In addition, combining anti-PD1 therapy with KDM3A inhibition effectively inhibited tumor growth. In conclusions, this study highlights KDM3A as a potential target for TME remodeling and the enhancement of antitumor immunity in gastric cancer through the regulation of the ERV-MAVS-IFN axis.

Safety and efficacy of restarting immune checkpoint inhibitors in non-small cell lung cancer patients following immune-related adverse events: a systematic review and meta-analysis.

OBJECTIVE: This meta-analysis aims to evaluate the safety and efficacy of restarting immune checkpoint inhibitors (ICIs) in patients with non-small cell lung cancer (NSCLC) after experiencing immune-related adverse events (irAEs). METHODS: A comprehensive search of PubMed, Web of Science, Embase, and the Cochrane Library was conducted to identify studies investigating the safety and efficacy of restarting ICIs in NSCLC patients after irAEs. Outcome measures, including objective response rate (ORR), progression-free survival (PFS), and overall survival (OS) after ICI restarting, were extracted. Meta-analysis was performed using the R meta-package. RESULTS: Four studies involving a total of 326 subjects were included, comprising 137 patients who restarted ICI treatment after irAEs and 189 patients who did not restart ICI treatment. The results revealed that ICI restarting was associated with an increased ORR (OR = 2.36, 95% CI 1.49-3.84), prolonged PFS (HR = 0.60, 95% CI 0.42-0.86), and prolonged OS (HR = 0.65, 95% CI 0.43-0.99) compared to non-restarting. The incidence of irAEs after ICI restarting was 45% (95% CI 0.27-0.63). CONCLUSION: Restarting ICI treatment after discontinuation due to previous irAEs appears to be a reasonable option for NSCLC patients. However, a comprehensive assessment of the potential benefits and risks to individual patients is crucial, and close monitoring of irAEs is warranted.

Comparative single-cell analysis reveals heterogeneous immune landscapes in adenocarcinoma of the esophagogastric junction and gastric adenocarcinoma.

Adenocarcinoma of the esophagogastric junction (AEG) is a type of tumor that arises at the anatomical junction of the esophagus and stomach. Although AEG is commonly classified as a subtype of gastric adenocarcinoma (GAC), the tumor microenvironment (TME) of AEG remains poorly understood. To address this issue, we conducted single-cell RNA sequencing (scRNA-seq) on tumor and adjacent normal tissues from four AEG patients and performed integrated analysis with publicly available GAC single-cell datasets. Our study for the first time comprehensively deciphered the TME landscape of AEG, where heterogeneous AEG malignant cells were identified with diverse biological functions and intrinsic malignant nature. We also depicted transcriptional signatures and T cell receptor (TCR) repertoires for T cell subclusters, revealing enhanced exhaustion and reduced clone expansion along the developmental trajectory of tumor-infiltrating T cells within AEG. Notably, we observed prominent enrichment of tumorigenic cancer-associated fibroblasts (CAFs) in the AEG TME compared to GAC. These CAFs played a critical regulatory role in the intercellular communication network with other cell types in the AEG TME. Furthermore, we identified that the accumulation of CAFs in AEG might be induced by malignant cells through FGF-FGFR axes. Our findings provide a comprehensive depiction of the AEG TME, which underlies potential therapeutic targets for AEG patient treatment.

Clinical characteristics and prognostic outcomes for adenocarcinoma of esophagogastric junction in early-onset patients: a population-based appraisal.

PURPOSE: Malignancies of the upper gastrointestinal tract are rare in early-onset patients outside the hereditary genetic disorders. There are few reports describing adenocarcinoma of the esophagogastric junction (AEG) in extremely early-onset patients aged under 50 years old. The aim of this study was to describe the clinicopathological features and prognosis of adenocarcinoma of esophagogastric junction (AEG) in early-onset patients among three successive periods: 1975-1989 (period 1), 1990-2004 (period 2), and 2005-2017 (period 3). METHODS: Between 1975 and 2017, data were extracted from the Surveillance, Epidemiology, and End Results database, and 18,278 patients with AEG were enrolled. Three age groups of patients were identified: < 50, 50-69, and ≥ 70 years of age. Clinicopathological characteristics and prognostic outcomes were reviewed and compared among three groups over three periods (1975-89, 1990-04, and 2005-2017). Multivariate Cox regression analysis was performed to adjust for covariate effects related to both overall survival (OS) and cancer-specific survival (CSS). RESULTS: Among three age groups, early-onset patients were more likely to present with higher tumor grade, advanced nodal, and distant metastatic disease at diagnosis than other groups (p < 0.01 for both). In comparison to the older group, a higher proportion of patients in the early-onset group received chemotherapy and radiation treatment. After adjusting for covariates, early-onset patients had a better CSS and OS than elderly patients. CONCLUSIONS: Early-onset AEG patients were more likely than other age groups to present with advanced disease upon diagnosis. However, the prognosis of early-onset patients was better than their older counterparts after adjustment for covariates. The dissimilarities in tolerance to treatment among early-onset, middle-aged, and elderly patients could be the reason for this difference.

Minimum number of necessary lymph nodes for the accurate staging of adenocarcinoma of esophagogastric junction.

OBJECTIVE: This study aims to explore the minimum number of lymph nodes (LNs) necessary for assessing the postoperative staging of adenocarcinoma of esophagogastric junction (AEG). METHODS: We extracted the data of patients from the Surveillance Epidemiology and End Results (SEER) database, who were pathologically diagnosed with AEG between 2000 and 2017. We explored the associations between the number of LNs and overall survival (OS) by univariate and multivariate analyses and determined the proper cutoff value of the number of LNs necessary for accurate postoperative staging. RESULTS: Of the patients with AEG in the SEER database, 2668 met our inclusion criteria. The total number of regional LNs dissected was found to be significantly associated with survival in analyses stratified by T stage. Univariate and multivariate regression showed that age, grade, positive LNs, number of LNs examined, and T stage were independently associated with OS. For patients with T1-2 tumors, the 5-year survival rate was 58.7%, and patients with more than 11 LNs examined obtained a greater survival benefit. Among patients with T3-4 tumors, the 5-year survival rates were 28.9% and 39.7% for those with 1-16 LNs examined and for those with more than 17 LNs examined, respectively. CONCLUSION: To accurately determine the pathological stage of patients with AEG, no less than 11 LNs must be resected for patients with stage T1-2 disease, and no less than 16 LNs must be resected for patients with stage T3-4 disease.

Microsatellite instability-related prognostic risk score (MSI-pRS) defines a subset of lung squamous cell carcinoma (LUSC) patients with genomic instability and poor clinical outcome.

Background: Lung squamous cell carcinoma (LUSC) shares less typical onco-drivers and target resistance, but a high overall mutation rate and marked genomic complexity. Mismatch repair (MMR) deficiency leads to microsatellite instability (MSI) and genomic instability. MSI is not an ideal option for prognosis of LUSC, whereas its function deserves exploration. Method: MSI status was classified by MMR proteins using unsupervised clustering in the TCGA-LUSC dataset. The MSI score of each sample was determined by gene set variation analysis. Intersections of the differential expression genes and differential methylation probes were classified into functional modules by weighted gene co-expression network analysis. Least absolute shrinkage and selection operator regression and stepwise gene selection were performed for model downscaling. Results: Compared with the MSI-low (MSI-L) phenotype, MSI-high (MSI-H) displayed higher genomic instability. The MSI score was decreased from MSI-H to normal samples (MSI-H > MSI-L > normal). A total of 843 genes activated by hypomethylation and 430 genes silenced by hypermethylation in MSI-H tumors were classified into six functional modules. CCDC68, LYSMD1, RPS7, and CDK20 were used to construct MSI-related prognostic risk score (MSI-pRS). Low MSI-pRS was a protective prognostic factor in all cohorts (HR = 0.46, 0.47, 0.37; p-value = 7.57e-06, 0.009, 0.021). The model contains tumor stage, age, and MSI-pRS that showed good discrimination and calibration. Decision curve analyses indicated that microsatellite instability-related prognostic risk score added extra value to the prognosis. A low MSI-pRS was negatively correlated with genomic instability. LUSC with low MSI-pRS was associated with increased genomic instability and cold immunophenotype. Conclusion: MSI-pRS is a promising prognostic biomarker in LUSC as the substitute of MSI. Moreover, we first declared that LYSMD1 contributed to genomic instability of LUSC. Our findings provided new insights in the biomarker finder of LUSC.

Traditional Chinese medicine in the era of immune checkpoint inhibitor: theory, development, and future directions.

Immune checkpoint inhibitors (ICIs) have revolutionized cancer management and have been widely applied; however, they still have some limitations in terms of efficacy and toxicity. There are multiple treatment regimens in Traditional Chinese Medicine (TCM) that play active roles in combination with Western medicine in the field of oncology treatment. TCM with ICIs works by regulating the tumor microenvironment and modulating gut microbiota. Through multiple targets and multiple means, TCM enhances the efficacy of ICIs, reverses resistance, and effectively prevents and treats ICI-related adverse events based on basic and clinical studies. However, there have been few conclusions on this topic. This review summarizes the development of TCM in cancer treatment, the mechanisms underlying the combination of TCM and ICIs, existing studies, ongoing trials, and prospects for future development.