Mechanistic insights into 125I seed implantation therapy for Cholangiocarcinoma: focus on ROS-Mediated apoptosis and the role of GPX2.

OBJECTIVES: Cholangiocarcinoma (CCA) is a rare tumor with a poor prognosis and poses significant therapeutic challenges. Herein, we investigated the mechanism of efficacy of 125I seed implantation therapy in CCA, focusing on the induction of reactive oxygen species (ROS)-mediated apoptosis and the involvement of glutathione peroxidase 2 (GPX2). MATERIALS AND METHODS: Human cholangiocarcinoma cell lines QBC939 and RBE were purchased for in vitro studies. In vivo studies were performed using a rabbit VX2 CCA model. Apoptosis and proliferation were detected by TUNEL staining and clone formation, respectively. ROS generation was detected by dihydroethidium staining. Histological evaluation was performed by hematoxylin and eosin staining. Protein expression was determined by Western blotting and immunohistochemistry. RESULTS: Our results demonstrate that 125I seeds effectively inhibited tumor growth in the rabbit VX2 tumor model and promoted the apoptosis of CCA cells in vitro in a dose-dependent manner. Molecular analyses indicate a marked increase in reactive oxygen species (ROS) levels following treatment with 125I seeds, suggesting the involvement of ROS-mediated apoptosis in the therapeutic mechanism. Furthermore, the downregulation of glutathione peroxidase 2 (GPX2) was observed, indicating its potential role in modulating ROS-mediated apoptosis in CCA. CONCLUSION: 125I seed implantation therapy exerts therapeutic effects on CCA by inducing ROS-mediated apoptosis. The downregulation of GPX2 may contribute to enhanced ROS accumulation and apoptotic cell death. These findings provide mechanistic insights into the therapeutic potential of 125I seed implantation for CCA and highlight ROS-mediated apoptosis and GPX2 regulation as promising targets for further investigation and therapeutic intervention in this malignancy.

Safety and efficacy of a programmed cell death 1 inhibitor combined with oxaliplatin plus S-1 in patients with Borrmann large type III and IV gastric cancers.

BACKGROUND: Gastric cancer (GC) is the fifth most common and the fourth most lethal malignant tumour in the world. Most patients are already in the advanced stage when they are diagnosed, which also leads to poor overall survival. The effect of postoperative adjuvant chemotherapy for advanced GC is unsatisfactory with a high rate of distant metastasis and local recurrence. AIM: To investigate the safety and efficacy of a programmed cell death 1 (PD-1) inhibitor combined with oxaliplatin and S-1 (SOX) in the treatment of Borrmann large type III and IV GCs. METHODS: A retrospective analysis (IRB-2022-371) was performed on 89 patients with Borrmann large type III and IV GCs who received neoadjuvant therapy (NAT) from January 2020 to December 2021. According to the different neoadjuvant treatment regimens, the patients were divided into the SOX group (61 patients) and the PD-1 + SOX (P-SOX) group (28 patients). RESULTS: The pathological response (tumor regression grade 0/1) in the P-SOX group was significantly higher than that in the SOX group (42.86% vs 18.03%, P = 0.013). The incidence of ypN0 in the P-SOX group was higher than that in the SOX group (39.29% vs 19.67%, P = 0.05). The use of PD-1 inhibitors was an independent factor affecting tumor regression grade. Meanwhile, the use of PD-1 did not increase postoperative complications or the adverse effects of NAT. CONCLUSION: A PD-1 inhibitor combined with SOX could significantly improve the rate of tumour regression during NAT for patients with Borrmann large type III and IV GCs.

Deep learning radio-clinical signatures for predicting neoadjuvant chemotherapy response and prognosis from pretreatment CT images of locally advanced gastric cancer patients.

BACKGROUND: Early noninvasive screening of patients who would benefit from neoadjuvant chemotherapy (NCT) is essential for personalized treatment of locally advanced gastric cancer (LAGC). The aim of this study was to identify radio-clinical signatures from pretreatment oversampled computed tomography (CT) images to predict the response to NCT and prognosis of LAGC patients. METHODS: LAGC patients were retrospectively recruited from six hospitals from January 2008 to December 2021. An SE-ResNet50-based chemotherapy response prediction system was developed from pretreatment CT images preprocessed with an imaging oversampling method (i.e. DeepSMOTE). Then, the deep learning (DL) signature and clinic-based features were fed into the deep learning radio-clinical signature (DLCS). The predictive performance of the model was evaluated based on discrimination, calibration, and clinical usefulness. An additional model was built to predict overall survival (OS) and explore the survival benefit of the proposed DL signature and clinicopathological characteristics. RESULTS: A total of 1060 LAGC patients were recruited from six hospitals; the training cohort (TC) and internal validation cohort (IVC) patients were randomly selected from center I. An external validation cohort (EVC) of 265 patients from five other centers was also included. The DLCS exhibited excellent performance in predicting the response to NCT in the IVC [area under the curve (AUC), 0.86] and EVC (AUC, 0.82), with good calibration in all cohorts ( P >0.05). Moreover, the DLCS model outperformed the clinical model ( P <0.05). Additionally, we found that the DL signature could serve as an independent factor for prognosis [hazard ratio (HR), 0.828, P =0.004]. The concordance index (C-index), integrated area under the time-dependent ROC curve (iAUC), and integrated Brier score (IBS) for the OS model were 0.64, 1.24, and 0.71 in the test set. CONCLUSION: The authors proposed a DLCS model that combined imaging features with clinical risk factors to accurately predict tumor response and identify the risk of OS in LAGC patients prior to NCT, which can then be used to guide personalized treatment plans with the help of computerized tumor-level characterization.

Development of a tongue image-based machine learning tool for the diagnosis of gastric cancer: a prospective multicentre clinical cohort study.

Background: Tongue images (the colour, size and shape of the tongue and the colour, thickness and moisture content of the tongue coating), reflecting the health state of the whole body according to the theory of traditional Chinese medicine (TCM), have been widely used in China for thousands of years. Herein, we investigated the value of tongue images and the tongue coating microbiome in the diagnosis of gastric cancer (GC). Methods: From May 2020 to January 2021, we simultaneously collected tongue images and tongue coating samples from 328 patients with GC (all newly diagnosed with GC) and 304 non-gastric cancer (NGC) participants in China, and 16 S rDNA was used to characterize the microbiome of the tongue coating samples. Then, artificial intelligence (AI) deep learning models were established to evaluate the value of tongue images and the tongue coating microbiome in the diagnosis of GC. Considering that tongue imaging is more convenient and economical as a diagnostic tool, we further conducted a prospective multicentre clinical study from May 2020 to March 2022 in China and recruited 937 patients with GC and 1911 participants with NGC from 10 centres across China to further evaluate the role of tongue images in the diagnosis of GC. Moreover, we verified this approach in another independent external validation cohort that included 294 patients with GC and 521 participants with NGC from 7 centres. This study is registered at ClinicalTrials.gov, NCT01090362. Findings: For the first time, we found that both tongue images and the tongue coating microbiome can be used as tools for the diagnosis of GC, and the area under the curve (AUC) value of the tongue image-based diagnostic model was 0.89. The AUC values of the tongue coating microbiome-based model reached 0.94 using genus data and 0.95 using species data. The results of the prospective multicentre clinical study showed that the AUC values of the three tongue image-based models for GCs reached 0.88-0.92 in the internal verification and 0.83-0.88 in the independent external verification, which were significantly superior to the combination of eight blood biomarkers. Interpretation: Our results suggest that tongue images can be used as a stable method for GC diagnosis and are significantly superior to conventional blood biomarkers. The three kinds of tongue image-based AI deep learning diagnostic models that we developed can be used to adequately distinguish patients with GC from participants with NGC, even early GC and precancerous lesions, such as atrophic gastritis (AG). Funding: The National Key R&D Program of China (2021YFA0910100), Program of Zhejiang Provincial TCM Sci-tech Plan (2018ZY006), Medical Science and Technology Project of Zhejiang Province (2022KY114, WKJ-ZJ-2104), Zhejiang Provincial Research Center for Upper Gastrointestinal Tract Cancer (JBZX-202006), Natural Science Foundation of Zhejiang Province (HDMY22H160008), Science and Technology Projects of Zhejiang Province (2019C03049), National Natural Science Foundation of China (82074245, 81973634, 82204828), and Chinese Postdoctoral Science Foundation (2022M713203).

Prognostic significance of inflammatory and nutritional markers in perioperative period for patients with advanced gastric cancer.

BACKGROUND: It has been reported that inflammatory and nutritional markers are related to prognosis in numerous malignancies. The present study analyzed the significance of these markers' alterations during neoadjuvant chemotherapy in the long-term outcomes in patients with advanced gastric cancer. METHODS: A retrospective review was performed of 437 advanced gastric cancer patients who underwent a neoadjuvant chemotherapy (NACT) regimen followed by surgical treatment. Inflammatory and nutritional markers measured from the blood samples collected from the patients before the first neoadjuvant chemotherapy and after the last neoadjuvant chemotherapy were used for analysis. Statistical analysis, including Mann-Whitney U or chi-square tests, the Kaplan-Meier method and Cox multivariate analysis, were performed to analyze the predictive value of these markers for overall survival outcomes (OS). RESULTS: Most biomarkers, including lymphocyte, leucocyte, neutrophil, monocyte, platelet, LMR, PLR, SII, CRP, CAR, hemoglobulin and albumin levels, changed during NACT (P <  0.05). After separately grouping the patients based on the normal range of hematologic indexes and the change rate (α) of systemic inflammatory and nutritional markers by the cutoff value derived from X-tile (P <  0.05), we found that differentiation, TRG, pre-NACT BMI, pre-NACT platelet counts, post-NACT lymphocyte counts, the change in lymphocyte counts, change in platelet counts and LMR(α), PLR(α), SII(α), and CAR(α) were associated with OS. Multivariate analysis revealed that PLR (α) > - 19% was correlated with a 3.193-fold (95% CI: 2.194-4.649) higher risk of death (P <  0.001) than others. CONCLUSION: NACT could significantly change several inflammatory and nutritional markers in the perioperative period; the platelet counts before NACT, and the change in lymphocytes during NACT truly correlated with long-term outcomes among patients with advanced gastric cancer. The systemic inflammatory marker PLR may be a reliable marker for the prediction of prognosis.

Preoperative chemotherapy combined with para-aortic lymph node dissection has clinical value in the treatment of gastric cancer with para-aortic lymph node metastases.

BACKGROUND: Lymph node metastases often occur in advanced gastric cancer, with some patients presenting with metastases in the para-aortic lymph nodes. There are persistent Controversies about the benefit of para-aortic lymph node dissection (PAND). Our purpose is to probe whether PAND following preoperative chemotherapy had any clinical significance in individuals with PALNs in gastric cancer. MATERIAL AND METHODS: To retrospectively analyze the clinical data of 86 gastric cancer patients (40 in the D2 + PAND group and 46 in the D2 group) who attended the abdominal surgery department of Zhejiang Cancer Hospital between September 1, 2008, and July 30, 2018. RESULTS: In the D2 + PAND group (40 cases), the average number of lymph nodes cleared per case was 4.3 in group 16 (16a2, 16b1), and the postoperative pathology confirmed lymph node positivity in 16 cases, with a metastasis rate of 40%. The median overall survival times were 63 and 34 months for the patients in the D2 + PAND group and D2 group, respectively. The 3-year overall survival (OS) compared to the D2 group (D2 + PAND 69.1% vs. D2 50%, P = 0.012) and a statistically significant difference in 3-year disease-free survival (DFS) (D2 + PAND 69.6% vs. D2 38.3%, P = 0.007). Lymph node dissection extent and recurrence of para-aortic lymph nodes were independent prognostic variables for the patients. The recurrence rate was reduced in the D2 + PAND group compared to the D2 group (D2 + PAND 7.5% vs. D2 26.1%, p = 0.023). CONCLUSIONS: For patients with gastric cancer whose imaging suggests metastasis in the para-aortic lymph nodes, preoperative chemotherapy combined with PAND is an effective and safe treatment that may benefit patient survival.

High HDAC5 expression correlates with a poor prognosis and the tumor immune microenvironment in gastric cancer.

Background: Gastric cancer (GC) is one of the most common malignant tumors worldwide and has a poor prognosis. Previous studies have confirmed differential histone deacetylase 5 (HDAC5) expression in various common tumors. HDAC5 is also associated with prognosis and plays a role in cancer cell proliferation, invasion, and metastasis, as well as the tumor immune microenvironment (TIME). However, HDAC5 in GC is not well understood. The aims of study were to investigate the HDAC5 expression correlates with prognosis and the TIME in GC. Methods: A total of 355 tumor tissues and 300 matched paracancerous tissues were collected from GC patients who underwent radical surgery. The correlation between clinicopathological characteristics, immune-related factors and HDAC5 expression were analyzed. Univariate and multivariate Cox regression analyses were used to confirm the independent factors affecting the prognosis of GC. Survival curves were plotted using the Kaplan-Meier method. Furthermore, the stomach adenocarcinoma (STAD) dataset was downloaded from The Cancer Genome Atlas (TCGA). The expression levels of HDAC5 were defined as high or low using the gene set variance analysis (GSVA) package. Identification of differential immune infiltrating cells was performed by single sample gene set enrichment analysis (ssGSEA). Results: The positive expression rate of HDAC5 was higher in tumor tissues than in paracancerous tissues (38.87% vs. 14.67%, P<0.001). Univariate and multivariate Cox analyses showed that HDAC5 was an independent factor affecting the prognosis of GC. The HDAC5 expression levels were correlated with age (P=0.046), smoking history (P=0.001), Lauren type (P=0.042), and pM stage (P=0.012). Furthermore, these levels were correlated with CD3+ T cells (P<0.001), CD4+ T cells (P<0.001), CD8+ T cells (P<0.001) and PD-L1 (P=0.001). Further analysis of patients in TCGA cohort confirmed the association between HDAC5 and activated CD4 T cells, activated CD8 T cells, and other immune infiltrating cells. Conclusions: HDAC5 is highly expressed in tumor tissues and is an independent factor affecting the prognosis of GC. Additionally, HDAC5 can regulate the TIME of GC and is a potential target for immunotherapy.

High CHAF1A Expression Levels Are Positively-Correlated with PD-L1 Expression and Indicate Poor Prognosis in Gastric Cancer.

Objective: The aim of this study was to analyze the association between the expression of chromatin assembly factor 1 subunit A (CHAF1A) in gastric cancer (GC) and clinicopathological features, disease prognosis, and expression of programmed cell death-ligand 1 (PD-L1). Material and Methods. A total of 140 GC tissue specimens were collected between January 2013 and December 2017. CHAF1A expression in GC and paracancerous tissues was determined. Then, the associations between CHAF1A expression level in the collected tissues and clinicopathological features as well as PD-L1 expression level were investigated. Cox regression analyses were carried out to determine whether CHAF1A is an independent prognostic factor for GC. Finally, the association between CHAF1A expression levels and survival of the GC patients was investigated. Results: A significantly higher level of CHAF1A expression in GC tissues was found compared to that in paracancerous tissues (p=0.042). CHAF1A expression level in GC tissues was found to be strongly associated with family history (p=0.005), smoking history (p=0.016), T stage (p=0.001), tumor marker AFP (p=0.017), tumor marker CEA (p=0.027), and PD-L1 expression (p=0.029). CHAF1A expression was also found to be positively correlated to PD-L1 expression (p=0.012). Moreover, high CHAF1A expression levels were found to lead to poor prognosis (p=0.019). Univariate and multivariate analyses all showed that CHAF1A was an independent poorer prognostic factor for gastric cancer (p=0.021, HR = 1.175, 95% CI: 1.090-2.890 for univariate analyses; p=0.014, HR = 2.191, 95% CI:1.170-4.105 for multivariate analyses). A high level of CHAF1A expression was thus found to be an independent risk factor for GC prognosis. Conclusion: High CHAF1A expression is associated with poor GC prognosis and positively correlated to PD-L1 expression. Thus, CHAF1A expression level may be used as a novel biomarker for GC diagnosis.

SFRP4 Is a Potential Biomarker for the Prognosis and Immunotherapy for Gastric Cancer.

Purpose: Secreted frizzled-related protein 4 (SFRP4) is a member of the SFRP family, which functions as either a tumor suppressor or a prooncogenic factor in distinct tumor types. Our research aimed to explore the expression of SFRP4 in gastric cancer, its prognostic significance, and its relationship with immune cell infiltration. Materials and Methods: Gastric cancer and paracancerous tissue specimens from surgically resected gastric cancer patients were collected to construct tissue microarrays, and immunohistochemistry was used to detect the expression of SFRP4, PD-L1, CD3+ T, CD4+ T, and CD8+ T in these microarrays. The differential expression of SFRP4 and its relationship with the immune microenvironment were evaluated using the TIMER and TISIDB databases. Finally, patient survival was assessed. Results: SFRP4 expression was elevated in gastric cancer tissues and linked to a poor prognosis (P=0.021). The 5-year survival rate for patients with high SFRP4 expression was only 39.81% but reached 60.02% for patients with low SFRP4 expression. Increased SFRP4 expression correlated with high CD8+ T-cell infiltration (P=0.015) and positive PD-L1 expression (P=0.036). High SFRP4 expression was an independent predictor of overall survival (P=0.024 in univariable analysis, P=0.011 in multivariable analysis). Using online databases, we found that SFRP4 expression was higher in gastric cancer tissues and substantially was associated with the immune microenvironment. Conclusion: SFRP4 is an oncogenic driver that can predict patient survival time in gastric cancer, as well as an important immune-related factor. SFRP4 may be important for guiding immunotherapy in gastric cancer patients.

Prognostic value and clinicopathological correlation of the tumor regression grade in neoadjuvant chemotherapy for gastric adenocarcinoma: a retrospective cohort study.

Background: Neoadjuvant chemotherapy (NACT) and radical gastrectomy are the gold standard treatments for resectable advanced gastric cancer (GC). However, the prognostic value of the pathological tumor regression grade (TRG) of NACT remains controversial. This retrospective study aimed to investigate the correlation between the TRG after NACT and clinicopathological features as well as its prognostic value in advanced GC. Methods: In total, 551 patients with GC who received NACT combined with surgical resection at the Zhejiang Cancer Hospital from April 2004 to December 2019 were included. The demographic characteristics, treatment response, tumor characteristics, treatment regimens, and survival data were reviewed from the medical records of all patients. The Chi-square test was used to analyze the correlation between TRG and clinicopathological factors. Kaplan-Meier univariate analysis and Cox regression multivariate analysis were used to determine the independent risk factors affecting the prognosis of GC patients. Results: Among the 551 patients with advanced GC who accepted NACT treatment, 14 were determined to be in TRG 0, 98 in TRG 1, 257 in TRG 2, and 182 in TRG 3. Also, TRG was significantly correlated with the cT stage (P=0.015), ypT stage (P<0.001), ypN stage (P<0.001), ypTNM stage (P<0.001), vascular tumor thrombus (P<0.001), Borrmann classification (P=0.042), and lymph node ratio (LNR) (P<0.001). Furthermore, patients who had a good pathological response to NACT had a better prognosis, with a 3-year overall survival (OS) of 70.9% versus 48.8% in patients who had a poor pathological response. We also found that TRG (P=0.042, HR =1.65) was an independent prognostic factor affecting the OS of GC patients. Conclusions: TRG plays a significant role in the prognostic value in neoadjuvant chemotherapy for gastric adenocarcinoma. Patients with higher cT stage, higher levels of pre-CA199 and pre-CA125 may have worse pathological response.

CD3D Is an Independent Prognostic Factor and Correlates With Immune Infiltration in Gastric Cancer.

The protein encoded by CD3D is part of the T-cell receptor/CD3 complex (TCR/CD3 complex) and is involved in T-cell development and signal transduction. Previous studies have shown that CD3D is associated with prognosis and treatment response in breast, colorectal, and liver cancer. However, the expression and clinical significance of CD3D in gastric cancer are not clear. In this study, we collected 488 gastric cancer tissues and 430 paired adjacent tissues to perform tissue microarrays (TMAs). Then, immunohistochemical staining of CD3D, CD3, CD4, CD8 and PD-L1 was conducted to investigate the expression of CD3D in gastric cancer and the correlation between the expression of CD3D and tumor infiltrating lymphocytes (TILs) and PD-L1. The results showed that CD3D was highly expressed in gastric cancer tissues compared with paracancerous tissues (P<0.000). Univariate and multivariate analyses showed that CD3D was an independent good prognostic factor for gastric cancer (P=0.004, HR=0.677, 95%CI: 0.510-0.898 for univariate analyses; P=0.046, HR=0.687, 95%CI: 0.474-0.994 for multivariate analyses). In addition, CD3D was negatively correlated with the tumor location, Borrmann type and distant metastasis (P=0.012 for tumor location; P=0.007 for Borrmann type; P=0.027 for distant metastasis). In addition, the expression of CD3D was highly positively correlated with the expression of CD3, CD4, CD8, and PD-L1, and the combination of CD3D with CD3, CD4, CD8 and PD-L1 predicted the best prognosis (P=0.043). In summary, CD3D may play an important regulatory role in the tumor immune microenvironment of gastric cancer and may serve as a potential indicator of prognosis and immunotherapy response.

Prognostic significance of serum tumor marker normalization in the perioperative period for patients with advanced gastric cancer.

Background: Neoadjuvant chemotherapy (NCT) was developed to improve the prognosis of patients with advanced gastric cancer (AGC). Some studies have confirmed the diagnostic and prognostic value of various serum tumor markers in gastric cancer. However, most of these studies were focused on the value of preoperative and postoperative tumor markers in patients undergoing surgery with or without adjuvant therapy, and only a few studies focused on AGC patients undergoing NCT. Methods: We retrospectively analyzed the data of consecutive patients with histologically confirmed AGC who received NCT prior to surgical resection at Zhejiang Cancer Hospital from January 2010 to September 2018. The prognostic impact of tumor markers before and after NCT, including Carcinoembryonic antigen (CEA), Carbohydrate antigen199 (CA199), Carbohydrate antigen125 (CA125), Alpha-FetoProtein (AFP), Carbohydrate antigen242 (CA242), and Carbohydrate antigen724 (CA724), were evaluated using Kaplan-Meier log-rank survival analysis. The association between tumor marker normalization during preoperative chemotherapy and clinicopathological characteristics was also investigated. Results: Four hundred and seventy-two patients were included in the study. The levels of CEA, CA199, CA125, CA242, and CA724 before NCT could predict prognosis, and the levels of CA199, CA125, CA242, and CA724 after NCT were correlated with prognosis. The overall survival (OS) rate decreased with an increasing number of positive tumor markers before and after preoperative chemotherapy. Tumor marker abnormalization after NCT was not related to chemotherapy, whereas patients with tumor marker normalization after NCT obtained survival benefits. Conclusions: Tumor markers before and after NCT, such as CA199, CA125, CA242, and CA724, have a discriminatory ability for patients with GC. The normalization of tumor markers after NCT was associated with better survival.