Recurrence risk stratification based on Epstein-Barr virus DNA to identify enlarged retropharyngeal lymph nodes of nasopharyngeal carcinoma: A model-histopathologic correlation study.

Background: Accurate assessment of the nature of enlarged retropharyngeal lymph nodes (RLN) of nasopharyngeal carcinoma (NPC) patients after radiotherapy is related to selecting appropriate treatments and avoiding unnecessary therapy. This study aimed to develop a non-invasive and effective model for predicting the recurrence of RLN (RRLN) in NPC. Materials and methods: The data of post-radiotherapy NPC patients (N = 76) with abnormal enlargement of RLN who underwent endonasopharyngeal ultrasound-guided fine-needle aspirations (EPUS-FNA) were examined. They were randomly divided into a discovery (n = 53) and validation (n = 23) cohort. Univariate logistic regression was used to assess the association between variables (magnetic resonance imaging characteristics, EBV DNA) and RRLN. Multiple logistic regression was used to construct a prediction model. The accuracy of the model was assessed by discrimination and calibration, and decision curves were used to assess the clinical reliability of the model for the identification of high risk RLNs for possible recurrence. Results: Abnormal enhancement, minimum axis diameter (MAD) and EBV-DNA were identified as independent risk factors for RRLN and could stratify NPC patients into three risk groups. The probability of RRLN in the low-, medium-, and high-risk groups were 37.5, 82.4, and 100%, respectively. The AUC of the final predictive model was 0.882 (95% CI: 0.782-0.982) in the discovery cohort and 0.926 (95% CI, 0.827-1.000) in the validation cohort, demonstrating good clinical accuracy for predicting the RRLN of NPC patients. The favorable performance of the model was confirmed by the calibration plot and decision curve analysis. Conclusion: The nomogram model constructed in the study could be reliable in predicting the risk of RRLN after radiotherapy for NPC patients.

Standardizing the classification of gastric cancer patients with limited and adequate number of retrieved lymph nodes: an externally validated approach using real-world data.

BACKGROUND: Currently, there is no formal consensus regarding a standard classification for gastric cancer (GC) patients with < 16 retrieved lymph nodes (rLNs). Here, this study aimed to validate a practical lymph node (LN) staging strategy to homogenize the nodal classification of GC cohorts comprising of both < 16 (Limited set) and ≥ 16 (Adequate set) rLNs. METHODS: All patients in this study underwent R0 gastrectomy. The overall survival (OS) difference between the Limited and Adequate set from a large Chinese multicenter dataset was analyzed. Using the 8th American Joint Committee on Cancer (AJCC) pathological nodal classification (pN) for GC as base, a modified nodal classification (N') resembling similar analogy as the 8th AJCC pN classification was developed. The performance of the proposed and 8th AJCC GC subgroups was compared and validated using the Surveillance, Epidemiology, and End Results (SEER) dataset comprising of 10,208 multi-ethnic GC cases. RESULTS: Significant difference in OS between the Limited and Adequate set (corresponding N0-N3a) using the 8th AJCC system was observed but the OS of N0limited vs. N1adequate, N1limited vs. N2adequate, N2limited vs. N3aadequate, and N3alimited vs. N3badequate subgroups was almost similar in the Chinese dataset. Therefore, we formulated an N' classification whereby only the nodal subgroups of the Limited set, except for pT1N0M0 cases as they underwent less extensive surgeries (D1 or D1 + gastrectomy), were re-classified to one higher nodal subgroup, while those of the Adequate set remained unchanged (N'0 = N0adequate + pT1N0M0limited, N'1 = N1adequate + N0limited (excluding pT1N0M0limited), N'2 = N2adequate + N1limited, N'3a = N3aadequate + N2limited, and N'3b = N3badequate + N3alimited). This N' classification demonstrated less heterogeneity in OS between the Limited and Adequate subgroups. Further analyses demonstrated superior statistical performance of the pTN'M system over the 8th AJCC edition and was successfully validated using the SEER dataset. CONCLUSION: The proposed nodal staging strategy was successfully validated in large multi-ethnic GC datasets and represents a practical approach for homogenizing the classification of GC cohorts comprising of patients with < 16 and ≥ 16 rLNs.

Development and Validation of a Computed Tomography-Based Radiomics Signature to Predict Response to Neoadjuvant Chemotherapy for Locally Advanced Gastric Cancer.

Importance: Neoadjuvant therapies have been shown to decrease tumor burden, increase resection rate, and improve the outcomes among patients with locally advanced gastric cancer (GC). However, not all patients are equally responsive; therefore, differentiating potential respondents from nonrespondents is clinically important. Objective: To use pretreatment computed tomography (CT)-pixelated feature-difference extraction techniques to identify diagnostically relevant features that could predict patients' response to neoadjuvant chemotherapy at diagnosis. Design, Setting, and Participants: This multicenter cohort study included patients with locally advanced GC who were treated from January 2010 to July 2017 at 2 hospitals in southern China (training cohort) and 1 hospital in northern China (external validation cohort). Their clinicopathological data, pretreatment CT images, and pathological reports were retrieved and analyzed. Data analysis was conducted from December 2017 to May 2021. Exposures: All patients underwent 2 to 4 cycles of fluorouracil in combination with a platinum-based neoadjuvant chemotherapy regimen. All gastrectomies were performed according to the Japanese Classification of Gastric Carcinoma (14th edition) guidelines. Main Outcomes and Measures: Reliability of clinicopathological and radiomics-based features were assessed with area under receiver operating characteristic curve (AUC) and Mann-Whitney U test. Results: A total of 323 patients (242 [74.9%] men; median [range] age, 58 [24-82] years) were included in the study, with 250 patients (77.4%) in the training cohort and 73 (22.6%) in the validation cohort. The baseline pretreatment characteristics of the training and validation cohorts were well-balanced. The number of respondents in the training and validation cohort was 122 (48.8%) and 40 (54.8%), respectively, and the number of nonrespondents was 128 (51.2%) and 33 (45.2%), respectively. No clinicopathological variables were significantly associated with treatment response. Using radiomics, 20 low-intercorrelated features from a total of 7477 features were used to construct a radiomics signature that demonstrated significant association with treatment response. Good discrimination performance of the radiomics signature for predicting treatment response in the training (AUC, 0.736; 95% CI, 0.675-0.798) and external validation (AUC, 0.679; 95% CI, 0.554-0.803) cohorts was observed. Decision curve analysis confirmed the clinical utility of the radiomics signature. Conclusions and Relevance: In this study, the proposed radiomics signature showed potential as a clinical aid for predicting the response of patients with locally advanced GC before treatment, thereby allowing timely planning for effective treatments for potential nonrespondents.

Real-time artificial intelligence for detection of upper gastrointestinal cancer by endoscopy: a multicentre, case-control, diagnostic study.

BACKGROUND: Upper gastrointestinal cancers (including oesophageal cancer and gastric cancer) are the most common cancers worldwide. Artificial intelligence platforms using deep learning algorithms have made remarkable progress in medical imaging but their application in upper gastrointestinal cancers has been limited. We aimed to develop and validate the Gastrointestinal Artificial Intelligence Diagnostic System (GRAIDS) for the diagnosis of upper gastrointestinal cancers through analysis of imaging data from clinical endoscopies. METHODS: This multicentre, case-control, diagnostic study was done in six hospitals of different tiers (ie, municipal, provincial, and national) in China. The images of consecutive participants, aged 18 years or older, who had not had a previous endoscopy were retrieved from all participating hospitals. All patients with upper gastrointestinal cancer lesions (including oesophageal cancer and gastric cancer) that were histologically proven malignancies were eligible for this study. Only images with standard white light were deemed eligible. The images from Sun Yat-sen University Cancer Center were randomly assigned (8:1:1) to the training and intrinsic verification datasets for developing GRAIDS, and the internal validation dataset for evaluating the performance of GRAIDS. Its diagnostic performance was evaluated using an internal and prospective validation set from Sun Yat-sen University Cancer Center (a national hospital) and additional external validation sets from five primary care hospitals. The performance of GRAIDS was also compared with endoscopists with three degrees of expertise: expert, competent, and trainee. The diagnostic accuracy, sensitivity, specificity, positive predictive value, and negative predictive value of GRAIDS and endoscopists for the identification of cancerous lesions were evaluated by calculating the 95% CIs using the Clopper-Pearson method. FINDINGS: 1 036 496 endoscopy images from 84 424 individuals were used to develop and test GRAIDS. The diagnostic accuracy in identifying upper gastrointestinal cancers was 0·955 (95% CI 0·952-0·957) in the internal validation set, 0·927 (0·925-0·929) in the prospective set, and ranged from 0·915 (0·913-0·917) to 0·977 (0·977-0·978) in the five external validation sets. GRAIDS achieved diagnostic sensitivity similar to that of the expert endoscopist (0·942 [95% CI 0·924-0·957] vs 0·945 [0·927-0·959]; p=0·692) and superior sensitivity compared with competent (0·858 [0·832-0·880], p<0·0001) and trainee (0·722 [0·691-0·752], p<0·0001) endoscopists. The positive predictive value was 0·814 (95% CI 0·788-0·838) for GRAIDS, 0·932 (0·913-0·948) for the expert endoscopist, 0·974 (0·960-0·984) for the competent endoscopist, and 0·824 (0·795-0·850) for the trainee endoscopist. The negative predictive value was 0·978 (95% CI 0·971-0·984) for GRAIDS, 0·980 (0·974-0·985) for the expert endoscopist, 0·951 (0·942-0·959) for the competent endoscopist, and 0·904 (0·893-0·916) for the trainee endoscopist. INTERPRETATION: GRAIDS achieved high diagnostic accuracy in detecting upper gastrointestinal cancers, with sensitivity similar to that of expert endoscopists and was superior to that of non-expert endoscopists. This system could assist community-based hospitals in improving their effectiveness in upper gastrointestinal cancer diagnoses. FUNDING: The National Key R&D Program of China, the Natural Science Foundation of Guangdong Province, the Science and Technology Program of Guangdong, the Science and Technology Program of Guangzhou, and the Fundamental Research Funds for the Central Universities.

A homogenized approach to classify advanced gastric cancer patients with limited and adequate number of pathologically examined lymph nodes.

BACKGROUND: The prognosis of gastric cancer patients with a limited number of pathologically examined lymph nodes (eLN, < 16) is dismal compared to those with adequately eLN (≥ 16), yet they are still classified within the same subgroups using the American Joint Committee on Cancer (AJCC) staging system. We aimed at formulating an easy-to-adopt and clinically reliable stratification approach to homogenize the classification for these two categories of patients. METHODS: Patients staged according to the 8th AJCC pathological nodal (N) and tumor-node-metastasis (TNM) classification were stratified into a Limited and Adequate eLN cohort based on their number of pathologically examined LNs. The statistical differences between the 5-year overall survival (OS) rates of both cohorts were determined and based on which, patients from the Limited eLN cohort were re-classified to a proposed modified nodal (N') and TNM (TN'M) classification, by matching their survival rates with those of the Adequate eLN cohort. The prognostic performance of the N' and TN'M classification was then compared to a formulated lymph-node-ratio-based nodal classification, in addition to the 8th AJCC N and TNM classification. RESULTS: Significant heterogeneous differences in 5-year OS between patients from the Limited and Adequate eLN cohort of the same nodal subgroups were identified (all P < 0.001). However, no significant differences in 5-year OS were observed between the subgroups N0, N1, N2, and N3a of the Limited eLN cohort when compared with N1, N2, N3a, and N3b from the Adequate eLN cohort, respectively (P = 0.853, 0.476, 0.114, and 0.230, respectively). A novel approach was formulated in which only patients from the Limited eLN cohort were re-classified to one higher nodal subgroup, denoted as the N' classification. This re-classification demonstrated superior stratifying and prognostic ability as compared to the 8th AJCC N and lymph-node-ratio classification (Akaike information criterion values [AIC]: 12,276 vs. 12,358 vs. 12,283, respectively). The TN'M classification also demonstrated superior prognostic ability as compared to the 8th AJCC TNM classification (AIC value: 12,252 vs. 12,312). CONCLUSION: The proposed lymph node classification approach provides a clinically practical and reliable technique to homogeneously classify cohorts of gastric cancer patients with limited and adequate number of pathologically examined lymph nodes.

Prevalence of hypertension and prehypertension in Nepal: a systematic review and meta-analysis.

BACKGROUND: Studies regarding blood pressure of Nepal have demonstrated a contrasting prevalence. We aimed at providing a generalized estimate of the prevalence of hypertension and prehypertension in urban, suburban, and rural areas of Nepal. METHODS: This systematic review followed PRISMA guidelines. A thorough search of PubMed, EMBASE, and Web of Science was performed, and studies satisfying the eligibility criteria were reviewed. Pooled prevalence was calculated by random-effects model, and the sources of heterogeneity were explored with meta-regression and subgroup analysis. RESULTS: Twenty-three studies with 99,792 subjects were identified, and the estimated rate of hypertension and prehypertension were found to be 27.3% (95% CI: 23.8-30.9) and 35.4% (30.3-40.8). The prevalence of hypertension was 28.4% (22.4-34.7), 25.5% (21.4-29.8), and 24.4% (17.9-31.6) among urban, suburban, and rural populations, respectively. Moreover, rates of hypertension were found to be substantially higher in male (31.6%, 27.3-36.1) compared to female (20.0%, 14.2-26.6), and significantly higher among the middle-aged (≥40 years; 36.8%, 29.4-44.5) than among younger adults (< 40 years; 13.2%, 9.2-17.7). Further, prehypertension prevalence was found to be highest in rural areas (40.4%, 25.4-56.4) followed by urban areas (29.3%, 20.8-38.5) and lowest in suburban areas (25.5%, 18.9-32.7). CONCLUSIONS: Our study identified an alarming situation of hypertension among Nepalese males and middle-aged, and a situation of concern with prehypertension in rural areas affecting almost 40 % of the population.

Identification of molecular biomarkers for the diagnosis of gastric cancer and lymph-node metastasis.

BACKGROUND AND OBJECTIVE: Biomarkers are important tools for prompt diagnosis of cancer. This study aimed to identify reliable biomarkers for clinical applications in the diagnosis of gastric cancer and lymph-node (LN) metastasis. METHODS: Between 1 December 2014 and 31 December 2015, we prospectively collected samples of gastric-cancer tissues, corresponding matched-pair normal gastric mucosa, and their peri-gastric metastatic and non-metastatic LNs to identify quantitatively reliable genes using quantitative real-time polymerase chain reaction. Relative quantity (RQ) was used to calculate the mRNA expression levels of our target genes. Statistics were calculated using one-way analysis of variance (ANOVA) and Tukey's multiple comparison test. Analytical graphs were plotted using GraphPad Prism. RESULTS: Of nine assessed genes, the mRNA levels of inhibin beta A (INHBA) and secreted phosphoprotein 1 (SPP1) were most consistently highly expressed in tumor tissues by 15.4- and 15.6-fold, respectively, as compared with normal tissues (P < 0.001), with 91.3% sensitivity and 95.7% specificity (receiver operating characteristic [ROC] curve area = 0.974) for the former and 82.6% sensitivity and 87.0% specificity (ROC curve area = 0.924) for the latter. Further analysis revealed no differentiating significance of SPP1 mRNA expression between metastatic and non-metastatic LNs (P = 0.470). In contrast, the INHBA mRNA level was up-regulated 4.1-fold in metastatic LNs (P < 0.001), with 80.0% sensitivity and 81.5% specificity (ROC curve area = 0.857), and was also able to successfully differentiate between more severe disease conditions, T3 and T4 (P = 0.003), M0 and M1 (P = 0.043) and different histological variants (intestinal type vs diffuse type, P = 0.019). CONCLUSIONS: Our results showed that INHBA was the most optimally reliable biomarker for diagnosing gastric cancer and LN metastasis.

Maximum Somatic Allele Frequency in Combination With Blood-Based Tumor Mutational Burden to Predict the Efficacy of Atezolizumab in Advanced Non-small Cell Lung Cancer: A Pooled Analysis of the Randomized POPLAR and OAK Studies.

Background: Blood-based tumor mutational burden (bTMB) was recently found to be suboptimal in predicting overall survival (OS) benefits of atezolizumab over docetaxel among patients with advanced non-small cell lung cancer (NSCLC). The maximum somatic allele frequency (MSAF) is an indicator of the proportion of tumor-derived plasma DNA, which could affect the concordance between bTMB and tissue-based TMB. Therefore, we aimed to evaluate the utility of MSAF, alone or in combination with bTMB, to identify NSCLC patients with or without survival benefit from atezolizumab over docetaxel. Methods: We analyzed the individual patient-level data from the randomized POPLAR and OAK studies. The bTMB and MSAF were derived from the pre-treatment blood-based genomic data. Results: In both the bTMB-high (i.e., bTMB ≥ 13) and bTMB-low subgroups, atezolizumab significantly improved OS compared with docetaxel (hazard ratio [HR] = 0.43 [95% CI, 0.29-0.65], P < 0.001 and HR = 0.73 [95% CI, 0.61-0.87], P < 0.001, respectively). Among patients with a low MSAF (i.e., MSAF < 10.3%), OS significantly favored atezolizumab (HR = 0.59 [95% CI, 0.48-0.72], P < 0.001), whereas OS with atezolizumab was similar to that with docetaxel in the MSAF-high subgroup (HR = 0.91 [95% CI, 0.68-1.20], P = 0.500; interaction test P = 0.017). Among patients from the bTMB-low and MSAF-high subgroup, OS was numerically worse with atezolizumab than with docetaxel (HR = 1.06 [95% CI, 0.78-1.45], P = 0.710); in contrast, OS was significantly improved with atezolizumab compared with docetaxel in those with either a high bTMB or low MSAF (HR = 0.57 [95% CI, 0.47-0.69], P < 0.001; interaction test P < 0.001). Consistent findings were obtained for progression-free survival data. Conclusions: MSAF alone or in combination with bTMB can effectively distinguish patients with or without survival benefit from atezolizumab compared with docetaxel. MSAF and the combined bTMB-MSAF classification may become practical predictive markers for atezolizumab in advanced NSCLC.

Proposal and validation of a modified staging system to improve the prognosis predictive performance of the 8th AJCC/UICC pTNM staging system for gastric adenocarcinoma: a multicenter study with external validation.

BACKGROUND: The 8th edition of the American Joint Committee on Cancer/Union for International Cancer Control (AJCC/UICC) pathological tumor-node-metastasis (pTNM) staging system may have increased accuracy in predicting prognosis of gastric cancer due to its important modifications from previous editions. However, the homogeneity in prognosis within each subgroup classified according to the 8th edition may still exist. This study aimed to compare and analyze the prognosis prediction abilities of the 8th and 7th editions of AJCC/UICC pTNM staging system for gastric cancer and propose a modified pTNM staging system with external validation. METHODS: In total, clinical data of 7911 patients from three high-capacity institutions in China and 10,208 cases from the Surveillance, Epidemiology, and End Results (SEER) Program Registry were analyzed. The homogeneity, discriminatory ability, and monotonicity of the gradient assessments of the 8th and 7th editions of AJCC/UICC pTNM staging system were compared using log-rank χ2, linear-trend χ2, likelihood-ratio χ2 statistics and Akaike information criterion (AIC) calculations, on which a modified pTNM classification with external validation using the SEER database was proposed. RESULTS: Considerable stage migration, mainly for stage III, between the 8th and 7th editions was observed in both cohorts. The survival rates of subgroups of patients within stage IIIA, IIIB, or IIIC classified according to both editions were significantly different, demonstrating poor homogeneity for patient stratification. A modified pTNM staging system using data from the Chinese cohort was then formulated and demonstrated an improved homogeneity in these abovementioned subgroups. This staging system was further validated using data from the SEER cohort, and similar promising results were obtained. Compared with the 8th and 7th editions, the modified pTNM staging system displayed the highest log-rank χ2, linear-trend χ2, likelihood-ratio χ2, and lowest AIC values, indicating its superior discriminatory ability, monotonicity, homogeneity and prognosis prediction ability in both populations. CONCLUSIONS: The 8th edition of AJCC/UICC pTNM staging system is superior to the 7th edition, but still results in homogeneity in prognosis prediction. Our modified pTNM staging system demonstrated the optimal stratification and prognosis prediction ability in two large cohorts of different gastric cancer populations.

Functions of the AP-2α gene in activating apoptosis and inhibiting proliferation of gastric cancer cells both in vitro and in vivo.

INTRODUCTION: This study was designed to investigate the potential function of the activating protein 2α (AP-2α) gene in controlling the proliferation and apoptosis of gastric cancer. MATERIAL AND METHODS: Gastric cancer cell line MCG-803 cells and normal cell line GES-1 cells were selected to transfect pcDNA3.1(+)-AP-2α and pcDNA3.1(+) plasmids, respectively. Both mRNA and protein levels of AP-2α in each group transfected with the pcDNA3.1(+)-AP-2α plasmids were up-regulated after 48 h by real-time PCR and Western blotting analysis, leading to marked proliferation inhibition and significant cell cycle arrest. RESULTS: pcDNA3.1(+)-AP-2α reduced tumor tissue growth in a subcutaneous tumor gastric carcinoma nude mouse model. Protein over-expression of AP-2α in the nude mouse model was accompanied by down-regulation of Blc-2 and ErbB2, resulting in the up-regulation of caspase-3, -8, and -9, ERα and p21WAF1/CIP1. CONCLUSIONS: The reintroduction of the AP-2α gene by pcDNA3.1 could inhibit gastric tumor growth in vitro and in vivo, which may be an alternative future therapeutic molecular target for human gastric cancer.

A comprehensive analysis comparing the eighth AJCC gastric cancer pathological classification to the seventh, sixth, and fifth editions.

To perform a comprehensive analysis comparing the prognostic and discriminative ability of the eighth AJCC gastric cancer (GC) pathological classification to that of the seventh, sixth and fifth editions, and secondly to assess their long-term significance. Patients who had undergone R0 gastrectomy were identified and restaged accordingly. To evaluate and confirm any difference in prognostic ability between the competing editions, the Akaike information criterion (AIC) and Bayesian information criterion (BIC) were computed and compared since both have different analytic strengths. The area under the curve (AUC) with 95% CI based on the time-dependent receiver-operating characteristics analyses were also calculated to assess any change in prognostic rankings from the first to tenth postoperative year. The rankings calculated by both statistical methods showed similar results, in which the seventh edition was identified as possessing the best prognostic ability. Additionally, these ranks were found to remain consistent over the ten postoperative years, but demonstrated no clinical significance as their respective 95% CIs calculated by the AIC, BIC, and AUC were found to overlap. However, the more detailed staging classifications of the eighth edition was shown to display the best prognostic demarcation for stratifying patients with higher-staged disease. This study thereby identified the eighth AJCC GC edition to possess similar long-term prognostic ability as to its previous three editions but contrastingly demonstrated the best distinctive ability for stratifying overall survival and can thus be considered as being clinically more reliable.

Incorporation of N0 Stage with Insufficient Numbers of Lymph Nodes into N1 Stage in the Seventh Edition of the TNM Classification Improves Prediction of Prognosis in Gastric Cancer: Results of a Single-Institution Study of 1258 Chinese Patients.

PURPOSE: This study examined the prognosis of the "node-negative with eLNs ≤ 15" designation and the additional value of incorporating it into the pN1 designation in the seventh edition of the N classification. METHODS: From January 2000 to September 2010, a total of 1258 gastric cancer patients (patients with eLNs > 15 or node-negative with eLNs ≤ 15) undergoing radical gastric resection were enrolled in this study. We incorporated node-negative patients with eLNs ≤ 15 into pN1 and compared this designation with the current 7th edition UICC N stage for 3, 5-year overall survival by univariate and multivariate analysis. Homogeneity, discriminatory ability, and monotonicity of gradients in the hypothetical N stage and the UICC N stage were compared using linear trend χ2, likelihood ratio χ2 statistics, and Akaike information criterion (AIC) calculations. RESULTS: Node-negative patients with eLNs ≤ 15 had worse survival compared with those with eLNs > 15. In univariate and multivariate analyses, the hypothetical N stage showed superiority to the 7th edition pN staging. The hypothetical staging system had higher linear trend and likelihood ratio χ (2) scores and smaller AIC values compared with those for the TNM system, which represented the optimum prognostic stratification. CONCLUSIONS: Node-negative patients with eLNs ≤ 15 can be considered to be incorporated into the pN1 stage in the 7th edition of the TNM classification.

Prognostic Significance of Carcinoembryonic Antigen Staining in Cancer Tissues of Gastric Cancer Patients.

PURPOSE: The aim of this study was to assess the significance of the correlation among tissue carcinoembryonic antigen (CEA) expression with serum CEA (sCEA) levels and long-term survival to highlight the clinical prognostic significance of tissue CEA expression in gastric cancer patients. METHODS: Immunohistological method and radioimmunoassay were used to assess tissue and sCEA expression, respectively. Univariate and multivariate analyses were performed to determine correlations, and the Kaplan-Meier method was used to investigate the prognostic significance. RESULTS: Our results demonstrate that tissue CEA in gastric cancer is significantly correlated with preoperative sCEA levels (p = 0.031), depth of invasion (p = 0.001), lymph node metastasis (p < 0.001), distant metastasis (p = 0.001), and TNM staging (p < 0.001). The 5-year survival rates were 67.6, 53.9, and 40.1 % for negatively, moderately, and intensely positively stained tissues (p < 0.001), and 57.0 and 37.9 % for serum with normal and elevated CEA expression (p = 0.031). Multivariate analysis revealed that tissue CEA can be considered an independent prognostic factor. Further analysis illustrated that patients with negative expression in both tissue and serum had better prognosis compared with those positively expressing CEA in both tissue and serum and/or those positively expressing CEA in either tissue or serum (p < 0.001). Our results also demonstrated that patients with negative tissue CEA staining and elevated sCEA expression had a better 5-year survival. CONCLUSION: Tissue CEA expression in gastric cancer is directly correlated with sCEA levels and long-term prognosis. Thus, tissue CEA expression can be considered as a useful biomarker to improve the interpretation of sCEA levels in predicting long-term survival.

Comprehensive treatment of a functional pancreatic neuroendocrine tumor with multifocal liver metastases.

A 64-year-old man was admitted to the Sun Yat-Sen University Cancer Center with chief complaints of recurrent abdominal pain and diarrhea for about 3 years and with a history of surgical repair for intestinal perforation owing to stress ulcer. Positron emission tomography (PET)/computed tomography (CT) demonstrated a primary tumor on the pancreatic tail with multifocal liver metastases. Pathological and immunohistochemistry staining revealed the lesion to be a pancreatic neuroendocrine tumor (pNET). According to the latest World Health Organization (WHO, 2013) classification, the tumor was classified as stage IV functional G1 pNET. After referral to the multidisciplinary treatment board (MDT), the patient was started on periodic dose of omeprazole, somatostatin analogues and Interferon α (IFNα) and had scanning follow-ups. Based upon the imaging results, CT-guided radioactive iodine-125 ((125)I) seeds implantation therapy, radiofrequency ablation therapy (RFA) or microwave ablation technique were chosen for the treatment of the primary tumor. Transarterial chemoembolization (TACE), RFA and microwave ablation techniques were decided upon for liver metastases. The patient showed beneficial response to the treatment with clinically manageable low-grade side effects and attained partial remission (RECIST criteria) with a good quality of life.

A new strategy using ALDHhigh-CD8+T cells to inhibit tumorigenesis.

BACKGROUND: Currently, many studies suggest that cancer stem cells (CSCs) are responsible for tumor initiation, tumorigenesis, metastasis and recurrence. CSCs have been identified from various human and murine tumors. The identification of CSCs allows us to develop strategies to target the CSCs. METHODS AND RESULTS: In this study, we used ALDEFLUOR as a single marker to isolate the CSCs from the human lung cancer cell line H460. We then characterized the CSCs by testing their sphere formation ability and tumorigenicity. Furthermore, we used CSC lysate-pulsed dendritic cells to stimulate CD8+T cells as a treatment strategy. Our study demonstrated that ALDEFLUOR could be used as a single marker to identify CSCs from the human lung cancer cell line H460. The ALDHhigh cells could form more spheres and were more tumorigenic than the ALDHlow cells. Further study demonstrated that ALDHhigh-CD8+T cells conferred more significant antitumor effects, resulting in the inhibition of tumor growth and prolonged survival. And the ALDHhigh-CD8+T cells-mediated anti-tumor immunity might be due to the directly targeting against ALDHhigh cancer stem cells (CSCs). CONCLUSIONS: This study shows that ALDHhigh-CD8+T cells mediate anti-tumor immunity by selectively targeting cancer stem cells, which result in inhibiting tumor growth and prolonging the survival of tumor-bearing mice, which provides a new strategy using ALDHhigh-CD8+T cells to treat tumors.