Protein predictive signatures for lymph node metastasis of gastric cancer

Role of radiomics in predicting lymph node metastasis in gastric cancer: a systematic review

Introduction

Gastric cancer (GC) is an aggressive and clinically heterogeneous tumor, and better risk stratification of lymph node metastasis (LNM) could lead to personalized treatments. The role of radiomics in the prediction of nodal involvement in GC has not yet been systematically assessed. This study aims to assess the role of radiomics in the prediction of LNM in GC.

Methods

A PubMed/MEDLINE systematic review was conducted to assess the role of radiomics in LNM. The inclusion criteria were as follows: i. original articles, ii. articles on radiomics, and iii. articles on LNM prediction in GC. All articles were selected and analyzed by a multidisciplinary board of two radiation oncologists and one surgeon, under the supervision of one radiation oncologist, one surgeon, and one medical oncologist.

Results

A total of 171 studies were obtained using the search strategy mentioned on PubMed. After the complete selection process, a total of 20 papers were considered eligible for the analysis of the results. Radiomics methods were applied in GC to assess the LNM risk. The number of patients, imaging modalities, type of predictive models, number of radiomics features, TRIPOD classification, and performances of the models were reported.

Conclusions

Radiomics seems to be a promising approach for evaluating the risk of LNM in GC. Further and larger studies are required to evaluate the clinical impact of the inclusion of radiomics in a comprehensive decision support system (DSS) for GC.

A thirty-three gene-based signature predicts lymph node metastasis and prognosis in patients with gastric cancer

Recently, several studies have indicated the great potential of gene expression signature of the primary tumor in predicting lymph node metastasis; however, few current gene biomarkers can predict lymph node status and prognosis in gastric cancer (GC). Thus, we used the RNA-seq data from The Cancer Genome Atlas (TCGA) to identify differentially expressed genes between pathological lymph node-negative (pN0) and positive (pN+) patients and to establish a gene signature that could predict lymph node metastasis. Meanwhile, the robustness of identified gene signatures was validated in an independent dataset Asian Cancer Research Group (n = 300). In this study, our thirty-three gene-based signature was highly correlated with lymph node metastasis and could successfully discriminate pN + patients in the training set (Area under the receiver operating characteristic curve = 0.951). Moreover, Disease-free survival (P = 0.0029) and overall survival (P = 0.026) were significantly worse in high-risk compared with low-risk patients overall and when confined to pN0 patients only (P < 0.0001). Of note, this gene signature also proved useful in predicting lymph node status and survival in the validation cohort. The present study suggests a thirty-three gene-based signature that could effectively predict lymph node metastasis and prognosis in GC.

Polymorphism rs1057147 located in mesothelin gene predicts lymph node metastasis in patients with gastric cancer

Lymph node metastasis, a crucial factor in the spread of gastric cancer (GC), is strongly associated with a negative prognosis for patients. This study aimed to investigate the association of the mesothelin (MSLN) gene polymorphisms (rs3764247, rs3764246, rs12597489, rs1057147, and rs3765319) with the risk of lymph node metastasis of GC patients in a Chinese Han population. The PCR-LDR genotyping was used to detect the genotypes of MSLN polymorphisms in GC patients with lymph node metastasis (n = 610) or without (n = 356). Our research indicates that certain genetic markers, specifically rs3764247, rs3764246, rs12597489, and rs3765319, do not appear to be linked with an increased risk of lymph node metastasis in GC. However, we did observe that patients with the rs1057147 GA genotype exhibited a higher likelihood of lymph node metastasis in GC when compared to those with the GG genotype (OR = 1.33, 95% CI = 1.01 - 1.76, P = 0.045). Patients with rs1057147 GA + AA genotype were found to have a higher likelihood of lymph node involvement (OR = 1.35, 95% CI = 1.03 - 1.77, P = 0.029) when compared to those with GG genotype in the dominant model. The allelic model revealed that the A allele of rs1057147 exhibited a stronger correlation with lymph node metastasis compared to the G allele (OR = 1.28, 95% CI = 1.02 - 1.60, P = 0.031). In addition, we found that rs1057147 polymorphism revealed a poor prognosis for GC patients with lymph node metastasis. Further stratified analysis revealed that the prognostic effect of rs1057147 was more pronounced in patients with GC who had lymph node metastasis and had a tumor size of 4 cm or greater, as well as more than 2 lymph node metastases. Bioinformatics studies showed that the binding mode of miR-3144-5p or miR-3619-3p to MSLN was altered by the mutation of rs1057147. Our study confirmed the important role of MSLN rs1057147 polymorphism locus in GC lymph node metastases and suggested a potential prognostic factor during GC progression. KEY POINTS: • Rs1057147 GA genotype had an increased risk of lymph node metastasis in gastric cancer. • The A allele of rs1057147 had a stronger association with lymph node metastasis than the G allele. • The binding mode of miR-3144-5p or miR-3619-3p to MSLN was altered by the mutation of rs1057147.

Fibrinogen-to-Lymphocyte Ratio Was an Independent Predictor of Lymph Node Metastasis in Patients with Clinically Node-Negative Advanced-Stage Gastric Cancer

Purpose

Various hematological indicators have been reported to predict lymph node metastasis (LNM) in gastric cancer (GC) patients, but the relationship between FLR and LNM has not been studied. Therefore, the aim of this study was to evaluate the role of preoperative fibrinogen-to-lymphocyte ratio (FLR) in predicting LNM in patients with clinically node-negative (cN0) advanced gastric cancer (AGC).

Patients and Methods

We retrospectively reviewed 571 eligible patients with primary AGC adenocarcinoma who underwent radical gastrectomy (discovery cohort). Patients were divided into high and low FLR groups according to the optimal cutoff value determined by Youden index. FLR is an independent predictor of LNM determined by logistic regression and validated in the validation cohort of 207 patients. Receiver operating characteristic (ROC) curve analysis was used to evaluate the predictive value of FLR for LNM. The nonlinear relationship between FLR and LNM risk was assessed using restricted cubic spline. Sensitivity analyses were performed according to FLR quartiles to further assess the robustness of the results. The nomogram was built based on FLR and clinicopathological characteristics, and was evaluated by calibration curves, ROC curve analysis and decision curve analysis.

Results

In the discovery cohort, the area under the curve (AUC) value for FLR to predict LNM was 0.592. There is a linear relationship between the FLR value and the risk of LNM, and the risk of LNM increased with FLR value. High FLR level is an independent risk factor for LNM, and the results of sensitivity analysis robust this finding. The nomogram for individual risk assessment performed well. Furthermore, we verified the FLR was an independent predictor of LNM in the validation cohort.

Conclusion

FLR was an independent predictor of LNM in patients with cN0 AGC.

Machine learning for lymph node metastasis prediction of in patients with gastric cancer: A systematic review and meta-analysis

Objective

To evaluate the diagnostic performance of machine learning (ML) in predicting lymph node metastasis (LNM) in patients with gastric cancer (GC) and to identify predictors applicable to the models.

Methods

PubMed, EMBASE, Web of Science, and Cochrane Library were searched from inception to March 16, 2022. The pooled c-index and accuracy were used to assess the diagnostic accuracy. Subgroup analysis was performed based on ML types. Meta-analyses were performed using random-effect models. Risk of bias assessment was conducted using PROBAST tool.

Results

A total of 41 studies (56182 patients) were included, and 33 of the studies divided the participants into a training set and a test set, while the rest of the studies only had a training set. The c-index of ML for LNM prediction in training set and test set was 0.837 [95%CI (0.814, 0.859)] and 0.811 [95%CI (0.785-0.838)], respectively. The pooled accuracy was 0.781 [(95%CI (0.756-0.805)] in training set and 0.753 [95%CI (0.721-0.783)] in test set. Subgroup analysis for different ML algorithms and staging of GC showed no significant difference. In contrast, in the subgroup analysis for predictors, in the training set, the model that included radiomics had better accuracy than the model with only clinical predictors (F = 3.546, p = 0.037). Additionally, cancer size, depth of cancer invasion and histological differentiation were the three most commonly used features in models built for prediction.

Conclusion

ML has shown to be of excellent diagnostic performance in predicting the LNM of GC. One of the models covering radiomics and its ML algorithms showed good accuracy for the risk of LNM in GC. However, the results revealed some methodological limitations in the development process. Future studies should focus on refining and improving existing models to improve the accuracy of LNM prediction.

Systematic Review Registration

https://www.crd.york.ac.uk/PROSPERO/, identifier CRD42022320752

Association between neutrophil-lymphocyte ratio and lymph node metastasis in gastric cancer: A meta-analysis

INTRODUCTION AND AIM

The prognostic role of neutrophil to lymphocyte ratio (NLR) has been explored extensively in the literature. The aim of this meta-analysis was to evaluate the link between NLR and lymph node metastasis in gastric cancer. A method for increasing specificity and sensitivity of pre-treatment staging has implications on treatment algorithms and survival.

SEARCH STRATEGY

The relevant databases were searched as per the Preferred Reporting Items for Systematic Reviews and Meta-Analyses flowchart. After selection, 12 full text articles that met the inclusion criteria were included for quantitative analysis. 2 × 2 squares were generated using lymph node positive/negative, and NLR high/low data. The effect size for each study was calculated using the DerSimonian-Laird random effects model. P values were calculated using the chi-square method. Finally publication bias was evaluated. All statistics were calculated using R Studio.

RESULTS

Meta-analysis showed a 1.90 times (odds ratio, with 95% CI 1.52-2.38) increase in risk of positive lymph node status with high neutrophil to lymphocyte ratio. This has significant implications for cancer screening and staging, as NLR is a highly reproducible, cost-effective, and widely available prognostic factor for gastric cancer patients. Additionally, high or low NLR values may have implications for management pathways. Patients with lymph node metastasis can be offered neoadjuvant chemotherapy, avoiding salvage therapy in the form of adjuvant chemoradiotherapy, which is poorly tolerated.

CONCLUSION

This meta-analysis shows an association between NLR and positive lymph node status in gastric cancer patients with implications for staging, as well as preoperative personalisation of therapy.

RBPMS2, as a novel biomarker for predicting lymph node metastasis, guides therapeutic regimens in gastric cancer

RNA-binding protein with multiple splicing 2 (RBPMS2) is a critical gene that encodes a member of the RNA-recognition-motif-containing protein family and is involved in the development and dedifferentiation of digestive smooth muscle cells. However, whether RBPMS2 has an effect on the prognosis of gastric cancer (GC) and its possible mechanism during GC progression remain unknown. Here, we collected 596 GC patients who underwent curative surgical resection to evaluate expression of RBPMS2. RBPMS2 was upregulated in GC tissues, and was associated with lymph node metastasis. We analysis the KEGG pathway and GO biological processes, cellular component and molecular function of RBPMS2 interactive genes, as well as RBPMS2-binding partner ESRP1 interactive genes. We also focus on the correlation analysis between EMT-related genes and RBPMS2/ESRP1. Finally, we analysed the correlation between RBPMS2 expression and chemotherapeutic drugs which may assist in GC therapy and demonstrated that RBPMS2 expression was associated with tumour mutation burden (TMB) and Microsatellite Instability (MSI), as well as immune infiltration level in GC.

A novel robust nomogram based on preoperative hemoglobin and albumin levels and lymphocyte and platelet counts (HALP) for predicting lymph node metastasis of gastric cancer

BACKGROUND

Accurate assessment of lymph node status in gastric cancer (GC) patients can help to select appropriate treatment strategies for GC, but the diagnostic accuracy of conventional methods needs to be improved. The aim of this study was to investigate the predictive value of preoperative hemoglobin and albumin levels and lymphocyte and platelet counts (HALP) on lymph node status in GC patients and to construct a risk prediction model.

METHODS

This study retrospectively analyzed the clinicopathological characteristics of 349 patients with GC who underwent radical gastrectomy, among which 250 patients were recruited in the training cohort and 99 patients in the independent validation cohort. Significant risk factors in univariate analysis were further identified as independent variables in multivariate logistic regression analysis, which were then incorporated and presented in a nomogram. Receiver operating characteristic (ROC) curves, Calibration curve and decision curve analysis (DCA) curves were used to evaluate the discrimination, prediction accuracy and clinical effectiveness of the model.

RESULTS

Multifactorial logistic regression analysis showed that alcohol use (OR =2.203, P=0.036), Depth of invasion (OR =7.756, P<0.001), differentiation (OR =2.252, P=0.018), carcinoembryonic antigen (CEA) (OR =2.443, P=0.017), carbohydrate antigen 19-9 (CA199) (OR =2.715, P=0.008) and HALP (OR =2.276, P=0.032) were independent risk factors for lymph node metastasis (LNM) in GC. We used these factors to construct a nomogram for predicting LNM in GC patients, and the ROC curves showed good discrimination of the model with AUC values of 0.854 (training cohort) and 0.868 (validation cohort), respectively, and the calibration curves showed good predictive ability of the nomogram, in addition to the DCA curves results showed the clinical usefulness of the model.

CONCLUSIONS

In conclusion, we established a nomogram for predicting LNM in patients with GC.

Establishment of Decision Rules and Risk Assessment Model for Preoperative Prediction of Lymph Node Metastasis in Gastric Cancer

Background: Preoperative accurate prediction of lymph node status is especially important for the formulation of treatment plans for patients with gastric cancer (GC). The purpose of this study was to establish decision rules and a risk assessment model for lymph node metastasis (LNM) in GC using preoperative indicators. Methods: The clinical data of 554 patients who underwent gastrectomy with D2 lymphadenectomy were collected. A 1:1 propensity score matching (PSM) system was used, and the clinical data of the matched 466 patients were further analyzed. The important risk factors for LNM were extracted by the random forest algorithm, and decision rules and nomogram models for LNM were constructed with a classification tree and the "rms" package of R software, respectively. Results: Tumor size (OR: 2.058; P = 0.000), computed tomography (CT) findings (OR: 1.969; P = 0.001), grade (OR: 0.479; P = 0.000), hemoglobin (Hb) (OR: 1.211; P = 0.005), CEA (OR: 1.111; P = 0.017), and CA19-9 (OR: 1.040; P = 0.033) were independent risk factors for LNM in GC. Tumor size did rank first in the ranking of important factors for LNM in GC and was the first-level segmentation of the two initial branches of the classification tree. The accuracy, sensitivity, specificity, and positive predictive value of the decision rules in diagnosing preoperative LNM in GC were 75.6, 85.7, 73.9, 73.5, and 79.3%, respectively. The accuracy, sensitivity, and specificity of the risk assessment model in predicting preoperative LNM in GC were 79.3, 80.3, and 79.4%, respectively. Conclusion: Tumor size was the most important factor for evaluating LNM in GC. This decision rules and nomogram model constructed to take into account tumor size, CT findings, grade, hemoglobin, CEA, and CA19-9 effectively predicted the incidence of LNM in preoperative GC.

Profiling of serum metabolites in advanced colon cancer using liquid chromatography-mass spectrometry

Lymph node metastasis remains a key factor that affects the prognosis of patients with colon cancer. The aim of the present study was to identify and evaluate serum metabolites as biomarkers for the detection of tumor lymph node metastasis and the prediction of patient survival. The present study analyzed the metabolites in the serum of patients with advanced colon cancer both with and without lymph node metastasis. Blood samples from 104 patients with stage T3 colon cancer were collected and analyzed using liquid chromatography-mass spectrometry. The metabolites were structurally confirmed with data from the Human Metabolome Database. The association between the serum metabolites and the clinicopathological characteristics and survival time of patients from the present study was analyzed. Overall, 227 different metabolites were identified in the serum of patients with stage T3 colon cancer with or without lymph node metastasis. Furthermore, 17 of these metabolites may potentially distinguish those patients with lymph node metastasis from those patients without. In addition, five factors, including abscisic acid, calcitroic acid and glucosylsphingosine presence in the serum, age and sex, were identified as independent predictors for lymph node metastasis (P<0.05). Furthermore, three factors, including abscisic acid, calcitroic acid and glucosylsphingosine presence in the serum were independent predictors for patient survival (P<0.05). In conclusion, the serum levels of abscisic acid, calcitroic-acid and glucosylsphingosine may be considered as potential biomarkers to predict the occurrence of lymph node metastasis and the survival time of patients with colon cancer.

The value of preoperative lymphocytes-to-monocytes ratio in predicting lymph node metastasis in gastric cancer

Background

This study was aimed to evaluate value of preoperative lymphocytes-to-monocytes ratio (LMR) as a predictor for lymph node metastasis in gastric cancer.

Methods

Patients with pathologically diagnosed malignant gastric tumor were reviewed retrospectively. Patients’ demographic data, clinical manifestations and LMR were collected. The postoperative pathology data including the tumor size, tumor sites, differentiation degree of tumor, depth of tumor invasion, metastatic lymph nodes, total dissected lymph nodes, distant metastasis, vessel carcinoma embolus, neural invasion, Lauren’s classification, Ki-67 and TNM stage were collected. Receiver operating characteristic curve (ROC) was used to determine the cut-off point of LMR. The association between LMR and the clinicopathologic factors was further analyzed.

Results

A total of 177 subjects were enrolled into the study. LMR =3.79 was used as cut-off point; the patients with LMR ≥3.79 were classified as high-LMR group (123 cases) and the patients with LMR <3.79 as low-LMR group (54 cases). LMR was an independent risk factor for lymph node metastasis.

Conclusions

Low preoperative LMR was positively correlated with lymph node metastasis in gastric cancer patients, and had predictive value for lymph node metastasis in gastric cancer patients.

A Disintegrin and Metalloproteinase 8 as a Potential Blood Biomarker for Early Diagnosis of Gastric Cancer

PURPOSE

We aimed to evaluate the clinical significance of a disintegrin and metalloproteinase 8 (ADAM 8) as a potential blood biomarker for gastric cancer (GC).

MATERIALS AND METHODS

Blood ADAM 8 was measured by ELISA. Cytokines/chemokines [interleukin-23 (IL-23), stromal cell-derived factor 1α/CXC chemokine ligand 12 (SDF-1α/CXCL12), interleukin-8 (IL-8), and soluble CD40 ligand (sCD40L)] were measured by chemiluminescent immunoassay. They were compared among five groups; normal/gastritis, high-risk, early GC (EGC), advanced GC (AGC) without distant metastasis, and AGC with distant metastasis by one-way analysis of variance in both training (n=80) and validation dataset (n=241). Clinicopathological features of GC and GC-associated cytokines were evaluated for their correlations with blood ADAM 8. To evaluate the diagnostic accuracy to predict GC, receiver operating characteristic (ROC) curve and logistic regression were used.

RESULTS

Blood ADAM 8 significantly increased along GC carcinogenesis in both training (ANOVA, p<0.001) and validation dataset (p<0.001). It was significantly higher in EGC compared to high-risk (post-hoc Bonferroni, p=0.041) and normal (p<0.001). It was also higher in AGC compared with high-risk (p<0.001) and normal (p<0.001) groups. However, no significant difference was found between cancer groups. Blood ADAM 8 was correlated with N-stage (Spearman's correlation, γ_s=0.320, p=0.011), but not with T-stage or M-stage. Pearson's correlations showed blood ADAM 8 was closely correlated with pre-inflammatory cytokines, IL-23 (p=0.036) and SDF-1α/CXCL12 (p=0.037); however, it was not correlated with pro-angiogenic cytokine IL-8 (p=0.313), and sCD40L (p=0.702). ROC curve and logistic regression demonstrated that blood ADAM 8 showed higher diagnostic accuracy (sensitivity, 73.7%; specificity, 86.2%) than CEA (sensitivity, 23.1%; specificity, 91.4%). Combination of ADAM 8 and CEA further increased the diagnostic accuracy to predict GC (sensitivity, 81.8%; specificity, 84.0%).

CONCLUSION

Blood ADAM 8 is a promising biomarker for early detection of GC.

ADAM8 in invasive cancers: links to tumor progression, metastasis, and chemoresistance

Ectodomain shedding of extracellular and membrane proteins is of fundamental importance for cell-cell communication in neoplasias. A Disintegrin And Metalloproteinase (ADAM) proteases constitute a family of multifunctional, membrane-bound proteins with traditional sheddase functions. Their protumorigenic potential has been attributed to both, essential (ADAM10 and ADAM17) and 'dispensable' ADAM proteases (ADAM8, 9, 12, 15, and 19). Of specific interest in this review is the ADAM proteinase ADAM8 that has been identified as a significant player in aggressive malignancies including breast, pancreatic, and brain cancer. High expression levels of ADAM8 are associated with invasiveness and predict a poor patient outcome, indicating a prognostic and diagnostic potential of ADAM8. Current knowledge of substrates and interaction partners gave rise to the hypothesis that ADAM8 dysregulation affects diverse processes in tumor biology, attributable to different functional cores of the multidomain enzyme. Proteolytic degradation of extracellular matrix (ECM) components, cleavage of cell surface proteins, and subsequent release of soluble ectodomains promote cancer progression via induction of angiogenesis and metastasis. Moreover, there is increasing evidence for significance of a non-proteolytic function of ADAM8. With the disintegrin (DIS) domain ADAM8 binds integrins such as β1 integrin, thereby activating integrin signaling pathways. The cytoplasmic domain is critical for that activation and involves focal adhesion kinase (FAK), extracellular regulated kinase (ERK1/2), and protein kinase B (AKT/PKB) signaling, further contributing to cancer progression and mediating chemoresistance against first-line therapies. This review highlights the remarkable effects of ADAM8 in tumor biology, concluding that pharmacological inhibition of ADAM8 represents a promising therapeutic approach not only for monotherapy, but also for combinatorial therapies.

Serum protein marker panel for predicting preeclampsia

BACKGROUND

Preeclampsia is a multi-system disorder in pregnancy which has no effective treatment. The diagnosis of preeclampsia is based on clinical presentation and routine laboratory tests.

OBJECTIVE

This study aimed at identifying serum protein markers for diagnosis of preeclampsia and predicting its severe features.

STUDY DESIGN

In total, 172 pregnant women were enrolled in this study including 110 subjects with preeclampsia and 62 normotensive subjects. Eleven serum proteins (VEGF, sFlt-1, sEndoglin, PlGF, sEGFR, prolactin, PTX3, PAI-1, NGAL, IL-27, COX-2) were assessed using Luminex multiplex immunoassay and ELISA.

RESULTS

The levels of seven proteins (sFlt-1, VEGF, sEndoglin, sEGFR, PlGF, NGAL, COX-2) correlated with preeclampsia, and 4 proteins (VEGF, sEndoglin, PlGF, sEGFR) were identified as independent factors associated with preeclampsia. The levels of three proteins (sEndoglin, PTX3, sFlt-1) correlated with severe features of preeclampsia, and three variables (serum creatinine, platelet count and sEndoglin) were identified as independent factors in predicting severe features of preeclampsia.

CONCLUSIONS

A combination of serum protein markers (VEGF, sEndoglin, PlGF, sEGFR) and clinical variables (serum creatinine, platelet count and sEndoglin) could be used as analytical tool in diagnosis of preeclampsia and its severe features, respectively. Serum sEGFR, a novel biomarker in preeclampsia, may be involved in the pathogenesis of preeclampsia.

GRIK3: A novel oncogenic protein related to tumor TNM stage, lymph node metastasis, and poor prognosis of GC

Glutamate receptor, ionotropic, kainate 3 (GRIK3), as a member of the glutamate kainate receptor family, mainly participated in neuroactive ligand receptor interaction pathway. Other members of GRIK family were previously reported to regulate cellular migration, transformation, and proliferation in tumor. However, the mechanism of GRIK3 in tumor is still unclear. Therefore, the purpose of our study was to reveal the expression and clinical significance of GRIK3 in gastric cancer (GC). First, we performed the expression analysis and survival analysis of GRIK3 using The Cancer Genome Atlas (TCGA) database, and the results showed that the GRIK3 expressed differentially between gastric cancer tissues and the adjacent normal tissues and that higher expression of GRIK3 was associated with poor survival outcomes. And the gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis suggested that GRIK3 mainly took part in cancer-related process. Subsequently, the validated immunohistochemistry showed that GRIK3 expressed higher in the GC tissues than in the matched normal tissues and the patients with overexpressed GRIK3 had worse survival outcomes. The univariate and multivariate analyses suggested that the expression of GRIK3 was an independent prognostic factor to predict GC prognosis. Furthermore, additional experiment showed that the lymph node metastasis tissues had higher GRIK3 expression than their matched primary GC tissues. These findings suggested that elevated GRIK3 expression could serve as an independent prognostic biomarker and a novel potential treatment target for patients with GC.

Magnetic Resonance Imaging-Detected Tumor Residue after Intensity-Modulated Radiation Therapy and its Association with Post-Radiation Plasma Epstein-Barr Virus Deoxyribonucleic Acid in Nasopharyngeal Carcinoma

Purpose: To evaluate the prognostic value of magnetic resonance imaging (MRI)-detected tumor residue after intensity-modulated radiation therapy (IMRT) and its association with post-treatment plasma Epstein-Barr virus deoxyribonucleic acid (EBV DNA) in nasopharyngeal carcinoma (NPC).

Methods and materials: A prospective database of patients with histologically-proven NPC was used to retrospectively analyze 664 cases. Pre- and post-treatment MRI scans were independently reviewed by two senior radiologists who were blinded to clinical findings. Factors significantly associated with MRI-detected tumor residue were identified and included in the following multivariate logistic regression model. Residual risk model were established. Receiver operating characteristic (ROC) identify the optimal cut-off risk score for tumor residue.

Results: MRI-detected residual tumor at three months after IMRT was associated with poor prognosis. The 5-year survival rates for the non-residual and residual groups were: OS (93.8% vs. 76.6%, P<0.001), PFS (84.7% vs. 67.9%, P=0.006), LRFS (93.4% vs. 80.4%, P=0.002), and DMFS (90.3% vs. 87.9%, P=0.305), respectively. Three-month post-treatment EBV DNA was significantly associated with tumor residue (P<0.001). A residual risk score model was established, consisting of T and N categories and post-treatment EBV DNA. ROC identified 22.74 as the optimal cut-off risk score for tumor residue. High-risk score was independently associated with poor treatment outcomes.

Conclusions: MRI-detected tumor residue was an independent adverse prognostic factor in NPC; and significantly associated with three-month post-treatment EBV DNA. As limited resources in some endemic areas prevent patients from undergoing routine post-treatment imaging, our study identifies a selection risk-model, providing a cost-effective reference for the selection of follow-up strategies and clinical decision-making.

Selumetinib suppresses cell proliferation, migration and trigger apoptosis, G1 arrest in triple-negative breast cancer cells

BACKGROUND

Triple-negative breast cancer (TNBC) has aggressive progression with poor prognosis and ineffective treatments. Selumetinib is an allosteric, ATP-noncompetitive inhibitor of MEK1/2, which has benn known as effective antineoplastic drugs for several malignant tumors. We hypothesized that Selumetinib might be potential drug for TNBC and explore the mechanism.

METHODS

After treated with Selumetinib, the viability and mobility of HCC1937 and MDA-MB-231 were detected by MTT, tunnel, wound-healing assay, transwell assay and FCM methods. MiR array was used to analysis the change of miRs. We predicted and verified CUL1 is the target of miR-302a using Luciferase reporter assay. We also silenced the CUL1 by siRNA, to clarify whether CUL1 take part in the cell proliferation, migration and regulated its substrate TIMP1 and TRAF2. Moreover, after transfection, the antagomir of miR-302a and CUL1 over-expressed plasmid into HCC1937 and MDA-MB-231 cell accompanied with the Selumetinib treatment, we detected the proliferation and migration again.

RESULTS

Selumetinib reduce the proliferation, migration, triggered apoptosis and G1 arrest in TNBC cell lines. In this process, the miR-302a was up-regulated and inhibited the CUL1 expression. The later negatively regulated the TIMP1 and TRAF2. As soon as we knockdown miR-302a and over-expression CUL1 in TNBC cells, the cytotoxicity of Selumetinib was reversed.

CONCLUSIONS

MiR-302a targeted regulated the CUL1 expression and mediated the Selumetinib-induced cytotoxicity of triple-negative breast cancer.

A novel scoring system associating with preoperative platelet/lymphocyte and clinicopathologic features to predict lymph node metastasis in early gastric cancer

BACKGROUND

Precise determination of the lymph node status is critical for determining appropriate treatment for early gastric cancer (EGC). This study attempted to establish a simple, effective risk scoring system to predict lymph node metastasis (LNM) in EGC by investigating the relationship between platelet-to-lymphocyte ratio (PLR) and neutrophil-to-lymphocyte ratio (NLR) and EGC LNM.

MATERIALS AND METHODS

We retrospectively reviewed 312 operable patients with EGC. The clinical utility of PLR and NLR was tested by receiver operating characteristic curves. The scoring system was developed using independent risk factors. Finally, 89 EGC patients were collected from prospective database to validate the scoring system's accuracy.

RESULTS

The optimal PLR and NLR cut-off values were 106 and 2.97, respectively. High NLR (P = 0.009) and PLR (P = 0.007) values were associated with LNM of EGC in univariate analyses, although only high PLR (P = 0.025) was an independent risk factor in multivariate analyses, together with age (P = 0.009), differentiation (P = 0.017), invasive depth (P < 0.001), and tumor size (P = 0.003). The scoring system's accuracy for retrospective and prospective data was 0.781 (95% confidence interval: 0.721-0.841) and 0.817 (95% confidence interval 0.714-0.920), respectively.

CONCLUSIONS

Preoperative PLR and NLR correlate with EGC LNM. Our scoring system is reliable, accurate, and effective in predicting LNM in EGC patients.

Combination of preoperative platelet/lymphocyte and neutrophil/lymphocyte rates and tumor-related factors to predict lymph node metastasis in patients with gastric cancer

OBJECTIVE

Lymph node (LN) metastasis is widely accepted as a poor prognosis indicator in patients with gastric cancer. An accurate preoperative prediction of LN status is of crucial importance for the planning treatment. The aim of the present study was to assess the predictive value of the preoperative platelet/lymphocyte (PLR) and neutrophil/lymphocyte rates (NLR) on the LN metastasis in gastric cancer patients and to develop a new preoperative score system to predict LN metastasis.

PATIENTS AND METHODS

A total of 492 operable patients with gastric cancer were enrolled in our study. The clinical utility of the PLR and NLR was evaluated by receiver operating characteristic (ROC) curves. The logistic analysis was used to identify the independent parameters associated with LN metastasis. Then, a score system including those independent parameters that can be detected preoperatively was established, which was also tested by an ROC curve.

RESULTS

The ideal cutoff values for predicting LN metastasis were 1.59 for NLR and 155.67 for PLR according to the ROC curve. Multivariate analyses showed that both PLR and NLR are significantly associated with LN metastasis independent of depth of invasion, lymphatic invasion, macroscopic type, and tumor size. The area under the ROC curve of the score system was 0.830 (95% confidence interval 0.782-0.878), showing a reliable ability to evaluate the status of nodal involvement.

CONCLUSION

Preoperative PLR and NLR are useful biomarkers to predict LN metastasis and the score system in our study may serve as a reliable instrument to predict LN metastasis in gastric cancer patients.

Serum biomarker panels for diagnosis of gastric cancer

Purpose

Currently, serum biomarkers that are sufficiently sensitive and specific for early detection and risk classification of gastric adenocarcinomas are not known. In this study, ten serum markers were assessed using the Luminex system and enzyme-linked immunosorbent assay for the diagnosis of gastric cancer and analysis of the relation between prognosis and metastases.

Patients and methods

A training set consisting of 228 gastric adenocarcinoma and 190 control samples was examined. A Luminex multiplex panel with nine biomarkers, consisting of three proteins discovered through our previous studies and six proteins previously reported to be cancer-associated, was constructed. One additional biomarker was detected using a commercial kit containing EDTA. Logistic regression, random forest (RF), and support vector machine (SVM) were used to identify the panel of discriminatory biomarkers in the training set. After selecting five proteins as candidate biomarkers, multivariate classification analyses were used to identify algorithms for diagnostic biomarker combinations. These algorithms were independently validated using a set of 57 gastric adenocarcinoma and 48 control samples.

Results

Serum pepsinogen I, serum pepsinogen II, A Disintegrin And Metalloproteinase domain-containing protein 8 (ADAM8), vascular endothelial growth factor (VEGF), and serum IgG to Helicobacter pylori were selected as classifiers in the three algorithms. These algorithms differentiated between the majority of gastric adenocarcinoma and control serum samples in the training/test set with high accuracy (RF 79.0%, SVM 83.8%, logistic regression 76.2%). These algorithms also differentiated the samples in the validation set (accuracy: RF 82.5%, SVM 86.1%, logistic regression 78.7%).

Conclusion

A panel of combinatorial biomarkers comprising VEGF, ADAM8, IgG to H. pylori, serum pepsinogen I, and pepsinogen II were developed. The use of biomarkers is a less invasive method for the diagnosis of gastric adenocarcinoma. They may supplement clinical gastroscopic evaluation of symptomatic gastric cancer patients and enhance the diagnostic accuracy.

Upregulation of a disintegrin and metalloprotease 8 is associated with progression and prognosis of patients with gastric cancer

A disintegrin and metalloprotease 8 (ADAM8) is involved in the tumorigenesis of several types of solid tumors. However, its exact role in gastric cancer (GC) remains unclear. The aim of this study was to evaluate the clinical significance of ADAM8 in GC and to explore its biological effects on gastric carcinogenesis. In this study, quantitative reverse transcription-polymerase chain reaction, Western blotting, and immunohistochemical staining analysis revealed that ADAM8 messenger RNA expression was significantly upregulated in GC tissues compared with noncancerous tissues (P = 0.004), and that positive ADAM8 expression is much more common in tumor tissues compared with normal tissues (P < 0.001) and is correlated with T stage (P = 0.036), N stage (P = 0.048), vessel invasion (P = 0.002), and a shorter patient overall survival (P = 0.024). In vitro assay indicated that ADAM8 overexpression promoted cell growth and increased migration and invasion abilities by decreasing the p-p38/p-extracellular regulated protein kinases (p-ERK) ratio. In conclusion, ADAM8 promotes GC cell proliferation and invasion, and its expression is positively correlated with poor survival, indicating that it might be a promising target in GC therapy.

Overexpression of Plasminogen Activator Inhibitor-1 in Advanced Gastric Cancer with Aggressive Lymph Node Metastasis

Purpose

The purpose of this study is to investigate differentially expressed genes using DNA microarray between advanced gastric cancer (AGC) with aggressive lymph node (LN) metastasis and that with a more advanced tumor stage but without LN metastasis.

Materials and Methods

Five sample pairs of gastric cancer tissue and normal gastric mucosa were taken from three patients with T3N3 stage (highN) and two with T4N0 stage (lowN). Data from triplicate DNA microarray experiments were analyzed, and candidate genes were identified using a volcano plot that showed ≥ 2-fold differential expression and were significant by Welch's t test (p < 0.05) between highN and lowN. Those selected genes were validated independently by reverse-transcriptase–polymerase chain reaction (RT-PCR) using five AGC patients, and tissue-microarray (TMA) comprising 47 AGC patients.

Results

CFTR, LAMC2, SERPINE2, F2R, MMP7, FN1, TIMP1, plasminogen activator inhibitor-1 (PAI-1), ITGB8, SDS, and TMPRSS4 were commonly up-regulated over 2-fold in highN. REG3A, CD24, ITLN1, and WBP5 were commonly down-regulated over 2-fold in lowN. Among these genes, overexpression of PAI-1 was validated by RT-PCR, and TMA showed 16.7% (7/42) PAI-1 expression in T3N3, but none (0/5) in T4N0 (p=0.393).

Conclusion

DNA microarray analysis and validation by RT-PCR and TMA showed that overexpression of PAI-1 is related to aggressive LN metastasis in AGC.

Expression of A disintegrin and metalloprotease 8 is associated with cell growth and poor survival in colorectal cancer

Background

A disintegrin and metalloprotease 8 (ADAM8) has been reported to be associated with various malignancies. However, no studies have examined ADAM8 association in colorectal cancer (CRC). The aim of this study was to investigate the expression and function of ADAM8 in CRC.

Methods

Expression level of ADAM8 in CRC was evaluated by quantitative RT-PCR, western blot and immunohistochemical staining analysis. The role of ADAM8 in colorectal carcinogenesis was evaluated by in vitro assays. The correlations between ADAM8 status and clinicopathological features including survival were analyzed.

Results

ADAM8 was highly expressed in CRC tissues compared with adjacent normal tissues. Knockdown of ADAM8 in two CRC cell lines resulted in reduced cellular growth and proliferation, and increased apoptosis. Immunohistochemistry analysis showed no significant correlations of ADAM8 protein expression with clinicopathologic features. Survival analysis indicated that patients with ADAM8-positive tumors had worse 5-year overall survival (OS, p = 0.037) and 5-year disease free survival (DFS, p = 0.014) compared with those with ADAM8-negative tumors. Multivariate analysis indicated ADAM8 expression was an independent prognostic factor for both OS and DFS (both p< 0.001). Subgroup analysis showed that 5-year OS of colon cancer, T3-T4 stage and N0 stage was worse for patients with ADAM8-positive tumors than those with ADAM8-negative tumors (p< 0.05). The 5-year DFS in colon cancer, T3-T4 stage, N0 stage, TNM stage II, adenocarcinoma, moderate differentiation and male patient subgroups was also worse for patients with ADAM8-positive tumors than those with ADAM8-negative tumors (p < 0.05).

Conclusions

Our results show that ADAM8 is overexpressed in CRC, promotes cell growth and correlates with worse OS and DFS, and thus could serve as a biomarker for individual CRC patient therapy.

MEK inhibitor effective against proliferation in breast cancer cell

The targeted small-molecule drug AZD6244 is an allosteric, ATP-noncompetitive inhibitor of MEK1/2 that has shown activity against several malignant tumors. Here, we report that AZD6244 repressed cell growth and induced apoptosis and G1-phase arrest in the breast cancer cell lines MDA-MB-231 and HCC1937. Using microRNA (miRNA) arrays and quantitative RT-PCR, we found that miR-203 was up-regulated after AZD6244 treatment. In accordance with bioinformatics and luciferase activity analyses, CUL1 was found to be the direct target of miR-203. Furthermore, miR-203 inhibition and CUL1 overexpression reversed the cytotoxicity of AZD6244 on the MDA-MB-231 and HCC1937 cells. Collectively, our data indicate that miR-203 mediates the AZD6244-induced cytotoxicity of breast cancer cells and that the MEK/ERK/miR-203/CUL1 signaling pathway may participate in this process.

Laser microdissection and two-dimensional difference gel electrophoresis reveal the role of a novel macrophage-capping protein in lymph node metastasis in gastric cancer

To reveal the proteomic background of lymph node metastasis (LNM) in gastric cancer, we performed a proteomic study of tumor and matched nontumor tissues obtained from surgically resected specimens of 22 patients with or without LNM. Using laser microdissection, we recovered specific populations of tumor and nontumor cells. We used two-dimensional difference gel electrophoresis with a large format electrophoresis apparatus to obtain protein expression profiles consisting of 3228 protein spots, and we classified them according to their expression pattern. We found that macrophage-capping protein (CapG) was up-regulated in the tumor tissues of patients with LNM, whereas it showed an equivalent expression level between nontumor and tumor tissues of patients without LNM. It was reported that CapG associated with invasion and metastasis in various malignancies. However, CapG was not investigated in gastric cancer until our study. Western blotting of the laser microdissected tissue samples confirmed up-regulation of CapG in the tumor tissues of patients with LNM. Functional assays demonstrated that CapG promoted tumor cell invasion, but not cell proliferation. The association between CapG expression and LNM is a novel finding in gastric cancer. Further investigation for a prognostic utility of CapG may lead to a risk stratification therapy for gastric cancer.