A 15-Inflammation-Related Gene Signature Predicts the Prognosis of Patients With Pancreatic Ductal Adenocarcinoma.

Chronic inflammation promotes the development of pancreatic ductal adenocarcinoma (PDAC) and PDAC-related inflammatory tumor microenvironment facilitates tumor growth and metastasis. Thus, we aimed to study the association between inflammatory response and prognosis in patients with PDAC. We conducted the whole transcriptomic sequencing using tissue samples collected from patients diagnosed with PDAC (n = 106) recruited from Shandong Cancer Hospital. We first constructed a prognostic signature using 15 inflammation-related genes in The Cancer Genome Atlas (TCGA) cohort (n = 177) and further validated it in an independent International Cancer Genome Consortium (ICGC) cohort (n = 90) and our in-house cohort. PDAC patients with a higher risk score had poorer overall survival (OS) (P < 0.001; HR, 3.02; 95% CI, 1.94-4.70). The association between the prognostic signature and OS remained significant in the multivariable Cox regression adjusting for age, sex, alcohol exposure, diabetes, and stage (P < 0.001; HR, 2.91; 95% CI, 1.73-4.89). This gene signature also robustly predicted prognosis in the ICGC cohort (P = 0.01; HR, 1.94; 95% CI, 1.14-3.30) and our cohort (P < 0.001; HR, 2.40; 95% CI, 1.45-3.97). Immune subtype C3 (inflammatory) was enriched and CD8+ T cells were higher in patients with a lower risk score (P < 0.05). Furthermore, PDAC patients with higher risk scores were more sensitive to chemotherapy, immunotherapy, and PARP inhibitors (P < 0.05). In sum, we identified a novel gene signature that was associated with inflammatory response for risk stratification, prognosis prediction, and therapy guidance in PDAC patients. Future studies are warranted to validate the clinical utility of the signature.

MAEL in human cancers and implications in prognostication and predicting benefit from immunotherapy over VEGFR/mTOR inhibitors in clear cell renal cell carcinoma: a bioinformatic analysis.

Maelstrom (MAEL), a novel cancer/testis-associated gene, may facilitate the initiation and progression of human malignancies, warranting comprehensive investigations. Single-cell and tissue-bulk transcriptomic data demonstrated higher MAEL expression in testis (spermatogonia/spermatocyte), kidney (proximal tubular cell), and brain (neuron/astrocyte), and corresponding cancers, including testicular germ cell tumor, glioma, papillary renal cell carcinoma, and clear cell renal cell carcinoma (ccRCC). Of these cancers, only in ccRCC did MAEL expression exhibit associations with both recurrence-free survival and overall survival. High MAEL expression was associated with an anti-inflammatory tumor immune microenvironment and VEGFR/mTOR activation in ccRCC tissues and high sensitivities to VEGFR/PI3K-AKT-mTOR inhibitors in ccRCC cell lines. Consistent with these, low rather than high MAEL expression indicated remarkable progression-free survival benefits from immune checkpoint inhibitor (ICI)-based immunotherapies over VEGFR/mTOR inhibitors in two large phase III trials (JAVELIN Renal 101 and CheckMate-025). MAEL is a biologically and clinically significant determinant with potential for prognostication after nephrectomy and patient selection for VEGFR/mTOR inhibitors and immunotherapy-based treatments.

Complement and coagulation cascades pathway-related signature as a predictor of immunotherapy in metastatic urothelial cancer.

BACKGROUND: Immune checkpoint inhibitors (ICIs) have shown efficacy in patients with metastatic urothelial cancer (mUC), however, only a small subset of patients could benefit from ICIs. Identifying predictive biomarkers of ICIs in patients with mUC is clinical meaningful for patient stratification and administration. METHODS: Clinical and transcriptomic data of mUC patients treated with ICIs from mUC cohort (IMvigor210 study) was utilized to explore the predictive biomarkers. LASSO Cox regression was performed to construct a predictive model. The predictive model was trained and tested in the mUC cohort, and then exploratively tested in clear cell renal cell carcinoma (ccRCC) and melanoma cohorts in which patients also received ICIs regimens. RESULTS: The differentially expressed genes (DEGs) in complement and coagulation cascades pathway (CCCP) were mainly enriched in non-responders of ICIs in the mUC cohort. A CCCP risk score was constructed based on the DEGs in CCCP. Patients with a low-risk score were more responsive to ICIs and had better overall survival (OS) than those with a high-risk score in the training set (HR, 0.38; 95%CI, 0.27-0.53, P<0.001) and the test set (HR, 0.34; 95%CI, 0.17-0.71, P=0.003). The association between the CCCP risk score and OS remained significant in the multivariable cox regression by adjusting PD-L1 expression and TMB (P<0.05). In addition, there was no difference for OS in the bladder cancer patients without ICIs (TCGA-BLCA cohort, HR, 0.76, 95%CI, 0.49-1.18, P=0.22), suggesting a predictive but not prognostic effect of the risk score. For the exploratory analysis, consistent results were observed that low-risk group showed superior OS in ccRCC cohort (HR, 0.52, 95%CI, 0.37-0.75, P<0.001) and melanoma cohort (HR, 0.27, 95%CI, 0.12-0.62, P=0.001). CONCLUSIONS: Our study showed that the CCCP risk score is an independent biomarker that predicts the efficacy of ICIs in mUC patients. The patients with a low-risk score tend to have a better response to ICIs and a longer life time probably due to the immune-activated TME. Further studies are needed to validate the clinical utility of the seven-gene signature.

A prognostic and immunotherapeutic predictive model based on the cell-originated characterization of tumor microenvironment in lung adenocarcinoma.

Tumor microenvironment (TME) plays a crucial role in predicting prognosis and response to therapy in lung cancer. Our study established a prognostic and immunotherapeutic predictive model, the tumor immune cell score (TICS), by differentiating cell origins in lung adenocarcinoma (LUAD) based on the transcriptomic data of 2,510 patients in 14 independent cohorts, including 12 public datasets and two in-house cohorts. The high TICS was associated with prolonged overall survival (OS), especially in the early-stage LUAD. For the advanced-stage LUAD, high TICS predicted a superior OS in patients who were treated with immunotherapy instead of chemotherapy or TKI. The result suggested that TICS could serve as an indicator for the prognostic stratification management of patients in the early-stage LUAD, and as a potential guide for therapeutic decision-marking in the advanced-stage LUAD. Our findings provided an insight into prognosis stratification and potential guidance for treatment strategy selection.

Development and validation of an inflammatory response-related gene and clinical factor-based signature for predicting prognosis in gastric cancer.

Background: Gastric cancer (GC) is an aggressive disease that requires prognostic tools to aid in clinical management. The prognostic power of clinical features is unsatisfactory, which might be improved by combining mRNA-based signatures. Inflammatory response is widely associated with cancer development and treatment response. It is worth exploring the prognostic performance of inflammatory-related genes plus clinical factors in GC. Methods: An 11-gene signature was trained using the least absolute shrinkage and selection operator (LASSO) based on the messenger RNA (mRNA) and overall survival (OS) data of The Cancer Genome Atlas-stomach adenocarcinoma (TCGA-STAD) cohort. A nomogram was established using the signature and clinical factors with a significant linkage with OS and was validated in 3 independent cohorts (GSE15419, GSE13861, and GSE66229) via calculating the area under the receiver operator characteristic curve (AUC). The association between the signature and immunotherapy efficacy was explored in the ERP107734 cohort. Results: A high risk score was associated with shorter OS in both the training and the validation sets (the AUC for 1-, 3-, 5-year in TCGA-STAD cohort: 0.691, 0.644, and 0.707; GSE15459: 0.602, 0.602, and 0.650; GSE13861: 0.648, 0.611, and 0.647; GSE66229: 0.661, 0.630, and 0.610). Its prognostic power was improved by combining clinical factors including age, sex, and tumor stage (the AUC for 1-, 3-, 5-year in TCGA-STAD cohort: 0.759, 0.706, and 0.742; GSE15459: 0.773, 0.786, and 0.803; GSE13861: 0.749, 0.881, and 0.795; GSE66229: 0.773, 0.735, and 0.722). Moreover, a low-risk score was associated with a favorable response to pembrolizumab monotherapy in the advanced setting (AUC =0.755, P=0.010). Conclusions: In GCs, the inflammatory response-related gene-based signature was related to immunotherapy efficacy, and its risk score plus clinical features yielded robust prognostic power. With prospective validation, this model may improve the management of GC by enabling risk stratification and the prediction of response to immunotherapy.

A pyroptosis-related gene signature for prognosis prediction in hepatocellular carcinoma.

Introduction: Hepatocellular carcinoma (HCC) is one of the most invasive cancers with a low 5-year survival rate. Pyroptosis, a specialized form of cell death, has shown its association with cancer progression. However, its role in the prognosis of HCC has not been fully understood. Methods: In our study, clinical information and mRNA expression for 1076 patients with HCC were obtained from the five public cohorts. Pyroptotic clusters were generated by unsupervised clustering based on 40 pyroptosis-related genes (PRGs) in the TCGA and ICGC cohort. A pyroptosis-related signature was constructed using least absolute shrinkage and selection operator (LASSO) regression according to differentially expressed genes (DEGs) of pyroptotic clusters. The signature was then tested in the validation cohorts (GES10142 and GSE14520) and subsequently validated in the CPTAC cohort (n=159) at both mRNA and protein levels. Response to sorafenib was explored in GSE109211. Results: Three clusters were identified based on the 40 PRGs in the TCGA cohort. A total of 24 genes were selected based on DEGs of the above three pyroptotic clusters to construct the pyroptotic risk score. Patients with the high-risk score showed shorter overall survival (OS) compared to those with the low-risk score in the training set (P<0.001; HR, 3.06; 95% CI, 2.22-4.24) and the test set (P=0.008; HR, 1.61; 95% CI, 1.13-2.28). The predictive ability of the risk score was further confirmed in the CPTAC cohort at both mRNAs (P<0.001; HR, 2.99; 95% CI, 1.67-5.36) and protein levels (P<0.001; HR, 2.97; 95% CI 1.66-5.31). The expression of the model genes was correlated with immune cell infiltration, angiogenesis-related genes, and sensitivity to antiangiogenic therapy (P<0.05). Discussion: In conclusion, we established a prognostic signature of 24 genes based on pyroptosis clusters for HCC patients, providing insight into the risk stratification of HCC.

bITH, a blood-based metric of intratumor heterogeneity, is associated with clinical response to immune checkpoint blockade in non-small cell lung cancer.

BACKGROUND: Intratumor heterogeneity (ITH) has been associated with poor prognosis in advanced non-small cell cancer (NSCLC) patients receiving immune checkpoint blockade (ICB) therapies. However, there is currently no evidence supporting an ITH metric as a predictor of clinical benefit from ICB. The unique advantages of blood make it a promising material for ITH estimation and relevant applications. This study aims to develop and validate a blood-based ITH index for predicting ICB response. METHODS: NSCLC patients from the OAK and POPLAR clinical trials were used as the training cohorts for algorithm development. Survival analyses with overall survival (OS) and progression-free survival (PFS) as endpoints were performed to assess clinical response. The predictive value of bITH was subsequently validated with an independent cohort of 42 NSCLC patients treated with PD-1 blockade. FINDINGS: bITH was significantly associated with the differential OS and PFS elicited by atezolizumab vs. docetaxel in both univariable and multivariable analyses in the OAK patients, suggesting bITH as an independent predictor for response to ICB. Moreover, compared with blood tumor mutation burden (bTMB), bITH enabled greater OS segregation and comparable PFS segregation, and obtained a predictive role regardless of bTMB status. Moreover, the association between bITH and PFS was validated with an independent cohort. INTERPRETATION: Patients with low blood-based ITH metric manifest significant OS and PFS benefit from immunotherapy versus chemotherapy. Future research is awaited to corroborate our findings and to enrich the clinical utility of ITH. FUNDING: This study was supported by the National Natural Science Foundation of China (Nos. 81972718 and 81572321), the Natural Scientific Foundation of Zhejiang Province, China (No. LY19H160007), the Science and Technology Program for Health and Medicine in Zhejiang Province, China (No. 2021KY541), the Scientific Research Project, Science and Technology Department of Sichuan Province (No. 21YYJC1616), the Scientific Research Project, Sichuan Medical Association (No. S20002), Wu Jieping Medical Foundation (No. 320.6750), and 2018 Entrepreneurial Leading Talent of Guangzhou Huangpu District and Guangzhou Development District (No. 2022-L023).

Senescence-related genes define prognosis, immune contexture, and pharmacological response in gastric cancer.

As one of the prevalent tumors worldwide, gastric cancer (GC) has obtained sufficient attention in its clinical management and prognostic stratification. Senescence-related genes are involved in the tumorigenesis and progression of GC. A machine learning algorithm-based prognostic signature was developed from six senescence-related genes including SERPINE1, FEN1, PDGFRB, SNCG, TCF3, and APOC3. The TCGA-STAD cohort was utilized as a training set while the GSE84437 and GSE13861 cohorts were analyzed for validation. Immune cell infiltration and immunotherapy efficacy were investigated in the PRJEB25780 cohort. Data from the genomics of drug sensitivity in cancer (GDSC) database revealed pharmacological response. The GSE13861 and GSE54129 cohorts, single-cell dataset GSE134520, and The Human Protein Atlas (THPA) database were utilized for localization of the key senescence-related genes. Association of a higher risk-score with worse overall survival (OS) was identified in the training cohort (TCGA-STAD, P<0.001; HR = 2.03, 95% CI, 1.45-2.84) and the validation cohorts (GSE84437, P = 0.005; HR = 1.48, 95% CI, 1.16-1.95; GSE13861, P = 0.03; HR = 2.23, 95% CI, 1.07-4.62). The risk-score was positively correlated with densities of tumor-infiltrating immunosuppressive cells (P < 0.05) and was lower in patients who responded to pembrolizumab monotherapy (P = 0.03). Besides, patients with a high risk-score had higher sensitivities to the inhibitors against the PI3K-mTOR and angiogenesis (P < 0.05). Expression analysis verified the promoting roles of FEN1, PDGFRB, SERPINE1, and TCF3, and the suppressing roles of APOC3 and SNCG in GC, respectively. Immunohistochemistry staining and single-cell analysis revealed their location and potential origins. Taken together, the senescence gene-based model may potentially change the management of GC by enabling risk stratification and predicting response to systemic therapy.

Tumor immune contexture predicts recurrence after prostatectomy and efficacy of androgen deprivation and immunotherapy in prostate cancer.

BACKGROUND: Prostate cancer is one of the most common cancers in men with notable interpatient heterogeneity. Implications of the immune microenvironment in predicting the biochemical recurrence-free survival (BCRFS) after radical prostatectomy and the efficacy of systemic therapies in prostate cancer remain ambiguous. METHODS: The tumor immune contexture score (TICS) involving eight immune contexture-related signatures was developed using seven cohorts of 1120 patients treated with radical prostatectomy (training: GSE46602, GSE54460, GSE70769, and GSE94767; validation: GSE70768, DKFZ2018, and TCGA). The association between the TICS and treatment efficacy was investigated in GSE111177 (androgen deprivation therapy [ADT]) and EGAS00001004050 (ipilimumab). RESULTS: A high TICS was associated with prolonged BCRFS after radical prostatectomy in the training (HR = 0.32, 95% CI 0.24-0.45, P < 0.001) and the validation cohorts (HR = 0.45, 95% CI 0.32-0.62, P < 0.001). The TICS showed stable prognostic power independent of tumor stage, surgical margin, pre-treatment prostatic specific antigen (PSA), and Gleason score (multivariable HR = 0.50, 95% CI 0.39-0.63, P < 0.001). Adding the TICS into the prognostic model constructed using clinicopathological features significantly improved its 1/2/3/4/5-year area under curve (P < 0.05). A low TICS was associated with high homologous recombination deficiency scores, abnormally activated pathways concerning DNA replication, cell cycle, steroid hormone biosynthesis, and drug metabolism, and fewer tumor-infiltrating immune cells (P < 0.05). The patients with a high TICS had favorable BCRFS with ADT (HR = 0.25, 95% CI 0.06-0.99, P = 0.034) or ipilimumab monotherapy (HR = 0.23, 95% CI 0.06-0.81, P = 0.012). CONCLUSIONS: Our study delineates the associations of tumor immune contexture with molecular features, recurrence after radical prostatectomy, and the efficacy of ADT and immunotherapy. The TICS may improve the existing risk stratification systems and serve as a patient-selection tool for ADT and immunotherapy in prostate cancer.

A prognostic 15-gene model based on differentially expressed genes among metabolic subtypes in diffuse large B-cell lymphoma.

The outcomes of patients with diffuse large B-cell lymphoma (DLBCL) vary widely, and about 40% of them could not be cured by the standard first-line treatment, R-CHOP, which could be due to the high heterogeneity of DLBCL. Here, we aim to construct a prognostic model based on the genetic signature of metabolic heterogeneity of DLBCL to explore therapeutic strategies for DLBCL patients. Clinical and transcriptomic data of one training and four validation cohorts of DLBCL were obtained from the GEO database. Metabolic subtypes were identified by PAM clustering of 1,916 metabolic genes in the 7 major metabolic pathways in the training cohort. DEGs among the metabolic clusters were then analyzed. In total, 108 prognosis-related DEGs were identified. Through univariable Cox and LASSO regression analyses, 15 DEGs were used to construct a risk score model. The overall survival (OS) and progression-free survival (PFS) of patients with high risk were significantly worse than those with low risk (OS: HR 2.86, 95%CI 2.04-4.01, p < 0.001; PFS: HR 2.42, 95% CI 1.77-3.31, p < 0.001). This model was also associated with OS in the four independent validation datasets (GSE10846: HR 1.65, p = 0.002; GSE53786: HR 2.05, p = 0.02; GSE87371: HR 1.85, p = 0.027; GSE23051: HR 6.16, p = 0.007) and PFS in the two validation datasets (GSE87371: HR 1.67, p = 0.033; GSE23051: HR 2.74, p = 0.049). Multivariable Cox analysis showed that in all datasets, the risk model could predict OS independent of clinical prognosis factors (p < 0.05). Compared with the high-risk group, patients in the low-risk group predictively respond to R-CHOP (p = 0.0042), PI3K inhibitor (p < 0.05), and proteasome inhibitor (p < 0.05). Therefore, in this study, we developed a signature model of 15 DEGs among 3 metabolic subtypes, which could predict survival and drug sensitivity in DLBCL patients.

A DNA Damage Response Related Signature to Predict Prognosis in Patients with Acute Myeloid Leukemia.

The prognosis of acute myeloid leukemia (AML) is disappointing in most subtypes and varies widely. DNA damage response (DDR) is associated with prognosis and immunotherapy in multiple cancers. Here, we identify a signature of eight DDR-related genes associated with overall survival, which stratifies AML patients into high- and low-risk groups. Patients in low-risk group were more likely to respond to sorafenib. The signature could be an independent prognostic predictor for patients treated with ADE and ADE plus gemtuzumab ozogamicin. Therefore, this DDR prognostic signature might be applied to prognostic stratification and treatment selection in AML patients, which warrants further studies.

A prognostic signature based on adenosine metabolism related genes for ovarian cancer.

Background: Ovarian cancer is one of the most common cause of cancer death in women due to its late diagnosis and susceptibility to drug resistance. Adenosine (ADO) signaling plays a key role in immune activity and tumor progression. In this study, we constructed a signature of ADO metabolism related genes expression in patients with ovarian cancer. Methods: A total of 372 ovarian cancer patients from TCGA was used as training set and 1,137 patients from six GEO datasets were as validation set. The gene expression and drug response inhibitory concentration values for ovarian cancer cell line from GDSC were used for drug sensitivity analysis. The non-negative matrix factorization algorithm and ssGSVA were used to construct the ADO score. Results: Patients with high ADO score had shorter overall survival (OS) than those with low ADO score in both training set (HR = 1.42, 95% CI, 1.06-1.88) and validation sets (pooled HR = 1.24, 95% CI = 1.02-1.51). In GSEA analysis, genes in ATP synthesis related pathways were enriched in the low ADO score group (adjusted P value = 0.02). Further, we observed that the high ADO score group had significantly higher levels of most cancer hallmark signatures (all adjusted P values < 0.01) and T cell dysfunction and exclusion signatures than the low ADO score group (all adjusted P values < 0.001). Patients with lower ADO score tended to be sensitive to common drugs including Olaparib and Paclitaxel (adjusted P values = 0.05 and 0.04, respectively). Conclusions: In conclusion, the established ADO signature could be used as a prognostic biomarker to stratify ovarian cancer patients and had the potential to guide the drug exploitation and personalized therapy selection.

The mechanism of oxymatrine on atopic dermatitis in mice based on SOCS1/JAK-STAT3 pathway.

Based on the suppressor of cytokine signaling 1 (SOCS1)/Janus kinase (JAK)/signal transducer and activator of transcription 3 (STAT3) pathway, the mechanism of oxymatrine in the treatment of atopic dermatitis (AD) was preliminarily explored in this study. C57BL/6 mice were induced to establish AD model by smearing carbotriol (MC903) on their back. The AD mice were randomly divided into model group, oxymatrine groups with three dosages (25, 50 and 100 mg/kg), (n = 10). Oxymatrine groups were intragastric administered once daily for 14 days. The same volume of saline was given in the normal control group and model group once daily for 14 days. Subsequently, HE staining was used to observe the pathological changes of skin tissue, ELISA was used to detect the levels of serum inflammatory factors including interleukin-4, 6 and 17 (IL-4, IL-6, and IL-17), tumor necrosis factor-α (TNF-α) and immunoglobulin E (IgE). Immunohistochemistry was used to detect the expression of suppressor of cytokine signaling 1 and CD3 in skin tissue, and Western blotting was used to detect the proteins in suppressor of cytokine signaling 1/JAK-STAT3 pathway. Compared with the normal control group, the pathological damage of mice in the model group, such as skin hyperplasia, edema, congestion and inflammatory infiltration, aggravated increased significantly. And the expression of serum inflammatory factors, CD3 positive expression and JAK-STAT3 pathway protein in the model group were increased (p < .05), and the expression of suppressor of cytokine signaling 1 protein (p < .05) was decreased. Compared with the model group, the above pathological damage of the mice was reduced, and the serum inflammatory factors, JAK-STAT3 pathway protein, and CD3 positive expression were decreased as a dose-dependant manner (p < .05), and the expression of suppressor of cytokine signaling 1 protein was increased as a dose-dependent manner (p < .05). Oxymatrine can improve the skin inflammation symptoms of AD mice by up regulating the expression of suppressor of cytokine signaling 1, inhibiting the activation of JAK-STAT3 pathway and blocking the activation of T lymphocytes.

Circulating tumor DNA clearance predicts prognosis across treatment regimen in a large real-world longitudinally monitored advanced non-small cell lung cancer cohort.

BACKGROUND: Although growth advantage of certain clones would ultimately translate into a clinically visible disease progression, radiological imaging does not reflect clonal evolution at molecular level. Circulating tumor DNA (ctDNA), validated as a tool for mutation detection in lung cancer, could reflect dynamic molecular changes. We evaluated the utility of ctDNA as a predictive and a prognostic marker in disease monitoring of advanced non-small cell lung cancer (NSCLC) patients. METHODS: This is a multicenter prospective cohort study. We performed capture-based ultra-deep sequencing on longitudinal plasma samples utilizing a panel consisting of 168 NSCLC-related genes on 949 advanced NSCLC patients with driver mutations to monitor treatment responses and disease progression. The correlations between ctDNA and progression-free survival (PFS)/overall survival (OS) were performed on 248 patients undergoing various treatments with the minimum of 2 ctDNA tests. RESULTS: The results of this study revealed that higher ctDNA abundance (P=0.012) and mutation count (P=8.5×10-4) at baseline are associated with shorter OS. We also found that patients with ctDNA clearance, not just driver mutation clearance, at any point during the course of treatment were associated with longer PFS (P=2.2×10-16, HR 0.28) and OS (P=4.5×10-6, HR 0.19) regardless of type of treatment and evaluation schedule. CONCLUSIONS: This prospective real-world study shows that ctDNA clearance during treatment may serve as predictive and prognostic marker across a wide spectrum of treatment regimens.

Evaluation of Rosemont criteria for non-calcific chronic pancreatitis (NCCP) based on histopathology - A retrospective study.

BACKGROUND: Rosemont classification for chronic pancreatitis has not been evaluated specifically in non-calcific chronic pancreatitis (NCCP) patients and to this date, it has not been correlated with the gold standard namely histopathology. OBJECTIVE: To assess the correlation of EUS Rosemont criteria for NCCP with histopathology from surgical specimens and evaluate the impact of age, sex, BMI, smoking and alcohol on Rosemont classification. METHODS: Adult patients undergoing TPIAT for NCCP between July 2009 and January 2013 were identified from our institutional database. The presence or absence of standard and Rosemont (major and minor) criteria were determined by expert endosonographers using linear endosonography. Patients were categorized into normal, indeterminate and suggestive with CP based on Rosemont classification. Histology was obtained at time of TPIAT from the resected pancreas by wedge biopsy of head, body and tail. All histopathology were re-reviewed by a GI pathologist blinded to endosonographic features and clinical outcomes. Available pancreatic tissue was graded for severity of intralobular and perilobular pancreatic fibrosis by the Ammann classification system. RESULTS: 50 patients with NCCP (42 females, mean age± SD = 37.9 ± 10.8) underwent TPIAT with preoperative EUS during the study period. Univariate analysis of features such as age, sex, BMI, smoking and alcohol history showed no significant difference between patients identified as normal and those identified as indeterminate/suggestive (p > 0.05). Rosemont "Normal" was poor in excluding CP as 5/9 patients (55.5%) had CP on histopathology. 25/26 patients (96.2%) with features "suggestive" of CP had evidence of CP on histopathology. 12/15 patients (80.0%) with "indeterminate" features had CP on histopathology. CONCLUSIONS: Rosemont classification can be used independent of patient characteristics (age, sex and BMI) and environmental factors (smoking and alcohol exposure). In our cohort, Rosemont classification was strongly predictive of CP in patients with features "suggestive" of CP. However, "normal" Rosemont classification had poor correlation in this study. This is maybe due to lack of true comparator "normal" pancreas which cannot be obtained reasonably. The strength of agreement for diagnosis of CP was substantial between the standard and Rosemont criteria.

Diagnostic Performance of Endoscopic Ultrasound (EUS) for Non-Calcific Chronic Pancreatitis (NCCP) Based on Histopathology.

OBJECTIVES: Studies correlating endoscopic ultrasound (EUS) with histopathology for chronic pancreatitis (CP) are limited by small sample size, and/or inclusion of many patients without CP, limiting applicability to patients with painful CP. The aim of this study was to assess correlation of standard EUS features for CP with surgical histopathology in a large cohort of patients with non-calcific CP (NCCP). METHODS: Adult patients undergoing total pancreatectomy and islet autotransplantation (TPIAT) for NCCP, between 2008 and 2013, with EUS <1 year before surgery. Histology from resected pancreas at the time of TPIAT (from head, body, and tail) was graded by a GI pathologist blinded to the EUS features. A fibrosis score (FS) ≥2 was abnormal, and FS≥6 was considered severe fibrosis. A multivariate regression analysis for the EUS features predicting fibrosis, after taking age, sex, smoking, and body mass index into consideration, was performed. A quantitative receiver operating characteristic (ROC) curve analysis was performed and Spearman rank correlation co-efficient (r) was calculated. RESULTS: 68 patients (56 females, mean±s.d. age-38.77±10.92) underwent TPIAT for NCCP with pre-operative EUS. ROC curve showed that four or more EUS features provided the best balance of sensitivity (61%), specificity (75%), and accuracy (63%). Although significant, correlation between standard EUS features and degree of fibrosis was poor (r=0.24, P<0.05). Multivariate regression analysis showed that main pancreatic duct irregularity was the only independent EUS feature (P=0.02) which predicted CP. CONCLUSIONS: Correlation between standard EUS features and histopathology is poor in NCCP. MPD irregularity is an independent predictor for NCCP.

Diagnostic Performance of Contrast-Enhanced MRI With Secretin-Stimulated MRCP for Non-Calcific Chronic Pancreatitis: A Comparison With Histopathology.

OBJECTIVES: Diagnosis of non-calcific chronic pancreatitis (NCCP) in patients presenting with chronic abdominal pain is challenging and controversial. Contrast-enhanced magnetic resonance imaging (MRI) with secretin-stimulated MRCP (sMRCP) offers a safe and noninvasive modality to diagnose mild CP, but its findings have not been correlated with histopathology. We aimed to assess the correlation of a spectrum of MRI/sMRCP findings with surgical histopathology in a cohort of NCCP patients undergoing total pancreatectomy with islet autotransplantation (TPIAT). METHODS: Adult patients undergoing TPIAT for NCCP between 2008 and 2013 were identified from our institution's surgery database and were included if they had MRI/sMRCP within a year before surgery. Histology was obtained from resected pancreas at the time of TPIAT by wedge biopsy of head, body, and tail, and was graded by a gastrointestinal pathologist who was blinded to the imaging features. A fibrosis score (FS) of 2 or more was considered as abnormal, with FS ≥6 as severe fibrosis. A multivariate regression analysis was performed for MRI features predicting fibrosis, after taking age, sex, smoking, alcohol, and body mass index (BMI) into consideration. A quantitative receiver operating characteristic (ROC) curve analysis was performed and Spearman rank correlation coefficient (r) was calculated. RESULTS: Fifty-seven patients (females=49, males=8) with NCCP and MRI/sMRCP were identified. ROC curve analysis showed that two or more MRI/sMRCP features provided the best balance of sensitivity (65%), specificity (89%), and accuracy (68%) to differentiate abnormal (FS≥2) from normal pancreatic tissue. Two or more features provided the best cutoff (sensitivity 88%, specificity 78%) for predicting severe fibrosis (FS≥6). There was a significant correlation between the number of features and severity of fibrosis (r=0.6, P<0.0001). A linear regression after taking age, smoking, and BMI into consideration showed that main pancreatic duct irregularity, T1-weighted signal intensity ratio between pancreas and paraspinal muscle, and duodenal filling after secretin injection to be significant independent predictors of fibrosis. CONCLUSIONS: A strong correlation exists between MRI/sMRCP findings and histopathology of NCCP.

Association of roasting meat intake with the risk of esophageal squamous cell carcinoma of Kazakh Chinese via affecting promoter methylation of p16 gene.

BACKGROUND: Esophageal squamous cell carcinoma (ESCC) incidence is high in Kazak Autonomous Prefecture, Xinjiang, China. Roasting food has been reported to be related with the risk of various cancers and is very popular in the area, and may be related with the risk of ESCC. The promoter methylation inactivation of p16 gene can increase the risk of ESCC. Thus, we want to know whether long-term roasting food is related with the risk of ESCC by effecting the promoter methylation of p16 gene. MATERIALS AND METHODS: Ninety ESCC patients and 60 healthy subjects were recruited from Kazak Autonomous Prefecture. MassARRAY was used to detect p16 promoter methylation in ESCC tissues, as well as in normal esophageal tissues. The association between the p16 promoter methylation and daily roasting meat intake was examined. RESULTS: Daily roasting meat intake was related with the risk of ESCC (p<0.01) and the mean CpG methylation rates of p16 promoter (p<0.01). In ESCC patients, the mean methylation rates of CpG 11-12 and CpG 33-34-35 were 29.4% and 37.4%, respectively, which was significantly higher than the rates in normal esophageal tissues (16.7% and 12.4%, respectively; p<0.01). The methylation of p16 promoter is also related with daily roasting meat intake (p<0.01) in Kazakh Chinese with ESCC. For the CpG methylation of the p16 promoter in the well, moderately and poorly differentiated ESCC, there are significant differences (p<0.05) for the 19 CpG units in the ESCC and controls. CONCLUSION: Roasting meat intake was associated with the risk of ESCC via effects on the methylation of p16 promoter. These results suggest roasting food intake should be limited in the diet.

Gene chip technology used in the detection of HPV infection in esophageal cancer of Kazakh Chinese in Xinjiang Province.

This study was aimed to screen human papillomavirus (HPV) types associated with esophageal squamous cell carcinoma of Kazakh in Xinjiang using the gene chip technique and study the clinical significance of this application. The DNAs were collected from esophageal squamous cell carcinoma tissues and healthy esophageal mucosa of Kazakh adults in Xinjiang, and amplified firstly using HPV MY09/11 and then using HPV G5+/6+ to screen positive HPV specimens. These positive specimens were further detected by the gene chip technique to screen highly pathogenic HPV types. After determination with nested PCR amplification with HPV MY09/11 and G5+/6+, the infection rate of HPV was 66.67% in the esophageal squamous cell carcinoma group and 12.12% in the healthy control group. By testing the positive HPV specimens from the esophageal squamous cell carcinoma group, the infection rate of HPV16 was 97.72% and the co-infection rate of HPV16 and HPV18 was 2.27%. HPV16 infection may be involved in the development of esophageal squamous cell carcinoma in Xinjiang Hazakh adults.