Lymph node ratio and preoperative CA 19-9 levels predict overall survival and recurrence-free survival in patients with resected pancreatic adenocarcinoma

AIM:Clinicopathologic factors predicting overall survival (OS) would help identify a subset to benefit from adjuvant therapy. METHODS: One hundred and sixty-nine patients patients from 1984 to 2009 with curative resections for pancreatic adenocarcinoma were included. Tumors were staged by American Joint Committee on Cancer 7th edition criteria. Univariate and multivariable analyses were performed using Kaplan-Meier methodology or Cox proportional hazard models. Log-rank tests were performed. Statistical inferences were assessed by two-sided 5% significance level. RESULTS: Median age was 67.1 (57.2-73.0) years with equal gender distribution. Tumors were in the head (89.3%) or body/tail (10.7%). On univariate analysis, adjuvant therapy, lymph node (LN) ratio, histologic grade, negative margin status, absence of peripancreatic extension, and T stage were associated with improved OS. Adjuvant therapy, LN ratio, histologic grade, number of nodes examined, negative LN status, and absence of peripancreatic extension were associated with improved recurrence-free survival (RFS). On multivariable analysis, LN ratio and carbohydrate antigen (CA) 19-9 levels were associated with OS. LN ratio was associated with RFS. CONCLUSION: The LN ratio and CA 19-9 levels are independent prognostic factors following curative resections of pancreatic cancer.

Shanghai Score： A Prognostic and Adjuvant Treatment-evaluating System Constructed for Chinese Patients with Hepatocellular Carcinoma after Curative Resection

Background： For Chinese patients with hepatocellular carcinoma （HCC）, surgical resection is the most important treatment to achieve long-term survival for patients with an early-stage tumor, and yet the prognosis after surgery is diverse. We aimed to construct a scoring system （Shanghai Score） for individualized prognosis estimation and adjuvant treatment evaluation. Methods： A multivariate Cox proportional hazards model was constructed based on 4166 HCC patients undergoing resection during 2001-2008 at Zhongshan Hospital. Age, hepatitis B surface antigen, hepatitis B e antigen, partial thromboplastin time, total bilirubin, alkaline phosphatase, y-glutamyltransferase, a-fetoprotein, tumor size, cirrhosis, vascular invasion, differentiation, encapsulation, and tumor number were finally retained by a backward step-down selection process with the Akaike information criterion. The Harrell＇s concordance index （C-index） was used to measure model performance. Shanghai Score is calculated by summing the products of the 14 variable values times each variable＇s corresponding regression coefficient. Totally 1978 patients from Zhongshan Hospital undergoing resection during 2009-2012, 808 patients from Eastern Hepatobiliary Surgery Hospital during 2008-2010, and 244 patients from Tianjin Medical University Cancer Hospital during 2010-2011 were enrolled as external validation cohorts. Shanghai Score was also implied in evaluating adjuvant treatment choices based on propensity score matching analysis.Results： Shanghai Score showed good calibration and discrimination in postsurgical HCC patients. The bootstrap-corrected C-index （confidence interval [CI]） was 0.74 for overall survival （OS） and 0.68 for recurrence-free survival （RFS） in derivation cohort （4166 patients）, and in the three independent validation cohorts, the CIs for OS ranged 0.70 0.72 and that for RFS ranged 0.63 0.68. Furthermore, Shanghai Score provided evaluation for adjuvant treatment choices （transcatheter arterial chemoembolization or interferon-a）. The identified subset of patients at low risk could be ideal candidates for curative surgery, and subsets of patients at moderate or high risk could be recommended with possible adjuvant therapies after surgery. Finally, a web server with individualized outcome prediction and treatment recommendation was constructed. Conclusions： Based on the largest cohort up to date, we established Shanghai Score - an individualized outcome prediction system specifically designed for Chinese HCC patients after surgery. The Shanghai Score web server provides an easily accessible tool to stratify the prognosis of patients undergoing liver resection for HCC.

Very Low-Level Heteroplasmy mtDNA Variations Are Inherited in Humans

Little is known about the inheritance of very low heteroplasmy mitochondria DNA （mtDNA） variations. Even with the development of new next-generation sequencing methods, the practical lower limit of measured heteroplasmy is still about 1% due to the inherent noise level of the sequencing. In this study, we sequenced the mitochondrial genome of 44 individuals using Illumina high-throughput sequencing technology and obtained high-coverage mitochondria sequencing data. Our study population contains many mother-offspring pairs. This unique study design allows us to bypass the usual heteroplasmy limitation by analyzing the correlation of mutation levels at each position in the mtDNA sequence between maternally related pairs and non-related pairs. The study showed that very low heteroplasmy variants, down to almost 0.1%, are inherited maternally and that this inheritance begins to decrease at about 0.5%, cor- resnondin to abottleneck of about 200 mtDNA.

Immu-Mela:An open resource for exploring immunotherapy-related multidimensional genomic profiles in melanoma

There are increasing studies aimed to reveal genomic hallmarks predictive of immune checkpoint blockade(ICB)treatment response,which generated a large number of data and provided an unprecedented opportunity to identify response-related features and evaluate their robustness across cohorts.However,those valuable data sets are not easily accessible to the research community.To take full advantage of existing large-scale immuno-genomic profiles,we developed Immu-Mela(http://bioinfo.vanderbilt.edu/database/Immu-Mela/),a multidimensional immuno-genomic portal that provides interactive exploration of associations between ICB responsiveness and multi-omics features in melanoma,including genetic,transcriptomics,immune cells,and single-cell populations.Immu-Mela also enables integrative analysis of any two genomic features.We demonstrated the value of Immu-Mela by identifying known and novel genomic features associated with ICB response.In addition,Immu-Mela allows users to upload their data sets(unrestricted to any cancer types)and co-analyze with existing data to identify and validate signatures of interest.Immu-Mela reduces barriers between researchers and complex genomic data,facilitating discoveries in cancer immunotherapy.