Robotic Living Donor Right Hepatectomy: A Systematic Review and Meta-Analysis

The introduction of robotics in living donor liver transplantation has been revolutionary. We aimed to examine the safety of robotic living donor right hepatectomy (RLDRH) compared to open (ODRH) and laparoscopic (LADRH) approaches. A systematic review was carried out in Medline and six additional databases following PRISMA guidelines. Data on morbidity, postoperative liver function, and pain in donors and recipients were extracted from studies comparing RLDRH, ODRH, and LADRH published up to September 2020; PROSPERO (CRD42020214313). Dichotomous variables were pooled as risk ratios and continuous variables as weighted mean differences. Four studies with a total of 517 patients were included. In living donors, the postoperative total bilirubin level (MD: −0.7 95%CI −1.0, −0.4), length of hospital stay (MD: −0.8 95%CI −1.4, −0.3), Clavien–Dindo complications I–II (RR: 0.5 95%CI 0.2, 0.9), and pain score at day > 3 (MD: −0.6 95%CI −1.6, 0.4) were lower following RLDRH compared to ODRH. Furthermore, the pain score at day > 3 (MD: −0.4 95%CI −0.8, −0.09) was lower after RLDRH when compared to LADRH. In recipients, the postoperative AST level was lower (MD: −0.5 95%CI −0.9, −0.1) following RLDRH compared to ODRH. Moreover, the length of stay (MD: −6.4 95%CI −11.3, −1.5) was lower after RLDRH when compared to LADRH. In summary, we identified low- to unclear-quality evidence that RLDRH seems to be safe and feasible for adult living donor liver transplantation compared to the conventional approaches. No postoperative deaths were reported

No evidence that genetic variation in the myeloid-derived suppressor cell pathway influences ovarian cancer survival

BACKGROUND: The precise mechanism by which the immune system is adversely affected in cancer patients remains poorly understood, but the accumulation of immune suppressive/pro-tumorigenic myeloid-derived suppressor cells (MDSCs) is thought to be one prominent mechanism contributing to immunologic tolerance of malignant cells in epithelial ovarian cancer (EOC). To this end, we hypothesized genetic variation in MDSC pathway genes would be associated with survival after EOC diagnoses. METHODS: We measured the hazard of death due to EOC within 10 years of diagnosis, overall and by invasive subtype, attributable to SNPs in 24 genes relevant in the MDSC pathway in 10,751 women diagnosed with invasive EOC. Versatile Gene-based Association study (VEGAS) and the Admixture Likelihood method (AML), were used to test gene and pathway associations with survival. RESULTS: We did not identify individual SNPs that were significantly associated with survival after correction for multiple testing (p<3.5 x 10-5), nor did we identify significant associations between the MDSC pathway overall, or the 24 individual genes and EOC survival. CONCLUSIONS: In this well-powered analysis, we observed no evidence that inherited variations in MDSC-associated SNPs, individual genes, or the collective genetic pathway contributed to EOC survival outcomes. IMPACT: Common inherited variation in genes relevant to MDSCs were not associated with survival in women diagnosed with invasive EOC

Network-Based Integration of GWAS and Gene Expression Identifies a HOX-Centric Network Associated with Serous Ovarian Cancer Risk

BACKGROUND: Genome-wide association studies (GWAS) have so far reported 12 loci associated with serous epithelial ovarian cancer (EOC) risk. We hypothesized that some of these loci function through nearby transcription factor (TF) genes and that putative target genes of these TFs as identified by coexpression may also be enriched for additional EOC risk associations. METHODS: We selected TF genes within 1 Mb of the top signal at the 12 genome-wide significant risk loci. Mutual information, a form of correlation, was used to build networks of genes strongly coexpressed with each selected TF gene in the unified microarray dataset of 489 serous EOC tumors from The Cancer Genome Atlas. Genes represented in this dataset were subsequently ranked using a gene-level test based on results for germline SNPs from a serous EOC GWAS meta-analysis (2,196 cases/4,396 controls). RESULTS: Gene set enrichment analysis identified six networks centered on TF genes (HOXB2, HOXB5, HOXB6, HOXB7 at 17q21.32 and HOXD1, HOXD3 at 2q31) that were significantly enriched for genes from the risk-associated end of the ranked list (P < 0.05 and FDR < 0.05). These results were replicated (P < 0.05) using an independent association study (7,035 cases/21,693 controls). Genes underlying enrichment in the six networks were pooled into a combined network. CONCLUSION: We identified a HOX-centric network associated with serous EOC risk containing several genes with known or emerging roles in serous EOC development. IMPACT: Network analysis integrating large, context-specific datasets has the potential to offer mechanistic insights into cancer susceptibility and prioritize genes for experimental characterization

Polygenic risk modeling for prediction of epithelial ovarian cancer risk

Polygenic risk scores (PRS) for epithelial ovarian cancer (EOC) have the potential to improve risk stratification. Joint estimation of Single Nucleotide Polymorphism (SNP) effects in models could improve predictive performance over standard approaches of PRS construction. Here, we implemented computationally efficient, penalized, logistic regression models (lasso, elastic net, stepwise) to individual level genotype data and a Bayesian framework with continuous shrinkage, "select and shrink for summary statistics" (S4), to summary level data for epithelial non-mucinous ovarian cancer risk prediction. We developed the models in a dataset consisting of 23,564 non-mucinous EOC cases and 40,138 controls participating in the Ovarian Cancer Association Consortium (OCAC) and validated the best models in three populations of different ancestries: prospective data from 198,101 women of European ancestries; 7,669 women of East Asian ancestries; 1,072 women of African ancestries, and in 18,915 BRCA1 and 12,337 BRCA2 pathogenic variant carriers of European ancestries. In the external validation data, the model with the strongest association for non-mucinous EOC risk derived from the OCAC model development data was the S4 model (27,240 SNPs) with odds ratios (OR) of 1.38 (95% CI: 1.28-1.48, AUC: 0.588) per unit standard deviation, in women of European ancestries; 1.14 (95% CI: 1.08-1.19, AUC: 0.538) in women of East Asian ancestries; 1.38 (95% CI: 1.21-1.58, AUC: 0.593) in women of African ancestries; hazard ratios of 1.36 (95% CI: 1.29-1.43, AUC: 0.592) in BRCA1 pathogenic variant carriers and 1.49 (95% CI: 1.35-1.64, AUC: 0.624) in BRCA2 pathogenic variant carriers. Incorporation of the S4 PRS in risk prediction models for ovarian cancer may have clinical utility in ovarian cancer prevention programs

Brivanib in combination with Notch3 silencing shows potent activity in tumour models

Background: Sorafenib is the first targeted agent proven to improve survival of patients with advanced hepatocellular carcinoma (HCC) and it has been used in first line treatments with heterogeneous response across patients. Most of the promising agents evaluated in first-line or second-line phase III trials for HCC failed to improve patient survival. The absence of molecular characterisation, including the identification of pathways driving resistance might be responsible for these disappointing results. Methods: 2D DIGE and MS analyses were used to reveal proteomic signatures resulting from Notch3 inhibition in HepG2 cells, combined with brivanib treatment. The therapeutic potential of Notch3 inhibition combined with brivanib treatment was also demonstrated in a rat model of HCC and in cell lines derived from different human cancers. Results: Using a proteomic approach, we have shown that Notch3 is strongly involved in brivanib resistance through a p53-dependent regulation of enzymes of the tricarboxylic acid (TCA), both in vitro and in vivo. Conclusion: We have demonstrated that regulation of the TCA cycle is a common mechanism in different human cancers, suggesting that Notch3 inhibitors combined with brivanib treatment may represent a strong formulation for the treatment of HCC as well as Notch3-driven cancers