METHOD: For 293 consecutive patients admitted to our hospital via the emergency department for COVID-19 between 01/03/20 -18/05/20, demographic data, laboratory findings, admission electrocardiograph and clinical observations were compared in those who survived and those who died within 6 weeks. Hospital records were reviewed for prior electrocardiograms for comparison with those recorded on presentation with COVID-19.
RESULTS: Patients who died were older than survivors (82 vs 69.8 years, p 455 ms (males) and >465 ms (females) (p = 0.028, HR 1.49 [1.04-2.13]), as predictors of mortality. QTc prolongation beyond these dichotomy limits was associated with increased mortality risk (p = 0.0027, HR 1.78 [1.2-2.6]).
CONCLUSION: QTc prolongation occurs in COVID-19 illness and is associated with poor outcome.
METHODS: This randomized, open-label, phase 3 study was conducted at 36 medical centers in China (mainland), Malaysia, South Korea, and Taiwan. Patients were randomly assigned 1:1 to 200 mg of pembrolizumab intravenously every 3 weeks for ≤2 years or 80 mg/m2 of paclitaxel intravenously every week. Primary end points were overall survival (OS) and progression-free survival (PFS). Secondary end points were objective response rate (ORR) per Response Evaluation Criteria in Solid Tumors version 1.1 and safety.
RESULTS: Between February 16, 2017, and March 12, 2018, 94 patients were randomly assigned (47 pembrolizumab/47 paclitaxel) after screening; enrollment was stopped on March 12, 2018, based on the results of the global KEYNOTE-061 study, and patients were followed until the last patient's last visit. Median OS was 8 months (95% confidence interval [CI], 4-10 months) with pembrolizumab versus 8 months (95% CI, 5-11 months) with paclitaxel (hazard ratio [HR], 0.99; 95% CI, 0.63-1.54). Median PFS was 2 months (95% CI, 1-3 months) with pembrolizumab versus 4 months (95% CI, 3-6 months) with paclitaxel (HR, 1.62; 95% CI, 1.04-2.52). ORR was 13% for pembrolizumab versus 19% for paclitaxel. Any-grade treatment-related adverse events occurred in 28 pembrolizumab-treated patients (60%) and 42 paclitaxel-treated patients (96%); grades 3 to 5 events occurred in 5 patients (11%) and 28 patients (64%), respectively.
CONCLUSIONS: Definitive conclusions about the efficacy of second-line pembrolizumab in Asian patients with advanced PD-L1-positive gastric/GEJ cancer are limited because of insufficient power, but pembrolizumab was well tolerated in this patient population. Efficacy followed a trend similar to that observed in the phase 3 KEYNOTE-061 trial.
IMPORTANCE: This collaborative international study defined the global heterogeneity of HPV11 and established the largest collection of globally circulating HPV11 genomic variants to date. Thirty novel complete HPV11 genomes were determined and submitted to the available sequence repositories. Global phylogenetic analysis revealed two HPV11 variant lineages and four sublineages. The HPV11 (sub)lineage-specific SNPs and the representative region identified within the partial genomic region E2/noncoding region 2 (NCR2) will enable the simpler identification and comparison of HPV11 variants worldwide. This study provides an important knowledge base for HPV11 for future studies in HPV epidemiology, evolution, pathogenicity, prevention, and molecular assay development.
IMPORTANCE: This study established the largest database of globally circulating HPV6 genomic variants and contributed a total of 130 new, complete HPV6 genome sequences to available sequence repositories. Two HPV6 variant lineages and five sublineages were identified and showed some degree of association with geographical location, anatomical site of infection/disease, and/or gender. We additionally identified several HPV6 lineage- and sublineage-specific SNPs to facilitate the identification of HPV6 variants and determined a representative region within the L2 gene that is suitable for HPV6 whole-genome-based phylogenetic analysis. This study complements and significantly expands the current knowledge of HPV6 genetic diversity and forms a comprehensive basis for future epidemiological, evolutionary, functional, pathogenicity, vaccination, and molecular assay development studies.
METHODS: In total, DNA samples were obtained from 14,525 case subjects with invasive EOC and from 23,447 controls from 43 sites in the Ovarian Cancer Association Consortium (OCAC). Two hundred seventy nine SNPs, representing 131 genes, were genotyped using an Illumina Infinium iSelect BeadChip as part of the Collaborative Oncological Gene-environment Study (COGS). SNP analyses were conducted using unconditional logistic regression under a log-additive model, and the FDR q<0.2 was applied to adjust for multiple comparisons.
RESULTS: The most significant evidence of an association for all invasive cancers combined and for the serous subtype was observed for SNP rs17216603 in the iron transporter gene HEPH (invasive: OR = 0.85, P = 0.00026; serous: OR = 0.81, P = 0.00020); this SNP was also associated with the borderline/low malignant potential (LMP) tumors (P = 0.021). Other genes significantly associated with EOC histological subtypes (p<0.05) included the UGT1A (endometrioid), SLC25A45 (mucinous), SLC39A11 (low malignant potential), and SERPINA7 (clear cell carcinoma). In addition, 1785 SNPs in six genes (HEPH, MGST1, SERPINA, SLC25A45, SLC39A11 and UGT1A) were imputed from the 1000 Genomes Project and examined for association with INV EOC in white-European subjects. The most significant imputed SNP was rs117729793 in SLC39A11 (per allele, OR = 2.55, 95% CI = 1.5-4.35, p = 5.66x10-4).
CONCLUSION: These results, generated on a large cohort of women, revealed associations between inherited cellular transport gene variants and risk of EOC histologic subtypes.
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.
METHODS: Using LDScore regression, we explored the genetic correlation between endometrial cancer and ovarian cancer. To identify loci associated with the risk of both cancers, we implemented a pipeline of statistical genetic analyses (i.e., inverse-variance meta-analysis, colocalization, and M-values) and performed analyses stratified by subtype. Candidate target genes were then prioritized using functional genomic data.
RESULTS: Genetic correlation analysis revealed significant genetic correlation between the two cancers (rG = 0.43, P = 2.66 × 10-5). We found seven loci associated with risk for both cancers (P Bonferroni < 2.4 × 10-9). In addition, four novel subgenome-wide regions at 7p22.2, 7q22.1, 9p12, and 11q13.3 were identified (P < 5 × 10-7). Promoter-associated HiChIP chromatin loops from immortalized endometrium and ovarian cell lines and expression quantitative trait loci data highlighted candidate target genes for further investigation.
CONCLUSIONS: Using cross-cancer GWAS meta-analysis, we have identified several joint endometrial and ovarian cancer risk loci and candidate target genes for future functional analysis.
IMPACT: Our research highlights the shared genetic relationship between endometrial cancer and ovarian cancer. Further studies in larger sample sets are required to confirm our findings.