Esophageal squamous cell carcinoma (ESCC) is one of the most common cancers worldwide and the fourth most lethal cancer in China. However, although genomic studies have identified some mutations associated with ESCC, we know little of the mutational processes responsible. To identify genome-wide mutational signatures, we performed either whole-genome sequencing (WGS) or whole-exome sequencing (WES) on 104 ESCC individuals and combined our data with those of 88 previously reported samples. An APOBEC-mediated mutational signature in 47% of 192 tumors suggests that APOBEC-catalyzed deamination provides a source of DNA damage in ESCC. Moreover, PIK3CA hotspot mutations (c.1624G>A [p.Glu542Lys] and c.1633G>A [p.Glu545Lys]) were enriched in APOBEC-signature tumors, and no smoking-associated signature was observed in ESCC. In the samples analyzed by WGS, we identified focal (<100 kb) amplifications of CBX4 and CBX8. In our combined cohort, we identified frequent inactivating mutations in AJUBA, ZNF750, and PTCH1 and the chromatin-remodeling genes CREBBP and BAP1, in addition to known mutations. Functional analyses suggest roles for several genes (CBX4, CBX8, AJUBA, and ZNF750) in ESCC. Notably, high activity of hedgehog signaling and the PI3K pathway in approximately 60% of 104 ESCC tumors indicates that therapies targeting these pathways might be particularly promising strategies for ESCC. Collectively, our data provide comprehensive insights into the mutational signatures of ESCC and identify markers for early diagnosis and potential therapeutic targets.

Comprehensive identification of somatic structural variations (SVs) and understanding their mutational mechanisms in cancer might contribute to understanding biological differences and help to identify new therapeutic targets. Unfortunately, characterization of complex SVs across the whole genome and the mutational mechanisms underlying esophageal squamous cell carcinoma (ESCC) is largely unclear. To define a comprehensive catalog of somatic SVs, affected target genes, and their underlying mechanisms in ESCC, we re-analyzed whole-genome sequencing (WGS) data from 31 ESCCs using Meerkat algorithm to predict somatic SVs and Patchwork to determine copy-number changes. We found deletions and translocations with NHEJ and alt-EJ signature as the dominant SV types, and 16% of deletions were complex deletions. SVs frequently led to disruption of cancer-associated genes (e.g., CDKN2A and NOTCH1) with different mutational mechanisms. Moreover, chromothripsis, kataegis, and breakage-fusion-bridge (BFB) were identified as contributing to locally mis-arranged chromosomes that occurred in 55% of ESCCs. These genomic catastrophes led to amplification of oncogene through chromothripsis-derived double-minute chromosome formation (e.g., FGFR1 and LETM2) or BFB-affected chromosomes (e.g., CCND1, EGFR, ERBB2, MMPs, and MYC), with approximately 30% of ESCCs harboring BFB-derived CCND1 amplification. Furthermore, analyses of copy-number alterations reveal high frequency of whole-genome duplication (WGD) and recurrent focal amplification of CDCA7 that might act as a potential oncogene in ESCC. Our findings reveal molecular defects such as chromothripsis and BFB in malignant transformation of ESCCs and demonstrate diverse models of SVs-derived target genes in ESCCs. These genome-wide SV profiles and their underlying mechanisms provide preventive, diagnostic, and therapeutic implications for ESCCs.

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In the originally published version of this article, Figure 5C mistakenly included the image of KYSE150 instead of KYSE140. Here we have included the correct image for ZNF750-si KYSE140 cells in Figure 5C. The authors regret the error.

Background Intensive statins are superior to moderate statins in reducing morbidity and mortality after an acute myocardial infarction (AMI). While studies have documented rates of statin prescription as a quality performance measure, variations in hospitals’ rates of initiating, intensifying and maximizing statin therapy after AMI are unknown. Methods and Results We assessed statins at admission and discharge among 4340 AMI patients from 24 US hospitals (2005–08). Hierarchical models estimated site variation in statin initiation in naïve patients, intensification in those on sub-maximal therapy, and discharge on maximal therapy (defined as a statin with expected LDL-C lowering ≥50%), after adjusting for patient factors including LDL-C. Site variation was explored with a median rate ratio (MRR), which estimates the relative difference in risk ratios of 2 hypothetically identical patients at 2 different hospitals. Among statin naïve patients, 87% without a contraindication were prescribed a statin, with no variability across sites (MRR 1.02). Among patients who arrived on sub-maximal statins, 26% had their statin therapy intensified with modest site variability (MRR 1.47). Among all patients without a contraindication, 23% were discharged on maximal statin therapy with substantial hospital variability (MRR 2.79). Conclusions In a large, multicenter AMI cohort, nearly 90% of patients were started on statins during hospitalization, with no variability across sites. However, rates of statin intensification and maximization were low and varied substantially across hospitals. Given that more intense statin therapy is associated with better outcomes, changing the existing performance measures to include the intensity of statin therapy may improve care.