ACGH detects distinct genomic alterations of primary intrahepatic cholangiocarcinomas and matched lymph node metastases and identifies a poor prognosis subclass

Lymph node metastases (LNM) are an important prognostic factor for patients with intrahepatic cholangiocarcinoma, but underlying genetic alterations are poorly understood. Whole genome array comparative genomic hybridization (aCGH) was performed in 37 tumors and 14 matched LNM. Genomic analyses of tumors confirmed known and identified new (gains in 19q) copy number alterations (CNA). Tumors with LNM (N1) had more alterations and exclusive gains (3p, 4q, 5p, 13q) and losses (17p and 20p). LNM shared most alterations with their matched tumors (86%), but 79% acquired new isolated gains [12q14 (36%); 1p13, 2p23, 7p22, 7q11, 11q12, 13q13 and 14q12 (>20%)]. Unsupervised clustering revealed a poor prognosis subclass with increased alterations significantly associated to tumor differentiation and survival. TP53 and KRAS mutations occurred in 19% of tumors and 6% of metastases. Pathway analyses revealed association to cancer-associated pathways. Advanced tumor stage, microvascular/perineural invasion, and microscopic positive resection margin (R1) were significantly correlated to metastases, while N1-status, R1-resection, and poor tumor differentiation were significantly correlated to survival. ACGH identified clear differences between N0 (no LNM) and N1 tumors, while N1 tumors and matched LNM displayed high clonality with exclusive gains in the metastases. A novel subclass with increased CNAs and poor tumor differentiation was significantly correlated to survival

Serum microRNA profiles as prognostic or predictive markers in the multimodality treatment of patients with gastric cancer

Despite the implementation of multimodality treatment strategies, the persistently poor prognosis of gastric cancer patients is predominantly caused by the lack of predictive markers for response assessment in the neoadjuvant setting, preventing individualized therapy. Therefore, the identification of novel predictive and prognostic markers for application in the multimodality treatment of gastric cancer patients is required. The aim of the present study was to characterize the serum microRNA (miRNA/miR) profile of gastric cancer patients undergoing multimodality therapy to identify possible prognostic and predictive markers. The study consisted of 32 patients with gastric cancer who had undergone either primary surgical resection (n=14) or neoadjuvant therapy followed by surgical resection (n=18). Histopathological regression was defined as a major histopathological response when the resected specimens contained <10% vital residual tumor cells. Intratumoral miRNA was isolated from pre-operative or post-neoadjuvant blood serum samples. Initially, microarray analyses were performed in six of the patients that received neoadjuvant treatment (three responders versus three non-responders), to assess the amplification profile of dysregulated miRNAs. Based on these findings, possible predictive or prognostic markers were validated in all study patients by performing single reverse transcription-polymerase chain reaction (RT-PCR) analysis. Depending on the extent of the histopathological regression, a differential miRNA expression profile was identified in the microarray analyses. Based on the amplification profile, miR-21, miR-29a and miR-221 were selected for additional validation. However, the single RT-PCR measurements of the three selected miRNAs did not exhibit any prognostic or predictive value in the patients treated with primary resection or neoadjuvant therapy and resection. Thus, the current pilot study failed to identify a prognostic or predictive value in selected miRNAs using single RT-PCR measurements, however, the microarray results revealed a differential microRNA expression profile depending on the histopathological regression. The findings of the present study may have been affected by the small sample size

A New Workflow for Whole-Genome Sequencing of Single Human Cells

Binder V, Bartenhagen C, Okpanyi V, et al. A New Workflow for Whole-Genome Sequencing of Single Human Cells. Human mutation. 2014;35(10):1260-1270.: Unbiased amplification of the whole-genome amplification (WGA) of single cells is crucial to study cancer evolution and genetic heterogeneity, but is challenging due to the high complexity of the human genome. Here, we present a new workflow combining an efficient adapter-linker PCR-based WGA method with second-generation sequencing. This approach allows comparison of single cells at base pair resolution. Amplification recovered up to 74% of the human genome. Copy-number variants and loss of heterozygosity detected in single cell genomes showed concordance of up to 99% to pooled genomic DNA. Allele frequencies of mutations could be determined accurately due to an allele dropout rate of only 2%, clearly demonstrating the low bias of our PCR-based WGA approach. Sequencing with paired-end reads allowed genome-wide analysis of structural variants. By direct comparison to other WGA methods, we further endorse its suitability to analyze genetic heterogeneity

Unscrambling the genomic chaos of osteosarcoma reveals extensive transcript fusion, recurrent rearrangements and frequent novel TP53 aberrations

In contrast to many other sarcoma subtypes, the chaotic karyotypes of osteosarcoma have precluded the identification of pathognomonic translocations. We here report hundreds of genomic rearrangements in osteosarcoma cell lines, showing clear characteristics of microhomology-mediated break-induced replication (MMBIR) and end-joining repair (MMEJ) mechanisms. However, at RNA level, the majority of the fused transcripts did not correspond to genomic rearrangements, suggesting the involvement of trans-splicing, which was further supported by typical trans-splicing characteristics. By combining genomic and transcriptomic analysis, certain recurrent rearrangements were identified and further validated in patient biopsies, including a PMP22-ELOVL5 gene fusion, genomic structural variations affecting RB1, MTAP/CDKN2A and MDM2, and, most frequently, rearrangements involving TP53. Most cell lines (7/11) and a large fraction of tumor samples (10/25) showed TP53 rearrangements, in addition to somatic point mutations (6 patient samples, 1 cell line) and MDM2 amplifications (2 patient samples, 2 cell lines). The resulting inactivation of p53 was demonstrated by a deficiency of the radiation-induced DNA damage response. Thus, TP53 rearrangements are the major mechanism of p53 inactivation in osteosarcoma. Together with active MMBIR and MMEJ, this inactivation probably contributes to the exceptional chromosomal instability in these tumors. Although rampant rearrangements appear to be a phenotype of osteosarcomas, we demonstrate that among the huge number of probable passenger rearrangements, specific recurrent, possibly oncogenic, events are present. For the first time the genomic chaos of osteosarcoma is characterized so thoroughly and delivered new insights in mechanisms involved in osteosarcoma development and may contribute to new diagnostic and therapeutic strategies