Tumor biology and immune infiltration define primary liver cancer subsets linked to overall survival after immunotherapy.

Primary liver cancer is a rising cause of cancer deaths in the US. Although immunotherapy with immune checkpoint inhibitors induces a potent response in a subset of patients, response rates vary among individuals. Predicting which patients will respond to immune checkpoint inhibitors is of great interest in the field. In a retrospective arm of the National Cancer Institute Cancers of the Liver: Accelerating Research of Immunotherapy by a Transdisciplinary Network (NCI-CLARITY) study, we use archived formalin-fixed, paraffin-embedded samples to profile the transcriptome and genomic alterations among 86 hepatocellular carcinoma and cholangiocarcinoma patients prior to and following immune checkpoint inhibitor treatment. Using supervised and unsupervised approaches, we identify stable molecular subtypes linked to overall survival and distinguished by two axes of aggressive tumor biology and microenvironmental features. Moreover, molecular responses to immune checkpoint inhibitor treatment differ between subtypes. Thus, patients with heterogeneous liver cancer may be stratified by molecular status indicative of treatment response to immune checkpoint inhibitors.

Structural variant analysis of a cancer reference cell line sample using multiple sequencing technologies.

BACKGROUND: The cancer genome is commonly altered with thousands of structural rearrangements including insertions, deletions, translocation, inversions, duplications, and copy number variations. Thus, structural variant (SV) characterization plays a paramount role in cancer target identification, oncology diagnostics, and personalized medicine. As part of the SEQC2 Consortium effort, the present study established and evaluated a consensus SV call set using a breast cancer reference cell line and matched normal control derived from the same donor, which were used in our companion benchmarking studies as reference samples. RESULTS: We systematically investigated somatic SVs in the reference cancer cell line by comparing to a matched normal cell line using multiple NGS platforms including Illumina short-read, 10X Genomics linked reads, PacBio long reads, Oxford Nanopore long reads, and high-throughput chromosome conformation capture (Hi-C). We established a consensus SV call set of a total of 1788 SVs including 717 deletions, 230 duplications, 551 insertions, 133 inversions, 146 translocations, and 11 breakends for the reference cancer cell line. To independently evaluate and cross-validate the accuracy of our consensus SV call set, we used orthogonal methods including PCR-based validation, Affymetrix arrays, Bionano optical mapping, and identification of fusion genes detected from RNA-seq. We evaluated the strengths and weaknesses of each NGS technology for SV determination, and our findings provide an actionable guide to improve cancer genome SV detection sensitivity and accuracy. CONCLUSIONS: A high-confidence consensus SV call set was established for the reference cancer cell line. A large subset of the variants identified was validated by multiple orthogonal methods.

Whole genome and exome sequencing reference datasets from a multi-center and cross-platform benchmark study.

With the rapid advancement of sequencing technologies, next generation sequencing (NGS) analysis has been widely applied in cancer genomics research. More recently, NGS has been adopted in clinical oncology to advance personalized medicine. Clinical applications of precision oncology require accurate tests that can distinguish tumor-specific mutations from artifacts introduced during NGS processes or data analysis. Therefore, there is an urgent need to develop best practices in cancer mutation detection using NGS and the need for standard reference data sets for systematically measuring accuracy and reproducibility across platforms and methods. Within the SEQC2 consortium context, we established paired tumor-normal reference samples and generated whole-genome (WGS) and whole-exome sequencing (WES) data using sixteen library protocols, seven sequencing platforms at six different centers. We systematically interrogated somatic mutations in the reference samples to identify factors affecting detection reproducibility and accuracy in cancer genomes. These large cross-platform/site WGS and WES datasets using well-characterized reference samples will represent a powerful resource for benchmarking NGS technologies, bioinformatics pipelines, and for the cancer genomics studies.

Establishing community reference samples, data and call sets for benchmarking cancer mutation detection using whole-genome sequencing.

The lack of samples for generating standardized DNA datasets for setting up a sequencing pipeline or benchmarking the performance of different algorithms limits the implementation and uptake of cancer genomics. Here, we describe reference call sets obtained from paired tumor-normal genomic DNA (gDNA) samples derived from a breast cancer cell line-which is highly heterogeneous, with an aneuploid genome, and enriched in somatic alterations-and a matched lymphoblastoid cell line. We partially validated both somatic mutations and germline variants in these call sets via whole-exome sequencing (WES) with different sequencing platforms and targeted sequencing with >2,000-fold coverage, spanning 82% of genomic regions with high confidence. Although the gDNA reference samples are not representative of primary cancer cells from a clinical sample, when setting up a sequencing pipeline, they not only minimize potential biases from technologies, assays and informatics but also provide a unique resource for benchmarking 'tumor-only' or 'matched tumor-normal' analyses.

Genome Assembly and Annotation of the Trichoplusia ni Tni-FNL Insect Cell Line Enabled by Long-Read Technologies.

BACKGROUND: Trichoplusiani derived cell lines are commonly used to enable recombinant protein expression via baculovirus infection to generate materials approved for clinical use and in clinical trials. In order to develop systems biology and genome engineering tools to improve protein expression in this host, we performed de novo genome assembly of the Trichoplusiani-derived cell line Tni-FNL. METHODS: By integration of PacBio single-molecule sequencing, Bionano optical mapping, and 10X Genomics linked-reads data, we have produced a draft genome assembly of Tni-FNL. RESULTS: Our assembly contains 280 scaffolds, with a N50 scaffold size of 2.3 Mb and a total length of 359 Mb. Annotation of the Tni-FNL genome resulted in 14,101 predicted genes and 93.2% of the predicted proteome contained recognizable protein domains. Ortholog searches within the superorder Holometabola provided further evidence of high accuracy and completeness of the Tni-FNL genome assembly. CONCLUSIONS: This first draft Tni-FNL genome assembly was enabled by complementary long-read technologies and represents a high-quality, well-annotated genome that provides novel insight into the complexity of this insect cell line and can serve as a reference for future large-scale genome engineering work in this and other similar recombinant protein production hosts.

Interleukin-27 treated human macrophages induce the expression of novel microRNAs which may mediate anti-viral properties.

Interleukin-27 (IL-27) is a pleiotropic cytokine which plays important and diverse roles in the immune system. We have previously demonstrated that IL-27 induces potent anti-viral effects against HIV-1, HIV-2, SIV, HSV-2, KSHV and influenza viruses in macrophages. This induction occurred in an interferon (IFN) independent manner and involved down regulation of SPTBN1. MicroRNAs (miRNAs) are critical regulators of mRNA translation and turnover. There have been reports that some miRNAs inhibit viral replication. In this study, we hypothesized that IL-27 could induce the expression of novel miRNAs in macrophages which may have functional relevance in terms of anti-viral activity and primary monocytes were differentiated into macrophages using either M-CSF (M-Mac) or a combination of M-CSF and IL-27 (I-Mac) for seven days. Following this, total RNA was extracted from these cells and deep sequencing was performed, in parallel with gene expression microarrays. Using the novel miRNA discovery software, miRDeep, seven novel miRNAs were discovered in these macrophages. Four of which were preferentially expressed in I-Mac (miR-SX1, -SX2, -SX3 and -SX6) whilst three were detected in both M-Mac and I-Mac (miR-SX4, -SX5 and -SX7). The expression of six of the seven novel miRNAs was highly correlated with qRT-PCR using specific primer/probes designed for the novel miRNAs. Gene expression microarray further demonstrated that a number of genes were potentially targeted by these differentially expressed novel miRNAs. Finally, several of these novel miRNAs (miR-SX1, -SX4, -SX5, -SX6 and -SX7) were shown to target the open reading frames of a number of viruses (including HSV-1, HSV-2 and HHV-8) which may partially explain the anti-viral properties observed.