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.

Aging and obesity prime the methylome and transcriptome of adipose stem cells for disease and dysfunction.

The epigenome of stem cells occupies a critical interface between genes and environment, serving to regulate expression through modification by intrinsic and extrinsic factors. We hypothesized that aging and obesity, which represent major risk factors for a variety of diseases, synergistically modify the epigenome of adult adipose stem cells (ASCs). Using integrated RNA- and targeted bisulfite-sequencing in murine ASCs from lean and obese mice at 5- and 12-months of age, we identified global DNA hypomethylation with either aging or obesity, and a synergistic effect of aging combined with obesity. The transcriptome of ASCs in lean mice was relatively stable to the effects of age, but this was not true in obese mice. Functional pathway analyses identified a subset of genes with critical roles in progenitors and in diseases of obesity and aging. Specifically, Mapt, Nr3c2, App, and Ctnnb1 emerged as potential hypomethylated upstream regulators in both aging and obesity (AL vs. YL and AO vs. YO), and App, Ctnnb1, Hipk2, Id2, and Tp53 exhibited additional effects of aging in obese animals. Furthermore, Foxo3 and Ccnd1 were potential hypermethylated upstream regulators of healthy aging (AL vs. YL), and of the effects of obesity in young animals (YO vs. YL), suggesting that these factors could play a role in accelerated aging with obesity. Finally, we identified candidate driver genes that appeared recurrently in all analyses and comparisons undertaken. Further mechanistic studies are needed to validate the roles of these genes capable of priming ASCs for dysfunction in aging- and obesity-associated pathologies.

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.

HNRNPH1 destabilizes the G-quadruplex structures formed by G-rich RNA sequences that regulate the alternative splicing of an oncogenic fusion transcript.

In the presence of physiological monovalent cations, thousands of RNA G-rich sequences can form parallel G-quadruplexes (G4s) unless RNA-binding proteins inhibit, destabilize, or resolve the formation of such secondary RNA structures. Here, we have used a disease-relevant model system to investigate the biophysical properties of the RNA-binding protein HNRNPH1's interaction with G-rich sequences. We demonstrate the importance of two EWSR1-exon 8 G-rich regions in mediating the exclusion of this exon from the oncogenic EWS-FLI1 transcripts expressed in a subset of Ewing sarcomas, using complementary analysis of tumor data, long-read sequencing, and minigene studies. We determined that HNRNPH1 binds the EWSR1-exon 8 G-rich sequences with low nM affinities irrespective of whether in a non-G4 or G4 state but exhibits different kinetics depending on RNA structure. Specifically, HNRNPH1 associates and dissociates from G4-folded RNA faster than the identical sequences in a non-G4 state. Importantly, we demonstrate using gel shift and spectroscopic assays that HNRNPH1, particularly the qRRM1-qRRM2 domains, destabilizes the G4s formed by the EWSR1-exon 8 G-rich sequences in a non-catalytic fashion. Our results indicate that HNRNPH1's binding of G-rich sequences favors the accumulation of RNA in a non-G4 state and that this contributes to its regulation of RNA processing.

Structure-guided bifunctional molecules hit a DEUBAD-lacking hRpn13 species upregulated in multiple myeloma.

Proteasome substrate receptor hRpn13 is a promising anti-cancer target. By integrated in silico and biophysical screening, we identified a chemical scaffold that binds hRpn13 with non-covalent interactions that mimic the proteasome and a weak electrophile for Michael addition. hRpn13 Pru domain binds proteasomes and ubiquitin whereas its DEUBAD domain binds deubiquitinating enzyme UCHL5. NMR revealed lead compound XL5 to interdigitate into a hydrophobic pocket created by lateral movement of a Pru ß-hairpin with an exposed end for Proteolysis Targeting Chimeras (PROTACs). Implementing XL5-PROTACs as chemical probes identified a DEUBAD-lacking hRpn13 species (hRpn13Pru) present naturally with cell type-dependent abundance. XL5-PROTACs preferentially target hRpn13Pru, causing its ubiquitination. Gene-editing and rescue experiments established hRpn13 requirement for XL5-PROTAC-triggered apoptosis. These data establish hRpn13 as an anti-cancer target for multiple myeloma and introduce an hRpn13-targeting scaffold that can be optimized for preclinical trials against hRpn13Pru-producing cancer types.

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.

Changes in the core endophytic mycobiome of carrot taproots in response to crop management and genotype.

Fungal endophytes can influence production and post-harvest challenges in carrot, though the identity of these microbes as well as factors affecting their composition have not yet been determined, which prevents growers from managing these organisms to improve crop performance. Consequently, we characterized the endophytic mycobiome in the taproots of three carrot genotypes that vary in resistance to two pathogens grown in a trial comparing organic and conventional crop management using Illumina sequencing of the internal transcribed spacer (ITS) gene. A total of 1,480 individual operational taxonomic units (OTUs) were identified. Most were consistent across samples, indicating that they are part of a core mycobiome, though crop management influenced richness and diversity, likely in response to differences in soil properties. There were also differences in individual OTUs among genotypes and the nematode resistant genotype was most responsive to management system indicating that it has greater control over its endophytic mycobiome, which could potentially play a role in resistance. Members of the Ascomycota were most dominant, though the exact function of most taxa remains unclear. Future studies aimed at overcoming difficulties associated with isolating fungal endophytes are needed to identify these microbes at the species level and elucidate their specific functional roles.

Cross-site comparison of ribosomal depletion kits for Illumina RNAseq library construction.

BACKGROUND: Ribosomal RNA (rRNA) comprises at least 90% of total RNA extracted from mammalian tissue or cell line samples. Informative transcriptional profiling using massively parallel sequencing technologies requires either enrichment of mature poly-adenylated transcripts or targeted depletion of the rRNA fraction. The latter method is of particular interest because it is compatible with degraded samples such as those extracted from FFPE and also captures transcripts that are not poly-adenylated such as some non-coding RNAs. Here we provide a cross-site study that evaluates the performance of ribosomal RNA removal kits from Illumina, Takara/Clontech, Kapa Biosystems, Lexogen, New England Biolabs and Qiagen on intact and degraded RNA samples. RESULTS: We find that all of the kits are capable of performing significant ribosomal depletion, though there are differences in their ease of use. All kits were able to remove ribosomal RNA to below 20% with intact RNA and identify ~ 14,000 protein coding genes from the Universal Human Reference RNA sample at >1FPKM. Analysis of differentially detected genes between kits suggests that transcript length may be a key factor in library production efficiency. CONCLUSIONS: These results provide a roadmap for labs on the strengths of each of these methods and how best to utilize them.

Phylogenetic Heatmaps Highlight Composition Biases in Sequenced Reads.

Due to advancements in sequencing technology, sequence data production is no longer a constraint in the field of microbiology and has made it possible to study uncultured microbes or whole environments using metagenomics. However, these new technologies introduce different biases in metagenomic sequencing, affecting the nucleotide distribution of resulting sequence reads. Here, we illustrate such biases using two methods. One is based on phylogenetic heatmaps (PGHMs), a novel approach for compact visualization of sequence composition differences between two groups of sequences containing the same phylogenetic groups. This method is well suited for finding noise and biases when comparing metagenomics samples. We apply PGHMs to detect noise and bias in the data produced with different DNA extraction protocols, different sequencing platforms and different experimental frameworks. In parallel, we use principal component analysis displaying different clustering of sequences from each sample to support our findings and illustrate the utility of PGHMs. We considered contributions of the read length and GC-content variation and observed that in most cases biases were generally due to the GC-content of the reads.

Comparative metagenome analysis of an Alaskan glacier.

The temperature in the Arctic region has been increasing in the recent past accompanied by melting of its glaciers. We took a snapshot of the current microbial inhabitation of an Alaskan glacier (which can be considered as one of the simplest possible ecosystems) by using metagenomic sequencing of 16S rRNA recovered from ice/snow samples. Somewhat contrary to our expectations and earlier estimates, a rich and diverse microbial population of more than 2,500 species was revealed including several species of Archaea that has been identified for the first time in the glaciers of the Northern hemisphere. The most prominent bacterial groups found were Proteobacteria, Bacteroidetes, and Firmicutes. Firmicutes were not reported in large numbers in a previously studied Alpine glacier but were dominant in an Antarctic subglacial lake. Representatives of Cyanobacteria, Actinobacteria and Planctomycetes were among the most numerous, likely reflecting the dependence of the ecosystem on the energy obtained through photosynthesis and close links with the microbial community of the soil. Principal component analysis (PCA) of nucleotide word frequency revealed distinct sequence clusters for different taxonomic groups in the Alaskan glacier community and separate clusters for the glacial communities from other regions of the world. Comparative analysis of the community composition and bacterial diversity present in the Byron glacier in Alaska with other environments showed larger overlap with an Arctic soil than with a high Arctic lake, indicating patterns of community exchange and suggesting that these bacteria may play an important role in soil development during glacial retreat.

Metagenome sequencing of prokaryotic microbiota collected from Byron Glacier, Alaska.

Cold environments, such as glaciers, are large reservoirs of microbial life. The present study employed 16S rRNA gene amplicon metagenomic sequencing to survey the prokaryotic microbiota on Alaskan glacial ice, revealing a rich and diverse microbial community of some 2,500 species of bacteria and archaea.

Carbon availability triggers fungal nitrogen uptake and transport in arbuscular mycorrhizal symbiosis.

The arbuscular mycorrhizal (AM) symbiosis, formed between the majority of land plants and ubiquitous soil fungi of the phylum Glomeromycota, is responsible for massive nutrient transfer and global carbon sequestration. AM fungi take up nutrients from the soil and exchange them against photosynthetically fixed carbon (C) from the host. Recent studies have demonstrated that reciprocal reward strategies by plant and fungal partners guarantee a "fair trade" of phosphorus against C between partners [Kiers ET, et al. (2011) Science 333:880-882], but whether a similar reward mechanism also controls nitrogen (N) flux in the AM symbiosis is not known. Using mycorrhizal root organ cultures, we manipulated the C supply to the host and fungus and followed the uptake and transport of N sources in the AM symbiosis, the enzymatic activities of arginase and urease, and fungal gene expression in the extraradical and intraradical mycelium. We found that the C supply of the host plant triggers the uptake and transport of N in the symbiosis, and that the increase in N transport is orchestrated by changes in fungal gene expression. N transport in the symbiosis is stimulated only when the C is delivered by the host across the mycorrhizal interface, not when C is supplied directly to the fungal extraradical mycelium in the form of acetate. These findings support the importance of C flux from the root to the fungus as a key trigger for N uptake and transport and provide insight into the N transport regulation in the AM symbiosis.