To compare lung adenocarcinoma (ADC) and lung squamous cell carcinoma (SqCC) and to identify new drivers of lung carcinogenesis, we examined exome sequences and copy number profiles of 660 lung ADC and 484 lung SqCC tumor/normal pairs. Recurrent alterations in lung SqCCs were more similar to other squamous carcinomas than to lung ADCs. Novel significantly mutated genes included PPP3CA, DOT1L, and FTSJD1 in lung ADC, RASA1 in lung SqCC, and KLF5, EP300, and CREBBP in both tumor types. Novel amplification peaks encompassed MIR21 in lung ADC, MIR205 in lung SqCC, and MAPK1 in both. Lung ADCs lacking receptor tyrosine kinase/Ras/Raf alterations revealed mutations in SOS1, VAV1, RASA1, and ARHGAP35. Regarding neoantigens, 47% of the lung ADC and 53% of the lung SqCC tumors had at least 5 predicted neoepitopes. While targeted therapies for lung ADC and lung SqCC are largely distinct, immunotherapies may aid in treatment for both subtypes.

BackgroundThe process of generating raw genome sequence data continues to become cheaper, faster, and more accurate. However, assembly of such data into high-quality, finished genome sequences remains challenging. Many genome assembly tools are available, but they differ greatly in terms of their performance (speed, scalability, hardware requirements, acceptance of newer read technologies) and in their final output (composition of assembled sequence). More importantly, it remains largely unclear how to best assess the quality of assembled genome sequences. The Assemblathon competitions are intended to assess current state-of-the-art methods in genome assembly.ResultsIn Assemblathon 2, we provided a variety of sequence data to be assembled for three vertebrate species (a bird, a fish, and snake). This resulted in a total of 43 submitted assemblies from 21 participating teams. We evaluated these assemblies using a combination of optical map data, Fosmid sequences, and several statistical methods. From over 100 different metrics, we chose ten key measures by which to assess the overall quality of the assemblies.ConclusionsMany current genome assemblers produced useful assemblies, containing a significant representation of their genes and overall genome structure. However, the high degree of variability between the entries suggests that there is still much room for improvement in the field of genome assembly and that approaches which work well in assembling the genome of one species may not necessarily work well for another.

Alpha satellite domains that currently function as centromeres of human chromosomes are flanked by layers of older alpha satellite, thought to contain dead centromeres of primate progenitors, which lost their function and the ability to homogenize satellite repeats, upon appearance of a new centromere. Using cladistic analysis of alpha satellite monomers, we elucidated complete layer patterns on chromosomes 8, 17, and X and related them to each other and to primate alpha satellites. We show that discrete and chronologically ordered alpha satellite layers are partially symmetrical around an active centromere and their succession is partially shared in non-homologous chromosomes. The layer structure forms a visual representation of the human evolutionary lineage with layers corresponding to ancestors of living primates and to entirely fossil taxa. Surprisingly, phylogenetic comparisons suggest that alpha satellite arrays went through periods of unusual hypermutability after they became “dead” centromeres. The layer structure supports a model of centromere evolution where new variants of a satellite repeat expanded periodically in the genome by rounds of inter-chromosomal transfer/amplification. Each wave of expansion covered all or many chromosomes and corresponded to a new primate taxon. Complete elucidation of the alpha satellite phylogenetic record would give a unique opportunity to number and locate the positions of major extinct taxa in relation to human ancestors shared with extant primates. If applicable to other satellites in non-primate taxa, analysis of centromeric layers could become an invaluable tool for phylogenetic studies.

The “cancer immunogenomics” paradigm has facilitated the search for tumor-specific antigens over the last 4 years by applying comprehensive cancer genomics to tumor antigen discovery. We applied this methodology to identify tumor-specific “neoantigens” in the C57BL/6-derived GL261 and VM/Dk-derived SMA-560 tumor models. Following DNA whole exome and RNA sequencing, high-affinity candidate neoepitopes were predicted and screened for immunogenicity by ELISPOT and tetramer analyses. GL261 and SMA-560 harbored 4,932 and 2,171 non-synonymous exome mutations, respectively, of which less than half were expressed. To establish the immunogenicities of H-2Kb and H-2Db candidate neoantigens, we assessed the ability of the epitopes predicted in silico to be the highest affinity binders to activate tumor-infiltrating T cells harvested from GL261 and SMA-560 tumors. Using IFNγ ELISPOT, we confirmed H-2Db–restricted Imp3D81N (GL261) and Odc1Q129L (SMA-560) along with H-2Kb–restricted E2f8K272R (SMA-560) as endogenous tumor-specific neoantigens that are functionally immunogenic. Furthermore, neoantigen-specific T cells to Imp3D81N and Odc1Q129L were detected within intracranial tumors as well as cervical draining lymph nodes by tetramer analysis. By establishing the immunogenicities of predicted high-affinity neoepitopes in these models, we extend the immunogenomics-based neoantigen discovery pipeline to glioblastoma models and provide a tractable system to further study the mechanism of action of T cell–activating immunotherapeutic approaches in preclinical models of glioblastoma.

In the latest hg38 human genome assembly, centromeric gaps has been filled in by alpha satellite (AS) reference models (RMs) which are statistical representations of homogeneous higher-order repeat (HOR) arrays that make up the bulk of the centromeric regions. We analyzed these models to compose an atlas of human AS HORs where each monomer of a HOR was represented by a number of its polymorphic sequence variants. We combined these data and HMMER sequence analysis platform to annotate AS HORs in the assembly. This led to discovery of a new type of low copy number highly divergent HORs which were not represented by RMs. These were included in the dataset. The annotation can be viewed as UCSC Genome Browser custom track (the HOR-track) and used together with our previous annotation of AS suprachromosomal families (SFs) in the same assembly, where each AS monomer can be viewed in its genomic context together with its classification into one of the 5 major SFs (the SF-track). To catalog the diversity of AS HORs in the human genome we introduced a new naming system. Each HOR received a name which showed its SF, chromosomal location and index number. Here we present the first installment of the HOR-track covering only the 17 HORs that belong to SF1 which forms live functional centromeres in chromosomes 1, 3, 5, 6, 7, 10, 12, 16 and 19 and also a large number of minor dead HOR domains, both homogeneous and divergent. Monomer-by-monomer HOR annotation used for this dataset as opposed to annotation of whole HOR repeats provides for mapping and quantification of various structural variants of AS HORs which can be used to collect data on inter-individual polymorphism of AS.

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Head and neck squamous cell carcinomas (HNSCC) are an ideal immunotherapy target due to their high mutation burden and frequent infiltration with lymphocytes. Preclinical models to investigate targeted and combination therapies as well as defining biomarkers to guide treatment represent an important need in the field. Immunogenomics approaches have illuminated the role of mutation-derived tumor neoantigens as potential biomarkers of response to checkpoint blockade as well as representing therapeutic vaccines. Here, we aimed to define a platform for checkpoint and other immunotherapy studies using syngeneic HNSCC cell line models (MOC2 and MOC22), and evaluated the association between mutation burden, predicted neoantigen landscape, infiltrating T cell populations and responsiveness of tumors to anti-PD1 therapy. We defined dramatic hematopoietic cell transcriptomic alterations in the MOC22 anti-PD1 responsive model in both tumor and draining lymph nodes. Using a cancer immunogenomics pipeline and validation with ELISPOT and tetramer analysis, we identified the H-2Kb-restricted ICAM1 P315L (mICAM1) as a neoantigen in MOC22. Finally, we demonstrated that mICAM1 vaccination was able to protect against MOC22 tumor development defining mICAM1 as a bona fide neoantigen. Together these data define a pre-clinical HNSCC model system that provides a foundation for future investigations into combination and novel therapeutics. www.impactjournals.com/oncotarget/

Memory traces for words are frequently conceptualized neurobiologically as networks of neurons interconnected via reciprocal links developed through associative learning in the process of language acquisition. Neurophysiological reflection of activation of such memory traces has been reported using the mismatch negativity brain potential (MMN), which demonstrates an enhanced response to meaningful words over meaningless items. This enhancement is believed to be generated by the activation of strongly intraconnected long-term memory circuits for words that can be automatically triggered by spoken linguistic input and that are absent for unfamiliar phonological stimuli. This conceptual framework critically predicts different amounts of activation depending on the strength of the word's lexical representation in the brain. The frequent use of words should lead to more strongly connected representations, whereas less frequent items would be associated with more weakly linked circuits. A word with higher frequency of occurrence in the subject's language should therefore lead to a more pronounced lexical MMN response than its low-frequency counterpart. We tested this prediction by comparing the event-related potentials elicited by low- and high-frequency words in a passive oddball paradigm; physical stimulus contrasts were kept identical. We found that, consistent with our prediction, presenting the high-frequency stimulus led to a significantly more pronounced MMN response relative to the low-frequency one, a finding that is highly similar to previously reported MMN enhancement to words over meaningless pseudowords. Furthermore, activation elicited by the higher-frequency word peaked earlier relative to low-frequency one, suggesting more rapid access to frequently used lexical entries. These results lend further support to the above view on word memory traces as strongly connected assemblies of neurons. The speed and magnitude of their activation appears to be linked to the strength of internal connections in a memory circuit, which is in turn determined by the everyday use of language elements.