Patent trend and competitive analysis of cancer immunotherapy in the United States.

Immunotherapy has brought high hopes for cancer treatment, and attracted tremendous resources from the biopharmaceutical community. Here we analyze cancer immunotherapy-related patents granted by the United States Patent and Trademark Office in the past decade (2006-2016). A total of 2,229 patents were identified in 13 subfields. The growth of patent number in this field has outpaced the background rate, with cytokine-related therapies, immune checkpoint inhibitors, and natural killer cell therapies growing the most rapidly. The top 15 assignees possess 27.6% (616) of the patents. Amgen is the largest patent holder, followed by Novartis, and then by Chugai Seiyaku. The top assignees have focused on different subfields, and collaborated with each other for technology development. Our competitive analysis reveals that Novartis, Chugai Seiyaku, and Abbvie lead in both patent number and average quality of patents. Meanwhile, Immunomedics owns a high-quality though relatively small patent portfolio in single-chain variable fragment technology, which is not the focus of the abovementioned forerunners. Overall, our analysis illustrates an ecosystem where industry giants and smaller-size players each occupies a niche. Selection and succession are expected to continue for years in this young ecosystem.

Functional divergence and convergence between the transcript network and gene network in lung adenocarcinoma.

INTRODUCTION: Alternative RNA splicing is a critical regulatory mechanism during tumorigenesis. However, previous oncological studies mainly focused on the splicing of individual genes. Whether and how transcript isoforms are coordinated to affect cellular functions remain underexplored. Also of great interest is how the splicing regulome cooperates with the transcription regulome to facilitate tumorigenesis. The answers to these questions are of fundamental importance to cancer biology. RESULTS: Here, we report a comparative study between the transcript-based network (TN) and the gene-based network (GN) derived from the transcriptomes of paired tumor-normal tissues from 77 lung adenocarcinoma patients. We demonstrate that the two networks differ significantly from each other in terms of patient clustering and the number and functions of network modules. Interestingly, the majority (89.5%) of multi-transcript genes have their transcript isoforms distributed in at least two TN modules, suggesting regulatory and functional divergences between transcript isoforms. Furthermore, TN and GN modules share only50%-60% of their biological functions. TN thus appears to constitute a regulatory layer separate from GN. Nevertheless, our results indicate that functional convergence and divergence both occur between TN and GN, implying complex interactions between the two regulatory layers. Finally, we report that the expression profiles of module members in both TN and GN shift dramatically yet concordantly during tumorigenesis. The mechanisms underlying this coordinated shifting remain unclear yet are worth further explorations. CONCLUSION: We show that in lung adenocarcinoma, transcript isoforms per se are coordinately regulated to conduct biological functions not conveyed by the network of genes. However, the two networks may interact closely with each other by sharing the same or related biological functions. Unraveling the effects and mechanisms of such interactions will significantly advance our understanding of this deadly disease.

Functional Implications of RNA Splicing for Human Long Intergenic Noncoding RNAs.

Long intergenic noncoding RNAs (lincRNAs) have been suggested as playing important roles in human gene regulation. The majority of annotated human lincRNAs include multiple exons and are alternatively spliced. However, the connections between alternative RNA splicing (AS) and the functions/regulations of lincRNAs have remained elusive. In this study, we compared the sequence evolution and biological features between single-exonic lincRNAs and multi-exonic lincRNAs (SELs and MELs, respectively) that were present only in the hominoids (hominoid-specific) or conserved in primates (primate-conserved). The MEL exons were further classified into alternatively spliced exons (ASEs) and constitutively spliced exons (CSEs) for evolutionary analyses. Our results indicate that SELs and MELs differed significantly from each other. Firstly, in hominoid-specific lincRNAs, MELs (both CSEs and ASEs) evolved slightly more rapidly than SELs, which evolved approximately at the neutral rate. In primate-conserved lincRNAs, SELs and ASEs evolved slightly more slowly than CSEs and neutral sequences. The evolutionary path of hominid-specific lincRNAs thus seemed to have diverged from that of their more ancestral counterparts. Secondly, both of the exons and transcripts of SELs were significantly longer than those of MELs, and this was probably because SEL transcripts were more resistant to RNA splicing than MELs. Thirdly, SELs were physically closer to coding genes than MELs. Fourthly, SELs were more widely expressed in human tissues than MELs. These results suggested that SELs and MELs represented two biologically distinct groups of genes. In addition, the SEL-MEL and ASE-CSE differences implied that splicing might be important for the functionality or regulations of lincRNAs in primates.

Assessing determinants of exonic evolutionary rates in mammals.

From studies investigating the differences in evolutionary rates between genes, gene compactness and gene expression level have been identified as important determinants of gene-level protein evolutionary rate, as represented by nonsynonymous to synonymous substitution rate (d(N)/d(S)) ratio. However, the causes of exon-level variances in d(N)/d(S) are less understood. Here, we use principal component regression to examine to what extent 13 exon features explain the variance in d(N), d(S), and the d(N)/d(S) ratio of human-rhesus macaque or human-mouse orthologous exons. The exon features were grouped into six functional categories: expression features, mRNA splicing features, structural-functional features, compactness features, exon duplicability, and other features, including G + C content and exon length. Although expression features are important for determining d(N) and d(N)/d(S) between exons of different genes, structural-functional features and splicing features explained more of the variance for exons of the same genes. Furthermore, we show that compactness features can explain only a relatively small percentage of variance in exon-level d(N) or d(N)/d(S) in either between-gene or within-gene comparison. By contrast, d(S) yielded inconsistent results in the human-mouse comparison and the human-rhesus macaque comparison. This inconsistency may suggest rapid evolutionary changes of the mutation landscape in mammals. Our results suggest that between-gene and within-gene variation in d(N)/d(S) (and d(N)) are driven by different evolutionary forces and that the role of mRNA splicing in causing the variation in evolutionary rates of coding sequences may be underappreciated.

Independent effects of alternative splicing and structural constraint on the evolution of mammalian coding exons.

Alternative splicing (AS) is known to significantly affect exon-level protein evolutionary rates in mammals. Particularly, alternatively spliced exons (ASEs) have a higher nonsynonymous-to-synonymous substitution rate (dN/dS) ratio than constitutively spliced exons (CSEs), possibly because the former are required only occasionally for normal biological functions. Meanwhile, intrinsically disordered regions (IDRs), the protein regions lacking fixed 3D structures, are also reported to have an increased evolutionary rate due to lack of structural constraint. Interestingly, IDRs tend to be located in alternative protein regions. Yet which of these two factors is the major determinant of the increased dN/dS in mammalian ASEs remains unclear. By comparing human-macaque and human-mouse one-to-one orthologous genes, we demonstrate that AS and protein structural disorder have independent effects on mammalian exon evolution. We performed analyses of covariance to demonstrate that the slopes of the (dN/dS-percentage of IDR) regression lines differ significantly between CSEs and ASEs. In other words, the dN/dS ratios of both ASEs and CSEs increase with the proportion of IDR (PIDR), whereas ASEs have higher dN/dS ratios than CSEs when they have similar PIDRs. Since ASEs and IDRs may less frequently overlap with protein domains (which also affect dN/dS), we also examined the correlations between dN/dS ratio and exon type/PIDR by controlling for the density of protein domain. We found that the effects of exon type and PIDR on dN/dS are both independent of domain density. Our results imply that nature can select for different biological features with regard to ASEs and IDRs, even though the two biological features tend to be localized in the same protein regions.

The genomic features that affect the lengths of 5' untranslated regions in multicellular eukaryotes.

BACKGROUND: The lengths of 5'UTRs of multicellular eukaryotes have been suggested to be subject to stochastic changes, with upstream start codons (uAUGs) as the major constraint to suppress 5'UTR elongation. However, this stochastic model cannot fully explain the variations in 5'UTR length. We hypothesize that the selection pressure on a combination of genomic features is also important for 5'UTR evolution. The ignorance of these features may have limited the explanatory power of the stochastic model. Furthermore, different selective constraints between vertebrates and invertebrates may lead to differences in the determinants of 5'UTR length, which have not been systematically analyzed. METHODS: Here we use a multiple linear regression model to delineate the correlation between 5'UTR length and the combination of a series of genomic features (G+C content, observed-to-expected (OE) ratios of uAUGs, upstream stop codons (uSTOPs), methylation-related CG/UG dinucleotides, and mRNA-destabilizing UU/UA dinucleotides) in six vertebrates (human, mouse, rat, chicken, African clawed frog, and zebrafish) and four invertebrates (fruit fly, mosquito, sea squirt, and nematode). The relative contributions of each feature to the variation of 5'UTR length were also evaluated. RESULTS: We found that 14%~33% of the 5'UTR length variations can be explained by a linear combination of the analyzed genomic features. The most important genomic features are the OE ratios of uSTOPs and G+C content. The surprisingly large weightings of uSTOPs highlight the importance of selection on upstream open reading frames (which include both uAUGs and uSTOPs), rather than on uAUGs per se. Furthermore, G+C content is the most important determinants for most invertebrates, but for vertebrates its effect is second to uSTOPs. We also found that shorter 5'UTRs are affected more by the stochastic process, whereas longer 5'UTRs are affected more by selection pressure on genomic features. CONCLUSIONS: Our results suggest that upstream open reading frames may be the real target of selection, rather than uAUGs. We also show that the selective constraints on genomic features of 5'UTRs differ between vertebrates and invertebrates, and between longer and shorter 5'UTRs. A more comprehensive model that takes these findings into consideration is needed to better explain 5'UTR length evolution.

The plausible reason why the length of 5' untranslated region is unrelated to organismal complexity.

BACKGROUND: Organismal complexity is suggested to increase with the complexity of transcriptional and translational regulations. Supporting this notion is a recent study that demonstrated a higher level of tissue-specific gene expression in human than in mouse. However, whether this correlation can be extended beyond mammals remains unclear. In addition, 5' untranslated regions (5'UTRs), which have undergone stochastic elongation during evolution and potentially included an increased number of regulatory elements, may have played an important role in the emergence of organismal complexity. Although the lack of correlation between 5'UTR length and organismal complexity has been proposed, the underlying mechanisms remain unexplored. RESULTS: In this study, we select the number of cell types as the measurement of organismal complexity and examine the correlation between (1) organismal complexity and transcriptional regulatory complexity; and (2) organismal complexity and 5'UTR length by comparing the 5'UTRs and multiple-tissue expression profiles of human (Homo sapiens), mouse (Mus musculus), and fruit fly (Drosophila melanogaster). The transcriptional regulatory complexity is measured by using the tissue specificity of gene expression and the ratio of non-constitutively expressed to constitutively expressed genes. We demonstrate that, whereas correlation (1) holds well in the three-way comparison, correlation (2) is not true. Results from a larger dataset that includes more than 15 species, ranging from yeast to human, also reject correlation (2). The reason for the failure of correlation (2) may be ascribed to: Firstly, longer 5'UTRs do not contribute to increased tissue specificity of gene expression. Secondly, the increased numbers of common translational regulatory elements in longer 5'UTRs do not lead to increased organismal complexity. CONCLUSIONS: Our study has extended the evidence base for the correlation between organismal complexity and transcriptional regulatory complexity from mammals to fruit fly, the representative model organism of invertebrates. Furthermore, our results suggest that the elongation of 5'UTRs alone can not lead to the increase in regulatory complexity or the emergence of organismal complexity.

CAPIH: a Web interface for comparative analyses and visualization of host-HIV protein-protein interactions.

BACKGROUND: The Human Immunodeficiency Virus type one (HIV-1) is the major causing pathogen of the Acquired Immune Deficiency Syndrome (AIDS). A large number of HIV-1-related studies are based on three non-human model animals: chimpanzee, rhesus macaque, and mouse. However, the differences in host-HIV-1 interactions between human and these model organisms have remained unexplored. DESCRIPTION: Here we present CAPIH (Comparative Analysis of Protein Interactions for HIV-1), the first web-based interface to provide comparative information between human and the three model organisms in the context of host-HIV-1 protein interactions. CAPIH identifies genetic changes that occur in HIV-1-interacting host proteins. In a total of 1,370 orthologous protein sets, CAPIH identifies approximately 86,000 amino acid substitutions, approximately 21,000 insertions/deletions, and approximately 33,000 potential post-translational modifications that occur only in one of the four compared species. CAPIH also provides an interactive interface to display the host-HIV-1 protein interaction networks, the presence/absence of orthologous proteins in the model organisms in the networks, the genetic changes that occur in the protein nodes, and the functional domains and potential protein interaction hot sites that may be affected by the genetic changes. The CAPIH interface is freely accessible at http://bioinfo-dbb.nhri.org.tw/capih. CONCLUSION: CAPIH exemplifies that large divergences exist in disease-associated proteins between human and the model animals. Since all of the newly developed medications must be tested in model animals before entering clinical trials, it is advisable that comparative analyses be performed to ensure proper translations of animal-based studies. In the case of AIDS, the host-HIV-1 protein interactions apparently have differed to a great extent among the compared species. An integrated protein network comparison among the four species will probably shed new lights on AIDS studies.