Feng-Chi Chen

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.

Introduction: Biotech patents are facing increasingly stern challenges. The patent statue holds that a multi-step method patent is not directly infringed unless all steps are carried out and attributed to a single entity. When separate steps are performed jointly by two or more parties, those parties are liable for divided infringement if there exists a direct infringement. Possibilities thus exist for unauthorized but non-infringing joint performance, i.e. enforcing a method patent will be difficult if joint performance stands as a valid defense against direct infringement. Areas covered: This analysis covers issues on patent infringement, specifically on divided infringement of diagnostic and method patents. Expert opinion: A retrospective analysis indicates that a large number of cancer diagnostic patents issued during 2005-2014 are potentially vulnerable to read on unauthorized use in the manner of joint performance. Inventors should draft patent claims appropriately to reduce the risk to assert their patents in this regard.

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 only ~50%–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.

Triple-layer dissection of the lung adenocarcinoma transcriptome – regulation at the gene, transcript, and exon levels

Drug-resistant Mycobacterium tuberculosis (MTB), the causative pathogen of tuberculosis (TB), has become a serious threat to global public health. Yet the development of novel drugs against MTB has been lagging. One potentially powerful approach to drug development is computation-aided repositioning of current drugs. However, the effectiveness of this approach has rarely been examined. Here we select the “TB drugome” approach – a protein structure-based method for drug repositioning for tuberculosis treatment – to (1) experimentally validate the efficacy of the identified drug candidates for inhibiting MTB growth, and (2) computationally examine how consistently drug candidates are prioritized, considering changes in input data. Twenty three drugs in the TB drugome were tested. Of them, only two drugs (tamoxifen and 4-hydroxytamoxifen) effectively suppressed MTB growth at relatively high concentrations. Both drugs significantly enhanced the inhibitory effects of three first-line anti-TB drugs (rifampin, isoniazid, and ethambutol). However, tamoxifen is not a top-listed drug in the TB drugome, and 4-hydroxytamoxifen is not approved for use in humans. Computational re-examination of the TB drugome indicated that the rankings were subject to technical and data-related biases. Thus, although our results support the effectiveness of the TB drugome approach for identifying drugs that can potentially be repositioned for stand-alone applications or for combination treatments for TB, the approach requires further refinements via incorporation of additional biological information. Our findings can also be extended to other structure-based drug repositioning methods.

The evolution of the coding exome is a major driving force of functional divergence both between species and between protein isoforms. Exons at different positions in the transcript or in different transcript isoforms may (1) mutate at different rates due to variations in DNA methylation level; and (2) serve distinct biological roles, and thus be differentially targeted by natural selection. Furthermore, intrinsic exonic features, such as exon length, may also affect the evolution of individual exons. Importantly, the evolutionary effects of these intrinsic/extrinsic features may differ significantly between animals and plants. Such inter-lineage differences, however, have not been systematically examined.