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BackgroundThe Worldwide Innovative Network (WIN) Consortium has developed the Simplified Interventional Mapping System (SIMS) to better define the cancer molecular milieu based on genomics/transcriptomics from tumor and analogous normal tissue biopsies. SPRING is the first trial to assess a SIMS-based tri-therapy regimen in advanced non-small cell lung cancer (NSCLC).MethodsPatients with advanced NSCLC (no EGFR, ALK, or ROS1 alterations; PD-L1 unrestricted; ≤2 prior therapy lines) received avelumab, axitinib, and palbociclib (3 + 3 dose escalation design).ResultsFifteen patients were treated (five centers, four countries): six at each of dose levels 1 (DL1) and DL2; three at DL3. The most common ≥Grade 3 adverse events were neutropenia, hypertension, and fatigue. The recommended Phase II dose (RP2D) was DL1: avelumab 10 mg/kg IV q2weeks, axitinib 3 mg po bid, and palbociclib 75 mg po daily (7 days off/21 days on). Four patients (27%) achieved a partial response (PR) (progression-free survival [PFS]: 14, 24, 25 and 144+ weeks), including two after progression on pembrolizumab. Four patients attained stable disease (SD) that lasted ≥24 weeks: 24, 27, 29, and 64 weeks. At DL1 (RP2D), four of six patients (66%) achieved stable disease (SD) ≥6 months/PR (2 each). Responders included patients with no detectable PD-L1 expression and low tumor mutational burden.ConclusionsOverall, eight of 15 patients (53%) achieved clinical benefit (SD ≥ 24 weeks/PR) on the avelumab, axitinib, and palbociclib combination. This triplet showed antitumor activity in NSCLC, including in tumors post-pembrolizumab progression, and was active at the RP2D, which was well tolerated. NCT03386929 clinicaltrial.gov.

Non-small cell lung cancer (NSCLC) is a leading cause of death worldwide. Targeted monotherapies produce high regression rates, albeit for limited patient subgroups, who inevitably succumb. We present a novel strategy for identifying customized combinations of triplets of targeted agents, utilizing a simplified interventional mapping system (SIMS) that merges knowledge about existent drugs and their impact on the hallmarks of cancer. Based on interrogation of matched lung tumor and normal tissue using targeted genomic sequencing, copy number variation, transcriptomics, and miRNA expression, the activation status of 24 interventional nodes was elucidated. An algorithm was developed to create a scoring system that enables ranking of the activated interventional nodes for each patient. Based on the trends of co-activation at interventional points, combinations of drug triplets were defined in order to overcome resistance. This methodology will inform a prospective trial to be conducted by the WIN consortium, aiming to significantly impact survival in metastatic NSCLC and other malignancies.

Increasing efforts are being dedicated towards improving cancer care via personalized medicine. These efforts depend to a large degree on the availability of a knowledge foundation. Unfortunately, existing knowledge linking cancer drugs and potential efficacy biomarkers is in its infancy; and where links are known, they are frequently unstructured and poorly documented. We have developed a new open-access knowledgebase for precision cancer medicine (the PCM Wiki and Knowledgebase). This knowledgebase was constructed using an innovative, two-pronged approach involving a structured knowledgebase at the back-end, and an intuitive knowledge-sharing interface and user-friendly query engine in front. The knowledgebase was seeded with several patient case reports and information was mined via text-mining and literature review by human curators. Using our novel Wiki-based platform to present and share knowledge stored in the PCM knowledgebase, users are able to suggest corrections, propose additions or point to errors in the knowledgebase. The result is a community-driven evolving knowledgebase holding integrated and consolidated knowledge of markers and indications for personalized cancer medicine. We suggest that the PCM Knowledgebase and Wiki could serve as an important tool for the advancement of clinical trials and care in the field of precision cancer medicine.

Melanoma is the deadliest form of skin cancer, due to its tendency to metastasize early. Brother of regulator of imprinted sites (BORIS), also known as CCCTC binding factor-like (CTCFL), is a transcription regulator that becomes ectopically expressed in melanoma. We recently showed that BORIS contributes to melanoma phenotype switching by altering the gene expression program of melanoma cells from an intermediate melanocytic state toward a more mesenchymal-like state. However, the mechanism underlying this transcriptional switch remains unclear. Here, ATAC-seq was used to study BORIS-mediated chromatin accessibility alterations in melanoma cells harboring an intermediate melanocytic state. The gene set that gained promoter accessibility, following ectopic BORIS expression, showed enrichment for biological processes associated with melanoma invasion, while promoters of genes associated with proliferation showed reduced accessibility. Integration of ATAC-seq and RNA-seq data demonstrated that increased chromatin accessibility was associated with transcriptional upregulation of genes involved in tumor progression processes, and the aberrant activation of oncogenic transcription factors, while reduced chromatin accessibility and downregulated genes were associated with repressed activity of tumor suppressors and proliferation factors. Together, these findings indicate that BORIS mediates transcriptional reprogramming in melanoma cells by altering chromatin accessibility and gene expression, shifting the cellular transcription landscape of melanoma cells toward a mesenchymal-like genetic signature. [ABSTRACT FROM AUTHOR]

The need to support bioinformatics training has been widely recognized by scientists, industry, and government institutions. However, the discussion of instructional methods for teaching bioinformatics is only beginning. Here we report on a systematic attempt to design two bioinformatics workshops for graduate biology students on the basis of Gagne's Conditions of Learning instructional design theory. This theory, although first published in the early 1970s, is still fundamental in instructional design and instructional technology. First, top-level as well as prerequisite learning objectives for a microarray analysis workshop and a primer design workshop were defined. Then a hierarchy of objectives for each workshop was created. Hands-on tutorials were designed to meet these objectives. Finally, events of learning proposed by Gagne's theory were incorporated into the hands-on tutorials. The resultant manuals were tested on a small number of trainees, revised, and applied in 1-day bioinformatics workshops. Based on this experience and on observations made during the workshops, we conclude that Gagne's Conditions of Learning instructional design theory provides a useful framework for developing bioinformatics training, but may not be optimal as a method for teaching it. (Contains 3 figures and 1 table.)

Abstract Background Currently, data about age-phenotype associations are not systematically organized and cannot be studied methodically. Searching for scientific articles describing phenotypic changes reported as occurring at a given age is not possible for most ages. Results Here we present the Age-Phenome Knowledge-base (APK), in which knowledge about age-related phenotypic patterns and events can be modeled and stored for retrieval. The APK contains evidence connecting specific ages or age groups with phenotypes, such as disease and clinical traits. Using a simple text mining tool developed for this purpose, we extracted instances of age-phenotype associations from journal abstracts related to non-insulin-dependent Diabetes Mellitus. In addition, links between age and phenotype were extracted from clinical data obtained from the NHANES III survey. The knowledge stored in the APK is made available for the relevant research community in the form of 'Age-Cards', each card holds the collection of all the information stored in the APK about a particular age. These Age-Cards are presented in a wiki, allowing community review, amendment and contribution of additional information. In addition to the wiki interaction, complex searches can also be conducted which require the user to have some knowledge of database query construction. Conclusions The combination of a knowledge model based repository with community participation in the evolution and refinement of the knowledge-base makes the APK a useful and valuable environment for collecting and curating existing knowledge of the connections between age and phenotypes.