Utility of the JAX Clinical Knowledgebase in capture and assessment of complex genomic cancer data.

Cancer genomic data is continually growing in complexity, necessitating improved methods for data capture and analysis. Tumors often contain multiple therapeutically relevant alterations, and co-occurring alterations may have a different influence on therapeutic response compared to if those alterations were present alone. One clinically important example of this is the existence of a resistance conferring alteration in combination with a therapeutic sensitizing mutation. The JAX Clinical Knowledgebase (JAX-CKB) (https://ckb.jax.org/) has incorporated the concept of the complex molecular profile, which enables association of therapeutic efficacy data with multiple genomic alterations simultaneously. This provides a mechanism for rapid and accurate assessment of complex cancer-related data, potentially aiding in streamlined clinical decision making. Using the JAX-CKB, we demonstrate the utility of associating data with complex profiles comprising ALK fusions with another variant, which have differing impacts on sensitivity to various ALK inhibitors depending on context.

Barriers preventing the adoption of comprehensive cancer genomic profiling in the clinic.

INTRODUCTION: Comprehensive cancer genomic profiling provides the opportunity to expose the various molecular aberrations potentially driving tumor progression. Consequently, the identity of these genetic drivers can be utilized to match a patient to the most appropriate targeted therapy, thereby increasing the probability of improved clinical outcome. Despite its capability of informing patient care, the adoption of comprehensive cancer genomic profiling in the clinic has not been widespread. The barriers surrounding its universal acceptance are attributed to both physician and patient perspectives. Areas covered: The following report discusses the various obstacles in place, including those related to clinical utility, education, insurance coverage, and clinical trials, which can deter physicians and patients from utilizing genomic profiling for therapeutic decision-making. Expert commentary: The authors review the recent growth and potential of clinical utility studies over the last two years, provide a suggestive framework for educational support, and comment on the use of social media to enhance clinical trial recruitment.

mTOR Inhibitors in Castration-Resistant Prostate Cancer: A Systematic Review.

BACKGROUND: The progression of prostate cancer to castration-resistant prostate cancer (CRPC) is often a result of somatic alterations in the PI3K/Akt/mTOR (mammalian target of rapamycin) pathway, suggesting that therapies targeting this pathway might lead to improved survival and efficacy. Here, we systematically evaluate the results of clinical trials investigating mTOR inhibition in CRPC and utilize preclinical data to predict clinical outcomes. METHODS: Trials included in the study were identified through PubMed and via review of conference abstracts cited by relevant review articles. The eligibility of trials was independent of sample size, clinical setting, or date. RESULTS: A total of 14 studies were eligible for qualitative analysis. The clinical setting was variable among studies, and all utilized an allosteric mTOR inhibitor as either a monotherapy or in combination. Molecular criteria were evaluated in three trials. Among most studies, the prostate-specific antigen level declined during treatment, but often increased shortly thereafter. Partial responses to treatment were minimal, and no complete responses were reported. Two studies exploring therapy with an mTOR inhibitor in combination with bicalutamide resulted in minimal efficacy. Overall, allosteric mTOR inhibition was deemed to be inadequate for the treatment of CRPC. CONCLUSION: Preclinical data suggest that a reciprocal feedback mechanism between PI3K and androgen receptor signaling is a potential mechanism behind the clinical inefficacy of mTOR inhibitors in CRPC, indicating combinatorial targeting of PI3K, mTORC1/2, and the androgen receptor might be more effective. Comprehensive analysis of preclinical data to assess clinical trial targets and efficacy may reduce the number of unproductive trials and identify potentially beneficial combinatorial therapies for resistant disease.

The clinical trial landscape in oncology and connectivity of somatic mutational profiles to targeted therapies.

BACKGROUND: Precision medicine in oncology relies on rapid associations between patient-specific variations and targeted therapeutic efficacy. Due to the advancement of genomic analysis, a vast literature characterizing cancer-associated molecular aberrations and relative therapeutic relevance has been published. However, data are not uniformly reported or readily available, and accessing relevant information in a clinically acceptable time-frame is a daunting proposition, hampering connections between patients and appropriate therapeutic options. One important therapeutic avenue for oncology patients is through clinical trials. Accordingly, a global view into the availability of targeted clinical trials would provide insight into strengths and weaknesses and potentially enable research focus. However, data regarding the landscape of clinical trials in oncology is not readily available, and as a result, a comprehensive understanding of clinical trial availability is difficult. RESULTS: To support clinical decision-making, we have developed a data loader and mapper that connects sequence information from oncology patients to data stored in an in-house database, the JAX Clinical Knowledgebase (JAX-CKB), which can be queried readily to access comprehensive data for clinical reporting via customized reporting queries. JAX-CKB functions as a repository to house expertly curated clinically relevant data surrounding our 358-gene panel, the JAX Cancer Treatment Profile (JAX CTP), and supports annotation of functional significance of molecular variants. Through queries of data housed in JAX-CKB, we have analyzed the landscape of clinical trials relevant to our 358-gene targeted sequencing panel to evaluate strengths and weaknesses in current molecular targeting in oncology. Through this analysis, we have identified patient indications, molecular aberrations, and targeted therapy classes that have strong or weak representation in clinical trials. CONCLUSIONS: Here, we describe the development and disseminate system methods for associating patient genomic sequence data with clinically relevant information, facilitating interpretation and providing a mechanism for informing therapeutic decision-making. Additionally, through customized queries, we have the capability to rapidly analyze the landscape of targeted therapies in clinical trials, enabling a unique view into current therapeutic availability in oncology.