The Role of Physician Specialty in the Underutilization of Standard-of-Care Treatment Intensification in Patients With Metastatic Castration-sensitive Prostate Cancer.

PURPOSE: We evaluate utilization of treatment intensification of androgen deprivation therapy with androgen receptor pathway inhibitor/docetaxel for metastatic castration-sensitive prostate cancer patients across physician specialties. MATERIALS AND METHODS: This retrospective study identified patients with metastatic castration-sensitive prostate cancer in the Optum Research Database between 2014 and 2019. Adult men with ≥1 claim for metastatic disease within 90 days before or any time after the first prostate cancer claim who received androgen deprivation therapy were included. Physician specialty, determined from medical/pharmacy claims during each line of therapy, was categorized as urologist only, oncologist only, both (urologists and oncologists), or other (other specialties). Treatment intensification and patient characteristics were analyzed descriptively. RESULTS: Of 4,675 patients, 16% were treated by urologists only, 20% by oncologists only, 63% by both, and 1.1% by others. The most frequent first line of therapy was androgen deprivation therapy ± first-generation nonsteroidal antiandrogens (>50%). Androgen deprivation therapy + docetaxel use declined over time, while androgen deprivation therapy + androgen receptor pathway inhibitor use increased. Patients seen by oncologists or both were younger, had fewer comorbidities, and were likelier to receive treatment intensification compared to those treated by urologists. By 2019, however, treatment intensification remained <40% from oncologists only or both, and <15% from urologists only. In the second and third lines of therapy, androgen deprivation therapy + androgen receptor pathway inhibitor was the most prescribed regimen across specialties (>50%). CONCLUSIONS: Treatment intensification was underused in first lines of therapy across urology and oncology specialties despite evidence of improved survival. In subsequent lines, androgen deprivation therapy + androgen receptor pathway inhibitor was prescribed more frequently across specialties. These results underscore the need for earlier treatment intensification by urologists and oncologists.

Topsentinol L Trisulfate, a Marine Natural Product That Targets Basal-like and Claudin-Low Breast Cancers.

Patients diagnosed with basal-like breast cancer suffer from poor prognosis and limited treatment options. There is an urgent need to identify new targets that can benefit patients with basal-like and claudin-low (BL-CL) breast cancers. We screened fractions from our Marine Invertebrate Compound Library (MICL) to identify compounds that specifically target BL-CL breast cancers. We identified a previously unreported trisulfated sterol, i.e., topsentinol L trisulfate (TLT), which exhibited increased efficacy against BL-CL breast cancers relative to luminal/HER2+ breast cancer. Biochemical investigation of the effects of TLT on BL-CL cell lines revealed its ability to inhibit activation of AMP-activated protein kinase (AMPK) and checkpoint kinase 1 (CHK1) and to promote activation of p38. The importance of targeting AMPK and CHK1 in BL-CL cell lines was validated by treating a panel of breast cancer cell lines with known small molecule inhibitors of AMPK (dorsomorphin) and CHK1 (Ly2603618) and recording the increased effectiveness against BL-CL breast cancers as compared with luminal/HER2+ breast cancer. Finally, we generated a drug response gene-expression signature and projected it against a human tumor panel of 12 different cancer types to identify other cancer types sensitive to the compound. The TLT sensitivity gene-expression signature identified breast and bladder cancer as the most sensitive to TLT, while glioblastoma multiforme was the least sensitive.

ASSIGN: context-specific genomic profiling of multiple heterogeneous biological pathways.

MOTIVATION: Although gene-expression signature-based biomarkers are often developed for clinical diagnosis, many promising signatures fail to replicate during validation. One major challenge is that biological samples used to generate and validate the signature are often from heterogeneous biological contexts-controlled or in vitro samples may be used to generate the signature, but patient samples may be used for validation. In addition, systematic technical biases from multiple genome-profiling platforms often mask true biological variation. Addressing such challenges will enable us to better elucidate disease mechanisms and provide improved guidance for personalized therapeutics. RESULTS: Here, we present a pathway profiling toolkit, Adaptive Signature Selection and InteGratioN (ASSIGN), which enables robust and context-specific pathway analyses by efficiently capturing pathway activity in heterogeneous sets of samples and across profiling technologies. The ASSIGN framework is based on a flexible Bayesian factor analysis approach that allows for simultaneous profiling of multiple correlated pathways and for the adaptation of pathway signatures into specific disease. We demonstrate the robustness and versatility of ASSIGN in estimating pathway activity in simulated data, cell lines perturbed pathways and in primary tissues samples including The Cancer Genome Atlas breast carcinoma samples and liver samples exposed to genotoxic carcinogens. AVAILABILITY AND IMPLEMENTATION: Software for our approach is available for download at: http://www.bioconductor.org/packages/release/bioc/html/ASSIGN.html and https://github.com/wevanjohnson/ASSIGN.

Genomic classification of the RAS network identifies a personalized treatment strategy for lung cancer.

Better approaches are needed to evaluate a single patient's drug response at the genomic level. Targeted therapy for signaling pathways in cancer has met limited success in part due to the exceedingly interwoven nature of the pathways. In particular, the highly complex RAS network has been challenging to target. Effectively targeting the pathway requires development of techniques that measure global network activity to account for pathway complexity. For this purpose, we used a gene-expression-based biomarker for RAS network activity in non-small cell lung cancer (NSCLC) cells, and screened for drugs whose efficacy was significantly highly correlated to RAS network activity. Results identified EGFR and MEK co-inhibition as the most effective treatment for RAS-active NSCLC amongst a panel of over 360 compounds and fractions. RAS activity was identified in both RAS-mutant and wild-type lines, indicating broad characterization of RAS signaling inclusive of multiple mechanisms of RAS activity, and not solely based on mutation status. Mechanistic studies demonstrated that co-inhibition of EGFR and MEK induced apoptosis and blocked both EGFR-RAS-RAF-MEK-ERK and EGFR-PI3K-AKT-RPS6 nodes simultaneously in RAS-active, but not RAS-inactive NSCLC. These results provide a comprehensive strategy to personalize treatment of NSCLC based on RAS network dysregulation and provide proof-of-concept of a genomic approach to classify and target complex signaling networks.